Publications by authors named "Marc Dewey"

191 Publications

Detection of relevant extracardiac findings on coronary computed tomography angiography vs. invasive coronary angiography.

Eur Radiol 2021 Jun 15. Epub 2021 Jun 15.

Department of Radiology, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Objectives: To compare the detection of relevant extracardiac findings (ECFs) on coronary computed tomography angiography (CTA) and invasive coronary angiography (ICA) and evaluate the potential clinical benefit of their detection.

Methods: This is the prespecified subanalysis of ECFs in patients presenting with a clinical indication for ICA based on atypical angina and suspected coronary artery disease (CAD) included in the prospective single-center randomized controlled Coronary Artery Disease Management (CAD-Man) study. ECFs requiring immediate therapy and/or further workup including additional imaging were defined as clinically relevant. We evaluated the scope of ECFs in 329 patients and analyzed the potential clinical benefit of their detection.

Results: ECFs were detected in 107 of 329 patients (32.5%; CTA: 101/167, 60.5%; ICA: 6/162, 3.7%; p < .001). Fifty-nine patients had clinically relevant ECFs (17.9%; CTA: 55/167, 32.9%; ICA: 4/162, 2.5%; p < .001). In the CTA group, ECFs potentially explained atypical chest pain in 13 of 101 patients with ECFs (12.9%). After initiation of therapy, chest pain improved in 4 (4.0%) and resolved in 7 patients (6.9%). Follow-up imaging was recommended in 33 (10.0%; CTA: 30/167, 18.0%; ICA: 3/162, 1.9%) and additional clinic consultation in 26 patients (7.9%; CTA: 25/167, 15.0%; ICA: 1/162, 0.6%). Malignancy was newly diagnosed in one patient (0.3%; CTA: 1/167, 0.6%; ICA: 0).

Conclusions: In this randomized study, CTA but not ICA detected clinically relevant ECFs that may point to possible other causes of chest pain in patients without CAD. Thus, CTA might preclude the need for ICA in those patients.

Trial Registration: NCT Unique ID: 00844220 KEY POINTS: • CTA detects ten times more clinically relevant ECFs than ICA. • Actionable clinically relevant ECFs affect patient management and therapy and may thus improve chest pain. • Detection of ECFs explaining chest pain on CTA might preclude the need for performing ICA.
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http://dx.doi.org/10.1007/s00330-021-07967-xDOI Listing
June 2021

Prognostic value of noninvasive combined anatomic/functional assessment by cardiac CT in patients with suspected coronary artery disease - Comparison with invasive coronary angiography and nuclear myocardial perfusion imaging for the five-year-follow up of the CORE320 multicenter study.

J Cardiovasc Comput Tomogr 2021 May 12. Epub 2021 May 12.

Department of Nuclear Medicine and Cardiovascular Imaging, Brigham and Women's Hospital, Boston, MA, USA.

Background: Few data exist on long-term outcome in patients undergoing combined coronary CT angiography (CTA) and myocardial CT perfusion imaging (CTP) as well as invasive coronary angiography (ICA) and single photon emission tomography (SPECT).

Methods: At 16 centers, 381 patients were followed for major adverse cardiac events (MACE) for the CORE320 study. All patients underwent coronary CTA, CTP, and SPECT before ICA within 60 days. Prognostic performance according binary results (normal/abnormal) was assessed by 5-year major cardiovascular events (MACE) free survival and area under the receiver-operating-characteristic curve (AUC).

Results: Follow up beyond 2-years was available in 323 patients. MACE-free survival rate was greater among patients with normal combined CTA-CTP findings compared to ICA-SPECT: 85 vs. 80% (95% confidence interval [CI] for difference 0.1, 11.3) though event-free survival time was similar (4.54 vs. 4.37 years, 95% CI for difference: -0.03, 0.36). Abnormal results by combined CTA-CTP was associated with 3.83 years event-free survival vs. 3.66 years after abnormal combined ICA-SPECT (95% CI for difference: -0.05, 0.39). Predicting MACE by AUC also was similar: 65 vs. 65 (difference 0.1; 95% CI -4.6, 4.9). When MACE was restricted to cardiovascular death, myocardial infarction, or stroke, AUC for CTA-CTP was 71 vs. 60 by ICA-SPECT (difference 11.2; 95% CI -1.0, 19.7).

Conclusions: Combined CTA-CTP evaluation yields at least equal 5-year prognostic information as combined ICA-SPECT assessment in patients presenting with suspected coronary artery disease. Noninvasive cardiac CT assessment may eliminate the need for diagnostic cardiac catheterization in many patients.

Clinical Trial Registration: NCT00934037.
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http://dx.doi.org/10.1016/j.jcct.2021.04.005DOI Listing
May 2021

Audio-guided self-hypnosis for reduction of claustrophobia during MR imaging: results of an observational 2-group study.

Eur Radiol 2021 Jul 15;31(7):4483-4491. Epub 2021 Apr 15.

Department of Radiology, Charité - Universitätsmedizin Berlin Campus Mitte, Humboldt-Universität zu Berlin, Freie Universität Berlin, Charité Platz 1, 10117, Berlin, Germany.

Objectives: To evaluate the influence of audio-guided self-hypnosis on claustrophobia in a high-risk cohort undergoing magnetic resonance (MR) imaging.

Methods: In this prospective observational 2-group study, 55 patients (69% female, mean age 53.6 ± 13.9) used self-hypnosis directly before imaging. Claustrophobia included premature termination, sedation, and coping actions. The claustrophobia questionnaire (CLQ) was completed before self-hypnosis and after MR imaging. Results were compared to a control cohort of 89 patients examined on the same open MR scanner using logistic regression for multivariate analysis. Furthermore, patients were asked about their preferences for future imaging.

