Automated Collateral Scoring on CT Angiography of Patients with Acute Ischemic Stroke Using Hybrid CNN and Transformer Network

Radiomics-Based Prediction of Collateral Status from CT Angiography of Patients Following a Large Vessel Occlusion Stroke

BACKGROUND

A major driver of individual variation in long-term outcomes following a large vessel occlusion (LVO) stroke is the degree of collateral arterial circulation. We aimed to develop and evaluate machine-learning models that quantify LVO collateral status using admission computed tomography angiography (CTA) radiomics.

METHODS

We extracted 1116 radiomic features from the anterior circulation territories from admission CTAs of 600 patients experiencing an acute LVO stroke. We trained and validated multiple machine-learning models for the prediction of collateral status based on consensus from two neuroradiologists as ground truth. Models were first trained to predict (1) good vs. intermediate or poor, or (2) good vs. intermediate or poor collateral status. Then, model predictions were combined to determine a three-tier collateral score (good, intermediate, or poor). We used the receiver operating characteristics area under the curve (AUC) to evaluate prediction accuracy.

RESULTS

We included 499 patients in training and 101 in an independent test cohort. The best-performing models achieved an averaged cross-validation AUC of 0.80 ± 0.05 for poor vs. intermediate/good collateral and 0.69 ± 0.05 for good vs. intermediate/poor, and AUC = 0.77 (0.67-0.87) and AUC = 0.78 (0.70-0.90) in the independent test cohort, respectively. The collateral scores predicted by the radiomics model were correlated with (rho = 0.45, p = 0.002) and were independent predictors of 3-month clinical outcome (p = 0.018) in the independent test cohort.

CONCLUSIONS

Automated tools for the assessment of collateral status from admission CTA-such as the radiomics models described here-can generate clinically relevant and reproducible collateral scores to facilitate a timely treatment triage in patients experiencing an acute LVO stroke.

Inter-Rater Reliability of Collateral Status Assessment Based on CT Angiography: A Retrospective Study of Middle Cerebral Artery Ischaemic Stroke

The importance of assessing the collateral status (CS) in patients with ischaemic stroke (IS) has repeatedly been emphasised in clinical guidelines. Various publications offer qualitative or semiquantitative scales with gradations corresponding to the different extents of the collaterals, visualised mostly on the basis of CTA images. However, information on their inter-rater reliability is limited. Therefore, the aim of this study is to investigate the inter-rater reliability of the scales for collateral assessment. CTA images of 158 patients in the acute period of IS were used in the study. The assessment of CS was performed by two experts using three methodologies: the modified Tan scale, the Miteff scale, and the Rosenthal scale. Cohen's kappa, weighted kappa and Krippendorff's alpha were used as reliability measures. For the modified Tan scale and the Miteff and Rosenthal scales, the weighted kappa values were 0.72, 0.49 and 0.59, respectively. Although the best measure of consistency was found for the modified Tan scale, no statistically significant differences were revealed among the scales. The impact of the CS on the degree of neurological deficit at discharge was shown for the modified Tan and Rosenthal scales. In conclusion, the analysis showed a moderate inter-rater reliability of the three scales, but was not able to distinguish the best one among them.