A simplified strategy for donor-recipient size-matching in lung transplant for interstitial lung disease

Pollution exposure in the first 3 months post transplant is associated with lower baseline FEV1 and higher CLAD risk

BACKGROUND

Exposure to air pollution post-lung transplant has been shown to decrease graft and patient survival. This study examines the impact of air pollution exposure in the first 3 months post-transplant on baseline (i.e., highest) forced expiratory volume in 1 second (FEV1) achieved and development of chronic lung allograft dysfunction (CLAD).

METHODS

Double-lung transplant recipients (n = 82) were prospectively enrolled for comprehensive indoor and personal environmental monitoring at 6- and 12-week post transplant and followed for >4 years. Associations between clinical and exposure variables were investigated using an exposomics approach followed by analysis with a Cox proportional hazards model. Multivariable analyses were used to examine the impact of air pollution on baseline % predicted FEV1 (defined as the average of the 2 highest values post transplant) and risk of CLAD.

RESULTS

Multivariable analysis revealed a significant inverse relationship between personal black carbon (BC) levels and baseline % FEV1. The multivariable model indicated that patients with higher-than-median exposure to BC (>350 ng/m3) attained a baseline % FEV1 that was 8.8% lower than those with lower-than-median BC exposure (p = 0.019). Cox proportional hazards model analysis revealed that patients with high personal BC exposure had a 2.4 times higher hazard risk for CLAD than patients with low BC exposure (p = 0.045).

CONCLUSIONS

Higher personal BC levels during the first 3 months post-transplant decrease baseline FEV1 and double the risk of CLAD. Strategies to reduce BC exposure early following a lung transplant may help improve lung function and long-term outcomes.

Outcomes of lung transplantation for pleuroparenchymal fibroelastosis: A French multicentric retrospective study

BACKGROUND

Pleuroparenchymal fibroelastosis (PPFE) has no currently available specific treatment. Benefits of lung transplantation (LT) for PPFE are poorly documented.

METHODS

We conducted a nation-wide multicentric retrospective study in patients who underwent lung or heart-lung transplantation for chronic end-stage lung disease secondary to PPFE between 2012 and 2022 in France.

RESULTS

Thirty-one patients were included. At transplantation, median age was 48 years [IQR 35-55]. About 64.5% were women. Twenty-one (67.7%) had idiopathic PFFE. Sixteen (52%) had bilateral LT, 10 (32%) had single LT, 4 (13%) had lobar transplantation and one (3%) had heart-lung transplantation. Operative mortality was 3.2%. Early mortality (<90 days or during the first hospitalization) was 32%. Eleven patients (35.5%) underwent reoperation for hemostasis. Eight (30.8%) experienced bronchial complications. Mechanical ventilation time was 10 days [IQR 2-55]. Length of stay in intensive care unit and hospital were 34 [IQR 18-73] and 64 [IQR 36-103] days, respectively. Median survival was 21 months. Post-transplant survival rates after 1, 2, and 5 years were 57.9%, 42.6% and 38.3% respectively. Low albuminemia (p = 0.046), FVC (p = 0.021), FEV1 (p = 0.009) and high emergency lung transplantation (p = 0.04) were associated with increased early mortality. Oversized graft tended to be correlated to a higher mortality (p = 0.07).

CONCLUSION

LT for PPFE is associated with high post-operative morbi-mortality rates. Patients requiring high emergency lung transplantation with advanced disease, malnutrition, or critical clinical status experienced worse outcomes.

CLINICALTRIALS

GOV IDENTIFIER

NCT05044390.

Artificial intelligence-driven automated lung sizing from chest radiographs

Lung size measurements play an important role in transplantation, as optimal donor-recipient size matching is necessary to ensure the best possible outcome. Although several strategies for size matching are currently used, all have limitations, and none has proven superior. In this pilot study, we leveraged deep learning and computer vision to develop an automated system for generating standardized lung size measurements using portable chest radiographs to improve accuracy, reduce variability, and streamline donor/recipient matching. We developed a 2-step framework involving lung mask extraction from chest radiographs followed by feature point detection to generate 6 distinct lung height and width measurements, which we validated against measurements reported by 2 radiologists (M.K.I. and R.R.) for 50 lung transplant recipients. Our system demonstrated <2.5% error (<7.0 mm) with robust interrater and intrarater agreement compared with an expert radiologist review. This is especially promising given that the radiographs used in this study were purposely chosen to include images with technical challenges such as consolidations, effusions, and patient rotation. Although validation in a larger cohort is necessary, this study highlights artificial intelligence's potential to both provide reproducible lung size assessment in real patients and enable studies on the effect of lung size matching on transplant outcomes in large data sets.

Thoracic and vertebral deformities in lung transplantation: perioperative complications and long-term prognoses

BACKGROUND

Lung transplantation (LTx) is a crucial therapeutic strategy for patients suffering from end-stage respiratory diseases, necessitating precise donor-recipient size matching to ensure optimal graft function. While standard allocation protocols rely on predicted lung capacity based on factors such as sex, age, and height, a subset of patients with respiratory diseases presents an additional challenge - thoracic or vertebral deformities. These deformities can complicate accurate volume predictions and may impact the success of lung transplantation.

METHODS

In this retrospective cohort study of patients who underwent LTx at Tohoku University Hospital between January 2007 and April 2022, with follow-up until October 2022, the primary objective was to assess the influence of thoracic and vertebral deformities on perioperative complications, emphasizing interventions, such as volume reduction surgery. The secondary objective aimed to identify any noticeable impact on long-term prognoses in recipients with these deformities.