Results: There was significantly fewer claustrophobia in the self-hypnosis group (16%; 9/55), compared with the control group (43%; 38/89; odds ratio .14; p = .001). Self-hypnosis patients also needed less sedation (2% vs 16%; 1/55 vs 14/89; odds ratio .1; p = .008) and non-sedation coping actions (13% vs 28%; 7/55 vs 25/89; odds ratio .3; p = .02). Self-hypnosis did not influence the CLQ results measured before and after MR imaging (p = .79). Self-hypnosis reduced the frequency of claustrophobia in the subgroup of patients above an established CLQ cut-off of .33 from 47% (37/78) to 18% (9/49; p = .002). In the subgroup below the CLQ cut-off of 0.33, there were no significant differences (0% vs 9%, 0/6 vs 1/11; p = 1.0). Most patients (67%; 35/52) preferred self-hypnosis for future MR examinations.

Conclusions: Self-hypnosis reduced claustrophobia in high-risk patients undergoing imaging in an open MR scanner and might reduce the need for sedation and non-sedation coping actions.

Key Points: • Forty percent of the patients at high risk for claustrophobia may also experience a claustrophobic event in an open MR scanner. • Self-hypnosis while listening to an audio in the waiting room before the examination may reduce claustrophobic events in over 50% of patients with high risk for claustrophobia. • Self-hypnosis may also reduce the need for sedation and other time-consuming non-sedation coping actions and is preferred by high-risk patients for future examinations.
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http://dx.doi.org/10.1007/s00330-021-07887-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213599PMC
July 2021

Incorporating radiomics into clinical trials: expert consensus endorsed by the European Society of Radiology on considerations for data-driven compared to biologically driven quantitative biomarkers.

Eur Radiol 2021 Aug 25;31(8):6001-6012. Epub 2021 Jan 25.

European Imaging Biomarkers Alliance (EIBALL), European Society of Radiology, Vienna, Austria.

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory.
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http://dx.doi.org/10.1007/s00330-020-07598-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8270834PMC
August 2021

Evaluation of PEEP and prone positioning in early COVID-19 ARDS.

EClinicalMedicine 2020 Nov 11;28:100579. Epub 2020 Oct 11.

Department of Infectious Diseases and Respiratory Medicine, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.

Background: In face of the Coronavirus Disease (COVID)-19 pandemic, best practice for mechanical ventilation in COVID-19 associated Acute Respiratory Distress Syndrome (ARDS) is intensely debated. Specifically, the rationale for high positive end-expiratory pressure (PEEP) and prone positioning in early COVID-19 ARDS has been questioned.

Methods: The first 23 consecutive patients with COVID-19 associated respiratory failure transferred to a single ICU were assessed. Eight were excluded: five were not invasively ventilated and three received veno-venous ECMO support. The remaining 15 were assessed over the first 15 days of mechanical ventilation. Best PEEP was defined by maximal oxygenation and was determined by structured decremental PEEP trials comprising the monitoring of oxygenation, airway pressures and trans-pulmonary pressures. In nine patients the impact of prone positioning on oxygenation was investigated. Additionally, the effects of high PEEP and prone positioning on pulmonary opacities in serial chest x-rays were determined by applying a semiquantitative scoring-system. This investigation is part of the prospective observational PA-COVID-19 study.

Findings: Patients responded to initiation of invasive high PEEP ventilation with markedly improved oxygenation, which was accompanied by reduced pulmonary opacities within 6 h of mechanical ventilation. Decremental PEEP trials confirmed the need for high PEEP (17.9 (SD ± 3.9) mbar) for optimal oxygenation, while driving pressures remained low. Prone positioning substantially increased oxygenation (<0.01).

Interpretation: In early COVID-19 ARDS, substantial PEEP values were required for optimizing oxygenation. Pulmonary opacities resolved during mechanical ventilation with high PEEP suggesting recruitment of lung volume.

Funding: German Research Foundation, German Federal Ministry of Education and Research.
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http://dx.doi.org/10.1016/j.eclinm.2020.100579DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7547915PMC
November 2020

The role of body computed tomography in hospitalized patients with obscure infection: Retrospective consecutive cohort study.

Eur J Radiol 2020 Nov 1;132:109325. Epub 2020 Oct 1.

Department of Radiology, Charité - Universitätsmedizin Berlin, Germany.

Objective: Patients with severe infection or sepsis require fast identification of the focus and prompt eradication. This study aims at investigating the role of body computed tomography (CT) and identifying outcome predictors in a general ward setting of patients with obscure infection.

Methods: We retrospectively identified 196 consecutive body CTs acquired in 179 patients with obscure infection, i.e. severe infection or sepsis from general wards with unclear focus, over 12-months in the year 2018. Reports were extracted using a full-text search in the radiological information system (RIS) of a large university medical center. CT reports were classified according to diagnostic confidence of the reader (i.e. certain, likely, possible, no focus), and correlated with clinical and laboratory parameters. The discharge diagnosis was set as the diagnostic reference standard. Contingency tables were prepared for statistical analysis with Chi-squared test amongst other analyses and the calculation of AUC statistics.

