In this study, the authors developed a fully automated artificial intelligence (AI)-based image analysis tool for segmenting skeletal muscle of the torso and calculating the muscle volume. The authors were able to determine that the fully automated AI-based image analysis software was able to segment the skeletal muscle volume in over 97% of patients who were planning to undergo radical cystectomy for urinary bladder cancer, thus providing a low-cost and meaningful clinical measure that is an independent biomarker for overall survival following said radical cystectomy.
- This fully automated artificial intelligence-based image analysis could segment skeletal muscle volume in almost all the abdominal CT studies.
- The automatically calculated skeletal muscle volume predicted overall survival after radical cystectomy for bladder cancer.
- Further studies are needed to determine optimal volume limits and thresholds for determining sarcopenia.
Authors: Thomas Ying, Pablo Borrelli, Lars Edenbrandt, Olof Enqvist, Reza Kaboteh, Elin Trägårdh, Johannes Ulén & Henrik Kjölhede