Can automated CT body composition analysis predict high-grade Clavien–Dindo complications in patients with RCC undergoing partial and radical nephrectomy?

Author:

Demirel Emin1ORCID,Dilek Okan2

Affiliation:

1. Department of Radiology, Emirdag City of Hospital, Afyonkarahisar, Turkey

2. Department of Radiology, University of Health Sciences, Adana City Training and Research Hospital, Adana, Turkey

Abstract

Introduction This study investigated the relationship between body tissue composition analysis and complications according to the Clavien–Dindo classification in patients with renal cell carcinoma (RCC) who underwent partial (PN) or radical nephrectomies (RN). Methods We obtained all data of 210 patients with RCC from the 2019 Kidney and Kidney Tumor Segmentation Challenge (C4KC-KiTS) dataset and obtained radiological images from the cancer image archive. Body composition was assessed with automated artificial intelligence software using the convolutional network segmentation technique from abdominal computed tomography images. We included 125 PN and 63 RN in the study. The relationship between body fat and muscle tissue distribution and complications according to the Clavien–Dindo classification was evaluated between these two groups. Results Clavien–Dindo 3A and higher (high grade) complications were developed in 9 of 125 patients who underwent PN and 7 of 63 patients who underwent RN. There was no significant difference between all body composition values between patients with and without high-grade complications. Conclusion This study showed that body muscle-fat tissue distribution did not affect patients with 3A and above complications according to the Clavien–Dindo classification in patients who underwent nephrectomy due to RCC.

Publisher

SAGE Publications

Subject

General Medicine

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