Results: In 133 out of 196 (67.9 %) body CTs from general wards with severe infection or sepsis, body CT identified an infectious focus. 90 % of the infections were located in the chest, abdomen, and genitourinary tract, in descending order. In 76.5 % (150 of 196) of examinations, CT correctly predicted the final infectious source. The positive predictive value (PPV) of a CT-detected focus was 84.2 % (95 % CI 79.0%-88.3%). A high diagnostic confidence of the reader resulted in a PPV of 96.4 % (95 % CI 87.4%-99.1%) while a low confidence resulted in a PPV of 63.3 % (95 % CI 48.2%-76.3%).

Conclusion: In patients with obscure infection treated in general wards, body CT detects the infectious source with a high positive predictive value. Focus detection accuracy highly depends on the diagnostic confidence of the CT reader.
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http://dx.doi.org/10.1016/j.ejrad.2020.109325DOI Listing
November 2020

MRI for measuring therapy efficiency after revascularisation in ST-segment elevation myocardial infarction: a systematic review and meta-regression analysis.

BMJ Open 2020 09 28;10(9):e034359. Epub 2020 Sep 28.

Institute of Radiology, Charité - Universitätsmedizin Berlin, Humboldt-Universität and Freie Universität, Berlin, Germany

Objective: To summarise existing data on the relation between the time from symptom onset until revascularisation (time to reperfusion) and the myocardial salvage index (MSI) calculated as proportion of non-necrotic myocardium inside oedematous myocardium on T2-weighted and T1-weighted late gadolinium enhancement MRI after ST-segment elevation myocardial infarction (STEMI).

Methods: Studies including patients with revascularised STEMI and stating both the time to reperfusion and the MSI measured by T2-weighted and T1-weighted late gadolinium enhancement MRI were searched in MEDLINE, EMBASE and ISI Web of Science until 16 May 2020. A mixed effects model was used to evaluate the relation between the time to reperfusion and the MSI. The gender distribution and mean age in included patient groups, the timing of MRI, used MRI sequences and image interpretation methodology were included in the mixed effects model to explore between-study heterogeneity.

Results: We included 38 studies with 5106 patients. The pooled MSI was 42.6% (95% CI: 38.1 to 47.1). The pooled time to reperfusion was 3.8 hours (95% CI: 3.5 to 4.0). Every hour of delay in reperfusion was associated with an absolute decrease of 13.1% (95% CI: 11.5 to 14.6; p<0.001) in the MSI. Between-study heterogeneity was considerable (σ=167.8). Differences in the gender distribution, timing of MRI and image interpretation among studies explained 45.2% of the between-study heterogeneity.

Conclusions: The MSI on T2-weighted and T1-weighted late gadolinium enhancement MRI correlates inversely with the time to reperfusion, which indicates that cardioprotection achieved by minimising the time to reperfusion leads to a higher MSI. The analysis revealed considerable heterogeneity between studies. The heterogeneity could partly be explained by differences in the gender distribution, timing and interpretation of MRI suggesting that the MRI-assessed MSI is not only influenced by cardioprotective therapy but also by patient characteristics and MRI parameters.
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http://dx.doi.org/10.1136/bmjopen-2019-034359DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523216PMC
September 2020

Computed tomography for detection of septic foci: Retrospective analysis of patients presenting to the emergency department.

Clin Imaging 2021 Jan 19;69:223-227. Epub 2020 Sep 19.

Department of Radiology, Charité - Universitätsmedizin Berlin, Campus Mitte, Luisenstraße 7, 10117 Berlin, Germany.

Objective: Sepsis is defined as organ dysfunction due to severe infection. Septic patients face a significant mortality risk. Thus, timely recognition with prompt focus identification and control are essential. This study aims to determine the current role of computed tomography (CT) in the diagnostic workup of septic patients.

Methods: We retrospectively identified 357 patients in the emergency department (ED) of a large university center with suspected sepsis in a two-year period. A total of 132 patients underwent CT scanning within 72 h of admission. Patients were characterized by clinical and laboratory findings. CT reports were categorized and matched with clinical data.

Results: Of 357 ED patients with suspected sepsis, 37.0% (132/357) underwent CT imaging within 72 h. The most commonly identified septic foci in CT were chest 38.6% (49/127), abdomen 22.0% (28/127) and genitourinary tract 20.5% (26/127) in descending order. The focus detection rate was 76.5% per patient with a concurrent number-needed-to-scan of 1.31. Contrast medium administration in CT did not improve focus detection rate (p = 0.631) or diagnostic confidence in this patient population (p = 0.432). CT had a positive predictive value of 81.82% (CI 76.31 to 86.28%) in predicting the focus of the discharge diagnosis. Follow-up imaging in patients with unclear focus reveals a new focus in 39.5% of patients.

Conclusions: Our investigation of the role of CT in ED patients with suspected sepsis indicated a high positive predictive value for CT with regard to the discharge diagnosis. Repeat imaging may help identify further septic foci in a subgroup with persistently unclear focus. Use of contrast medium seems less relevant for focus detection than expected, as it did not increase diagnostic confidence.
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http://dx.doi.org/10.1016/j.clinimag.2020.09.004DOI Listing
January 2021

Coronary Computed Tomography Angiography.

JAMA 2020 Oct;324(14):1455-1456

Charité-Universitätsmedizin Berlin, Berlin, Germany.

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http://dx.doi.org/10.1001/jama.2020.10831DOI Listing
October 2020

Clinical pre-test probability for obstructive coronary artery disease: insights from the European DISCHARGE pilot study.

Eur Radiol 2021 Mar 9;31(3):1471-1481. Epub 2020 Sep 9.

Dept. of Coronary and Structural Heart Diseases, Institute of Cardiology, Warsaw, Poland.

Objectives: To test the accuracy of clinical pre-test probability (PTP) for prediction of obstructive coronary artery disease (CAD) in a pan-European setting.

