Semiautomated Detection of Early Infarct Signs on Noncontrast CT Improves Interrater Agreement

Author:

Christensen Soren1ORCID,Demeestere Jelle23,Verhaaren Benjamin F.J.4ORCID,Heit Jeremy J.1ORCID,Von Stein Erica Leah5ORCID,Madill Evan S.5,Kennedy Loube Deanne5ORCID,Dugue Rachelle1ORCID,Rengarajan Sophie5,Mlynash Michael1ORCID,Albers Gregory W.1ORCID,Lemmens Robin23ORCID,Lansberg Maarten G.1ORCID

Affiliation:

1. Stanford Stroke Center, Palo Alto, CA (S.C., J.J.H., R.D., M.M., G.W.A., M.G.L.).

2. KU Leuven – University of Leuven, Department of Neurosciences, Experimental Neurology, Belgium (J.D., R.L.).

3. University Hospitals Leuven, Department of Neurology, Belgium (J.D., R.L.).

4. Department of Radiology, University Hospitals Leuven, Belgium (B.F.J.V.).

5. Stanford Neurology Department, Palo Alto, CA (E.L.V.S., E.S.M., D.K.L., S.R.).

Abstract

BACKGROUND: Acute ischemic infarct identification on noncontrast computed tomography (NCCT) is highly variable between raters. A semiautomated method for segmentation of acute ischemic lesions on NCCT may improve interrater reliability. METHODS: Patients with successful endovascular reperfusion from the DEFUSE 3 trial (Endovascular Therapy Following Imaging Evaluation for Ischemic Stroke) were included. We created relative NCCT (rNCCT) color-gradient overlays by comparing the density of a voxel on NCCT to the homologous region in the contralateral hemisphere. Regions with a relative hypodensity of at least 5% were visualized. We coregistered baseline and follow-up images. Two neuroradiologists and 6 nonradiologists segmented the acute ischemic lesion on the baseline scans with 2 methods: (1) manually outlining hypodense regions on the NCCT (unassisted segmentation) and (2) manually excluding areas deemed outside of the ischemic lesion on the rNCCT color map (rNCCT-assisted segmentation). Voxelwise interrater agreement was quantified using the Dice similarity coefficient and volumetric agreement between raters with the detection index (DI), defined as the true positive volume minus the false positive volume. RESULTS: From a total of 92, we included 61 patients. Median age was 59 (64–77), and 57% were female. Stroke onset was known in 39%. Onset to NCCT was median, 8.5 hours (7–11) and median 10 hours (8.4–11.5) in patients with known and unknown onset, respectively. Compared with unassisted NCCT segmentation, rNCCT-assisted segmentation increased the Dice similarity coefficient by >50% for neuroradiologists (Dice similarity coefficient, 0.38 versus 0.83; P <0.001) and nonradiologists (Dice similarity coefficient, 0.14 versus 0.84; P <0.001), and improved the DI among nonradiologists (mean improvement, 5.8 mL [95% CI, 3.1–8.5] mL, P <0.001) but not among neuroradiologists. CONCLUSIONS: The high variability of manual segmentations of the acute ischemic lesion on NCCT is greatly reduced using semiautomated rNCCT. The rNCCT map may therefore aid acute infarct detection and provide more reliable infarct estimates for clinicians with less experience.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Advanced and Specialized Nursing,Cardiology and Cardiovascular Medicine,Neurology (clinical)

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