Department of Nuclear Medicine, University Hospital Münster, Münster, Germany.
West German Cancer Centre (WTZ), Münster Site, Münster, Germany.
Cardiovasc Intervent Radiol. 2024 Apr;47(4):462-471. doi: 10.1007/s00270-024-03680-6. Epub 2024 Feb 28.
To evaluate the benefit of a contrast-enhanced computed tomography (CT) radiomics-based model for predicting response and survival in patients with colorectal liver metastases treated with transarterial Yttrium-90 radioembolization (TARE).
Fifty-one patients who underwent TARE were included in this single-center retrospective study. Response to treatment was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST 1.1) at 3-month follow-up. Patients were stratified as responders (complete/partial response and stable disease, n = 24) or non-responders (progressive disease, n = 27). Radiomic features (RF) were extracted from pre-TARE CT after segmentation of the liver tumor volume. A model was built based on a radiomic signature consisting of reliable RFs that allowed classification of response using multivariate logistic regression. Patients were assigned to high- or low-risk groups for disease progression after TARE according to a cutoff defined in the model. Kaplan-Meier analysis was performed to analyze survival between high- and low-risk groups.
Two independent RF [Energy, Maximal Correlation Coefficient (MCC)], reflecting tumor heterogeneity, discriminated well between responders and non-responders. In particular, patients with higher magnitude of voxel values in an image (Energy), and texture complexity (MCC), were more likely to fail TARE. For predicting treatment response, the area under the receiver operating characteristic curve of the radiomics-based model was 0.75 (95% CI 0.48-1). The high-risk group had a shorter overall survival than the low-risk group (3.4 vs. 6.4 months, p < 0.001).
Our CT radiomics model may predict the response and survival outcome by quantifying tumor heterogeneity in patients treated with TARE for colorectal liver metastases.
评估基于增强 CT 放射组学模型预测接受经动脉钇-90 放射性栓塞术（TARE）治疗的结直肠癌肝转移患者治疗反应和生存获益的作用。
本单中心回顾性研究纳入了 51 例行 TARE 的患者。采用实体瘤反应评估标准（RECIST 1.1）于 3 个月随访时评估治疗反应。根据治疗后疾病进展情况将患者分为应答者（完全/部分缓解和疾病稳定，n=24）和无应答者（疾病进展，n=27）。对肝脏肿瘤体积进行分割后，从 TARE 前 CT 中提取放射组学特征（RF）。基于包含可靠 RF 的放射组学特征构建模型，使用多变量逻辑回归对反应进行分类。根据模型中定义的截定点，将患者分为 TARE 后疾病进展高风险和低风险组。采用 Kaplan-Meier 分析比较高风险和低风险组之间的生存情况。
2 个独立的 RF（能量、最大相关系数（MCC）），反映了肿瘤异质性，能很好地区分应答者和无应答者。特别是，图像中体素值幅度较大（能量）和纹理复杂度较高（MCC）的患者，更有可能 TARE 治疗失败。用于预测治疗反应的放射组学模型的受试者工作特征曲线下面积为 0.75（95%CI 0.48-1）。高风险组的总生存时间短于低风险组（3.4 个月 vs. 6.4 个月，p<0.001）。
我们的 CT 放射组学模型可以通过量化 TARE 治疗结直肠癌肝转移患者的肿瘤异质性，预测治疗反应和生存结局。
