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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
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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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