Methods: Patients with suspected CAD and stable chest pain who were clinically referred for invasive coronary angiography (ICA) or computed tomography (CT) were included by clinical sites participating in the pilot study of the European multi-centre DISCHARGE trial. PTP of CAD was determined using the Diamond-Forrester (D+F) prediction model initially introduced in 1979 and the updated D+F model from 2011. Obstructive coronary artery disease (CAD) was defined by one at least 50% diameter coronary stenosis by both CT and ICA.

Results: In total, 1440 patients (654 female, 786 male) were included at 25 clinical sites from May 2014 until July 2017. Of these patients, 725 underwent CT, while 715 underwent ICA. Both prediction models overestimated the prevalence of obstructive CAD (31.7%, 456 of 1440 patients, PTP: initial D+F 58.9% (28.1-90.6%), updated D+F 47.3% (34.2-59.9%), both p < 0.001), but overestimation of disease prevalence was higher for the initial D+F (p < 0.001). The discriminative ability was higher for the updated D+F 2011 (AUC of 0.73 95% confidence interval [CI] 0.70-0.76 versus AUC of 0.70 CI 0.67-0.73 for the initial D+F; p < 0.001; odds ratio (or) 1.55 CI 1.29-1.86, net reclassification index 0.11 CI 0.05-0.16, p < 0.001).

Conclusions: Clinical PTP calculation using the initial and updated D+F prediction models relevantly overestimates the actual prevalence of obstructive CAD in patients with stable chest pain clinically referred for ICA and CT suggesting that further refinements to improve clinical decision-making are needed.

Trial Registration: https://www.clinicaltrials.gov/ct2/show/NCT02400229 KEY POINTS: • Clinical pre-test probability calculation using the initial and updated D+F model overestimates the prevalence of obstructive CAD identified by ICA and CT. • Overestimation of disease prevalence is higher for the initial D+F compared with the updated D+F. • Diagnostic accuracy of PTP assessment varies strongly between different clinical sites throughout Europe.
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http://dx.doi.org/10.1007/s00330-020-07175-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880945PMC
March 2021

Patient preferences for development in MRI scanner design: a survey of claustrophobic patients in a randomized study.

Eur Radiol 2021 Mar 2;31(3):1325-1335. Epub 2020 Sep 2.

Department of Radiology, Charité Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Objective: To investigate which magnetic resonance imaging (MRI) scanner designs claustrophobic patients prefer.

Material/methods: We analyzed questionnaires completed by 160 patients at high risk for claustrophobia directly after a scan in either a short-bore or open panoramic scanner as part of a prospective randomized trial Enders et al (BMC Med Imaging 11:4, 2011). Scanner preferences were judged based on schematic drawings of four scanners. Information on the diagnostic performance of the depicted scanners was provided, too.

Results: A majority of patients suggested upright open (59/160, 36.9%) and open panoramic (53/160, 33.1%) before short-bore designs (26/160, 16.3%, for all p < 0.001) for future development. When asked about patients' preferred scanner choice for an upcoming examination, information about a better diagnostic performance of a short-bore scanner significantly improved its preference rates (from 6/160 to 49/160 or 3.8 to 30.5%, p < 0.001). Patients with a claustrophobic event preferred open designs significantly more often than patients without a claustrophobic event (p = 0.047). Patients scanned in a short-bore scanner in our trial preferred this design significantly more often (p = 0.003). Noise reduction (51/160, 31.9%), more space over the head (44/160, 27.5%), and overall more space (33/160, 20.6%) were the commonest suggested areas of improvement.

Conclusion: Patients at high risk for claustrophobia visually prefer open- over short-bore MRI designs for further development. Education about a better diagnostic performance of a visually less-attractive scanner can increase its acceptance. Noise and space were of most concern for claustrophobic patients. This information can guide individual referral of claustrophobic patients to scanners and future scanner development.

Key Points: • Patients at high risk for claustrophobia visually favor the further development of open scanners as opposed to short- and closed-bore scanner designs. • Educating claustrophobic patients about a higher diagnostic performance of a short-bore scanner can significantly increase their acceptance of this otherwise visually less-attractive design. • A medical history of earlier claustrophobic events in a given MRI scanner type and focusing on the features "more space" and "noise reduction" can help to guide referral of patients who are at high risk for claustrophobia.
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http://dx.doi.org/10.1007/s00330-020-07060-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880963PMC
March 2021

Automatic prostate and prostate zones segmentation of magnetic resonance images using DenseNet-like U-net.

Sci Rep 2020 08 31;10(1):14315. Epub 2020 Aug 31.

Department of Radiology, Charité Medical University, Berlin, Germany.

Magnetic resonance imaging (MRI) provides detailed anatomical images of the prostate and its zones. It has a crucial role for many diagnostic applications. Automatic segmentation such as that of the prostate and prostate zones from MR images facilitates many diagnostic and therapeutic applications. However, the lack of a clear prostate boundary, prostate tissue heterogeneity, and the wide interindividual variety of prostate shapes make this a very challenging task. To address this problem, we propose a new neural network to automatically segment the prostate and its zones. We term this algorithm Dense U-net as it is inspired by the two existing state-of-the-art tools-DenseNet and U-net. We trained the algorithm on 141 patient datasets and tested it on 47 patient datasets using axial T2-weighted images in a four-fold cross-validation fashion. The networks were trained and tested on weakly and accurately annotated masks separately to test the hypothesis that the network can learn even when the labels are not accurate. The network successfully detects the prostate region and segments the gland and its zones. Compared with U-net, the second version of our algorithm, Dense-2 U-net, achieved an average Dice score for the whole prostate of 92.1± 0.8% vs. 90.7 ± 2%, for the central zone of [Formula: see text]% vs. [Formula: see text] %, and for the peripheral zone of 78.1± 2.5% vs. [Formula: see text]%. Our initial results show Dense-2 U-net to be more accurate than state-of-the-art U-net for automatic segmentation of the prostate and prostate zones.
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http://dx.doi.org/10.1038/s41598-020-71080-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7459118PMC
August 2020

Continuous Learning AI in Radiology: Implementation Principles and Early Applications.

