Combining the Qualitative and Quantitative Parameters of Dual-layer Detector Spectral Computed Tomography to Predict Intracranial Hemorrhage in Acute Ischemic Stroke Patients After Mechanical Thrombectomy.

Abstract

Aim: To investigate the predictive value of combining qualitative and quantitative parameters from dual-layer spectral detector CT (DLCT) in identifying intracranial hemorrhage (ICH) after mechanical thrombectomy (MT) in patients with acute ischemic stroke and large vessel occlusion (AIS-LVO).

Materials and methods: This retrospective study consecutively enrolled 120 patients with AIS-LVO who underwent MT, followed by DLCT performed 3 hours postprocedure. After applying the inclusion and exclusion criteria, 30 patients were included in the final analysis. Two radiologists independently assessed the presence of high-density areas (HDA) on noncontrast DLCT images. Qualitative imaging signs and quantitative parameters were subsequently obtained through observation and measurement of HDAs. Follow-up CT examinations conducted during hospitalization were reviewed for ICH development. The sensitivity and specificity of the DLCT parameters for early ICH diagnosis were calculated, and the diagnostic accuracy was evaluated using receiver operating characteristic (ROC) curve analysis.

Results: Fifty-five HDAs were detected on DLCT images from 30 patients. Follow-up noncontrast CT confirmed the development of ICH in 19/55 (34.5%) HDAs. Univariate analysis revealed significant differences in the mass effect, low-density edema zone, the median maximum CT value, the median cross-sectional area, the median maximum iodine concentration, the median relative iodine concentration, and the median Z-effective value between the ICH and non-ICH groups were significantly different (P < 0.05). Multivariate logistic regression identified low-density edema zone and the relative iodine concentration as independent predictors, which were incorporated into a combined diagnostic model. ROC analysis revealed an area under the curve (AUC) of 0.901 (95% CI: 0.807-0.994) for ICH prediction, with a sensitivity of 89.5% and specificity of 80.6%.

Conclusions: The combination of qualitative and quantitative DLCT parameters demonstrated excellent predictive performance for identifying ICH after MT in patients with AIS-LVO.