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- Petersson, Jesper, 1974
(author)
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Medicine At A Distance In Sweden: Spatiotemporal Matters In Accomplishing Working Telemedicine
- 2011
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In: Science Studies. - 0786-3012. ; 24:2, s. 43-62
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Journal article (peer-reviewed)abstract
- This paper examines the accomplishment of making technology work, using the discourse around telemedicine in Swedish healthcare during 1994-2003. The paper will compare four projects launched in the mid-1990s and policymakers’ visions of healthcare through telemedicine. I will employ a sociotechnical approach developed within Actor-Network Theory that understands functioning technology not as something intrinsic but as an outcome of an ongoing process of negotiations. In the paper, I will extend the sociotechnical approach of what constitutes working technology to include spatiotemporal matters. I will also approach the closely related issue of space that has become a concern of Actor-Network Theory scholars interested in the accomplishment and continued workings of technology as it travels. In this discussion, an emphasis on fixed relations (network space) has been challenged by investigations into changing relations (fluid space). This paper suggests that in order to travel well, technology must be both fixed and fluid.⁰
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5. |
- Ahlander, Britt-Marie, 1954-, et al.
(author)
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An echo-planar imaging sequence is superior to a steady-state free precession sequence for visual as well as quantitative assessment of cardiac magnetic resonance stress perfusion
- 2017
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In: Clinical Physiology and Functional Imaging. - : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 37:1, s. 52-61
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Journal article (peer-reviewed)abstract
- BACKGROUND: To assess myocardial perfusion, steady-state free precession cardiac magnetic resonance (SSFP, CMR) was compared with gradient-echo-echo-planar imaging (GRE-EPI) using myocardial perfusion scintigraphy (MPS) as reference.METHODS: Cardiac magnetic resonance perfusion was recorded in 30 patients with SSFP and in another 30 patients with GRE-EPI. Timing and extent of inflow delay to the myocardium was visually assessed. Signal-to-noise (SNR) and contrast-to-noise (CNR) ratios were calculated. Myocardial scar was visualized with a phase-sensitive inversion recovery sequence (PSIR). All scar positive segments were considered pathologic. In MPS, stress and rest images were used as in clinical reporting. The CMR contrast wash-in slope was calculated and compared with the stress score from the MPS examination. CMR scar, CMR perfusion and MPS were assessed separately by one expert for each method who was blinded to other aspects of the study.RESULTS: Visual assessment of CMR had a sensitivity for the detection of an abnormal MPS at 78% (SSFP) versus 91% (GRE-EPI) and a specificity of 58% (SSFP) versus 84% (GRE-EPI). Kappa statistics for SSFP and MPS was 0·29, for GRE-EPI and MPS 0·72. The ANOVA of CMR perfusion slopes for all segments versus MPS score (four levels based on MPS) had correlation r = 0·64 (SSFP) and r = 0·96 (GRE-EPI). SNR was for normal segments 35·63 ± 11·80 (SSFP) and 17·98 ± 8·31 (GRE-EPI), while CNR was 28·79 ± 10·43 (SSFP) and 13·06 ± 7·61 (GRE-EPI).CONCLUSION: GRE-EPI displayed higher agreement with the MPS results than SSFP despite significantly lower signal intensity, SNR and CNR.
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6. |
- Rosendahl, Lene, 1963-, et al.
(author)
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Computer-assisted calculation of myocardial infarct size shortens the evaluation time of contrast-enhanced cardiac MRI
- 2008
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In: Clinical Physiology and Functional Imaging. - : John Wiley & Sons. - 1475-0961 .- 1475-097X. ; 28:1, s. 1-7
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Journal article (peer-reviewed)abstract
- Background: Delayed enhancement magnetic resonance imaging depicts scar in the left ventricle which can be quantitatively measured. Manual segmentation and scar determination is time consuming. The purpose of this study was to evaluate a software for infarct quantification, to compare with manual scar determination, and to measure the time saved.Methods: Delayed enhancement magnetic resonance imaging was performed in 40 patients where myocardial perfusion single photon emission computed tomography imaging showed irreversible uptake reduction suggesting a myocardial scar. After segmentation, the semi-automatic software was applied. A scar area was displayed, which could be corrected and compared with manual delineation. The different time steps were recorded with both methods.Results: The software shortened the average evaluation time by 12.4min per cardiac exam, compared with manual delineation. There was good correlation of myocardial volume, infarct volume and infarct percentage (%) between the two methods, r = 0.95, r = 0.92 and r = 0.91 respectively.Conclusions: A computer software for myocardial volume and infarct size determination cut the evaluation time by more than 50% compared with manual assessment, with maintained clinical accuracy.
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7. |
- Ali, Muhaddisa Barat, 1986, et al.
(author)
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A novel federated deep learning scheme for glioma and its subtype classification
- 2023
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In: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
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Journal article (peer-reviewed)abstract
- Background: Deep learning (DL) has shown promising results in molecular-based classification of glioma subtypes from MR images. DL requires a large number of training data for achieving good generalization performance. Since brain tumor datasets are usually small in size, combination of such datasets from different hospitals are needed. Data privacy issue from hospitals often poses a constraint on such a practice. Federated learning (FL) has gained much attention lately as it trains a central DL model without requiring data sharing from different hospitals. Method: We propose a novel 3D FL scheme for glioma and its molecular subtype classification. In the scheme, a slice-based DL classifier, EtFedDyn, is exploited which is an extension of FedDyn, with the key differences on using focal loss cost function to tackle severe class imbalances in the datasets, and on multi-stream network to exploit MRIs in different modalities. By combining EtFedDyn with domain mapping as the pre-processing and 3D scan-based post-processing, the proposed scheme makes 3D brain scan-based classification on datasets from different dataset owners. To examine whether the FL scheme could replace the central learning (CL) one, we then compare the classification performance between the proposed FL and the corresponding CL schemes. Furthermore, detailed empirical-based analysis were also conducted to exam the effect of using domain mapping, 3D scan-based post-processing, different cost functions and different FL schemes. Results: Experiments were done on two case studies: classification of glioma subtypes (IDH mutation and wild-type on TCGA and US datasets in case A) and glioma grades (high/low grade glioma HGG and LGG on MICCAI dataset in case B). The proposed FL scheme has obtained good performance on the test sets (85.46%, 75.56%) for IDH subtypes and (89.28%, 90.72%) for glioma LGG/HGG all averaged on five runs. Comparing with the corresponding CL scheme, the drop in test accuracy from the proposed FL scheme is small (−1.17%, −0.83%), indicating its good potential to replace the CL scheme. Furthermore, the empirically tests have shown that an increased classification test accuracy by applying: domain mapping (0.4%, 1.85%) in case A; focal loss function (1.66%, 3.25%) in case A and (1.19%, 1.85%) in case B; 3D post-processing (2.11%, 2.23%) in case A and (1.81%, 2.39%) in case B and EtFedDyn over FedAvg classifier (1.05%, 1.55%) in case A and (1.23%, 1.81%) in case B with fast convergence, which all contributed to the improvement of overall performance in the proposed FL scheme. Conclusion: The proposed FL scheme is shown to be effective in predicting glioma and its subtypes by using MR images from test sets, with great potential of replacing the conventional CL approaches for training deep networks. This could help hospitals to maintain their data privacy, while using a federated trained classifier with nearly similar performance as that from a centrally trained one. Further detailed experiments have shown that different parts in the proposed 3D FL scheme, such as domain mapping (make datasets more uniform) and post-processing (scan-based classification), are essential.
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8. |
- Andersson, Jonas, 1975-, et al.
(author)
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Artificial intelligence and the medical physics profession-A Swedish perspective
- 2021
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In: Physica Medica-European Journal of Medical Physics. - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 88, s. 218-225
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Journal article (peer-reviewed)abstract
- Background: There is a continuous and dynamic discussion on artificial intelligence (AI) in present-day society. AI is expected to impact on healthcare processes and could contribute to a more sustainable use of resources allocated to healthcare in the future. The aim for this work was to establish a foundation for a Swedish perspective on the potential effect of AI on the medical physics profession. Materials and methods: We designed a survey to gauge viewpoints regarding AI in the Swedish medical physics community. Based on the survey results and present-day situation in Sweden, a SWOT analysis was performed on the implications of AI for the medical physics profession. Results: Out of 411 survey recipients, 163 responded (40%). The Swedish medical physicists with a professional license believed (90%) that AI would change the practice of medical physics but did not foresee (81%) that AI would pose a risk to their practice and career. The respondents were largely positive to the inclusion of AI in educational programmes. According to self-assessment, the respondents' knowledge of and workplace preparedness for AI was generally low. Conclusions: From the survey and SWOT analysis we conclude that AI will change the medical physics profession and that there are opportunities for the profession associated with the adoption of AI in healthcare. To overcome the weakness of limited AI knowledge, potentially threatening the role of medical physicists, and build upon the strong position in Swedish healthcare, medical physics education and training should include learning objectives on AI.
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9. |
- Chakarova, Roumiana, et al.
(author)
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A Monte Carlo evaluation of beam characteristics for total body irradiation at extended treatment distances
- 2014
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In: Journal of Applied Clinical Medical Physics. - 1526-9914. ; 15:3, s. 182-189
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Journal article (peer-reviewed)abstract
- The aim is to study beam characteristics at large distances when focusing on the electron component. In particular, to investigate the utility of spoilers with various thicknesses as an electron source, as well as the effect of different spoiler-to-surface distances (STSD) on the beam characteristics and, consequently, on the dose in the superficial region. A MC model of a 15 MV Varian accelerator, validated earlier by experimental data at isocenter and extended distances used in large-field total body irradiation, is applied to evaluate beam characteristics at distances larger than 400 cm. Calculations are carried out using BEAMnrc/DOSXYZnrc code packages and phase space data are analyzed by the beam data processor BEAMdp. The electron component of the beam is analyzed at isocenter and extended distances, with and without spoilers as beam modifiers, assuming vacuum or air surrounding the accelerator head. Spoiler thickness of 1.6 cm is found to be optimal compared to thicknesses of 0.8 cm and 2.4 cm. The STSD variations should be taken into account when treating patients, in particular when the treatment protocols are based on a fixed distance to the patient central sagittal plane, and also, in order to maintain high dose in the superficial region.
