Artificial intelligence measured 3D body composition to predict pathological response in rectal cancer patients
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence-derived body composition, specifically skeletal muscle volume, can predict pathological complete response (pCR) in locally advanced rectal cancer (LARC) patients undergoing neoadjuvant therapy (NAT). Higher muscle mass and older age are associated with better treatment outcomes.
Area Of Science
- Oncology
- Radiology
- Artificial Intelligence
Background
- Treatment for locally advanced rectal cancer (LARC) is evolving towards neoadjuvant therapy (NAT) and organ preservation.
- Predicting pathological complete response (pCR) is crucial for personalized treatment strategies in LARC.
- Body composition (BC) is an emerging area of interest for predicting treatment response, with no current clinical biomarkers available.
Purpose Of The Study
- To investigate if artificial intelligence (AI)-derived body composition variables can predict pCR in LARC patients.
- To establish novel biomarkers for predicting neoadjuvant therapy response in LARC.
Main Methods
- Retrospective analysis of 214 LARC patients who received NAT and surgery between 2012-2023.
- Utilized a pre-trained 3D AI model to quantify volumetric measurements of visceral fat (VF), subcutaneous fat (SCF), and skeletal muscle (SM) from CT images.
- Performed multivariate analysis to correlate BC variables with histological outcomes, specifically pCR.
Main Results
- 22.4% of LARC patients achieved pCR after NAT.
- Skeletal muscle (SM) volume and patient age were positively associated with pCR in both male and female patients (P=0.015 and P=0.03, respectively).
- Subcutaneous fat (SCF) volume showed an association with a decreased likelihood of pCR (P=0.059).
Conclusions
- This study is the first to use AI-measured 3D body composition to predict pathological response in LARC patients undergoing NAT.
- Skeletal muscle volume and age are significant positive predictors of pCR in LARC patients treated with NAT.
- Further research should explore the impact of body composition on clinical outcomes and patients receiving other neoadjuvant regimens, including total neoadjuvant therapy (TNT).
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