Radiology 2020 Oct 25;297(1):6-14. Epub 2020 Aug 25.

From the Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, FND-210, Boston, MA 02114-2698 (O.S.P., J.A.B.); International Society for Strategic Studies in Radiology (IS3R), Vienna, Austria (M.D., D.R.E., C.J.H., S.O.S., J.A.B.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (G.L., C.J.H.); Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Boston, Mass (G.L.); Department of Radiology, Charité-Universitätsmedizin, Berlin, Germany (M.D.); Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Calif (D.R.E.); and Institute of Clinical Radiology and Nuclear Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany (S.O.S.).

Artificial intelligence (AI) is becoming increasingly present in radiology and health care. This expansion is driven by the principal AI strengths: automation, accuracy, and objectivity. However, as radiology AI matures to become fully integrated into the daily radiology routine, it needs to go beyond replicating static models, toward discovering new knowledge from the data and environments around it. Continuous learning AI presents the next substantial step in this direction and brings a new set of opportunities and challenges. Herein, the authors discuss the main concepts and requirements for implementing continuous AI in radiology and illustrate them with examples from emerging applications.
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http://dx.doi.org/10.1148/radiol.2020200038DOI Listing
October 2020

Developing a lung nodule management protocol specifically for cardiac CT: Methodology in the DISCHARGE trial.

Eur J Radiol Open 2020 25;7:100235. Epub 2020 Jun 25.

Department of Radiology, Charité University Hospital, Chariteplatz 1, 10117, Berlin, Germany.

Purpose: In this methodology paper we describe the development of a lung nodule management algorithm specifically for patients undergoing cardiac CT.

Methods: We modified the Lung-RADS algorithm specifically to manage lung nodules incidentally detected on cardiac CT (Lung-RADS for cardiac CT). We will evaluate the modified algorithm as part of the DISCHARGE trial (www.dischargetrial.eu) in which patients with suspected coronary artery disease are randomly assigned to cardiac CT or invasive coronary angiography across Europe at 16 sites involving 3546 patients. Patients will be followed for up to four years.

Results: The major adjustments to Lung-RADS specifically for cardiac CT relate to 1) incomplete coverage of the lungs by cardiac CT compared with chest CT, and when to order a completion chest CT versus a follow up chest CT, 2) cardiac CT findings will not trigger annual lung-cancer screening, and 3) a lower threshold of at least 10 mm for classifying new ground glass nodules as probably benign (category 3).

Conclusions: The DISCHARGE trial will assess a lung nodule management algorithm designed specifically for cardiac CT in patients with stable chest pain across Europe.
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http://dx.doi.org/10.1016/j.ejro.2020.100235DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327416PMC
June 2020

Effectiveness of the clinical decision support tool ESR eGUIDE for teaching medical students the appropriate selection of imaging tests: randomized cross-over evaluation.

Eur Radiol 2020 Oct 20;30(10):5684-5689. Epub 2020 May 20.

Department of Radiology, Charité - Universitätsmedizin Berlin, Humboldt-Universität zu Berlin, Freie Universitat Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Objectives: To evaluate ESR eGUIDE-the European Society of Radiology (ESR) e-Learning tool for appropriate use of diagnostic imaging modalities-for learning purposes in different clinical scenarios.

Methods: This anonymized evaluation was performed after approval of ESR Education on Demand leadership. Forty clinical scenarios were developed in which at least one imaging modality was clinically most appropriate, and the scenarios were divided into sets 1 and 2. These sets were provided to medical students randomly assigned to group A or B to select the most appropriate imaging test for each scenario. Statistical comparisons were made within and across groups.

Results: Overall, 40 medical students participated, and 31 medical students (78%) answered both sets. The number of correctly chosen imaging methods per set in these 31 paired samples was significantly higher when answered with versus without use of ESR eGUIDE (13.7 ± 2.6 questions vs. 12.1 ± 3.2, p = 0.012). Among the students in group A, who first answered set 1 without ESR eGUIDE (11.1 ± 3.2), there was significant improvement when set 2 was answered with ESR eGUIDE (14.3 ± 2.5, p = 0.013). The number of correct answers in group B did not drop when set 2 was answered without ESR eGUIDE (12.4 ± 2.6) after having answered set 1 first with ESR eGUIDE (13.0 ± 2.7, p = 0.66).

Conclusion: The clinical decision support tool ESR eGUIDE is suitable for training medical students in choosing the best radiological imaging modality in typical scenarios, and its use in teaching radiology can thus be recommended.

Key Points: • ESR eGUIDE improved the number of appropriately selected imaging modalities among medical students. • This improvement was also seen in the group of students which first selected imaging tests without ESR eGUIDE. • In the student group which used ESR eGUIDE first, appropriate selection remained stable even without the teaching tool.
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http://dx.doi.org/10.1007/s00330-020-06942-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7476994PMC
October 2020

Health-related qualify of life, angina type and coronary artery disease in patients with stable chest pain.

Health Qual Life Outcomes 2020 05 14;18(1):140. Epub 2020 May 14.

