Endovascular treatment (EVT) for patients with intracranial atherosclerotic stenosis-related large vessel occlusion (ICAS-LVO) presents unique technical challenges. The presence of complex and calcified atherosclerotic plaques often complicates the achievement of successful recanalization. Despite significant advancements in EVT over the past decade, symptomatic intracerebral hemorrhage (sICH) remains a serious complication that contributes to poor clinical outcomes (1, 2).

Intracerebral hemorrhage(ICH) location strongly influences both clinical manifestations, prognosis and etiology (3–5). Acute spontaneous lobar intracerebral hemorrhages present a more severe early prognosis compared to deep subcortical hemorrhages (5). Furthermore, the underlying causes exhibit location specificity, with lobar hemorrhages showing a higher association with non-hypertensive vascular pathologies than deep hemorrhages (5).

The complexity of ICAS lesions may increase the risk of sICH following mechanical thrombectomy (MT), making this issue a key concern in clinical practice. sICH is a devastating event, with randomized controlled trials (RCTs) reporting an incidence rate of approximately 4.4% (6). However, real-world data suggest that the incidence of sICH may be higher than that observed in clinical trials (7–10). Given these risks, identifying independent predictors of sICH is crucial for optimizing peri-procedural management in patients with LVO.

The aim of this study is to investigate the clinical and procedural factors associated with sICH in patients with ICAS-LVO undergoing EVT. A comprehensive understanding of these factors may facilitate the optimization of treatment strategies and enhance clinical decision-making when managing this complex patient population.

In this retrospective study, we developed a nomogram incorporating onset-to-recanalization time, core infarct volume, and D-Dimer levels to predict the risk of symptomatic intracranial hemorrhage (sICH) in patients with ICAS-LVO following endovascular treatment (EVT). The clinical utility of this model was validated through decision curve analysis (DCA), which demonstrated significant net benefit within specific probability ranges. Early prediction of sICH is crucial for optimizing EVT in ICAS-LVO patients, and this nomogram provides a valuable tool for clinicians to guide treatment decisions and improve patient outcomes.

Previous studies have shown that the incidence of sICH after thrombectomy is higher in real-world settings than in randomized controlled trials (RCTs) (7–10). This is particularly true for patients with ICAS-LVO, where the complexity of ICAS lesions often poses challenges for neurointerventionalists, resulting in longer procedure durations (11, 12). Our study confirmed that longer onset-to-recanalization times are a significant predictor of sICH. This reflects the technical difficulties encountered during EVT for ICAS, as more attempts are often required to achieve successful recanalization. Our findings align with those of Kass-Hout et al. (13) who reported that longer procedure times are independently associated with sICH in patients undergoing thrombectomy for LVO stroke. To minimize the risk of sICH, it is essential to select the most appropriate techniques and devices to reduce procedure duration while achieving effective recanalization.

In our study, baseline infarct core volume also emerged as an independent predictor of sICH. This result is consistent with recent studies that reported an increased risk of sICH in patients with large infarct cores despite the benefits of EVT (14–16). Prior to these RCTs, studies using the ASPECTS score to measure infarct core found that a low ASPECTS score was a predictor of sICH after EVT (7, 17, 18). Several factors may explain why larger infarct cores increase the risk of sICH: reperfusion syndrome due to the rupture of necrotic vessel walls, and increased blood–brain barrier permeability caused by large infarct and edema volumes (19). These conditions are more likely to occur in patients with larger infarct cores, increasing the risk of complications like sICH, which can worsen clinical outcomes. Therefore, the risk–benefit ratio of thrombectomy must be carefully considered in patients with larger infarct cores.

Interestingly, we also found that D-Dimer levels were an independent predictor of sICH. D-Dimer is present in negligible amounts in healthy individuals but rises significantly in patients experiencing thrombotic or hyperfibrinolytic activity (20, 21). Previous studies have linked high D-Dimer levels with thrombotic diseases and stroke (22). Its dual role in hypercoagulation and subsequent fibrinolysis may contribute to hemorrhagic transformation in AIS patients after thrombectomy. Elevated baseline D-Dimer levels may indicate ongoing microthrombosis in the microcirculation of the occluded vessel, leading to extensive activation of the coagulation system, hyperfibrinolysis, and coagulopathic disturbances (23). This finding suggests that D-Dimer levels could be useful for early prediction of hemorrhagic transformation, and may aid in perioperative management by informing decisions on thrombectomy attempts, procedure timing, and the use of antithrombotic or anticoagulant therapies.

Multiple studies have established that the presence of intraventricular hemorrhage (IVH) is independently associated with increased mortality and poorer functional outcomes (24–26). Furthermore, IVH is closely linked to hematoma expansion (HE), a well-recognized predictor of unfavorable prognosis. Evidence also indicates that the detection of IVH on follow-up CT scans independently correlates with early hematoma expansion (27). In our study, patients with IVH extension exhibited a trend of poorer prognosis, which is consistent with previous research (24–26). Future studies could conduct more in-depth analyses by incorporating factors such as IVH severity scores.

This study has several limitations. First, it was a single-center, retrospective study with a relatively small sample size, which limits the generalizability of the findings to other populations and settings. A multicenter, prospective trial is necessary to validate the accuracy of the model. Second, not all potential risk factors were included in the analysis, meaning that additional predictors could enhance the model. Future studies should explore other parameters and investigate whether integrating additional biomarkers could improve the nomogram’s accuracy. Finally, while our study used prospectively collected data and the model showed good discriminative performance, external validation is needed to further assess its robustness and applicability in broader clinical settings.

Future research could integrate multi-omics data—such as genomic, proteomic, or metabolomic profiling of patients—to identify specific biomarkers associated with the occurrence of sICH. Furthermore, in-depth exploration of the underlying pathophysiological mechanisms and differentiation among hemorrhage subtypes may help develop more targeted prevention and management strategies tailored to sICH resulting from distinct etiological pathways.

A novel nomogram incorporating onset-to-recanalization time, core infarct volume, and D-dimer levels has demonstrated the ability to predict sICH in AIS patients with ICAS-LVO treated with EVT. Larger prospective studies are warranted to further validate the effectiveness of this predictive tool.