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10. |
- Khoshnood, Ardavan
(author)
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Prehospital Diagnosis and Oxygen Treatment in ST Elevation Myocardial Infarction
- 2017
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Doctoral thesis (other academic/artistic)abstract
- IntroductionPaper I: An Artificial Neural Network (ANN) was constructed to identify ST Elevation Myocardial Infarction (STEMI) and predict the need for Percutaneous Coronary Intervention (PCI). Paper II, III and IV: Studies suggest that O2 therapy may be harmful in STEMI patients. We therefore conducted the SOCCER study to evaluate the effects of O2 therapy in STEMI patients.MethodsPaper I: 560 ambulance ECGs sent to the Cardiac Care Unit (CCU), was together with the CCU physicians interpretation and decision of conducting an acute PCI or not collected, and compared with the interpretation and PCI decision of the ANN. Paper II, III, IV: Normoxic (≥94%) STEMI patients accepted for acute PCI were in the ambulance randomized to standard care with 10 L/min O2 or room air. A subset of the patients underwent echocardiography for determination of the Left Ventricular Ejection Fraction (LVEF) and the Wall Motion Score Index (WMSI). All patients had a Cardiac Magnetic Resonance Imaging (CMRI) to evaluate Myocardial area at Risk (MaR), Infarct Size (IS) and Myocardial Salvage Index (MSI).ResultsPaper I: The area under the ANN’s receiver operating characteristics curve for STEMI detection as well as predicting the need of acute PCI were very good.Paper II, III, IV: No significant differences could be shown in discussing MaR, MSI or IS between the O2 group (n=46) and the air group (n=49). Neither could any differences be shown for LVEF and WMSI at the index visit as well after six months between the O2 group (n=46) and the air group (n=41)ConclusionsPaper I: The results indicate that the number of ECGs sent to the CCU could be reduced with 2/3 as the ANN would safely identify ECGs not being STEMI.Paper II, III, IV: The results suggest that it is safe to withhold O2 therapy in normoxic, stable STEMI patients.
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11. |
- Ge, Chenjie, 1991, et al.
(author)
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Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
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In: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
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Journal article (peer-reviewed)abstract
- This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size, and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included.
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12. |
- Borrelli, P., et al.
(author)
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AI-based detection of lung lesions in F-18 FDG PET-CT from lung cancer patients
- 2021
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In: Ejnmmi Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 8:1
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Journal article (peer-reviewed)abstract
- Background[F-18]-fluorodeoxyglucose (FDG) positron emission tomography with computed tomography (PET-CT) is a well-established modality in the work-up of patients with suspected or confirmed diagnosis of lung cancer. Recent research efforts have focused on extracting theragnostic and textural information from manually indicated lung lesions. Both semi-automatic and fully automatic use of artificial intelligence (AI) to localise and classify FDG-avid foci has been demonstrated. To fully harness AI's usefulness, we have developed a method which both automatically detects abnormal lung lesions and calculates the total lesion glycolysis (TLG) on FDG PET-CT.MethodsOne hundred twelve patients (59 females and 53 males) who underwent FDG PET-CT due to suspected or for the management of known lung cancer were studied retrospectively. These patients were divided into a training group (59%; n = 66), a validation group (20.5%; n = 23) and a test group (20.5%; n = 23). A nuclear medicine physician manually segmented abnormal lung lesions with increased FDG-uptake in all PET-CT studies. The AI-based method was trained to segment the lesions based on the manual segmentations. TLG was then calculated from manual and AI-based measurements, respectively and analysed with Bland-Altman plots.ResultsThe AI-tool's performance in detecting lesions had a sensitivity of 90%. One small lesion was missed in two patients, respectively, where both had a larger lesion which was correctly detected. The positive and negative predictive values were 88% and 100%, respectively. The correlation between manual and AI TLG measurements was strong (R-2 = 0.74). Bias was 42 g and 95% limits of agreement ranged from -736 to 819 g. Agreement was particularly high in smaller lesions.ConclusionsThe AI-based method is suitable for the detection of lung lesions and automatic calculation of TLG in small- to medium-sized tumours. In a clinical setting, it will have an added value due to its capability to sort out negative examinations resulting in prioritised and focused care on patients with potentially malignant lesions.
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13. |
- Szaro, Pavel, 1981, et al.
(author)
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Magnetic resonance imaging of the brachial plexus. Part 2: Traumatic injuries
- 2022
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In: European Journal of Radiology Open (EJR Open). - : Elsevier BV. - 2352-0477. ; 9
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Journal article (peer-reviewed)abstract
- The most common indications for magnetic resonance imaging (MRI) of the brachial plexus (BP) are traumatic injuries. The role of MRI of the BP has increased because of recent trends favoring earlier surgery. Determining preganglionic vs. postganglionic injury is essential, as different treatment strategies are required. Thus, MRI of the BP should be supplemented with cervical spine MRI to assess the intradural part of the spinal nerves, including highly T2-weighted techniques. Acute preganglionic injuries usually manifest as various combinations of post-traumatic pseudomeningocele, the absence of roots, deformity of nerve root sleeves, displacement of the spinal cord, hemorrhage in the spinal canal, presence of scars in the spinal canal, denervation of the back muscles, and syrinx. Spinal nerve root absence is more specific than pseudomeningocele on MRI. Acute postganglionic injuries can present as lesions in continuity or tears. The following signs indicate injury to the BP: side-to-side difference, swelling, partial, or total BP rupture. Injury patterns and localization are associated with the mechanism of trauma, which implies a significant role for MRI in the work-up of patients. The identification and description of traumatic lesions involving the brachial plexus need to be systematic and detailed. Using an appropriate MRI protocol, obtaining details about the injury, applying a systematic anatomical approach, and correlating imaging findings to relevant clinical data to make a correct diagnosis. Information about the presence or suspicion of root avulsion should always be provided.
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14. |
- Rosendahl, Lene, et al.
(author)
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Image quality and myocardial scar size determined with magnetic resonance imaging in patients with permanent atrial fibrillation : A comparison of two imaging protocols
- 2010
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In: Clinical Physiology and Functional Imaging. - : John Wiley & Sons. - 1475-0961 .- 1475-097X. ; 30:2, s. 122-129
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Journal article (peer-reviewed)abstract
- Background: Magnetic resonance imaging (MRI) of the heart generally requires breath holding and a regular rhythm. Single shot 2D steady-state free precession (SS_SSFP) is a fast sequence insensitive to arrhythmia as well as breath holding. Our purpose was to determine image quality, signal-to-noise (SNR) and contrast-to-noise (CNR) ratios and infarct size with a fast single shot and a standard segmented MRI sequence in patients with permanent atrial fibrillation and chronic myocardial infarction.Methods: Twenty patients with chronic myocardial infarction and ongoing atrial fibrillation were examined with inversion recovery SS_SSFP and segmented inversion recovery 2D fast gradient echo (IR_FGRE). Image quality was assessed in four categories: delineation of infarcted and non-infarcted myocardium, occurrence of artefacts and overall image quality. SNR and CNR were calculated. Myocardial volume (ml) and infarct size, expressed as volume (ml) and extent (%), were calculated, and the methodological error was assessed.Results: SS_SSFP had significantly better quality scores in all categories (P = 0·037, P = 0·014, P = 0·021, P = 0·03). SNRinfarct and SNRblood were significantly better for IR_FGRE than for SS_SSFP (P = 0·048, P = 0·018). No significant difference was found in SNRmyocardium and CNR. The myocardial volume was significantly larger with SS_SSFP (170·7 versus 159·2 ml, P<0·001), but no significant difference was found in infarct volume and infarct extent.Conclusion: SS_SSFP displayed significantly better image quality than IR_FGRE. The infarct size and the error in its determination were equal for both sequences, and the examination time was shorter with SS_SSFP.
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15. |
- Pfeiffer, Christoph, 1989, et al.
(author)
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On-scalp MEG sensor localization using magnetic dipole-like coils: A method for highly accurate co-registration
- 2020
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In: Neuroimage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 212
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Journal article (peer-reviewed)abstract
- Source modelling in magnetoencephalography (MEG) requires precise co-registration of the sensor array and the anatomical structure of the measured individual's head. In conventional MEG, the positions and orientations of the sensors relative to each other are fixed and known beforehand, requiring only localization of the head relative to the sensor array. Since the sensors in on-scalp MEG are positioned on the scalp, locations of the individual sensors depend on the subject's head shape and size. The positions and orientations of on-scalp sensors must therefore be measured a every recording. This can be achieved by inverting conventional head localization, localizing the sensors relative to the head - rather than the other way around. In this study we present a practical method for localizing sensors using magnetic dipole-like coils attached to the subject's head. We implement and evaluate the method in a set of on-scalp MEG recordings using a 7-channel on-scalp MEG system based on high critical temperature superconducting quantum interference devices (high-T-c SQUIDs). The method allows individually localizing the sensor positions, orientations, and responsivities with high accuracy using only a short averaging time (<= 2 mm, < 3 degrees and < 3%, respectively, with 1-s averaging), enabling continuous sensor localization. Calibrating and jointly localizing the sensor array can further improve the accuracy of position and orientation (< 1 mm and < 1 degrees, respectively, with 1-s coil recordings). We demonstrate source localization of on-scalp recorded somatosensory evoked activity based on coregistration with our method. Equivalent current dipole fits of the evoked responses corresponded well (within 4.2 mm) with those based on a commercial, whole-head MEG system.
