Tumor contour irregularity on preoperative CT predicts prognosis in renal cell carcinoma: a multi-institutional studyResearch in context

Pingyi Zhu; Chenchen Dai; Ying Xiong; Jianyi Qu; Ruiting Wang; Linpeng Yao; Feng Zhang; Jun Hou; Mengsu Zeng; Jianming Guo; Shuo Wang; Feng Chen; Jianjun Zhou

EClinicalMedicine (Sep 2024)

Tumor contour irregularity on preoperative CT predicts prognosis in renal cell carcinoma: a multi-institutional studyResearch in context

Pingyi Zhu,
Chenchen Dai,
Ying Xiong,
Jianyi Qu,
Ruiting Wang,
Linpeng Yao,
Feng Zhang,
Jun Hou,
Mengsu Zeng,
Jianming Guo,
Shuo Wang,
Feng Chen,
Jianjun Zhou

Affiliations

Pingyi Zhu: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
Chenchen Dai: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
Ying Xiong: Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China
Jianyi Qu: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
Ruiting Wang: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
Linpeng Yao: Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
Feng Zhang: Department of Gastroenterology and Hepatology, Zhongshan Hospital, Fudan University, Shanghai, China
Jun Hou: Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, China
Mengsu Zeng: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
Jianming Guo: Department of Urology, Zhongshan Hospital, Fudan University, Shanghai, China
Shuo Wang: Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China; Shanghai Key Laboratory of MICCAI, Shanghai, China
Feng Chen: Department of Radiology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Corresponding author.
Jianjun Zhou: Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen 361015, China; Xiamen Municipal Clinical Research Center for Medical Imaging, Xiamen 361015, China; Fujian Province Key Clinical Specialty for Medical Imaging, Xiamen 361015, China; Xiamen Key Laboratory of Clinical Transformation of Imaging Big Data and Artificial Intelligence, Xiamen 361015, China; Corresponding author. Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, 668 Jinhu Road, Huli District, Xiamen 361015, China.

Journal volume & issue: Vol. 75
p. 102775

Abstract

Read online

Summary: Background: Radiology-based prognostic biomarkers play a crucial role in patient counseling, enhancing surveillance, and designing clinical trials effectively. This study aims to assess the predictive significance of preoperative CT-based tumor contour irregularity in determining clinical outcomes among patients with renal cell carcinoma (RCC). Methods: We conducted a retrospective multi-institutional review involving 2218 patients pathologically diagnosed with RCC. The training and internal validation sets included patients at Zhongshan Hospital between January 2009 and August 2019. The external test set comprised patients from the First Affiliated Hospital, Zhejiang University School of Medicine (January 2016 to January 2018), the Xiamen Branch of Zhongshan Hospital (November 2017 to June 2023), and the Cancer Imaging Archive. The contour irregularity degree (CID), quantified as the ratio of irregular cross-sections to the total tumor cross-sections, was analyzed for its prognostic relevance across different subgroups of RCC patients. A novel CID-based scoring system was developed, and its predictive efficacy was evaluated and compared with existing prognostic models. Findings: The CID exhibited significant discriminatory power in predicting overall survival (OS), recurrence-free survival (RFS), and disease-specific survival (DSS) among patients with RCC tumors measuring 3 cm or larger (all p < 0.001). Multivariate analyses confirmed the CID as an independent prognostic indicator. Notably, the CID augmented prognostic stratification among RCC patients within distinct risk subgroups delineated by SSIGN models and ISUP grades. The CID-based nomogram (C-Model) demonstrated robust predictive performance, with C-index values of 0.88 (95%CI: 0.84–0.92) in the training set, 0.92 (95%CI: 0.88–0.98) in the internal validation set, and 0.86 (95%CI: 0.81–0.90) in the external test set, surpassing existing prognostic models. Interpretation: Routine imaging-based assessment of the CID serves as an independent prognostic factor, offering incremental prognostic value to existing models in RCC patients with tumors measuring 3 cm or larger. Funding: This study was funded by grants from National Natural Science Foundation of China; Shanghai Municipal Health Commission; China National Key R&D Program and Science and Technology Commission of Shanghai Municipality.

Published in EClinicalMedicine

ISSN: 2589-5370 (Online)
Publisher: Elsevier
Country of publisher: United Kingdom
LCC subjects: Medicine: Medicine (General)
Website: https://www.thelancet.com/journals/eclinm/home

About the journal

Abstract

Keywords