Çukurova University Faculty of Medicine, Balçalı Hospital Health Application and Research Center, Department of Radiology, Adana, Türkiye
Çukurova University Faculty of Medicine, Balçalı Hospital Health Application and Research Center, Department of Biostatistics, Adana, Türkiye
Diagn Interv Radiol. 2024 May 13;30(3):193-199. doi: 10.4274/dir.2023.222025. Epub 2023 Mar 20.
The study aims to investigate the predictability of the radiological response in intrahepatic cholangiocarcinoma (iCC) patients undergoing Yttrium-90 transarterial radioembolization (TARE) with a combined model built on dynamic magnetic resonance imaging (MRI)-based radiomics and clinical features.
Thirty-six naive iCC patients who underwent TARE were included in this study. The tumor segmentation was performed on the axial T2-weighted (T2W) without fat suppression, axial T2W with fat suppression, and axial T1-weighted (T1W) contrast-enhanced (CE) sequence in equilibrium phase (Eq). At the sixth month MRI follow-up, all patients were divided into responders and non-responders according to the modified Response Evaluation Criteria in Solid Tumors. Subsequently, a radiomics score (rad-score) and a combined model of the rad-score and clinical features for each sequence were generated and compared between the groups.
Thirteen (36.1%) patients were considered responders, and the remaining 23 (63.9%) were non-responders. Responders exhibited significantly lower rad-scores than non-responders ( < 0.050 for all sequences). The radiomics models showed good discriminatory ability with an area under the curve (AUC) of 0.696 [95% confidence interval (CI), 0.522–0.870] for the axial T1W-CE-Eq, AUC of 0.839 (95% CI, 0.709–0.970) for the axial T2W with fat suppression, and AUC of 0.836 (95% CI, 0.678–0.995) for the axial T2W without fat suppression.
Radiomics models created by pre-treatment MRIs can predict the radiological response to Yttrium- 90 TARE in iCC patients with high accuracy. Combining radiomics with clinical features could increase the power of the test. Large-scale studies of multi-parametric MRIs with internal and external validations are needed to determine the clinical value of radiomics in iCC patients.
本研究旨在通过建立基于动态磁共振成像（MRI）的放射组学和临床特征的联合模型，探讨钇-90 经肝动脉放射栓塞（TARE）治疗肝内胆管癌（iCC）患者的放射学反应预测性。
本研究纳入了 36 例接受 TARE 的初治 iCC 患者。在轴向 T2 加权（T2W）无脂肪抑制、轴向 T2W 脂肪抑制和轴向 T1 加权（T1W）对比增强（CE）平衡期（Eq）序列上对肿瘤进行分割。在第六个月的 MRI 随访时，根据改良的实体瘤反应评价标准（RECIST）将所有患者分为应答者和无应答者。随后，生成每个序列的放射组学评分（rad-score）和 rad-score 与临床特征的联合模型，并对两组进行比较。
13 例（36.1%）患者被认为是应答者，其余 23 例（63.9%）为无应答者。应答者的 rad-score 显著低于无应答者（所有序列均<0.050）。放射组学模型具有良好的判别能力，轴向 T1W-CE-Eq 的曲线下面积（AUC）为 0.696[95%置信区间（CI），0.522-0.870]，轴向 T2W 脂肪抑制的 AUC 为 0.839（95%CI，0.709-0.970），轴向 T2W 无脂肪抑制的 AUC 为 0.836（95%CI，0.678-0.995）。
通过术前 MRI 建立的放射组学模型可以准确预测 iCC 患者接受钇-90 TARE 的放射学反应。将放射组学与临床特征相结合可以提高检验效能。需要进行多参数 MRI 的内部和外部验证的大规模研究，以确定放射组学在 iCC 患者中的临床价值。