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16. |
- Hagberg, Eva, et al.
(author)
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Semi-supervised learning with natural language processing for right ventricle classification in echocardiography—a scalable approach
- 2022
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In: Computers in Biology and Medicine. - : Elsevier BV. - 0010-4825 .- 1879-0534. ; 143
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Journal article (peer-reviewed)abstract
- We created a deep learning model, trained on text classified by natural language processing (NLP), to assess right ventricular (RV) size and function from echocardiographic images. We included 12,684 examinations with corresponding written reports for text classification. After manual annotation of 1489 reports, we trained an NLP model to classify the remaining 10,651 reports. A view classifier was developed to select the 4-chamber or RV-focused view from an echocardiographic examination (n = 539). The final models were two image classification models trained on the predicted labels from the combined manual annotation and NLP models and the corresponding echocardiographic view to assess RV function (training set n = 11,008) and size (training set n = 9951. The text classifier identified impaired RV function with 99% sensitivity and 98% specificity and RV enlargement with 98% sensitivity and 98% specificity. The view classification model identified the 4-chamber view with 92% accuracy and the RV-focused view with 73% accuracy. The image classification models identified impaired RV function with 93% sensitivity and 72% specificity and an enlarged RV with 80% sensitivity and 85% specificity; agreement with the written reports was substantial (both κ = 0.65). Our findings show that models for automatic image assessment can be trained to classify RV size and function by using model-annotated data from written echocardiography reports. This pipeline for auto-annotation of the echocardiographic images, using a NLP model with medical reports as input, can be used to train an image-assessment model without manual annotation of images and enables fast and inexpensive expansion of the training dataset when needed. © 2022
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17. |
- Olivo, G., et al.
(author)
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Immediate effects of a single session of physical exercise on cognition and cerebral blood flow: A randomized controlled study of older adults
- 2021
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In: Neuroimage. - : Elsevier BV. - 1053-8119 .- 1095-9572. ; 225
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Journal article (peer-reviewed)abstract
- Background: Regular physical activity is beneficial for cognitive performance in older age. A single bout of aerobic physical exercise can transiently improve cognitive performance. Researchers have advanced improvements in cerebral circulation as a mediator of long-term effects of aerobic physical exercise on cognition, but the immediate effects of exercise on cognition and cerebral perfusion are not well characterized and the effects in older adults are largely unknown. Methods: Forty-nine older adults were randomized to a 30-min aerobic exercise at moderate intensity or relaxation. Groups were matched on age and cardiovascular fitness (VO2 max). Average Grey Matter Blood Flow (GMBF), measured by a pulsed arterial-spin labeling (pASL) magnetic resonance imaging (MRI) acquisition, and working memory performance, measured by figurative n-back tasks with increasing loads were assessed before and 7 min after exercising/resting. Results: Accuracy on the n-back task increased from before to after exercising/resting regardless of the type of activity. GMBF decreased after exercise, relative to the control (resting) group. In the exercise group, higher n-back performance after exercise was associated with lower GMBF in the right hippocampus, left medial frontal cortex and right orbitofrontal cortex, and higher cardiovascular fitness was associated with lower GMBF. Conclusion: The decrease of GMBF reported in younger adults shortly after exercise also occurs in older adults and relates to cardiovascular fitness, potentially supporting the link between cardiovascular fitness and cerebrovascular reactivity in older age.
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18. |
- Forssell-Aronsson, Eva, 1961, et al.
(author)
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THE IMPACT OF CIRCADIAN RHYTHMS ON MEDICAL IMAGING AND RADIOTHERAPY REGIMES FOR THE PAEDIATRIC PATIENT
- 2017
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In: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 0144-8420 .- 1742-3406. ; 173:1-3, s. 16-20
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Journal article (peer-reviewed)abstract
- Daily rhythmic changes are found in cellular events in cell cycle, DNA repair, apoptosis and angiogenesis in both normal and tumour tissue, as well as in enzymatic activity and drug metabolism. In this paper, we hypothesize that circadian rhythms need to be considered in radiation protection and optimization in personalized medicine, especially for paediatric care. The sensitivity of the eye lens to ionizing radiation makes the case for limiting damage to the lens epithelium by planning medical radio-imaging procedures for the afternoon, rather than the morning. Equally, the tumour and normal tissue response to radiotherapy is also subject to diurnal variation enabling optimization of time of treatment.
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19. |
- Grynne, A., et al.
(author)
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Women's experience of the health information process involving a digital information tool before commencing radiation therapy for breast cancer : a deductive interview study
- 2023
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In: BMC Health Services Research. - : BioMed Central (BMC). - 1472-6963. ; 23:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: Individuals undergoing radiation therapy for breast cancer frequently request information before, throughout and after the treatment as a means to reduce distress. Nevertheless, the provision of information to meet individuals needs from their level of health literacy is often overlooked. Thus, individuals information needs are often unmet, leading to reports of discontent. Internet and digital information technology has significantly augmented the available information and changed the way in which persons accesses and comprehends information. As health information is no longer explicitly obtained from healthcare professionals, it is essential to examine the sequences of the health information process in general, and in relation to health literacy. This paper reports on qualitative interviews, targeting women diagnosed with breast cancer who were given access to a health information technology tool, Digi-Do, before commencing radiation therapy, during, and after treatment. METHODS: A qualitative research design, inspired by the integrated health literacy model, was chosen to enable critical reflection by the participating women. Semi-structured interviews were conducted with 15 women with access to a digital information tool, named Digi-Do, in addition to receiving standard information (oral and written) before commencing radiation therapy, during, and after treatment. A deductive thematic analysis process was conducted. RESULTS: The results demonstrate how knowledge, competence, and motivation influence women's experience of the health information process. Three main themes were found: Meeting interactive and personal needs by engaging with health information; Critical recognition of sources of information; and Capability to communicate comprehended health information. The findings reflect the women's experience of the four competencies: to access, understand, appraise, and apply, essential elements of the health information process. CONCLUSIONS: We can conclude that there is a need for tailored digital information tools, such as the Digi-Do, to enable iterative access and use of reliable health information before, during and after the radiation therapy process. The Digi-Do can be seen as a valuable complement to the interpersonal communication with health care professionals, facilitating a better understanding, and enabling iterative access and use of reliable health information before, during and after the radiotherapy treatment. This enhances a sense of preparedness before treatment starts.
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20. |
- Almén, Anja, et al.
(author)
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Challenges assessing radiation risk in image-guided treatments-implications on optimisation of radiological protection
- 2018
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In: Journal of Radiological Protection. - : IOP Publishing. - 0952-4746 .- 1361-6498. ; 38:3, s. 1064-1076
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Journal article (peer-reviewed)abstract
- The present work explores challenges when assessing organ dose and effective dose concerning image-guided treatments. During these treatments considerable x-ray imaging is employed using technically advanced angiographic x-ray equipment. Thus, the radiation dose to organs and the related radiation risk are relatively difficult to assess. This has implications on the optimisation process, in which assessing radiation dose is one important part. In this study, endovascular aortic repair treatments were investigated. Organ dose and effective dose were assessed using Monte Carlo calculations together with a detailed specification of the exposure situation and patient size. The resulting normalised organ dose and effective dose with respect to kerma-area product for patient sizes and radiation qualities representative for the patient group were evaluated. The variability and uncertainty were investigated and their possible impact on optimisation of radiation protection was discussed. Exposure parameters, source to detector distances etc varied between treatments and also varied between image acquisitions during one treatment. Thus the derived normalised organ dose and effective dose exhibited a large range of values depending greatly on used exposure parameters and patient configuration. The derived normalised values for effective dose varied approximately between 0.05 and 0.30 mSv per Gy.cm(2) when taking patient sizes and exposure parameters into consideration, the values for organ doses exhibited even larger variation. The study shows a possible systematic error for derived organ doses and effective dose up to a factor of 7 if detailed exposure or patient characteristics are not known and/or not taken into consideration. The intra-treatment variability was also substantial and the normalised dose values varied up to a factor of 2 between image acquisitions during one treatment. The study shows that the use of conversion factors that are not adapted to the clinic can cause the radiation dose to be exaggerated or underestimated considerably. A conclusion from the present study is that the systematic error could be large and should be estimated together with random errors. A large uncertainty makes it difficult to detect true differences in radiation dose between methods and technology-a prerequisite for optimising radiation protection for image-guided treatments.
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21. |
- Sund, Patrik
(author)
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IMPROVING IMAGE QUALITY BY INCREASING THE AMOUNT OF LIGHT IN THE READING ROOM
- 2021
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In: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 0144-8420 .- 1742-3406. ; 195:3-4, s. 426-433
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Journal article (peer-reviewed)abstract
- Many standards and guidelines related to the use of medical displays require viewers to be in dark rooms. The purpose of this theoretical study was to examine the validity of some commonly used requirements in terms of image contrast and contrast stability in rooms with fluctuating illuminance. By using the grayscale standard display function (Dicom part 14), contrast was calculated for several combinations of display minimum and maximum luminance as well as the possible range of illuminance fluctuations that will not exceed given contrast tolerance levels. The results show that some requirements are only valid in dark viewing rooms, which are also usually recommended or enforced. However, image contrast, contrast stability, ergonomics and fatigue would improve by using brighter displays in brighter rooms. With a better set of requirements, it would also be possible for displays in brighter rooms, like dentist departments and operating rooms, to conform to the requirements.
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22. |
- Sadik, May, 1970, et al.
