Division of Neurosurgery, PRISMA Health, Greenville , South Carolina , USA.
Department of Neurosurgery, Memorial Sloan Kettering Cancer Center, New York , New York , USA.
Neurosurgery. 2024 Feb 1;94(2):317-324. doi: 10.1227/neu.0000000000002667. Epub 2023 Sep 25.
Several neurosurgical pathologies, ranging from glioblastoma to hemorrhagic stroke, use volume thresholds to guide treatment decisions. For chronic subdural hematoma (cSDH), with a risk of retreatment of 10%-30%, the relationship between preoperative and postoperative cSDH volume and retreatment is not well understood. We investigated the potential link between preoperative and postoperative cSDH volumes and retreatment.
We performed a retrospective chart review of patients operated for unilateral cSDH from 4 level 1 trauma centers, February 2009-August 2021. We used a 3-dimensional deep learning, automated segmentation pipeline to calculate preoperative and postoperative cSDH volumes. To identify volume thresholds, we constructed a receiver operating curve with preoperative and postoperative volumes to predict cSDH retreatment rates and selected the threshold with the highest Youden index. Then, we developed a light gradient boosting machine to predict the risk of cSDH recurrence.
We identified 538 patients with unilateral cSDH, of whom 62 (12%) underwent surgical retreatment within 6 months of the index surgery. cSDH retreatment was associated with higher preoperative (122 vs 103 mL; P < .001) and postoperative (62 vs 35 mL; P < .001) volumes. Patients with >140 mL preoperative volume had nearly triple the risk of cSDH recurrence compared with those below 140 mL, while a postoperative volume >46 mL led to an increased risk for retreatment (22% vs 6%; P < .001). On multivariate modeling, our model had an area under the receiver operating curve of 0.76 (95% CI: 0.60-0.93) for predicting retreatment. The most important features were preoperative and postoperative volume, platelet count, and age.
Larger preoperative and postoperative cSDH volumes increase the risk of retreatment. Volume thresholds may allow identification of patients at high risk of cSDH retreatment who would benefit from adjunct treatments. Machine learning algorithm can quickly provide accurate estimates of preoperative and postoperative volumes.
从胶质母细胞瘤到脑出血等多种神经外科疾病都使用体积阈值来指导治疗决策。对于慢性硬脑膜下血肿（cSDH），其再治疗风险为 10%-30%，术前和术后 cSDH 体积与再治疗之间的关系尚不清楚。我们研究了术前和术后 cSDH 体积与再治疗之间的潜在联系。
我们对 2009 年 2 月至 2021 年 8 月在 4 个 1 级创伤中心接受单侧 cSDH 手术的患者进行了回顾性图表审查。我们使用 3 维深度学习自动分割流水线来计算术前和术后 cSDH 体积。为了确定体积阈值，我们构建了术前和术后体积的受试者工作特征曲线，以预测 cSDH 再治疗率，并选择具有最高 Youden 指数的阈值。然后，我们开发了一个轻梯度提升机来预测 cSDH 复发的风险。
我们确定了 538 例单侧 cSDH 患者，其中 62 例（12%）在指数手术后 6 个月内行手术再治疗。cSDH 再治疗与更高的术前（122 毫升比 103 毫升；P <.001）和术后（62 毫升比 35 毫升；P <.001）体积相关。术前体积＞140 毫升的患者发生 cSDH 复发的风险几乎是术前体积＜140 毫升的患者的 3 倍，而术后体积＞46 毫升则会增加再治疗的风险（22%比 6%；P <.001）。在多变量建模中，我们的模型预测再治疗的受试者工作特征曲线下面积为 0.76（95%CI：0.60-0.93）。最重要的特征是术前和术后体积、血小板计数和年龄。
更大的术前和术后 cSDH 体积增加了再治疗的风险。体积阈值可能有助于识别再治疗风险高的 cSDH 患者，这些患者可能受益于辅助治疗。机器学习算法可以快速提供术前和术后体积的准确估计。
