Department of Radiation Oncology, Seoul National University College of Medicine, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea.
Department of Radiation Oncology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, 82 Gumi-ro 173beon-gil, Bundang-gu, Seongnam, 13620, Republic of Korea.
Radiat Oncol. 2019 Mar 12;14(1):43. doi: 10.1186/s13014-019-1246-8.
To develop and compare delta-radiomics signatures from 2- (2D) and 3-dimensional (3D) features that predict treatment outcomes following preoperative chemoradiotherapy (CCRT) and surgery for locally advanced rectal cancer.
In total, 101 patients (training cohort, n = 67; validation cohort, n = 34) with locally advanced rectal adenocarcinoma between 2008 and 2015 were included. We extracted 55 features from T2-weighted magnetic resonance imaging (MRI) scans. Delta-radiomics feature was defined as the difference in radiomics feature before and after CCRT. Signatures were developed to predict local recurrence (LR), distant metastasis (DM), and disease-free survival (DFS) from 2D and 3D features. The least absolute shrinkage and selection operator regression was used to select features and build signatures. The delta-radiomics signatures and clinical factors were integrated into Cox regression analysis to determine if the signatures were independent prognostic factors.
The radiomics signatures for LR, DM, and DFS were developed and validated using both 2D and 3D features. Outcomes were significantly different in the low- and high-risk patients dichotomized by optimal cutoff in both the training and validation cohorts. In multivariate analysis, the signatures were independent prognostic factors even when considering the clinical parameters. There were no significant differences in C-index from 2D vs. 3D signatures.
This is the first study to develop delta-radiomics signatures for rectal cancer. The signatures successfully predicted the outcomes and were independent prognostic factors. External validation is warranted to ensure their performance.
开发并比较从 2 维（2D）和 3 维（3D）特征中提取的预测局部晚期直肠癌患者术前放化疗（CCRT）及手术治疗后结局的放射组学特征。
共纳入 2008 年至 2015 年间 101 例局部晚期直肠腺癌患者（训练队列，n=67；验证队列，n=34）。我们从 T2 加权磁共振成像（MRI）扫描中提取了 55 个特征。Delta 放射组学特征定义为 CCRT 前后放射组学特征的差异。从 2D 和 3D 特征中开发了预测局部复发（LR）、远处转移（DM）和无病生存（DFS）的特征。最小绝对收缩和选择算子回归用于选择特征和构建特征。将 Delta 放射组学特征和临床因素整合到 Cox 回归分析中，以确定特征是否为独立预后因素。
使用 2D 和 3D 特征开发并验证了 LR、DM 和 DFS 的放射组学特征。在训练和验证队列中，通过最佳截断值将患者分为低风险和高风险两组，两组的结果存在显著差异。多变量分析显示，即使考虑到临床参数，这些特征仍然是独立的预后因素。2D 与 3D 特征的 C 指数无显著差异。
这是第一项开发直肠癌 Delta 放射组学特征的研究。该特征成功预测了结局，是独立的预后因素。需要进行外部验证以确保其性能。