(author)
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Artificial Intelligence Increases the Agreement among Physicians Classifying Focal Skeleton/Bone Marrow Uptake in Hodgkin's Lymphoma Patients Staged with F-18 FDG PET/CT-a Retrospective Study
- 2023
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In: Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1869-3474 .- 1869-3482. ; 57:2, s. 110-116
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Journal article (peer-reviewed)abstract
- Purpose Classification of focal skeleton/bone marrow uptake (BMU) can be challenging. The aim is to investigate whether an artificial intelligence-based method (AI), which highlights suspicious focal BMU, increases interobserver agreement among a group of physicians from different hospitals classifying Hodgkin's lymphoma (HL) patients staged with [F-18]FDG PET/CT. Methods Forty-eight patients staged with [F-18]FDG PET/CT at Sahlgenska University Hospital between 2017 and 2018 were reviewed twice, 6 months apart, regarding focal BMU. During the second time review, the 10 physicians also had access to AI-based advice regarding focal BMU. Results Each physician's classifications were pairwise compared with the classifications made by all the other physicians, resulting in 45 unique pairs of comparisons both without and with AI advice. The agreement between the physicians increased significantly when AI advice was available, which was measured as an increase in mean Kappa values from 0.51 (range 0.25-0.80) without AI advice to 0.61 (range 0.19-0.94) with AI advice (p = 0.005). The majority of the physicians agreed with the AI-based method in 40 (83%) of the 48 cases. Conclusion An AI-based method significantly increases interobserver agreement among physicians working at different hospitals by highlighting suspicious focal BMU in HL patients staged with [F-18]FDG PET/CT.
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23. |
- Sundlöv, Anna, et al.
(author)
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Individualised Lu-177-DOTATATE treatment of neuroendocrine tumours based on kidney dosimetry
- 2017
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In: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 44:9, s. 1480-1489
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Journal article (peer-reviewed)abstract
- Purpose To present data from an interim analysis of a Phase II trial designed to determine the feasibility, safety, and efficacy of individualising treatment based on renal dosimetry, by giving as many cycles as possible within a maximum renal biologically effective dose (BED). Method Treatment was given with repeated cycles of 7.4 GBq 177Lu-DOTATATE at 8-12-week intervals. Detailed dosimetry was performed in all patients after each cycle using a hybrid method (SPECT + planar imaging). All patients received treatment up to a renal BED of 27 +/- 2 Gy (alpha/beta = 2.6 Gy) (Step 1). Selected patients were offered further treatment up to a renal BED of 40 +/- 2 Gy (Step 2). Renal function was followed by estimation and measurement of the glomerular filtration rate (GFR). Results Fifty-one patients were included in the present analysis. Among the patients who received treatment as planned, the median number of cycles in Step 1 was 5 (range 3-7), and for those who completed Step 2 it was 7 (range 5-8); 73% were able to receive >4 cycles. Although GFR decreased in most patients after the completion of treatment, no grade 3-4 toxicity was observed. Patients with a reduced baseline GFR seemed to have an increased risk of GFR decline. Five patients received treatment in Step 2, none of whom exhibited a significant reduction in renal function. Conclusions Individualising PRRT using renal dosimetry seems feasible and safe and leads to an increased number of cycles in the majority of patients. The trial will continue as planned.
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24. |
- Ge, Chenjie, 1991, et al.
(author)
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Multiscale Deep Convolutional Networks for Characterization and Detection of Alzheimer's Disease using MR Images
- 2019
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In: Proceedings - International Conference on Image Processing, ICIP. - 1522-4880. ; 2019-September, s. 789-793
-
Conference paper (peer-reviewed)abstract
- This paper addresses the issues of Alzheimer's disease (AD) characterization and detection from Magnetic Resonance Images (MRIs). Many existing AD detection methods use single-scale feature learning from brain scans. In this paper, we propose a multiscale deep learning architecture for learning AD features. The main contributions of the paper include: (a) propose a novel 3D multiscale CNN architecture for the dedicated task of AD detection; (b) propose a feature fusion and enhancement strategy for multiscale features; (c) empirical study on the impact of several settings, including two dataset partitioning approaches, and the use of multiscale and feature enhancement. Experiments were conducted on an open ADNI dataset (1198 brain scans from 337 subjects), test results have shown the effectiveness of the proposed method with test accuracy of 93.53%, 87.24% (best, average) on subject separated dataset, and 99.44%, 98.80% (best, average) on random brain scan-partitioned dataset. Comparison with eight existing methods has provided further support to the proposed method.
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25. |
- Reza, Salim, 1985-, et al.
(author)
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Smart dosimetry by pattern recognition using a single photon counting detector system in time over threshold mode
- 2012
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In: Journal of Instrumentation. - 1748-0221. ; 7:1
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Journal article (peer-reviewed)abstract
- The function of a dosimeter is to determine the absorbed dose of radiation, for those cases in which, generally, the particular type of radiation is already known. Lately, a number of applications have emerged in which all kinds of radiation are absorbed and are sorted by pattern recognition, such as the Medipix2 application in [1]. This form of smart dosimetry enables measurements where not only the total dosage is measured, but also the contributions of different types of radiation impacting upon the detector surface. Furthermore, the use of a photon counting system, where the energy deposition can be measured in each individual pixel, ensures measurements with a high degree of accuracy in relation to the pattern recognition. In this article a Timepix [2] detector system has been used in the creation of a smart dosimeter for Alpha, Beta and Gamma radiation. When a radioactive particle hits the detector surface it generates charge clusters and those impacting upon the detector surface are read out and image processing algorithms are then used to classify each charge cluster. The individual clusters are calculated and as a result, the dosage for each type of radiation is given. In some cases, several particles can impact in roughly the same place, forming overlapping clusters. In order to handle this problem, a cluster separation method has been added to the pattern recognition algorithm. When the clusters have been separated, they are classified by shape and sorted into the correct type of radiation. The algorithms and methods used in this dosimeter have been developed so as to be simple and computationally effective, in order to enable implementation on a portable device. © 2012 IOP Publishing Ltd and SISSA.
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26. |
- Borrelli, P., et al.
(author)
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Artificial intelligence-aided CT segmentation for body composition analysis: a validation study
- 2021
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In: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1
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Journal article (peer-reviewed)abstract
- BackgroundBody composition is associated with survival outcome in oncological patients, but it is not routinely calculated. Manual segmentation of subcutaneous adipose tissue (SAT) and muscle is time-consuming and therefore limited to a single CT slice. Our goal was to develop an artificial-intelligence (AI)-based method for automated quantification of three-dimensional SAT and muscle volumes from CT images.MethodsEthical approvals from Gothenburg and Lund Universities were obtained. Convolutional neural networks were trained to segment SAT and muscle using manual segmentations on CT images from a training group of 50 patients. The method was applied to a separate test group of 74 cancer patients, who had two CT studies each with a median interval between the studies of 3days. Manual segmentations in a single CT slice were used for comparison. The accuracy was measured as overlap between the automated and manual segmentations.ResultsThe accuracy of the AI method was 0.96 for SAT and 0.94 for muscle. The average differences in volumes were significantly lower than the corresponding differences in areas in a single CT slice: 1.8% versus 5.0% (p <0.001) for SAT and 1.9% versus 3.9% (p < 0.001) for muscle. The 95% confidence intervals for predicted volumes in an individual subject from the corresponding single CT slice areas were in the order of 20%.Conclusions The AI-based tool for quantification of SAT and muscle volumes showed high accuracy and reproducibility and provided a body composition analysis that is more relevant than manual analysis of a single CT slice.
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27. |
- Ying, T. M., et al.
(author)
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Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer
- 2021
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In: European Radiology Experimental. - : Springer Science and Business Media LLC. - 2509-9280. ; 5:1
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Journal article (peer-reviewed)abstract
- Background Radical cystectomy for urinary bladder cancer is a procedure associated with a high risk of complications, and poor overall survival (OS) due to both patient and tumour factors. Sarcopenia is one such patient factor. We have developed a fully automated artificial intelligence (AI)-based image analysis tool for segmenting skeletal muscle of the torso and calculating the muscle volume. Methods All patients who have undergone radical cystectomy for urinary bladder cancer 2011-2019 at Sahlgrenska University Hospital, and who had a pre-operative computed tomography of the abdomen within 90 days of surgery were included in the study. All patients CT studies were analysed with the automated AI-based image analysis tool. Clinical data for the patients were retrieved from the Swedish National Register for Urinary Bladder Cancer. Muscle volumes dichotomised by the median for each sex were analysed with Cox regression for OS and logistic regression for 90-day high-grade complications. The study was approved by the Swedish Ethical Review Authority (2020-03985). Results Out of 445 patients who underwent surgery, 299 (67%) had CT studies available for analysis. The automated AI-based tool failed to segment the muscle volume in seven (2%) patients. Cox regression analysis showed an independent significant association with OS (HR 1.62; 95% CI 1.07-2.44; p = 0.022). Logistic regression did not show any association with high-grade complications. Conclusion The fully automated AI-based CT image analysis provides a low-cost and meaningful clinical measure that is an independent biomarker for OS following radical cystectomy.
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28. |
- Pettersson, Erik, 1987, et al.
(author)
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COMPARISON OF METAL ARTEFACTS FOR DIFFERENT DUAL ENERGY CT TECHNIQUES
- 2021
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In: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 0144-8420 .- 1742-3406. ; 195:3-4, s. 232-245
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Journal article (peer-reviewed)abstract
- This study compares dual-energy computed tomography (DECT) images of a phantom including different material inserts and with additional lateral titanium or stainless steel inserts, simulating bilateral hip prostheses. Dual-source (DS) and fast kV-switching (FKS) DECT with/without metal artefact reduction (MAR) were compared with regards to virtually monoenergetic CT number accuracy and the depiction of different materials. Streak artefacts were observed between the metal inserts that were more severe with steel compared to titanium inserts. The artefact severity and CT number accuracy depended on the photon energy (keV) for both DECT techniques. While MAR generally increased the CT number accuracy and material depiction within the streak artefacts, it sometimes decreased the accuracy outside the streak artefacts for both DS and FKS. FKS depicted the metal inserts more accurately than DS with regards to both CT numbers and external diameter.
