2021
DOI: 10.1186/s41747-021-00225-1
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Evaluation of a CTA-based convolutional neural network for infarct volume prediction in anterior cerebral circulation ischaemic stroke

Abstract: Background Computed tomography angiography (CTA) imaging is needed in current guideline-based stroke diagnosis, and infarct core size is one factor in guiding treatment decisions. We studied the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from CTA and compared the results to a CT perfusion (CTP)-based commercially available software (RAPID, iSchemaView). Methods We retrospectively selected 83 consecutive stro… Show more

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Cited by 16 publications
(13 citation statements)
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“…As such, there is a need for accurate infarct core determinations using more widely available imaging modalities including Non-Contrast CT (NCCT) and CT Angiography (CTA). This problem has been pursued with automated machine learning approaches ( Hokkinen et al, 2021 , Hornung et al, 2020 , Kuang et al, 2021 , Lo et al, 2019 , Peter et al, 2017 , Qiu et al, 2020 , Sheth et al, 2019 , Srivatsan et al, 2019 , Wu et al, 2019 , Zhang et al, 2018 ) and visual semiquantitative inspection (NCCT / CTA-ASPECTS score) ( Coutts et al, 2004 , Lee et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…As such, there is a need for accurate infarct core determinations using more widely available imaging modalities including Non-Contrast CT (NCCT) and CT Angiography (CTA). This problem has been pursued with automated machine learning approaches ( Hokkinen et al, 2021 , Hornung et al, 2020 , Kuang et al, 2021 , Lo et al, 2019 , Peter et al, 2017 , Qiu et al, 2020 , Sheth et al, 2019 , Srivatsan et al, 2019 , Wu et al, 2019 , Zhang et al, 2018 ) and visual semiquantitative inspection (NCCT / CTA-ASPECTS score) ( Coutts et al, 2004 , Lee et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
“…All except two studies (45,48) reported validation methods for the proposed model including using an independent test set, k-fold cross-validation, and leave-one-out cross-validation.…”
Section: Resultsmentioning
confidence: 99%
“…Eleven studies used CT perfusion source data and parametric maps as model input for core infarct estimation (12,13,29,31,33,42,44,47,50,53,54), including one study generating a synthesized pseudo-DWI map based on CTP parametric maps (42). Five studies used source images and features derived from non-contrast CT (41,52) and CT angiography (15,45,46). Twenty-two studies adopted different combinations of MRI sequences including T1WI, T2WI, diffusion and perfusion for infarct core prediction (11, 14, 16, 17, 24-28, 30, 32, 34-40, 43, 48, 49, 51).…”
Section: Resultsmentioning
confidence: 99%
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“…CNN algorithm [ 17 ] and V-net network (V-net) algorithm [ 18 ] were introduced to be compared with the proposed Hessian matrix enhanced filtering segmentation algorithm. In this study, Jaccard index, Dice similarity coefficient, sensitivity, and specificity were used to express the effect of coronary artery segmentation, and the range of the two values was between 0 and 1, and the higher the value, the higher the segmentation accuracy.…”
Section: Methodsmentioning
confidence: 99%