AUTOMATED ASSESSMENT OF MUSCLE AND ADIPOSE TISSUE WITH COMPUTED TOMOGRAPHY DATA FOR NON-INVASIVE DETERMINATION OF INFLAMMATORY BOWEL DISEASES ACTIVITY: PILOT STUDY

This study endeavors to explore how parameters of adipose and muscle tissue, acquired through abdominal computed tomographic imaging and processed by artificial intelligence software, can be utilized to assess the activity of inflammatory bowel diseases without invasive procedures. We conducted a retrospective mono-centric cross-sectional study. Clinical and anamnestic, laboratory, and instrumental data of patients with inflammatory bowel diseases are analyzed. To analyze unenhanced computed tomographic images (middle level of the L3 vertebral body), artificial intelligence software is used to determine the cross-sectional areas and average X-Ray absorption of skeletal muscle tissue, areas of intramuscular, visceral, and subcutaneous adipose tissue. The skeletal muscle index and the percentage of intramuscular adipose tissue are calculated. Disease activity is determined based on endoscopic, histological, and tomographic data. The study included data from
61 patients (25 women (41%); 24 patients with ulcerative colitis (39,3%) and 37 with Crohn’s disease (60,7%); 50 patients with active disease (82%) and 11 in remission (18%)). Comparing the active group to the remission one, we observed a decrease in the area (p=0,038) and content (p=0,017) of the intramuscular fat. According to the results of the ROC analysis, the threshold level for predicting remission for the area of intramuscular fat is 3,53 cm2 (AUROC 0,67), for the intramuscular fat content – 3.72% (AUROC 0,71).

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