Transplantology, Volume 7, Issue 3 (September 2026) – 2 articles

Accurate donor–recipient allograft size matching remains a critical determinant of outcomes in lung transplantation, yet current approaches rely predominantly on predicted total lung capacity (pTLC) and height-based metrics derived from population-based equations. These simplified surrogates fail to capture individual anatomical variability, disease-specific alterations in thoracic geometry, and the spatial relationship between donor lungs and recipient chest cavities. In this review, we examine the limitations of conventional size matching and synthesize emerging evidence supporting imaging-based approaches, including computed tomography (CT) volumetry, radiomics, and machine learning. CT-derived volumetric analysis enables individualized anatomical assessment and has been associated with clinically relevant prediction of primary graft dysfunction and mortality. Advanced computational methods may further support the extraction of imaging-derived features and integration with clinical data, although these approaches remain investigational. Collectively, these developments signal a paradigm shift from crude population-based metrics toward imaging-driven and computational approaches in the modern era. With rigorous validation and careful clinical integration, imaging-based approaches may complement conventional size metrics and support more individualized donor–recipient assessment. Full article

Background: De novo donor-specific antibodies (dnDSA) are associated with impaired allograft outcomes and the development of acute and chronic antibody-mediated rejection. However, their clinical impact during the early post-transplant period remains incompletely characterized. Methods: In this prospective single-center cohort study, we analyzed 218 kidney transplant recipients between 2006 and 2013 All patients underwent serial screening for the development of de novo donor-specific antibodies at different time points (1, 3, 6, 12 months) after kidney transplantation using contemporaneously available ELISA- or Luminex-based solid-phase assays. The data were correlated with clinical parameters and histopathological results from indication biopsies and analyzed in relation to clinical outcomes and histopathological findings. All data were analyzed to assess the impact on 1-year kidney function, patient and graft survival. Results: One year after renal transplantation, 7% of patients (n = 37) developed de novo donor-specific antibodies (dnDSA). Among dnDSA-positive patients, 22% developed class I dnDSA, 67% class II dnDSA, and 11% both. In univariate analysis, markers of increased immunologic risk—such as previous transplantation, greater HLA mismatch, and reductions in immunosuppressive therapy—were associated with an increased risk of de novo donor-specific antibody (dnDSA) development. However, in multivariate analysis, only a panel-reactive antibody (PRA) level greater than 20% emerged as an independent predictor of dnDSA formation. Patients who developed dnDSA experienced a significant decline in graft function, with an approximately fourfold increased risk of overall graft failure within the first year. DnDSA-positive patients showed significantly reduced graft survival and impaired renal function at one year. Rejection rates were significantly higher in this group, with 48.6% experiencing histologically confirmed rejection, compared to 13.3% among dnDSA-negative patients. Conclusions: Monitoring for de novo DSA after kidney transplantation helps to identify patients at high risk for rejection, declining graft function, and poorer long-term outcomes. Routine post-transplant dnDSA monitoring may support early risk stratification and individualized clinical management. Full article