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29. |
- Hagmarker, Linn, et al.
(author)
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Bone Marrow Absorbed Doses and Correlations with Hematologic Response During Lu-177-DOTATATE Treatments Are Influenced by Image-Based Dosimetry Method and Presence of Skeletal Metastases
- 2019
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In: Journal of Nuclear Medicine. - : Society of Nuclear Medicine. - 0161-5505 .- 2159-662X. ; 60:10, s. 1406-1413
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Journal article (peer-reviewed)abstract
- This study aimed to compare different image-based methods for bone marrow dosimetry and study the dose-response relationship during treatment with Lu-177-DOTATATE in patients with and without skeletal metastases. Methods: This study included 46 patients with advanced neuroendocrine tumors treated with at least 2 fractions of Lu-177-DOTATATE at Sahlgrenska University Hospital. High- and low-uptake compartments were automatically outlined in planar images collected at 2, 24, 48, and 168 h after injection. The bone marrow absorbed doses were calculated from the cross doses of the high- and low-uptake compartments and the self-dose, using the time-activity concentration curve for the low-uptake compartment. This time-activity concentration curve was adjusted using a fixed constant of 1.8 for the planar dosimetry method and using the activity concentrations in vertebral bodies in SPECT images at 24 h after injection of Lu-177-DOTATATE in 4 hybrid methods: L4-SPECT used the activity concentration in the L4 vertebra, whereas V-SPECT, L-SPECT, and T-SPECT used the median activity concentration in all visible vertebrae, lumbar vertebrae, and thoracic vertebrae, respectively. Results: Using the planar method, L4-SPECT, V-SPECT, L-SPECT, and T-SPECT, the estimated median bone marrow absorbed doses were 0.19, 0.36, 0.40, 0.39, and 0.46 Gy/7.4 GBq, respectively, with respective ranges of 0.12-0.33, 0.15-1.44, 0.19-1.71, 0.21-1.60, and 0.18-2.12 Gy/7.4 GBq. For all methods, the bone marrow absorbed dose significantly correlated with decreased platelet counts. This correlation increased after treatment fraction 2: the Spearman correlation (r(s)) were -0.49 for the planar method, -0.61 for L4-SPECT, -0.63 for V-SPECT, -0.63 for L-SPECT, and -0.57 for T-SPECT. A separate analysis revealed an increased correlation for patients without skeletal metastases using the planar method (r(s) = -0.67). In contrast, hybrid methods had poor correlations for patients without metastases and stronger correlations for patients with skeletal metastases (r(s) = -0.61 to -0.74). The mean bone marrow absorbed doses were 3%-69% higher for patients with skeletal metastases than for patients without. Conclusion: The estimated bone marrow absorbed doses by image-based techniques and the correlation with platelets are influenced by the choice of measured vertebrae and the presence of skeletal metastases.
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30. |
- Nilsson, Christer, et al.
(author)
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Tracking the neurodegeneration of parkinsonian disorders - A pilot study
- 2007
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In: Neuroradiology. - : Springer Science and Business Media LLC. - 1432-1920 .- 0028-3940. ; 49:2, s. 111-119
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Journal article (peer-reviewed)abstract
- The purpose of the study was to explore the possibilities of using diffusion tensor imaging (DTI) and tractography (DTT) for the differential diagnosis and monitoring of disease progression in idiopathic Parkinson's disease (IPD), compared with the atypical parkinsonian disorders multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). A 3.0-T MR scanner was used. DTI was acquired using a single-shot EPI sequence with diffusion encoding in 32 directions and a voxel size of 2×2×2 mm3. DTI data were analysed and DTT was performed using the PRIDE fibre tracking tool supplied by the manufacturer. The fractional anisotropy (FA) and apparent diffusion coefficient (ADC) within each tract were determined. DTI and DTT images in patients with moderate to advanced MSA demonstrated degeneration of the middle cerebellar peduncles and pontine crossing tracts, with decreased FA and increased ADC. This accounted for most of the pontine and cerebellar atrophy characteristic of this disease. In contrast, patients with PSP showed a selective degeneration of the superior cerebellar peduncle. Three-dimensional images of whole-brain white matter tracts demonstrated a reduction of cortical projection fibres in all patients with PSP. Visualization of the selective degeneration of individual fibre tracts, using DTI and DTT, adds qualitative data facilitating the differential diagnosis of parkinsonian disorders. Repeated measurements of FA and ADC values in a whole fibre tract might be used for monitoring disease progression and studying the effect of treatment in neuroprotective trials. The results are preliminary considering the small number of subjects in the study. © Springer-Verlag 2007.
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31. |
- Schöll, Michael, 1980, et al.
(author)
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Biomarkers for tau pathology.
- 2019
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In: Molecular and cellular neurosciences. - : Elsevier BV. - 1095-9327 .- 1044-7431. ; 97, s. 18-33
-
Research review (peer-reviewed)abstract
- The aggregation of fibrils of hyperphosphorylated and C-terminally truncated microtubule-associated tau protein characterizes 80% of all dementia disorders, the most common neurodegenerative disorders. These so-called tauopathies are hitherto not curable and their diagnosis, especially at early disease stages, has traditionally proven difficult. A keystone in the diagnosis of tauopathies was the development of methods to assess levels of tau protein in vivo in cerebrospinal fluid, which has significantly improved our knowledge about these conditions. Tau proteins have also been measured in blood, but the importance of tau-related changes in blood is still unclear. The recent addition of positron emission tomography ligands to visualize, map and quantify tau pathology has further contributed with information about the temporal and spatial characteristics of tau accumulation in the living brain. Together, the measurement of tau with fluid biomarkers and positron emission tomography constitutes the basis for a highly active field of research. This review describes the current state of biomarkers for tau biomarkers derived from neuroimaging and from the analysis of bodily fluids and their roles in the detection, diagnosis and prognosis of tau-associated neurodegenerative disorders, as well as their associations with neuropathological findings, and aims to provide a perspective on how these biomarkers might be employed prospectively in research and clinical settings.
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32. |
- Rothenberg, Elisabet, et al.
(author)
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Texture-modified meat and carrot products for elderly people with dysphagia : preference in relation to health and oral status
- 2007
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In: Scandinavian Journal of Food and Nutrition. - : Taylor & Francis. - 1748-2976 .- 1748-2984. ; 51:4, s. 141-147
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Journal article (peer-reviewed)abstract
- Background: Reduced taste and smell, chewing problems and swallowing dysfunction are common among elderly people and affect perception, food choice and the ability to eat. Objective: To study the preference for texture-modified carrot and meat products in elderly people aiming to meet the needs of people with impaired chewing and/or swallowing. Design: Data were collected using questionnaires focusing on health, oral status and preference for the products. Altogether, 108 elderly people in ordinary housing (OH) and 50 living in special housing (SH) in Malmö (SH-M) and Göteborg (SH-G) participated. Results: 19% had a body mass index 522, predominantly in SH (24%). Stroke was reported by 20% of the subjects in SH. Among those with subjectively experienced difficulties in swallowing (12%), 58% reported coughing, 21% a gurgly voice in association with food intake and 50% obstruction during swallowing. Only 20% with subjective swallowing difficulties had been specifically examined regarding this problem. All the tested products were easy to masticate and swallow. Compared with OH, people in SH-M found the meatproducts easier to masticate and swallow. Compared with OH, subjects in SH found the carrot products easier to masticate. Conclusions: There is a need to develop tasty texture-modified nutritious food products for people with mastication and/or swallowing problems. Possible factors for differences in preference between groups, in this study OH and SH, may be related to health status in general and specifically mastication and swallowing functions.
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33. |
- Ali, Muhaddisa Barat, 1986, et al.
(author)
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Multi-stream Convolutional Autoencoder and 2D Generative Adversarial Network for Glioma Classification
- 2019
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In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11678 LNCS, s. 234-245
-
Conference paper (peer-reviewed)abstract
- Diagnosis and timely treatment play an important role in preventing brain tumor growth. Deep learning methods have gained much attention lately. Obtaining a large amount of annotated medical data remains a challenging issue. Furthermore, high dimensional features of brain images could lead to over-fitting. In this paper, we address the above issues. Firstly, we propose an architecture for Generative Adversarial Networks to generate good quality synthetic 2D MRIs from multi-modality MRIs (T1 contrast-enhanced, T2, FLAIR). Secondly, we propose a deep learning scheme based on 3-streams of Convolutional Autoencoders (CAEs) followed by sensor information fusion. The rational behind using CAEs is that it may improve glioma classification performance (as comparing with conventional CNNs), since CAEs offer noise robustness and also efficient feature reduction hence possibly reduce the over-fitting. A two-round training strategy is also applied by pre-training on GAN augmented synthetic MRIs followed by refined-training on original MRIs. Experiments on BraTS 2017 dataset have demonstrated the effectiveness of the proposed scheme (test accuracy 92.04%). Comparison with several exiting schemes has provided further support to the proposed scheme.
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34. |
- Andersson, Elisabeth, et al.
