Potential Role of Computed Tomography Volumetry in Size Matching in Lung Transplantation

Abstract

Accumulated knowledge on the outcomes related to size mismatch in lung transplantation derives from predicted total lung capacity equations rather than individualized measurements of donors and recipients. The increasing availability of computed tomography (CT) makes it possible to measure the lung volumes of donors and recipients before transplantation. We hypothesize that CT-derived lung volumes predict a need for surgical graft reduction and primary graft dysfunction. Donors from the local organ procurement organization and recipients from our hospital from 2012 to 2018 were included if their CT exams were available. The CT lung volumes and plethysmography total lung capacity were measured and compared with predicted total lung capacity using Bland Altman methods. We used logistic regression to predict the need for surgical graft reduction and ordinal logistic regression to stratify the risk for primary graft dysfunction. A total of 315 transplant candidates with 575 CT scans and 379 donors with 379 CT scans were included. The CT lung volumes closely approximated plethysmography lung volumes and differed from the predicted total lung capacity in transplant candidates. In donors, CT lung volumes systematically underestimated predicted total lung capacity. Ninety-four donors and recipients were matched and transplanted locally. Larger donor and smaller recipient lung volumes estimated by CT predicted a need for surgical graft reduction and were associated with higher primary graft dysfunction grade. The CT lung volumes predicted the need for surgical graft reduction and primary graft dysfunction grade. Adding CT-derived lung volumes to the donor-recipient matching process may improve recipients' outcomes.