Journal
JOURNAL OF STROKE & CEREBROVASCULAR DISEASES
Volume 33, Issue 1, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jstrokecerebrovasdis.2023.107512
Keywords
Artificial intelligence; CT; Stroke; Hemorrhage
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This study evaluated the performance of e-ASPECTS software in delineating the extent of intracranial hemorrhage (ICH) on brain CT scans. The results showed that the software achieved excellent or good delineation of ICH extent in 71% of cases. However, it was more likely to over- or under-estimate the extent when ICH was more extensive, intraventricular, or extra-axial.
Background: : The extent and distribution of intracranial hemorrhage (ICH) directly affects clinical management. Artificial intelligence (AI) software can detect and may delineate ICH extent on brain CT. We evaluated e-ASPECTS software (Brainomix Ltd.) performance for ICH delineation. Methods: : We qualitatively assessed software delineation of ICH on CT using patients from six stroke trials. We assessed hemorrhage delineation in five compartments: lobar, deep, posterior fossa, intraventricular, extra-axial. We categorized delineation as excellent, good, moderate, or poor. We assessed quality of software delineation with number of affected compartments in univariate analysis (Kruskall-Wallis test) and ICH location using logistic regression (dependent variable: dichotomous delineation categories 'excellent-good' versus 'moderatepoor'), and report odds ratios (OR) and 95 % confidence intervals (95 %CI). Results: : From 651 patients with ICH (median age 75 years, 53 % male), we included 628 with assessable CTs. Software delineation of ICH extent was 'excellent' in 189/628 (30 %), 'good' in 255/628 (41 %), 'moderate' in 127/628 (20 %), and 'poor' in 57/628 cases (9 %). The quality of software delineation of ICH was better when fewer compartments were affected (Z = 3.61-6.27; p = 0.0063). Software delineation of ICH extent was more likely to be 'excellent-good' quality when lobar alone (OR = 1.56, 95 %CI = 0.97-2.53) but 'moderate-poor' with any intraventricular (OR = 0.56, 95 %CI = 0.39-0.81, p = 0.002) or any extra-axial (OR = 0.41, 95 %CI = 0.270.62, p<0.001) extension. Conclusions: : Delineation of ICH extent on stroke CT scans by AI software was excellent or good in 71 % of cases but was more likely to over- or under-estimate extent when ICH was either more extensive, intraventricular, or extra-axial.
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