(author)
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Surveillance of indeterminate pulmonary nodules detected with CT in a Swedish population-based study (SCAPIS) : Psychosocial consequences and impact on health-related quality of life - A multicentre prospective cross-sectional study
- 2021
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In: BMJ Open. - : BMJ Publishing Group Ltd. - 2044-6055. ; 11:9
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Journal article (peer-reviewed)abstract
- Objectives: To investigate whether surveillance of pulmonary nodules detected with low-dose CT (LDCT) impacted health-related quality of life and psychosocial consequences in the Swedish population-based study, Swedish CArdioPulmonary bioImage Study (SCAPIS).Design: A prospective cross-sectional study.Settings and participants: This multicentre (five sites) observational study, which included a cohort from SCAPIS, consisted of 632 participants with indeterminate pulmonary nodules detected with LDCT. These participants continued surveillance for up to 36 months, during which lung cancer was not detected (surveillance group). Additionally, 972 participants with a negative pulmonary LDCT scan were included as a control group. Matching criteria were LDCT date (±2 weeks), gender and site.Outcome measures: All participants completed a health-related quality of life questionnaire (RAND-36) and the Consequences of Screening (COS) questionnaire, an average of 3 years after LDCT was conducted at entry into SCAPIS.Results: Participants were 51-70 years old at study commencement. Overall, the two groups did not differ in demographic or psychosocial variables, smoking habits or pulmonary medical history. Individuals from countries other than Sweden and those with low socioeconomic status were less likely to participate (p<0.001). No effects on health-related quality of life were observed via RAND-36. In COS, the surveillance group demonstrated a higher OR for anxiety about lung cancer (OR 3.96, 95% CI 2.35 to 6.66, p<0.001), experiencing a sense of dejection (OR 1.35, 95% CI 1.06 to 1.72, p=0.015) and thoughts about existential values (OR 1.30, 95% CI 1.04 to 1.60, p=0.018).Conclusions: Lung surveillance with LDCT contributed to significant experiences of sense of dejection, anxiety about lung cancer and development of thoughts about existential values among participants in the surveillance group compared with the controls. The risk of side effects should be communicated for informed decision-making about (non-)attendance in lung cancer screening.
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35. |
- Ahlander, Britt-Marie, 1954-, et al.
(author)
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Development and validation of a questionnaire evaluating patient anxiety during Magnetic Resonance Imaging : the Magnetic Resonance Imaging- Anxiety Questionnaire (MRI-AQ)
- 2016
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In: Journal of Advanced Nursing. - : Wiley-Blackwell. - 0309-2402 .- 1365-2648. ; 72:6, s. 1368-1380
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Journal article (peer-reviewed)abstract
- Aim: To develop and validate a new instrument measuring patient anxiety during Magnetic Resonance Imaging examinations, Magnetic Resonance Imaging-Anxiety Questionnaire.Background: Questionnaires measuring patients’ anxiety during Magnetic Resonance Imaging examinations have been the same as used in a wide range of conditions. To learn about patients’ experience during examination and to evaluate interventions, a specific questionnaire measuring patient anxiety during Magnetic Resonance Imaging is needed.Design: Psychometric cross-sectional study with test-retest design.Methods: A new questionnaire, Magnetic Resonance Imaging-Anxiety Questionnaire, was designed from patient expressions of anxiety in Magnetic Resonance Imagingscanners. The sample was recruited between October 2012–October 2014. Factor structure was evaluated with exploratory factor analysis and internal consistency with Cronbach’s alpha. Criterion-related validity, known-group validity and test-retest was calculated.Results: Patients referred for Magnetic Resonance Imaging of either the spine or the heart, were invited to participate. The development and validation of Magnetic Resonance Imaging-Anxiety Questionnaire resulted in 15 items consisting of two factors. Cronbach’s alpha was found to be high. Magnetic Resonance Imaging-Anxiety Questionnaire correlated higher with instruments measuring anxiety than with depression scales. Known-group validity demonstrated a higher level of anxiety for patients undergoing Magnetic Resonance Imaging scan of the heart than for those examining the spine. Test-retest reliability demonstrated acceptable level for the scale.Conclusion: Magnetic Resonance Imaging-Anxiety Questionnaire bridges a gap among existing questionnaires, making it a simple and useful tool for measuring patient anxiety during Magnetic Resonance Imaging examinations.
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36. |
- Nyholm, Tufve, et al.
(author)
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A national approach for automated collection of standardized and population-based radiation therapy data in Sweden
- 2016
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In: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140 .- 1879-0887. ; 119:2, s. 344-350
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Journal article (peer-reviewed)abstract
- Purpose: To develop an infrastructure for structured and automated collection of interoperable radiation therapy (RT) data into a national clinical quality registry. Materials and methods: The present study was initiated in 2012 with the participation of seven of the 15 hospital departments delivering RT in Sweden. A national RT nomenclature and a database for structured unified storage of RT data at each site (Medical Information Quality Archive, MIQA) have been developed. Aggregated data from the MIQA databases are sent to a national RT registry located on the same IT platform (INCA) as the national clinical cancer registries. Results: The suggested naming convention has to date been integrated into the clinical workflow at 12 of 15 sites, and MIQA is installed at six of these. Involvement of the remaining 3/15 RT departments is ongoing, and they are expected to be part of the infrastructure by 2016. RT data collection from ARIA (R), Mosaiq (R), Eclipse (TM), and Oncentra (R) is supported. Manual curation of RT-structure information is needed for approximately 10% of target volumes, but rarely for normal tissue structures, demonstrating a good compliance to the RT nomenclature. Aggregated dose/volume descriptors are calculated based on the information in MIQA and sent to INCA using a dedicated service (MIQA2INCA). Correct linkage of data for each patient to the clinical cancer registries on the INCA platform is assured by the unique Swedish personal identity number. Conclusions: An infrastructure for structured and automated prospective collection of syntactically inter operable RT data into a national clinical quality registry for RT data is under implementation. Future developments include adapting MIQA to other treatment modalities (e.g. proton therapy and brachytherapy) and finding strategies to harmonize structure delineations. How the RT registry should comply with domain-specific ontologies such as the Radiation Oncology Ontology (ROO) is under discussion.
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37. |
- Ge, Chenjie, 1991, et al.
(author)
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Multi-Stream Multi-Scale Deep Convolutional Networks for Alzheimer's Disease Detection using MR Images
- 2019
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In: Neurocomputing. - : Elsevier BV. - 0925-2312 .- 1872-8286. ; 350, s. 60-69
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Journal article (peer-reviewed)abstract
- This paper addresses the issue of Alzheimer's disease (AD) detection from Magnetic Resonance Images (MRIs). Existing AD detection methods rely on global feature learning from the whole brain scans, while depending on the tissue types, AD related features in dierent tissue regions, e.g. grey matter (GM), white matter (WM), and cerebrospinal uid (CSF), show different characteristics. In this paper, we propose a deep learning method for multi-scale feature learning based on segmented tissue areas. A novel deep 3D multi-scale convolutional network scheme is proposed to generate multi-resolution features for AD detection. The proposed scheme employs several parallel 3D multi-scale convolutional networks, each applying to individual tissue regions (GM, WM and CSF) followed by feature fusions. The proposed fusion is applied in two separate levels: the rst level fusion is applied on different scales within the same tissue region, and the second level is on dierent tissue regions. To further reduce the dimensions of features and mitigate overtting, a feature boosting and dimension reduction method, XGBoost, is utilized before the classication. The proposed deep learning scheme has been tested on a moderate open dataset of ADNI (1198 scans from 337 subjects), with excellent test performance on randomly partitioned datasets (best 99.67%, average 98.29%), and good test performance on subject-separated partitioned datasets (best 94.74%, average 89.51%). Comparisons with state-of-the-art methods are also included.
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38. |
- Klintström, Eva, et al.
(author)
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Trabecular bone microstructure analysis on data from a novel twin robotic X-ray device
- 2023
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In: Acta Radiologica. - : SAGE Publications. - 0284-1851 .- 1600-0455. ; 64:4, s. 1566-1572
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Journal article (peer-reviewed)abstract
- Background: Bone strength is related to both mineral density (BMD) and the bone microstructure. However, only the assessment of BMD is available in clinical routine care today. Purpose: To analyze and study the correlation of trabecular bone microstructure from the imaging data of a prototype Multitom Rax system, using micro-computed tomography (CT) data as the reference method (Skyscan 1176).Material and Methods: Imaging data from 14 bone samples from the human radius were analyzed regarding six bone structure parameters, i.e. trabecular nodes, separation, spacing, and thickness as well as bone volume (BV/TV) and structural model index (SMI).Results: All six structure parameters showed strong correlations to micro-CT with Spearman correlation coefficients in the range of 0.83–0.93. BV/TV and SMI had a correlation >0.90. Two of the parameters, namely, separation and number, had mean values in the same range as micro-CT. The other four were either over- or underestimated.Conclusion: The strong correlation between micro-CT and the clinical imaging system, indicates the possibility for analyzing bone microstructure with potential to add value in fracture assessment using the studied device in a clinical workflow.
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39. |
- Gryska, Emilia, 1992, et al.
(author)
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Deep learning for automatic brain tumour segmentation on MRI: evaluation of recommended reporting criteria via a reproduction and replication study.
- 2022
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In: BMJ open. - : BMJ. - 2044-6055. ; 12:7
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Journal article (peer-reviewed)abstract
- To determine the reproducibility and replicability of studies that develop and validate segmentation methods for brain tumours on MRI and that follow established reproducibility criteria; and to evaluate whether the reporting guidelines are sufficient.Two eligible validation studies of distinct deep learning (DL) methods were identified. We implemented the methods using published information and retraced the reported validation steps. We evaluated to what extent the description of the methods enabled reproduction of the results. We further attempted to replicate reported findings on a clinical set of images acquired at our institute consisting of high-grade and low-grade glioma (HGG, LGG), and meningioma (MNG) cases.We successfully reproduced one of the two tumour segmentation methods. Insufficient description of the preprocessing pipeline and our inability to replicate the pipeline resulted in failure to reproduce the second method. The replication of the first method showed promising results in terms of Dice similarity coefficient (DSC) and sensitivity (Sen) on HGG cases (DSC=0.77, Sen=0.88) and LGG cases (DSC=0.73, Sen=0.83), however, poorer performance was observed for MNG cases (DSC=0.61, Sen=0.71). Preprocessing errors were identified that contributed to low quantitative scores in some cases.Established reproducibility criteria do not sufficiently emphasise description of the preprocessing pipeline. Discrepancies in preprocessing as a result of insufficient reporting are likely to influence segmentation outcomes and hinder clinical utilisation. A detailed description of the whole processing chain, including preprocessing, is thus necessary to obtain stronger evidence of the generalisability of DL-based brain tumour segmentation methods and to facilitate translation of the methods into clinical practice.
