AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients

• URL: http://arxiv.org/abs/2407.00438v2
• Date: Tue, 2 Jul 2024 12:40:04 GMT
• Title: AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients
• Authors: Rikhil Seshadri, Jayant Siva, Angelica Bartholomew, Clara Goebel, Gabriel Wallerstein-King, Beatriz López Morato, Nicholas Heller, Jason Scovell, Rebecca Campbell, Andrew Wood, Michal Ozery-Flato, Vesna Barros, Maria Gabrani, Michal Rosen-Zvi, Resha Tejpaul, Vidhyalakshmi Ramesh, Nikolaos Papanikolopoulos, Subodh Regmi, Ryan Ward, Robert Abouassaly, Steven C. Campbell, Erick Remer, Christopher Weight,
• Abstract summary: This paper introduces AI Age Discrepancy, a novel metric derived from machine learning analysis of preoperative abdominal CT scans. A higher AI Age Discrepancy is significantly associated with longer hospital stays and lower overall survival rates, independent of established factors.
• Score: 3.2441121935479877
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Kidney cancer is a global health concern, and accurate assessment of patient frailty is crucial for optimizing surgical outcomes. This paper introduces AI Age Discrepancy, a novel metric derived from machine learning analysis of preoperative abdominal CT scans, as a potential indicator of frailty and postoperative risk in kidney cancer patients. This retrospective study of 599 patients from the 2023 Kidney Tumor Segmentation (KiTS) challenge dataset found that a higher AI Age Discrepancy is significantly associated with longer hospital stays and lower overall survival rates, independent of established factors. This suggests that AI Age Discrepancy may provide valuable insights into patient frailty and could thus inform clinical decision-making in kidney cancer treatment.

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