Development and validation of a prognostic nomogram incorporating automated collateral score and computed tomography perfusion parameters for patients with acute ischemic stroke undergoing endovascular thrombectomy.

Background: Prognostic evaluation of patients with acute ischemic stroke (AIS) after endovascular thrombectomy (EVT) remains challenging. Traditional computed tomography angiography (CTA) and computed tomography perfusion (CTP) have limitations, whereas multiphase CTA (mCTA) allows for more accurate collateral circulation assessment. However, the predictive utility of automated collateral scoring remains underexplored. This study aimed to develop and validate a nomogram combining automated collateral scores and CTP parameters to enhance the prognostic prediction in patients with AIS undergoing EVT.

Methods: This retrospective study enrolled patients with AIS due to large-vessel occlusion (LVO) who underwent multimodal computed tomography (CT) and EVT between January 2017 and December 2022. The inclusion criteria were as follows: (I) age ≥18 years; (II) symptom onset within 24 hours; (III) available non-contrast CT (NCCT) and CTP; and (IV) 90-day modified Rankin Scale (mRS) score. Meanwhile, the exclusion criteria included posterior circulation stroke, intracranial hemorrhage, extensive prior infarction, prestroke mRS ≥2, poor image quality, and missing outcome data. A total of 111 patients were included and randomly assigned to development (n=77) and validation (n=34) cohorts. Clinical data, National Institutes of Health Stroke Scale (NIHSS) features, and imaging features [including automated collateral scores from NeuBrainCARE (NBC) software and relative cerebral blood flow (rCBF) <30% volume] were analyzed. Agreement between automated and manual Menon collateral scores was assessed via Cohen's kappa. A nomogram was constructed through multivariable logistic regression and validated with bootstrapping (500 iterations). Clinical outcomes were assessed at 90 days through the mRS, with outcomes categorized as good (mRS 0-2) or poor (mRS 3-6).

Results: Manual collateral scoring between physicians showed substantial agreement (κ=0.667). For the automated scoring system, the consistency with manual scoring performed by a junior physician resulted in a kappa value of 0.597, while comparison with senior physicians yielded a higher kappa value of 0.872. The median age was 67 years [interquartile range (IQR), 54-74] years, and 60.3% were male. At 90 days, 54.1% had good outcomes (mRS 0-2). Key independent predictors included age, admission NIHSS, automated collateral score, and rCBF <30% volume (P<0.05). The nomogram achieved strong discrimination in both the development [concordance index (C-index) 0.872, sensitivity 82.9%, and specificity 80.6%] and validation (C-index 0.807, sensitivity 68.4%, and specificity 93.3%) cohorts.

Conclusions: This study supports the use of automated collateral scoring as a reliable and unbiased method in AIS prognosis. The proposed nomogram, integrating clinical and imaging parameters, provides an effective tool for outcome prediction after EVT, facilitating individualized treatment planning and optimizing patient selection.