Applicability of the CT Radiomics of Skeletal Muscle and Machine Learning for the Detection of Sarcopenia and Prognostic Assessment of Disease Progression in Patients with Gastric and Esophageal Tumors.
Daniel VogeleTeresa MuellerDaniel WolfStephanie OttoSabitha ManojMichael GötzThomas Jens EttrichMeinrad BeerPublished in: Diagnostics (Basel, Switzerland) (2024)
In the present study, the CT radiomics of skeletal muscle together with machine learning correlated with the presence of sarcopenia, and this can additionally assist in predicting disease progression. These features can be classified as promising alternatives to conventional methods, with great potential for further research and future clinical application. However, when sarcopenia was diagnosed with PMI, no significant correlation between sarcopenia and PD could be observed.
Keyphrases
- skeletal muscle
- machine learning
- contrast enhanced
- insulin resistance
- computed tomography
- image quality
- dual energy
- magnetic resonance imaging
- lymph node metastasis
- artificial intelligence
- positron emission tomography
- big data
- type diabetes
- deep learning
- metabolic syndrome
- current status
- community dwelling
- human health
- sensitive detection