{"title":"Infarct core segmentation using U-Net in CT perfusion imaging: a feasibility study.","authors":"Ching-Ching Yang, Shih-Sheng Chen","doi":"10.1177/02841851241305736","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The wide variability in thresholds on computed tomography (CT) perfusion parametric maps has led to controversy in the stroke imaging community about the most accurate measurement of core infarction.</p><p><strong>Purpose: </strong>To investigate the feasibility of using U-Net to perform infarct core segmentation in CT perfusion imaging.</p><p><strong>Material and methods: </strong>CT perfusion parametric maps were the input of U-Net, while the ground truth segmentation was determined based on diffusion-weighted imaging (DWI). The dataset used in this study was from the ISLES2018 challenge, which contains 63 acute stroke patients receiving CT perfusion imaging and DWI within 8 h of stroke onset. The segmentation accuracy of model outputs was assessed by calculating Dice similarity coefficient (DSC), sensitivity, and intersection over union (IoU).</p><p><strong>Results: </strong>The highest DSC was observed in U-Net taking mean transit time (MTT) or time-to-maximum (Tmax) as input. Meanwhile, the highest sensitivity and IoU were observed in U-Net taking Tmax as input. A DSC in the range of 0.2-0.4 was found in U-Net taking Tmax as input when the infarct area contains < 1000 pixels. A DSC of 0.4-0.6 was found in U-Net taking Tmax as input when the infarct area contains 1000-1999 pixels. A DSC value of 0.6-0.8 was found in U-Net taking Tmax as input when the infarct area contains ≥ 2000 pixels.</p><p><strong>Conclusion: </strong>Our model achieved good performance for infarct area containing ≥ 2000 pixels, so it may assist in identifying patients who are contraindicated for intravenous thrombolysis.</p>","PeriodicalId":7143,"journal":{"name":"Acta radiologica","volume":" ","pages":"2841851241305736"},"PeriodicalIF":1.1000,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta radiologica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/02841851241305736","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The wide variability in thresholds on computed tomography (CT) perfusion parametric maps has led to controversy in the stroke imaging community about the most accurate measurement of core infarction.
Purpose: To investigate the feasibility of using U-Net to perform infarct core segmentation in CT perfusion imaging.
Material and methods: CT perfusion parametric maps were the input of U-Net, while the ground truth segmentation was determined based on diffusion-weighted imaging (DWI). The dataset used in this study was from the ISLES2018 challenge, which contains 63 acute stroke patients receiving CT perfusion imaging and DWI within 8 h of stroke onset. The segmentation accuracy of model outputs was assessed by calculating Dice similarity coefficient (DSC), sensitivity, and intersection over union (IoU).
Results: The highest DSC was observed in U-Net taking mean transit time (MTT) or time-to-maximum (Tmax) as input. Meanwhile, the highest sensitivity and IoU were observed in U-Net taking Tmax as input. A DSC in the range of 0.2-0.4 was found in U-Net taking Tmax as input when the infarct area contains < 1000 pixels. A DSC of 0.4-0.6 was found in U-Net taking Tmax as input when the infarct area contains 1000-1999 pixels. A DSC value of 0.6-0.8 was found in U-Net taking Tmax as input when the infarct area contains ≥ 2000 pixels.
Conclusion: Our model achieved good performance for infarct area containing ≥ 2000 pixels, so it may assist in identifying patients who are contraindicated for intravenous thrombolysis.
期刊介绍:
Acta Radiologica publishes articles on all aspects of radiology, from clinical radiology to experimental work. It is known for articles based on experimental work and contrast media research, giving priority to scientific original papers. The distinguished international editorial board also invite review articles, short communications and technical and instrumental notes.