Vargas Hebert Alberto, Veeraraghavan Harini, Micco Maura, Nougaret Stephanie, Lakhman Yulia, Meier Andreas A, Sosa Ramon, Soslow Robert A, Levine Douglas A, Weigelt Britta, Aghajanian Carol, Hricak Hedvig, Deasy Joseph, Snyder Alexandra, Sala Evis
Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Department of Medical Physics, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Eur Radiol. 2017 Sep;27(9):3991-4001. doi: 10.1007/s00330-017-4779-y. Epub 2017 Mar 13.
To evaluate the associations between clinical outcomes and radiomics-derived inter-site spatial heterogeneity metrics across multiple metastatic lesions on CT in patients with high-grade serous ovarian cancer (HGSOC).
IRB-approved retrospective study of 38 HGSOC patients. All sites of suspected HGSOC involvement on preoperative CT were manually segmented. Gray-level correlation matrix-based textures were computed from each tumour site, and grouped into five clusters using a Gaussian Mixture Model. Pairwise inter-site similarities were computed, generating an inter-site similarity matrix (ISM). Inter-site texture heterogeneity metrics were computed from the ISM and compared to clinical outcomes.
Of the 12 inter-site texture heterogeneity metrics evaluated, those capturing the differences in texture similarities across sites were associated with shorter overall survival (inter-site similarity entropy, similarity level cluster shade, and inter-site similarity level cluster prominence; p ≤ 0.05) and incomplete surgical resection (similarity level cluster shade, inter-site similarity level cluster prominence and inter-site cluster variance; p ≤ 0.05). Neither the total number of disease sites per patient nor the overall tumour volume per patient was associated with overall survival. Amplification of 19q12 involving cyclin E1 gene (CCNE1) predominantly occurred in patients with more heterogeneous inter-site textures.
Quantitative metrics non-invasively capturing spatial inter-site heterogeneity may predict outcomes in patients with HGSOC.
• Calculating inter-site texture-based heterogeneity metrics was feasible • Metrics capturing texture similarities across HGSOC sites were associated with overall survival • Heterogeneity metrics were also associated with incomplete surgical resection of HGSOC.
评估高级别浆液性卵巢癌（HGSOC）患者CT上多个转移病灶的临床结局与放射组学衍生的部位间空间异质性指标之间的关联。
一项经机构审查委员会批准的对38例HGSOC患者的回顾性研究。对术前CT上疑似HGSOC累及的所有部位进行手动分割。从每个肿瘤部位计算基于灰度相关矩阵的纹理，并使用高斯混合模型将其分为五个簇。计算部位间的成对相似性，生成部位间相似性矩阵（ISM）。从ISM计算部位间纹理异质性指标，并与临床结局进行比较。
在评估的12个部位间纹理异质性指标中，那些反映部位间纹理相似性差异的指标与较短的总生存期（部位间相似性熵、相似性水平簇阴影和部位间相似性水平簇突出度；p≤0.05）和不完全手术切除（相似性水平簇阴影、部位间相似性水平簇突出度和部位间簇方差；p≤0.05）相关。每位患者的疾病部位总数和每位患者的总体肿瘤体积均与总生存期无关。涉及细胞周期蛋白E1基因（CCNE1）的19q12扩增主要发生在部位间纹理更异质的患者中。
非侵入性捕获空间部位间异质性的定量指标可能预测HGSOC患者的结局。
• 计算基于部位间纹理的异质性指标是可行的 • 反映HGSOC部位间纹理相似性的指标与总生存期相关 • 异质性指标也与HGSOC的不完全手术切除相关