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40. |
- Glans, Anton, et al.
(author)
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Health effects related to exposure of static magnetic fields and acoustic noise-comparison between MR and CT radiographers
- 2022
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In: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 32, s. 7896-7909
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Journal article (peer-reviewed)abstract
- Objectives We explored the prevalence of health complaints subjectively associated with static magnetic field (SMF) and acoustic noise exposure among MR radiographers in Sweden, using CT radiographers as a control group. Additionally, we explored radiographers' use of strategies to mitigate adverse health effects. Methods A cross-sectional survey was sent to all hospitals with MR units in Sweden. MR and/or CT personnel reported prevalence and attribution of symptoms (vertigo/dizziness, nausea, metallic taste, illusion of movement, ringing sensations/tinnitus, headache, unusual drowsiness/tiredness, forgetfulness, difficulties concentrating, and difficulties sleeping) within the last year. We used logistic regression to test associations between sex, age, stress, SMF strength, working hours, and symptom prevalence. Data regarding hearing function, work-environmental noise, and strategies to mitigate adverse symptoms were also analysed. Results In total, 529 out of 546 respondents from 86 hospitals were eligible for participation. A >= 20 working hours/week/modality cut-off rendered 342 participants grouped into CT (n = 75), MR (n = 121), or mixed personnel (n = 146). No significant differences in symptom prevalence were seen between groups. Working at >= 3T increased SMF-associated symptoms as compared with working at <= 1.5T (OR: 2.03, CI95: 1.05-3.93). Stress was a significant confounder. Work-related noise was rated as more troublesome by CT than MR personnel (p < 0.01). MR personnel tended to use more strategies to mitigate adverse symptoms. Conclusion No significant differences in symptom prevalence were seen between MR and CT radiographers. However, working at 3T increased the risk of SMF symptoms, and stress increased adverse health effects. Noise nuisance was considered more problematic by CT than MR personnel.
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41. |
- Nakajima, K., et al.
(author)
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Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study
- 2017
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In: European Journal of Nuclear Medicine and Molecular Imaging. - : Springer Science and Business Media LLC. - 1619-7070 .- 1619-7089. ; 44:13, s. 2280-2289
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Journal article (peer-reviewed)abstract
- Purpose Artificial neural networks (ANN) might help to diagnose coronary artery disease. This study aimed to determine whether the diagnostic accuracy of an ANN-based diagnostic system and conventional quantitation are comparable. Methods The ANN was trained to classify potentially abnormal areas as true or false based on the nuclear cardiology expert interpretation of 1001 gated stress/rest Tc-99m-MIBI images at 12 hospitals. The diagnostic accuracy of the ANN was compared with 364 expert interpretations that served as the gold standard of abnormality for the validation study. Conventional summed stress/rest/difference scores (SSS/SRS/SDS) were calculated and compared with receiver operating characteristics (ROC) analysis. Results The ANN generated a better area under the ROC curves (AUC) than SSS (0.92 vs. 0.82, p < 0.0001), indicating better identification of stress defects. The ANN also generated a better AUC than SDS (0.90 vs. 0.75, p < 0.0001) for stress-induced ischemia. The AUC for patients with old myocardial infarction based on rest defects was 0.97 (0.91 for SRS, p = 0.0061), and that for patients with and without a history of revascularization based on stress defects was 0.94 and 0.90 (p = 0.0055 and p < 0.0001 vs. SSS, respectively). The SSS/SRS/SDS steeply increased when ANN values (probability of abnormality) were > 0.80. Conclusion The ANN was diagnostically accurate in various clinical settings, including that of patients with previous myocardial infarction and coronary revascularization. The ANN could help to diagnose coronary artery disease.
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42. |
- Norrman, Eva, et al.
(author)
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Optimization of image process parameters through factorial experiments using a flat panel detector
- 2007
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In: Physics in Medicine and Biology. - Bristol : IOP publishing. - 0031-9155 .- 1361-6560. ; 52:17, s. 5263-5276
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Journal article (peer-reviewed)abstract
- In the optimization process of lumbar spine examinations, factorial experiments were performed addressing the question of whether the effective dose can be reduced and the image quality maintained by adjusting the image processing parameters. A 2(k)-factorial design was used which is a systematic and effective method of investigating the influence of many parameters on a result variable. Radiographic images of a Contrast Detail phantom were exposed using the default settings of the process parameters for lumbar spine examinations. The image was processed using different settings of the process parameters. The parameters studied were ROI density, gamma, detail contrast enhancement (DCE), noise compensation, unsharp masking and unsharp masking kernel (UMK). The images were computer analysed and an image quality figure (IQF) was calculated and used as a measurement of the image quality. The parameters with the largest influence on image quality were noise compensation, unsharp masking, unsharp masking kernel and detail contrast enhancement. There was an interaction between unsharp masking and kernel indicating that increasing the unsharp masking improved the image quality when combined with a large kernel size. Combined with a small kernel size however the unsharp masking had a deteriorating effect. Performing a factorial experiment gave an overview of how the image quality was influenced by image processing. By adjusting the level of noise compensation, unsharp masking and kernel, the IQF was improved to a 30% lower effective dose.
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43. |
- Nocum, D. J., et al.
(author)
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Predictors of radiation dose for uterine artery embolisation are angiography system-dependent
- 2022
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In: Journal of Radiological Protection. - : IOP Publishing. - 0952-4746 .- 1361-6498. ; 42:1
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Journal article (peer-reviewed)abstract
- This study sought to achieve radiation dose reductions for patients receiving uterine artery embolisation (UAE) by evaluating radiation dose measurements for the preceding generation (Allura) and upgraded (Azurion) angiography system. Previous UAE regression models in the literature could not be applied to this centre's practice due to being based on different angiography systems and radiation dose predictor variables. The aims of this study were to establish whether radiation dose is reduced with the upgraded angiography system and to develop a regression model to determine predictors of radiation dose specific to the upgraded angiography system. A comparison between Group I (Allura, n = 95) and Group II (Azurion, n = 95) demonstrated a significant reduction in kerma-area product (KAP) and Ka, r (reference air kerma) by 63% (143.2 Gy cm(2) vs 52.9 Gy cm(2); P < 0.001, d = 0.8) and 67% (0.6 Gy vs 0.2 Gy; P < 0.001, d = 0.8), respectively. The multivariable linear regression (MLR) model identified the UAE radiation dose predictors for KAP on the upgraded angiography system as total fluoroscopy dose, Ka, r, and total uterus volume. The predictive accuracy of the MLR model was assessed using a Bland-Altman plot. The mean difference was 0.39 Gy cm(2) and the limits of agreement were +28.49 and -27.71 Gy cm(2), and thus illustrated no proportional bias. The resultant MLR model was considered system-dependent and validated the upgraded angiography system and its advance capabilities to significantly reduce radiation dose. Interventional radiologist and interventional radiographer familiarisation of the system's features and the implementation of the newly established MLR model would further facilitate dose optimisation for all centres performing UAE procedures using the upgraded angiography system.
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44. |
- Nocum, D. J., et al.
(author)
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UTERINE ARTERY EMBOLISATION: CONTINUOUS QUALITY IMPROVEMENT REDUCES RADIATION DOSE WHILE MAINTAINING IMAGE QUALITY
- 2021
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In: Radiation Protection Dosimetry. - : Oxford University Press (OUP). - 0144-8420 .- 1742-3406. ; 196:3-4, s. 159-166
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Journal article (peer-reviewed)abstract
- The purpose of this study was to introduce a continuous quality improvement (CQI) program for radiation dose optimisation during uterine artery embolisation (UAE) and assess its impact on dose reduction and image quality. The CQI program investigated the effects of optimising radiation dose parameters on the kerma-area product (KAP) and image quality when comparing a 'CQI intervention' group (n = 50) and 'Control' group (n = 50). Visual grading characteristics (VGC) analysis was used to assess image quality, using the 'Control' group as a reference. A significant reduction in KAP by 17% ( P = 0.041, d = 0.2) and reference air kerma (Ka, r) by 20% (P = 0.027, d = 0.2) was shown between the two groups. The VGC analysis resulted in an area under the VGC curve (AUCVGC) of 0.54, indicating no significant difference in image quality between the two groups (P = 0.670). The implementation of the CQI program and optimisation of radiation dose parameters improved the UAE radiation dose practices at our centre. The dose reduction demonstrated no detrimental effects on image quality.
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45. |
- Arnoldussen, Ilse A. C., et al.
