Impact of Encephalomalacia and White Matter Hyperintensities on ASPECTS in Patients With Acute Ischemic Stroke: Comparison of Automated and Radiologist-Derived Scores.

Abstract

BACKGROUND. Automated software-based Alberta Stroke Program Early CT Score (ASPECTS) on unenhanced CT is associated with clinical outcomes after acute stroke. However, encephalomalacia or white matter hyperintensities (WMH) may result in a falsely low automated ASPECTS if such findings are interpreted as early ischemia. OBJECTIVE. The purpose of this study was to assess the impact of encephalomalacia and WMH on the automated ASPECTS in patients with acute stroke, in comparison with the radiologist-derived ASPECTS and clinical outcomes. METHODS. This retrospective three-center study included 459 patients (322 men, 137 women; median age, 65 years) with acute ischemic stroke treated by IV thrombolysis who underwent baseline unenhanced CT within 6 hours after symptom onset and MRI within 24 hours after treatment. ASPECTS was determined by automated software and by three radiologists in consensus. Presence of encephalomalacia and extent of WMH (categorized using the modified Scheltens score [mSS]) were also determined using MRI. Kappa coefficients were used to compare the ASPECTS between automated- and radiologist-derived methods. Multivariable logistic regression analyses and ROC analyses were performed to explore the predictive utility of the baseline ASPECTS for unfavorable clinical outcomes (90-day modified Rankin score of 3-6) after thrombolysis. RESULTS. The median automated software-derived ASPECTS was 9, and the median radiologist consensus-derived ASPECTS was 10. Agreement between automated and radiologist-consensus ASPECTS, expressed as kappa, was 0.68, though agreement was 0.76 in patients without encephalomalacia and 0.08 in patients with encephalomalacia. In patients without encephalomalacia, agreement decreased as the mSS increased (e.g., 0.78 in subgroup with mSS < 10 vs 0.19 in subgroup with mSS > 20). By anatomic region, agreement was highest for the lateral middle cerebral artery (κ, 0.52) and lowest for the internal capsule (κ, 0.18). In multivariable analyses, both the automated (odds ratio, 0.69) and the radiologist-consensus (odds ratio, 0.57) ASPECTS independently predicted an unfavorable clinical outcome. For unfavorable outcome, the automated ASPECTS had an AUC of 0.70, sensitivity of 60.4%, and specificity of 70.7%, whereas the radiologist-consensus ASPECTS had an AUC of 0.72, sensitivity of 60.4%, and specificity of 80.5%. CONCLUSION. Presence of encephalomalacia or extensive WMH results in a lower automated than radiologist-consensus ASPECTS, which may impact predictive utility of automated ASPECTS. CLINICAL IMPACT. When using an automated software-derived ASPECTS, radiologists should manually confirm the score in patients with encephalomalacia or extensive leukoencephalopathy.