Department of Cardiology, Hospital of Lithuanian University of Health Sciences Kaunas Clinics, Kaunas, Lithuania.

Background: Health-related quality of life (HRQoL) is impaired in patients with stable angina but patients often present with other forms of chest pain. The aim of this study was to compare the pre-diagnostic HRQoL in patients with suspected coronary artery disease (CAD) according to angina type, gender, and presence of obstructive CAD.

Methods: From the pilot study for the European DISCHARGE trial, we analysed data from 24 sites including 1263 patients (45.9% women, 61.1 ± 11.3 years) who were clinically referred for invasive coronary angiography (ICA; 617 patients) or coronary computed tomography angiography (CTA; 646 patients). Prior to the procedures, patients completed HRQoL questionnaires: the Short Form (SF)-12v2, the EuroQoL (EQ-5D-3 L) and the Hospital Anxiety and Depression Scale.

Results: Fifty-five percent of ICA and 35% of CTA patients had typical angina, 23 and 33% had atypical angina, 18 and 28% had non-anginal chest discomfort and 5 and 5% had other chest discomfort, respectively. Patients with typical angina had the poorest physical functioning compared to the other angina groups (SF-12 physical component score; 41.2 ± 8.8, 43.3 ± 9.1, 46.2 ± 9.0, 46.4 ± 11.4, respectively, all age and gender-adjusted p < 0.01), and highest anxiety levels (8.3 ± 4.1, 7.5 ± 4.1, 6.5 ± 4.0, 4.7 ± 4.5, respectively, all adjusted p < 0.01). On all other measures, patients with typical or atypical angina had lower HRQoL compared to the two other groups (all adjusted p < 0.05). HRQoL did not differ between patients with and without obstructive CAD while women had worse HRQoL compared with men, irrespective of age and angina type.

Conclusions: Prior to a diagnostic procedure for stable chest pain, HRQoL is associated with chest pain characteristics, but not with obstructive CAD, and is significantly lower in women.

Trial Registration: Clinicaltrials.gov, NCT02400229.
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http://dx.doi.org/10.1186/s12955-020-01312-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7222590PMC
May 2020

Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia.

Nat Rev Cardiol 2020 07 24;17(7):427-450. Epub 2020 Feb 24.

Department of Cellular and Molecular Imaging, Comprehensive Heart Failure Center, Würzburg University Clinics, Würzburg, Germany.

Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging, whereas PET is the clinical reference standard for the quantification of myocardial perfusion. MRI does not involve exposure to ionizing radiation, similar to echocardiography, which can be performed at the bedside. CT perfusion imaging is not frequently used but CT offers coronary angiography data, and invasive catheter-based methods can measure coronary flow and pressure. Technical improvements to the quantification of pathophysiological parameters of myocardial ischaemia can be achieved. Clinical consensus recommendations on the appropriateness of each technique were derived following a European quantitative cardiac imaging meeting and using a real-time Delphi process. SPECT using new detectors allows the quantification of myocardial blood flow and is now also suited to patients with a high BMI. PET is well suited to patients with multivessel disease to confirm or exclude balanced ischaemia. MRI allows the evaluation of patients with complex disease who would benefit from imaging of function and fibrosis in addition to perfusion. Echocardiography remains the preferred technique for assessing ischaemia in bedside situations, whereas CT has the greatest value for combined quantification of stenosis and characterization of atherosclerosis in relation to myocardial ischaemia. In patients with a high probability of needing invasive treatment, invasive coronary flow and pressure measurement is well suited to guide treatment decisions. In this Consensus Statement, we summarize the strengths and weaknesses as well as the future technological potential of each imaging modality.
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http://dx.doi.org/10.1038/s41569-020-0341-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7297668PMC
July 2020

Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations.

Eur Radiol 2020 Jun 17;30(6):3576-3584. Epub 2020 Feb 17.

Hogan Lovells US LLP, Washington, D.C., USA.

Artificial intelligence (AI) has the potential to significantly disrupt the way radiology will be practiced in the near future, but several issues need to be resolved before AI can be widely implemented in daily practice. These include the role of the different stakeholders in the development of AI for imaging, the ethical development and use of AI in healthcare, the appropriate validation of each developed AI algorithm, the development of effective data sharing mechanisms, regulatory hurdles for the clearance of AI algorithms, and the development of AI educational resources for both practicing radiologists and radiology trainees. This paper details these issues and presents possible solutions based on discussions held at the 2019 meeting of the International Society for Strategic Studies in Radiology. KEY POINTS: • Radiologists should be aware of the different types of bias commonly encountered in AI studies, and understand their possible effects. • Methods for effective data sharing to train, validate, and test AI algorithms need to be developed. • It is essential for all radiologists to gain an understanding of the basic principles, potentials, and limits of AI.
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http://dx.doi.org/10.1007/s00330-020-06672-5DOI Listing
June 2020

Prognostic value of the myocardial salvage index measured by T2-weighted and T1-weighted late gadolinium enhancement magnetic resonance imaging after ST-segment elevation myocardial infarction: A systematic review and meta-regression analysis.

PLoS One 2020 13;15(2):e0228736. Epub 2020 Feb 13.

Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany.

