Monday, December 1 | 8:30 a.m.-8:40 a.m. | M1-SSGU03-4 | Room E353B
In this talk, researchers will share how AI analysis of sarcopenia and myosteatosis parameters from routine CT exams can stratify risk in patients with metastatic renal cell carcinoma (mRCC).
In a retrospective study, presenter Johannes Christian Harmes, MD, of the University Hospital Essen in Germany and colleagues used an AI algorithm to automatically extract two body composition markers -- sarcopenia index (muscle-to-bone volume ratio) and the myosteatotic fat index (intra-/intermuscular fat relative to total fat) -- from 77 patients with mRCC.
Of these patients, 40 died during follow-up. Using multivariable Cox regression analysis, the researchers found that both the sarcopenia index and the myosteatotic fat index were independently associated with overall survival.
“The automated extraction of sarcopenia and myosteatosis parameters from routine CT scans enables individualized risk stratification in metastatic RCC without added workload or radiation exposure, supporting personalized therapeutic decision-making,” the authors wrote.
What else was associated with patient survival? Take in this Monday morning session to learn more.