(author)
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Adiposity is related to cerebrovascular and brain volumetry outcomes in the RUN DMC study
- 2019
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In: Neurology. - : Wolters Kluwer. - 0028-3878 .- 1526-632X. ; 93:9, s. e864-e878
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Journal article (peer-reviewed)abstract
- OBJECTIVE: Adiposity predictors, body mass index (BMI), waist circumference (WC), and blood leptin and total adiponectin levels were associated with components of cerebral small vessel disease (CSVD) and brain volumetry in 503 adults with CSVD who were ≥50 years of age and enrolled in the Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Imaging Cohort (RUN DMC).METHODS: RUN DMC participants were followed up for 9 years (2006-2015). BMI, WC, brain imaging, and dementia diagnoses were evaluated at baseline and follow-up. Adipokines were measured at baseline. Brain imaging outcomes included CSVD components, white matter hyperintensities, lacunes, microbleeds, gray and white matter, hippocampal, total brain, and intracranial volumes.RESULTS: Cross-sectionally among men at baseline, higher BMI, WC, and leptin were associated with lower gray matter and total brain volumes, and higher BMI and WC were associated with lower hippocampal volume. At follow-up 9 years later, higher BMI was cross-sectionally associated with lower gray matter volume, and an obese WC (>102 cm) was protective for ≥1 lacune or ≥1 microbleed in men. In women, increasing BMI and overweight or obesity (BMI ≥25 kg/m2 or WC >88 cm) were associated with ≥1 lacune. Longitudinally, over 9 years, a baseline obese WC was associated with decreasing hippocampal volume, particularly in men, and increasing white matter hyperintensity volume in women and men.CONCLUSIONS: Anthropometric and metabolic adiposity predictors were differentially associated with CSVD components and brain volumetry outcomes by sex. Higher adiposity is associated with a vascular-neurodegenerative spectrum among adults at risk for vascular forms of cognitive impairment and dementias.
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46. |
- Chiesa, C., et al.
(author)
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EANM dosimetry committee series on standard operational procedures: a unified methodology for Tc-99m-MAA pre- and Y-90 peri-therapy dosimetry in liver radioembolization with Y-90 microspheres
- 2021
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In: Ejnmmi Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 8:1
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Journal article (peer-reviewed)abstract
- The aim of this standard operational procedure is to standardize the methodology employed for the evaluation of pre- and post-treatment absorbed dose calculations in Y-90 microsphere liver radioembolization. Basic assumptions include the permanent trapping of microspheres, the local energy deposition method for voxel dosimetry, and the patient-relative calibration method for activity quantification.The identity of Tc-99m albumin macro-aggregates (MAA) and Y-90 microsphere biodistribution is also assumed. The large observed discrepancies in some patients between Tc-99m-MAA predictions and actual Y-90 microsphere distributions for lesions is discussed. Absorbed dose predictions to whole non-tumoural liver are considered more reliable and the basic predictors of toxicity. Treatment planning based on mean absorbed dose delivered to the whole non-tumoural liver is advised, except in super-selective treatments. Given the potential mismatch between MAA simulation and actual therapy, absorbed doses should be calculated both pre- and post-therapy. Distinct evaluation between target tumours and non-tumoural tissue, including lungs in cases of lung shunt, are vital for proper optimization of therapy. Dosimetry should be performed first according to a mean absorbed dose approach, with an optional, but important, voxel level evaluation. Fully corrected Tc-99m-MAA Single Photon Emission Computed Tomography (SPECT)/computed tomography (CT) and Y-90 TOF PET/CT are regarded as optimal acquisition methodologies, but, for institutes where SPECT/CT is not available, non-attenuation corrected Tc-99m-MAA SPECT may be used. This offers better planning quality than non dosimetric methods such as Body Surface Area (BSA) or mono-compartmental dosimetry. Quantitative Y-90 bremsstrahlung SPECT can be used if dedicated correction methods are available. The proposed methodology is feasible with standard camera software and a spreadsheet. Available commercial or free software can help facilitate the process and improve calculation time.
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47. |
- Edvardsson, A., et al.
(author)
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Breathing-motion induced interplay effects for stereotactic body radiotherapy of liver tumours using flattening-filter free volumetric modulated arc therapy
- 2019
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In: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 64:2
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Journal article (peer-reviewed)abstract
- The purpose of this study was to investigate breathing-motion induced interplay effects for stereotactic body radiotherapy (SBRT) of liver tumours treated with flattening-filter free (FFF) volumetric modulated arc therapy (VMAT). Ten patients previously treated with liver SBRT were included in this study. All patients had four-dimensional computed tomography (4DCT) scans acquired prior to treatment. The 4DCT was sorted into 8-10 phases covering an equal time interval. A FFF VMAT plan was created for one fraction in the mid-ventilation phase for each patient. To generate dose distributions including both interplay effects and dose blurring, a sub-plan was calculated for each phase. The total dose distributions were accumulated to the mid-ventilation phase using the deformed vector fields (DVF) from deformable image registration between the corresponding CT and the mid-ventilation phase CT. A blurred dose distribution, not including interplay effects, was also obtained by distributing the delivery of the whole plan uniformly on all phases, and was similarly accumulated to the mid-ventilation phase. To isolate interplay effects, this blurred dose distribution was subtracted from the total dose distribution with interplay effects. The near minimum dose (D-98%), mean dose (D-mean), heterogeneity index (HI), and the near minimum dose difference (Delta D-98%) between the accumulated dose distributions with and without interplay effects were calculated within the gross tumour volume (GTV) for each patient. Comparing the accumulated dose distributions with and without interplay effects, the D-98(%) decreased for nine of the ten patients and the HI increased for all patients. The median and minimum differences in D-98(%) were -2.1% and -5.0% (p = 0.006), respectively, and the median HI significantly increased from 6.2% to 12.2% (p = 0.002). The median Delta D-98% was -4.0% (range - 7% to - 1.5%). In conclusion, statistically significant breathing-induced interplay effects were observed for a single fraction of FFF VMAT liver SBRT, resulting in heterogeneous dose distributions within the GTV.
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48. |
- Sarve, Hamid, et al.
(author)
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Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes.
- 2011
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In: Computer methods and programs in biomedicine. - : Elsevier BV. - 1872-7565 .- 0169-2607. ; 102:1, s. 25-34
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Journal article (peer-reviewed)abstract
- Bone-implant integration is measured in several ways. Traditionally and routinely, 2D histological sections of samples, containing bone and the biomaterial, are stained and analyzed using a light microscope. Such histological section provides detailed cellular information about the bone regeneration in the proximity of the implant. However, this information reflects the integration in only a very small fraction, a 10 μm thick slice, of the sample. In this study, we show that feature values quantified on 2D sections are highly dependent on the orientation and the placement of the section, suggesting that a 3D analysis of the whole sample is of importance for a more complete judgment of the bone structure in the proximity of the implant. We propose features describing the 3D data by extending the features traditionally used for 2D-analysis. We present a method for extracting these features from 3D image data and we measure them on five 3D SRμCT image volumes. We also simulate cuts through the image volume positioned at all possible section positions. These simulations show that the measurement variations due to the orientation of the section around the center line of the implant are about 30%.
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49. |
- Saboori, Arash, et al.
(author)
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Unsupervised segmentation and data augmentation in image sequences of skeletal muscle contraction by cycle-consistent generative adversarial network
- 2023
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In: 2023 international conference on modeling, simulation & intelligent computing (MoSICom). - : IEEE. - 9798350393415 - 9798350393422 ; , s. 474-479
-
Conference paper (peer-reviewed)abstract
- This paper investigates a method addressing the unsupervised segmentation and joint data augmentation in medical ultrasound imaging based on the modified CycleGAN. Accurate quantification of fascia and muscle is the key for the diagnostics of neuromuscular disorders based on the analysis of image sequences of skeletal muscle contraction. Although the Deep Learning (DL) models represent encouraging results, some challenges exist. The traditional models don't consider the complex interaction between tissues within a muscle and its surroundings, which reduces the performance of the fascia segmentation. Also, the DL requires many annotated datasets, which ignores dealing with noisy and complex ultrasound images. To overcome these issues, we propose a method to generate realistic images, and then present an unsupervised fascia segmentation method. The results show that our method improves the segmentation accuracy in noisy and complex ultrasound images compared to the traditional methods.
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50. |
- Trägårdh, Elin, et al.
(author)
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RECOMIA-a cloud-based platform for artificial intelligence research in nuclear medicine and radiology
- 2020
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In: Ejnmmi Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 7:1
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Journal article (peer-reviewed)abstract
- Background: Artificial intelligence (AI) is about to transform medical imaging. The Research Consortium for Medical Image Analysis (RECOMIA), a not-for-profit organisation, has developed an online platform to facilitate collaboration between medical researchers and AI researchers. The aim is to minimise the time and effort researchers need to spend on technical aspects, such as transfer, display, and annotation of images, as well as legal aspects, such as de-identification. The purpose of this article is to present the RECOMIA platform and its AI-based tools for organ segmentation in computed tomography (CT), which can be used for extraction of standardised uptake values from the corresponding positron emission tomography (PET) image. Results: The RECOMIA platform includes modules for (1) local de-identification of medical images, (2) secure transfer of images to the cloud-based platform, (3) display functions available using a standard web browser, (4) tools for manual annotation of organs or pathology in the images, (5) deep learning-based tools for organ segmentation or other customised analyses, (6) tools for quantification of segmented volumes, and (7) an export function for the quantitative results. The AI-based tool for organ segmentation in CT currently handles 100 organs (77 bones and 23 soft tissue organs). The segmentation is based on two convolutional neural networks (CNNs): one network to handle organs with multiple similar instances, such as vertebrae and ribs, and one network for all other organs. The CNNs have been trained using CT studies from 339 patients. Experienced radiologists annotated organs in the CT studies. The performance of the segmentation tool, measured as mean Dice index on a manually annotated test set, with 10 representative organs, was 0.93 for all foreground voxels, and the mean Dice index over the organs were 0.86 (0.82 for the soft tissue organs and 0.90 for the bones). Conclusion: The paper presents a platform that provides deep learning-based tools that can perform basic organ segmentations in CT, which can then be used to automatically obtain the different measurement in the corresponding PET image. The RECOMIA platform is available on request atfor research purposes.
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