In all patients with ST-segment elevation myocardial infarction, risk stratification should be performed before discharge. The measurement of therapy efficiency with magnetic resonance imaging has been proposed as part of the risk assessment, but it has not been adopted widely. This meta-analysis was conducted to summarize published data on the prognostic value of the proportion of salvaged myocardium inside previously ischemic myocardium (myocardial salvage index) measured by T2-weighted and T1-weighted late gadolinium enhancement magnetic resonance imaging after ST-segment elevation myocardial infarction. Random and mixed effects models were used for analyzing the data of 10 studies with 2,697 patients. The pooled myocardial salvage index, calculated as the proportion of non-necrotic myocardium inside edematous myocardium measured by T2-weighted and T1-weighted late gadolinium enhancement MRI, was 43.0% (95% confidence interval: 37.4, 48.6). The pooled length of follow-up was 12.3 months (95% confidence interval: 7.0, 17.6). The pooled incidence of major cardiac events during follow-up, defined as cardiac death, nonfatal myocardial infarction, or admission for heart failure, was 10.6% (95% confidence interval: 5.7, 15.5). The applied mixed effects model showed an absolute decrease of 1.7% in the incidence of major cardiac events during follow-up (95% confidence interval: 1.6, 1.9) with every 1% of increase in the myocardial salvage index. The heterogeneity between studies was considerable (τ = 21.3). Analysis of aggregated follow-up data after ST-segment elevation myocardial infarction suggests that the myocardial salvage index measured by T2-weighted and T1-weighted late gadolinium enhancement magnetic resonance imaging provides prognostic information on the risk of major cardiac events, but considerable heterogeneity exists between studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228736PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7018083PMC
May 2020

Pilot study of the multicentre DISCHARGE Trial: image quality and protocol adherence results of computed tomography and invasive coronary angiography.

Eur Radiol 2020 Apr 16;30(4):1997-2009. Epub 2019 Dec 16.

Department of Cardiology, St. Vincent's University Hospital, Belfield Campus, 4, Dublin, Ireland.

Objective: To implement detailed EU cardiac computed tomography angiography (CCTA) quality criteria in the multicentre DISCHARGE trial (FP72007-2013, EC-GA 603266), we reviewed image quality and adherence to CCTA protocol and to the recommendations of invasive coronary angiography (ICA) in a pilot study.

Materials And Methods: From every clinical centre, imaging datasets of three patients per arm were assessed for adherence to the inclusion/exclusion criteria of the pilot study, predefined standards for the CCTA protocol and ICA recommendations, image quality and non-diagnostic (NDX) rate. These parameters were compared via multinomial regression and ANOVA. If a site did not reach the minimum quality level, additional datasets had to be sent before entering into the final accepted database (FADB).

Results: We analysed 226 cases (150 CCTA/76 ICA). The inclusion/exclusion criteria were not met by 6 of the 226 (2.7%) datasets. The predefined standard was not met by 13 of 76 ICA datasets (17.1%). This percentage decreased between the initial CCTA database and the FADB (multinomial regression, 53 of 70 vs 17 of 75 [76%] vs [23%]). The signal-to-noise ratio and contrast-to-noise ratio of the FADB did not improve significantly (ANOVA, p = 0.20; p = 0.09). The CTA NDX rate was reduced, but not significantly (initial CCTA database 15 of 70 [21.4%]) and FADB 9 of 75 [12%]; p = 0.13).

Conclusion: We were able to increase conformity to the inclusion/exclusion criteria and CCTA protocol, improve image quality and decrease the CCTA NDX rate by implementing EU CCTA quality criteria and ICA recommendations.

Key Points: • Failure to meet protocol adherence in cardiac CTA was high in the pilot study (77.6%). • Image quality varies between sites and can be improved by feedback given by the core lab. • Conformance with new EU cardiac CT quality criteria might render cardiac CTA findings more consistent and comparable.
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http://dx.doi.org/10.1007/s00330-019-06522-zDOI Listing
April 2020

Ischemia and No Obstructive Stenosis (INOCA) at CT Angiography, CT Myocardial Perfusion, Invasive Coronary Angiography, and SPECT: The CORE320 Study.

Radiology 2020 01 19;294(1):61-73. Epub 2019 Nov 19.

From the Global RDC, Canon Medical Systems Europe, Zoetermeer, the Netherlands (J.D.S.); Department of Epidemiology, Johns Hopkins University, Baltimore, Md (M.B.M., C.C.); Departments of Medicine and Radiology, Johns Hopkins School of Medicine, 600 N Wolfe St, Blalock 524, Baltimore, MD 21287 (M.R.O., A.A., J.A.C.L.); Department of Cardiology and Radiology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark (K.F.K.); Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands (A.J.H.A.S.); Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany (M.D.); Canon Medical Systems, Otawara, Japan (C.S.); InCor Heart Institute, University of São Paulo Medical School, São Paulo, Brazil (C.E.R.); Department of Radiology, Iwate Medical University, Morioka, Japan (K.Y.); and Departments of Radiology and Medicine, Brigham and Women's Hospital, Boston, Mass (M.F.D.C.).

