2023 ARRS ANNUAL MEETING - ABSTRACTS

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E1237. Predictive Value of CT Biomarkers in Lung Transplantation Survival: Preliminary Investigation in a Diverse Underserved Urban Population
Authors
  1. Renee Friedman; Albert Einstein College of Medicine
  2. Anna Tarasova; Albert Einstein College of Medicine
  3. Vineet Jain; Montefiore Medical Center
  4. Kenny Ye; Albert Einstein College of Medicine
  5. Ali Mansour; Montefiore Medical Center
  6. Linda Haramati; Albert Einstein College of Medicine; Montefiore Medical Center
Objective:
Survival after lung transplantation is 61.2% after five years, among the lowest of all organ transplants. As the number of donor lungs is limited, it is imperative to employ appropriate metrics to predict post-transplant survival. Frail and sarcopenic patients exhibit decreased survival. Limited literature suggests that quantitative CT metrics of muscle, fat, and bone may enhance prediction of post-transplant survival. The objective of the present study is to investigate the predictive value of CT biomarkers on lung transplant survival in a diverse underserved urban lung transplant population.

Materials and Methods:
We performed a single center retrospective cohort study of all adults who underwent lung transplants from November 2017 to May 2022, mean follow-up 1.78 (SD 1.23) years, at our urban academic medical center in Bronx, NY. CT scans closest to transplant date were analyzed using the Terarecon Intuition 4.4.14.P1 (52.283) software. Right and left erector spinae muscles at the carina and right and left pectoralis minor and major above the aortic arch were manually traced on axial images. Mean cross-sectional area and Hounsfield Units (HU) of all structures were recorded for each patient. HU values were categorized as sarcopenic or nonsarcopenic using cutoffs of 34.3HU in women and 38.5HU in men, as established in Derstine 2018. The Intuition fat analysis, which quantifies cross-sectional area and average HU of visceral and subcutaneous fat, was performed on the axial image at the carina and validated qualitatively. EMRs were reviewed for demographics and pre-transplant 6-minute walk distance (6MWD) and body mass index (BMI) in addition to survival time following transplant. Two patients who underwent multiple lung transplants were excluded. Survival analyses were performed using Kaplan-Meier methods and Cox proportional hazard model stratified by sex.

Results:
The study cohort comprised 131 patients, 50 women and 81 men, mean age of 60.82 (SD 10.15) years. 29.0% identified as White, 22.1% Latino, and 17.6% African American. Mortality was 32.1% (n=42) during the study period. While 88% (n=44) of women were sarcopenic at the erector spinae and 84% (n=42) at the pectoralis, women above the sarcopenic range at erector spinae or pectoralis had a 100% survival, significantly higher than sarcopenic women (p=0.007). Pectoralis and erector spinae muscle HU did not predict survival in men, and pectoralis and erector spinae muscle cross-sectional area did not predict survival in men or women. Cox proportional hazard models showed that men with higher visceral fat cross-sectional area and higher mean visceral fat HU had decreased survival (p = 0.02). 6MWD and BMI did not predict survival.

Conclusion:
Pre-transplantation CT biomarkers may have predictive value in lung transplant survival. Absence of sarcopenia in women and lower visceral fat area and HU in men were associated with improved survival in our diverse urban population. These results, if confirmed in multicenter trials, may aid in selecting patients for transplantation with the aim of improved survival.