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<p>Hemorrhagic transformation (HT) critically impacts outcomes in acute ischemic stroke (AIS) patients post-endovascular thrombectomy (EVT). Building upon the validated utility of post-EVT dual-energy CT (DECT), this study focused on developing and integrating a DECT-based predictive model with key clinical variables to achieve precise, individualized quantification of HT risk. This retrospective study analyzed 116 thrombectomy treated AIS patients stratified by HT status. Post-EVT DECT within 24&#xa0;h assessed CT values (in Hounsfield Units, HU) of ischemic lesions on mixed energy images; CT values (in HU) on virtual non-contrast (VNC) images and on Sn80 keV and Sn150 keV monoenergetic images; absolute iodine concentrations (AIC, in mg/mL); and relative iodine concentrations (RIC, in %, where RIC = lesion AIC/sigmoid sinus AIC), using follow-up imaging and clinical criteria as the gold standard for HT.. HT patients exhibited higher NIHSS (median 14.5 vs. 9.0) and lower ASPECTS (9 vs. 13) than non-HT (nHT) counterparts, with elevated glucose (GLU, 8.26 vs. 6.45&#xa0;mmol/L) and lower systolic blood pressure (SBP, 147.5 vs. 156.5&#xa0;mmHg) (all <i>P</i> &lt; 0.050). DECT-derived parameters demonstrated diagnostic utility, with both iodine overlay maps (IOM) and VNC positivity (χ<sup>2</sup> = 60.331, <i>P</i> &lt; 0.001) and dual negativity (χ<sup>2</sup> = 58.870, <i>P</i> &lt; 0.001) showing significant intergroup discrimination. Among 42 patients with IOM hyperdensity, RIC differed significantly between subgroups (<i>t</i> = − 2.566, <i>P</i> = 0.014), with elevated RIC independently associated with HT risk (OR = 1.040, 95% CI 1.003–1.078; <i>P</i> = 0.034). RIC alone exhibited strong predictive capacity for HT (AUC = 0.890, 95% CI 0.822–0.957). A nomogram-based model incorporating NIHSS, ASPECTS, and RIC achieved excellent HT prediction in both training (AUC = 0.947, 95% CI 0.903–0.991) and validation cohorts (AUC = 0.902, 95% CI 0.786–1.000), with stable calibration (training: <i>P</i> = 0.655; validation: <i>P</i> = 0.175) and clinical utility on decision curve analysis. Integration into stroke protocols may guide anticoagulation and secondary prevention decisions.</p>

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A bicentric study on the application of dual energy CT for predicting hemorrhagic transformation post endovascular thrombectomy

  • 期刊论文

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  • 发表日期：

    2025年11月24日

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  • Gangming Zhu,
  • Fanqi Xia,
  • Gai Yang,
  • Yongde Dong,
  • Ruiting Zhu,
  • Yuanman Tan,
  • Tuanxin Xu,
  • Dingxing Mo,
  • Chengkang Liu,
  • Nuo Chen,
  • Zihuan Fu,
  • Zengjin Lin,
  • Wenjun Su,
  • Siyi Yang,
  • Decheng Chen,
  • Xusen Liang

摘要

Hemorrhagic transformation (HT) critically impacts outcomes in acute ischemic stroke (AIS) patients post-endovascular thrombectomy (EVT). Building upon the validated utility of post-EVT dual-energy CT (DECT), this study focused on developing and integrating a DECT-based predictive model with key clinical variables to achieve precise, individualized quantification of HT risk. This retrospective study analyzed 116 thrombectomy treated AIS patients stratified by HT status. Post-EVT DECT within 24 h assessed CT values (in Hounsfield Units, HU) of ischemic lesions on mixed energy images; CT values (in HU) on virtual non-contrast (VNC) images and on Sn80 keV and Sn150 keV monoenergetic images; absolute iodine concentrations (AIC, in mg/mL); and relative iodine concentrations (RIC, in %, where RIC = lesion AIC/sigmoid sinus AIC), using follow-up imaging and clinical criteria as the gold standard for HT.. HT patients exhibited higher NIHSS (median 14.5 vs. 9.0) and lower ASPECTS (9 vs. 13) than non-HT (nHT) counterparts, with elevated glucose (GLU, 8.26 vs. 6.45 mmol/L) and lower systolic blood pressure (SBP, 147.5 vs. 156.5 mmHg) (all P < 0.050). DECT-derived parameters demonstrated diagnostic utility, with both iodine overlay maps (IOM) and VNC positivity (χ2 = 60.331, P < 0.001) and dual negativity (χ2 = 58.870, P < 0.001) showing significant intergroup discrimination. Among 42 patients with IOM hyperdensity, RIC differed significantly between subgroups (t = − 2.566, P = 0.014), with elevated RIC independently associated with HT risk (OR = 1.040, 95% CI 1.003–1.078; P = 0.034). RIC alone exhibited strong predictive capacity for HT (AUC = 0.890, 95% CI 0.822–0.957). A nomogram-based model incorporating NIHSS, ASPECTS, and RIC achieved excellent HT prediction in both training (AUC = 0.947, 95% CI 0.903–0.991) and validation cohorts (AUC = 0.902, 95% CI 0.786–1.000), with stable calibration (training: P = 0.655; validation: P = 0.175) and clinical utility on decision curve analysis. Integration into stroke protocols may guide anticoagulation and secondary prevention decisions.