Background CT allows evaluation of atherosclerosis, coronary stenosis, and myocardial ischemia. Data on the characterization of ischemia and no obstructive stenosis (INOCA) at CT remain limited. Purpose This was an observational study to describe the prevalence of INOCA defined at coronary CT angiography with CT perfusion imaging and associated clinical and atherosclerotic characteristics. The analysis was also performed for the combination of invasive coronary angiography (ICA) and SPECT as a secondary aim. Materials and Methods The prospective CORE320 study (: NCT00934037) enrolled participants between November 2009 and July 2011 who were symptomatic and referred for clinically indicated ICA. Participants underwent CT angiography, rest-adenosine stress CT perfusion, and rest-stress SPECT prior to ICA. For this ancillary study, the following three phenotypes were considered, using either CT angiography/CT perfusion or ICA/SPECT data: participants with obstructive (≥50%) stenosis, participants with no obstructive stenosis but ischemia (ie, INOCA) on the basis of abnormal perfusion imaging results, and participants with no obstructive stenosis and normal perfusion imaging results. Clinical characteristics and CT angiography atherosclerotic plaque measures were compared by using the Pearson χ or Wilcoxon rank-sum test. Results A total of 381 participants (mean age, 62 years [interquartile range, 56-68 years]; 129 [34%] women) were evaluated. A total of 31 (27%) of 115 participants without obstructive (≥50%) stenosis at CT angiography had abnormal CT perfusion findings. The corresponding value for ICA/SPECT was 45 (30%) of 151. The prevalence of INOCA was 31 (8%) of 381 (95% confidence interval [CI]: 5%, 11%) with CT angiography/CT perfusion and 45 (12%) of 381 (95% CI: 9%, 15%) with ICA/SPECT. Participants with CT-defined INOCA had greater total atheroma volume (118 vs 60 mm, = .008), more positive remodeling (13% vs 1%, = .006), and greater low-attenuation atheroma volume (20 vs 10 mm, = .007) than participants with no obstructive stenosis and no ischemia. Comparisons for ICA/SPECT showed similar trends. Conclusion In CORE320, ischemia and no obstructive stenosis (INOCA) prevalence was 8% and 12% at CT angiography/CT perfusion and invasive coronary angiography/SPECT, respectively. Participants with INOCA had greater atherosclerotic burden and more adverse plaque features at CT compared with those with no obstructive stenosis and no ischemia. © RSNA, 2019 See also the editorial by François in this issue.
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http://dx.doi.org/10.1148/radiol.2019190978DOI Listing
January 2020

Deep learning and medical diagnosis.

Lancet 2019 11;394(10210):1710-1711

Jena University Hospital, Institute for Medical Statistics, Computer Science and Data Science, Jena, Germany.

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http://dx.doi.org/10.1016/S0140-6736(19)32498-5DOI Listing
November 2019

Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.

Eur Radiol 2020 Feb 29;30(2):1243-1253. Epub 2019 Aug 29.

Department of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.

Objective: To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN).

Methods: Two hundred patients with a total of 318 lesions for which histological correlation was available were analyzed. A novel CNN was designed, trained, and validated using different combinations of distinct MRI sequences as input (e.g., T2-weighted, apparent diffusion coefficient (ADC), diffusion-weighted images, and K-trans) and the effect of different sequences on the network's performance was tested and discussed. The particular choice of modeling approach was justified by testing all relevant data combinations. The model was trained and validated using eightfold cross-validation.

Results: In terms of detection of significant prostate cancer defined by biopsy results as the reference standard, the 3D CNN achieved an area under the curve (AUC) of the receiver operating characteristics ranging from 0.89 (88.6% and 90.0% for sensitivity and specificity respectively) to 0.91 (81.2% and 90.5% for sensitivity and specificity respectively) with an average AUC of 0.897 for the ADC, DWI, and K-trans input combination. The other combinations scored less in terms of overall performance and average AUC, where the difference in performance was significant with a p value of 0.02 when using T2w and K-trans; and 0.00025 when using T2w, ADC, and DWI. Prostate cancer classification performance is thus comparable to that reported for experienced radiologists using the prostate imaging reporting and data system (PI-RADS). Lesion size and largest diameter had no effect on the network's performance.

Conclusion: The diagnostic performance of the 3D CNN in detecting clinically significant prostate cancer is characterized by a good AUC and sensitivity and high specificity.

Key Points: • Prostate cancer classification using a deep learning model is feasible and it allows direct processing of MR sequences without prior lesion segmentation. • Prostate cancer classification performance as measured by AUC is comparable to that of an experienced radiologist. • Perfusion MR images (K-trans), followed by DWI and ADC, have the highest effect on the overall performance; whereas T2w images show hardly any improvement.
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http://dx.doi.org/10.1007/s00330-019-06417-zDOI Listing
February 2020

Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI With Limited Training Data.

IEEE Trans Med Imaging 2020 03 9;39(3):703-717. Epub 2019 Aug 9.

In this work we reduce undersampling artefacts in two-dimensional (2D) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D spatio-temporal slices which are previously extracted from the image sequences. We compare our approach to two 2D and a 3D deep learning-based post processing methods, three iterative reconstruction methods and two recently proposed methods for dynamic cardiac MRI based on 2D and 3D cascaded networks. Our method outperforms the 2D spatially trained U-net and the 2D spatio-temporal U-net. Compared to the 3D spatio-temporal U-net, our method delivers comparable results, but requiring shorter training times and less training data. Compared to the compressed sensing-based methods kt-FOCUSS and a total variation regularized reconstruction approach, our method improves image quality with respect to all reported metrics. Further, it achieves competitive results when compared to the iterative reconstruction method based on adaptive regularization with dictionary learning and total variation and when compared to the methods based on cascaded networks, while only requiring a small fraction of the computational and training time. A persistent homology analysis demonstrates that the data manifold of the spatio-temporal domain has a lower complexity than the one of the spatial domain and therefore, the learning of a projection-like mapping is facilitated. Even when trained on only one single subject without data-augmentation, our approach yields results which are similar to the ones obtained on a large training dataset. This makes the method particularly suitable for training a network on limited training data. Finally, in contrast to the spatial 2D U-net, our proposed method is shown to be naturally robust with respect to image rotation in image space and almost achieves rotation-equivariance where neither data-augmentation nor a particular network design are required.
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http://dx.doi.org/10.1109/TMI.2019.2930318DOI Listing
March 2020