BackgroundHemorrhagic transformation (HT) following reperfusion therapies is a serious complication for patients with acute ischemic stroke. Segmentation and quantification of hemorrhage provides critical insights into patients’ condition and aids in prognosis. This study aims to automatically segment hemorrhagic regions on follow-up non-contrast head CT (NCCT) for stroke patients treated with endovascular thrombectomy (EVT).MethodsPatient data were collected from 10 stroke centers across two countries. We propose a semi-automated approach with adaptive thresholding methods, eliminating the need for extensive training data and reducing computational demands. We used Dice Similarity Coefficient (DSC) and Lin’s Concordance Correlation Coefficient (Lin’s CCC) to evaluate the performance of the algorithm.ResultsA total of 51 patients were included, with 28 Type 2 hemorrhagic infarction (HI2) cases and 23 parenchymal hematoma (PH) cases. The algorithm achieved a mean DSC of 0.66 ± 0.17. Notably, performance was superior for PH cases (mean DSC of 0.73 ± 0.14) compared to HI2 cases (mean DSC of 0.61 ± 0.18). Lin’s CCC was 0.88 (95% CI 0.79–0.93), indicating a strong agreement between the algorithm’s results and the ground truth. In addition, the algorithm demonstrated excellent processing time, with an average of 2.7 s for each patient case.ConclusionTo our knowledge, this is the first study to perform automated segmentation of post-treatment hemorrhage for acute stroke patients and evaluate the performance based on the radiological severity of HT. This rapid and effective tool has the potential to assist with predicting prognosis in stroke patients with HT after EVT.

中文翻译：

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急性缺血性脑卒中随访平扫CT出血转化的自动分割

背景再灌注治疗后的出血性转化（HT）是急性缺血性卒中患者的严重并发症。出血的分割和量化为了解患者的病情提供了重要的见解并有助于预后。本研究旨在对接受血管内血栓切除术 (EVT) 治疗的中风患者进行后续非对比头部 CT (NCCT) 自动分割出血区域。方法从两个国家的 10 个中风中心收集患者数据。我们提出了一种具有自适应阈值方法的半自动化方法，消除了对大量训练数据的需要并减少了计算需求。我们使用Dice相似系数（DSC）和林氏一致性相关系数（Lin's CCC）来评估算法的性能。结果共纳入51例患者，其中2型出血性梗死（HI2）28例，实质血肿（PH）23例案例。该算法的平均 DSC 为 0.66 ± 0.17。值得注意的是，PH 病例（平均 DSC 为 0.73 ± 0.14）的性能优于 HI2 病例（平均 DSC 为 0.61 ± 0.18）。 Lin 的 CCC 为 0.88（95% CI 0.79–0.93），表明算法结果与真实情况高度一致。此外，该算法表现出出色的处理时间，每个患者病例平均为 2.7 秒。结论据我们所知，这是第一项对急性中风患者治疗后出血进行自动分割并根据HT 的放射学严重程度。这种快速有效的工具有可能帮助预测 EVT 后患有 HT 的中风患者的预后。