Abstract
Objectives: We aimed to determine quantitative photon-counting CT (PCCT)-derived iodine map (IM) attenuation associated with visual detectability of parenchymal hyperattenuation on conventional brain window (BW) images after mechanical thrombectomy (MT) and to assess corresponding relative BW attenuation changes. Methods: In this retrospective single-center study, 12 patients with anterior circulation large vessel occlusion underwent MT followed by post-interventional PCCT. BW, IM, and virtual non-contrast reconstructions were generated. Follow-up non-contrast CT served as reference for final infarction extent. Of 54 ASPECTS regions with final infarction, 40 showed IM hyperattenuation and were included in the detectability analysis. Two blinded readers assessed visual detectability. IM attenuation and relative BW attenuation increase (%ΔHU) were evaluated using ROC analysis with clustered bootstrap resampling. Thresholds were determined using the Youden index. Results: Across all 54 regions with final infarction, median IM attenuation was significantly higher in infarcted than contralateral regions (6.39 vs. 2.18 HU, p < 0.001), while absolute BW attenuation did not differ significantly. Among the 40 regions with IM hyperattenuation, 15 were visually detectable on BW images. ROC analysis showed excellent performance for IM (AUC = 0.997) and %ΔHU (AUC = 0.984). The optimal IM threshold in the original cohort was 8.33 HU (sensitivity 100%, specificity 96.0%), and the optimal %ΔHU threshold was 3.06% (sensitivity 100%, specificity 92.0%). Bootstrap-derived median thresholds were 11.69 HU (95% interval 8.33–12.67) for IM and 3.06% (3.06–20.16%) for %ΔHU. Inter-reader agreement was excellent (κ = 0.81–0.86). Conclusions: PCCT-derived iodine quantification enables objective assessment of visual detectability of post-interventional parenchymal hyperattenuation. In this cohort, an internally derived IM cutoff of 8.33 HU was associated with BW visibility. These preliminary findings require validation in larger, independent multicenter cohorts.