Department of Nuclear Medicine, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.
Eur J Nucl Med Mol Imaging. 2022 Jul;49(8):2949-2959. doi: 10.1007/s00259-022-05773-1. Epub 2022 Mar 28.
Tumor heterogeneity, which is associated with poor outcomes, has not been exhibited in the University of California, Los Angeles, Integrated Staging System (UISS), and the Stage, Size, Grade and Necrosis (SSIGN) scores. Radiomics allows an in-depth characterization of heterogeneity across the tumor, but its incremental value to the existing prognostic models for clear cell renal cell carcinoma (ccRCC) outcome is unknown. The purpose of this study was to evaluate the association between the radiomics-based tumor heterogeneity and postoperative risk of recurrence in localized ccRCC, and to assess its incremental value to UISS and SSIGN.
A multicenter 866 ccRCC patients derived from 12 Chinese hospitals were studied. The endpoint was recurrence-free survival (RFS). A CT-based radiomics signature (RS) was developed and assessed in the whole cohort and in the subgroups stratified by UISS and SSIGN. Two combined nomograms, the R-UISS (combining RS and UISS) and R-SSIGN (combining RS and SSIGN), were developed. The incremental value of RS to UISS and SSIGN in RFS prediction was evaluated. R statistical software was used for statistics.
Patients with low radiomics scores were 4.44 times more likely to experience recurrence than those with high radiomics scores (P<0.001). Stratified analysis suggested the association is significant among low- and intermediate-risk patients identified by UISS and SSIGN. The R-UISS and R-SSIGN showed better predictive capability than UISS and SSIGN did with higher C-indices (R-UISS vs. UISS, 0.74 vs. 0.64; R-SSIGN vs. SSIGN, 0.78 vs. 0.76) and higher clinical net benefit.
The radiomics-based tumor heterogeneity can predict outcome and add incremental value to the existing prognostic models in localized ccRCC patients. Incorporating radiomics-based tumor heterogeneity in ccRCC prognostic models may provide the opportunity to better surveillance and adjuvant clinical trial design.
肿瘤异质性与不良预后相关，但尚未在加利福尼亚大学洛杉矶分校综合分期系统（UISS）和分期、大小、分级和坏死（SSIGN）评分中体现。放射组学允许对肿瘤内的异质性进行深入描述，但它对现有透明细胞肾细胞癌（ccRCC）预后的预测模型的增量价值尚不清楚。本研究旨在评估基于放射组学的肿瘤异质性与局限性 ccRCC 术后复发风险之间的关系，并评估其对 UISS 和 SSIGN 的增量价值。
研究纳入了来自 12 家中国医院的 866 例 ccRCC 患者，终点为无复发生存期（RFS）。建立并评估了基于 CT 的放射组学特征（RS）在整个队列以及根据 UISS 和 SSIGN 分层的亚组中的表现。建立了两个联合列线图，即 R-UISS（结合 RS 和 UISS）和 R-SSIGN（结合 RS 和 SSIGN）。评估了 RS 在 RFS 预测中对 UISS 和 SSIGN 的增量价值。使用 R 统计软件进行统计学分析。
低放射组学评分患者发生复发的可能性是高放射组学评分患者的 4.44 倍（P<0.001）。分层分析表明，在 UISS 和 SSIGN 确定的低危和中危患者中，这种关联具有统计学意义。R-UISS 和 R-SSIGN 与 UISS 和 SSIGN 相比，具有更高的 C 指数（R-UISS 与 UISS 相比，0.74 比 0.64；R-SSIGN 与 SSIGN 相比，0.78 比 0.76）和更高的临床净获益，具有更好的预测能力。
基于放射组学的肿瘤异质性可以预测结局，并为局限性 ccRCC 患者的现有预后模型提供增量价值。将基于放射组学的肿瘤异质性纳入 ccRCC 预后模型中，可能为更好的监测和辅助临床试验设计提供机会。
