| 1. |
- Petersson, Jesper, 1974
(författare)
-
Medicine At A Distance In Sweden: Spatiotemporal Matters In Accomplishing Working Telemedicine
- 2011
-
Ingår i: Science Studies. - 0786-3012. ; 24:2, s. 43-62
-
Tidskriftsartikel (refereegranskat)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
|
|
| 2. |
- Ahlander, Britt-Marie, 1954-, et al.
(författare)
-
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
-
Ingår i: Clinical Physiology and Functional Imaging. - : Blackwell Publishing. - 1475-0961 .- 1475-097X. ; 37:1, s. 52-61
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 3. |
- Rosendahl, Lene, 1963-, et al.
(författare)
-
Computer-assisted calculation of myocardial infarct size shortens the evaluation time of contrast-enhanced cardiac MRI
- 2008
-
Ingår i: Clinical Physiology and Functional Imaging. - : John Wiley & Sons. - 1475-0961 .- 1475-097X. ; 28:1, s. 1-7
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 4. |
- Ali, Muhaddisa Barat, 1986, et al.
(författare)
-
A novel federated deep learning scheme for glioma and its subtype classification
- 2023
-
Ingår i: Frontiers in Neuroscience. - 1662-4548 .- 1662-453X. ; 17
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 5. |
- Andersson, Jonas, 1975-, et al.
(författare)
-
Artificial intelligence and the medical physics profession-A Swedish perspective
- 2021
-
Ingår i: Physica Medica-European Journal of Medical Physics. - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 88, s. 218-225
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 6. |
- Chakarova, Roumiana, et al.
(författare)
-
A Monte Carlo evaluation of beam characteristics for total body irradiation at extended treatment distances
- 2014
-
Ingår i: Journal of Applied Clinical Medical Physics. - 1526-9914. ; 15:3, s. 182-189
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 7. |
- Ge, Chenjie, 1991, et al.
(författare)
-
Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification
- 2020
-
Ingår i: IEEE Access. - 2169-3536 .- 2169-3536. ; 8:1, s. 22560-22570
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 8. |
- Borrelli, P., et al.
(författare)
-
AI-based detection of lung lesions in F-18 FDG PET-CT from lung cancer patients
- 2021
-
Ingår i: Ejnmmi Physics. - : Springer Science and Business Media LLC. - 2197-7364. ; 8:1
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 9. |
- Szaro, Pavel, et al.
(författare)
-
Magnetic resonance imaging of the brachial plexus. Part 2: Traumatic injuries
- 2022
-
Ingår i: European Journal of Radiology Open (EJR Open). - : Elsevier BV. - 2352-0477. ; 9
-
Tidskriftsartikel (refereegranskat)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.
|
|
| 10. |
- Rosendahl, Lene, et al.
(författare)
-
Image quality and myocardial scar size determined with magnetic resonance imaging in patients with permanent atrial fibrillation : A comparison of two imaging protocols
- 2010
-
Ingår i: Clinical Physiology and Functional Imaging. - : John Wiley & Sons. - 1475-0961 .- 1475-097X. ; 30:2, s. 122-129
-
Tidskriftsartikel (refereegranskat)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.
|
|
