Sex-based differences in imaging-derived body composition and their association with clinical malnutrition in abdominal surgery patients

Background Malnutrition significantly impacts surgical outcomes yet is difficult to identify preoperatively. Few studies have investigated the association between comprehensive body composition assessment and malnutrition in males and females separately. This study evaluates sex-specific associations between preoperative imaging-derived body composition features and malnutrition in abdominal surgery patients.

We retrospectively analyzed patients who underwent computed tomography (CT) scans and elective abdominal surgery at a single institution (2018-2021). Preoperative CT scans were assessed using deep learning to quantify five muscle groups and two fat depots. Malnutrition was diagnosed by registered dietitians using standardized criteria. Sex-specific associations with malnutrition were evaluated using logistic regression.

Among 1,143 patients (52% female), clinical malnutrition was diagnosed in 20.2% of patients, with prevalence varying by procedure type (3.5-38.2%). Malnutrition was associated with reduced muscle volume for both sexes; in contrast, malnutrition was associated with myosteatosis in 3 of 5 muscle groups for females only. In males, malnutrition was associated with decreased psoas volume (OR 0.59 SD, p<0.01), decreased quadratus lumborum volume (OR 0.59 SD, p<0.01), and reduced erector spinae attenuation (OR 0.66 SD, p=0.048). In females, decreased psoas volume (OR 0.55 SD, p<0.001) and attenuation (OR 0.64 SD, p<0.01) were associated with malnutrition. Both sexes demonstrated increased subcutaneous fat attenuation associated with malnutrition (males: OR 1.51 SD, p<0.01; females: OR 1.73 SD, p<0.001), while increased visceral fat attenuation (OR 1.4 SD, p=0.027) was associated with malnutrition only in females.

Males and females differ in baseline body composition and features associated with clinical malnutrition. Comprehensive deep learning analysis of muscle and fat characteristics from cross-sectional imaging provides insight into the sex-specific relationships between body composition and malnutrition in the preoperative setting and provides an opportunity for early identification of patients with greater nutrition-related surgical risk. Competing Interest Statement The authors have declared no competing interest. Funding Statement Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award numbers KL2TR001879 and UL1TR001878. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was also supported in part by the Institute for Translational Medicine and Therapeutics' (ITMAT) Transdisciplinary Program in Translational Medicine and Therapeutics, the McCabe Fund Award, and the Biomedical Data Sciences Core of the Center for Molecular Studies in Digestive and Liver Diseases (P30 DK050306), and the Penn Center for Nutritional Science and Medicine. Additional support was provided by NIH grants R01 DK139663, R01 HL171709, P41 EB029460, and R01 HL169378. The funding sources had no role in the design, execution, interpretation, or writing of the study. Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee/IRB of Perelman School of Medicine at University of Pennsylvania waived ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Funding: Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award numbers KL2TR001879 and UL1TR001878. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. This work was also supported in part by the Institute for Translational Medicine and Therapeutics’ (ITMAT) Transdisciplinary Program in Translational Medicine and Therapeutics, the McCabe Fund Award, and the Biomedical Data Sciences Core of the Center for Molecular Studies in Digestive and Liver Diseases (P30 DK050306), and the Penn Center for Nutritional Science and Medicine. Additional support was provided by NIH grants R01 DK139663, R01 HL171709, P41 EB029460, and R01 HL169378. The funding sources had no role in the design, execution, interpretation, or writing of the study. Data Availability All data produced in the present study are available upon reasonable request to the authors Abbreviations - BMI - Body Mass Index - CT - Computed Tomography - HU - Hounsfield Units - SMI - Skeletal Muscle Index - SMRA - Skeletal Muscle Radiation Attenuation - L3 - 3rd Lumbar Vertebrae - AAIM - Academy ASPEN Indicators of Malnutrition - NSQIP - National Surgery Quality Improvement Program - OR - Odds Ratio