RESULTS

Of 129 LTx recipients analyzed, 17.8% exhibited thoracic deformities, characterized by pectus excavatum, while 16.3% had vertebral deformities. Perioperative complications, requiring delayed chest closure, tracheostomy, and volume reduction surgery, were more prevalent in the deformity group. Thoracic deformities were notably associated with the need for volume reduction surgery. However, long-term prognoses did not differ significantly between patients with deformities and those without. Vertebral deformities did not appear to significantly impact perioperative or long-term outcomes.

CONCLUSIONS

This study highlights the prevalence of thoracic deformities in LTx recipients, correlating with increased perioperative complications, particularly the potential need for volume reduction surgery. Importantly, these deformities do not exert a significant impact on long-term prognoses. Additionally, patients with vertebral deformities, such as scoliosis and kyphosis, appear to be manageable in the context of LTx.

Oversizing lung allografts deteriorates outcomes in patients with pulmonary fibrosis

BACKGROUND

Lung transplantation is the only curative treatment for patients with end-stage pulmonary fibrosis. It is still under debate whether over- or undersizing of lung allografts is preferably performed regarding the postoperative outcome. We therefore analyzed our data using predicted total lung capacity to compare size mismatches.

METHODS

Patient records were retrospectively reviewed. Three groups were formed, 1 including patients with a donor-recipients pTLC ratio (DRPR) of <1.0 (undersized group), the second with a DRPR of ≥1.0 and <1.1 (size-matched group), and the third group with a DRPR of ≥1.1 (oversized group). Outcomes were evaluated using chi-square test and Kruskall-Wallis test as well as Kaplan-Meier analysis, competing risk analysis, and multivariable analysis, respectively.

RESULTS

Between January 2010 and May 2023, among the 1501 patients transplanted at our institution, 422 (28%) patients were included, 26 (2%) patients forming the oversized group (median DRPR: 1.14), 101 (7%) patients forming the size-matched group (median DRPR: 1.03), and 296 (20%) patients forming the undersized group (median DRPR: 0.92). Patients from the oversized group had a higher PGD grade 3 rate at 24 (p < 0.001), 48 (p < 0.001), and 72 (p = 0.039) hours after transplantation as well as a higher in-hospital mortality compared to the undersized group (p = 0.033). The long-term survival was also better in the undersized group compared to the oversized group (p = 0.011) and to the size-matched group (p = 0.01).

CONCLUSIONS

Oversizing lung allografts more than 10% deteriorated early postoperative outcomes and long-term survival in patients with pulmonary fibrosis.

"Horses for courses" computed tomography or predicted total lung capacity for size matching in lung transplantation

Size-matching donors to recipients in lung transplantation continues to be a clinical challenge. Predicted total lung capacity equations, or more simply, donor and recipient heights, while widely used, are imprecise and may not be representative of the pool of donors and recipients. These inherent limitations may result in size discrepancies. The advent of easily accessible software and the widespread availability of computed tomography (CT) imaging in donor assessments have made it possible to directly measure lung volumes in donors and recipients. As a result, there is a growing interest in adopting personalized CT volumetry as an alternative. This article explores both methods and underscores the potential benefits and precision offered by CT.

Donor and recipient risk factors for the development of primary graft dysfunction following lung transplantation

Primary Graft Dysfunction (PGD) is a major cause of both short-term and long-term morbidity and mortality following lung transplantation. Various donor, recipient, and technical risk factors have been previously identified as being associated with the development of PGD. Here, we present a comprehensive review of the current literature as it pertains to PGD following lung transplantation, as well as discussing current strategies to mitigate PGD and future directions. We will pay special attention to recent advances in lung transplantation such as ex-vivo lung perfusion, thoracoabdominal normothermic regional perfusion, and up-to-date literature published in the interim since the 2016 ISHLT consensus statement on PGD and the COVID-19 pandemic.

Computed Tomography Volumetrics for Size Matching in Lung Transplantation for Restrictive Disease

BACKGROUND

There is no consensus on the optimal allograft sizing strategy for lung transplantation in restrictive lung disease. Current methods that are based on predicted total lung capacity (pTLC) ratios do not account for the diminutive recipient chest size. The study investigators hypothesized that a new sizing ratio incorporating preoperative recipient computed tomographic lung volumes (CTVol) would be associated with postoperative outcomes.

METHODS

A retrospective single-institution study was conducted of adults undergoing primary bilateral lung transplantation between January 2016 and July 2020 for restrictive lung disease. CTVol was computed for recipients by using advanced segmentation software. Two sizing ratios were calculated: pTLC ratio (pTLCdonor/pTLCrecipient) and a new volumetric ratio (pTLCdonor/CTVolrecipient). Patients were divided into reference, oversized, and undersized groups on the basis of ratio quintiles, and multivariable models were used to assess the effect of the ratios on primary graft dysfunction and survival.

RESULTS

CTVol was successfully acquired in 218 of 220 (99.1%) patients. In adjusted analysis, undersizing on the basis of the volumetric ratio was independently associated with decreased primary graft dysfunction grade 2 or 3 within 72 hours (odds ratio, 0.42; 95% CI, 0.20-0.87; P =.02). The pTLC ratio was not significantly associated with primary graft dysfunction. Oversizing on the basis of the volumetric ratio was independently associated with an increased risk of death (hazard ratio, 2.27; 95% CI, 1.04-4.99; P =.04], whereas the pTLC ratio did not have a significant survival association.

CONCLUSIONS

Using computed tomography-acquired lung volumes for donor-recipient size matching in lung transplantation is feasible with advanced segmentation software. This method may be more predictive of outcome compared with current sizing methods, which use gender and height only.

Predicted versus CT-derived total lung volume in a general population: The ImaLife study

Predicted lung volumes based on the Global Lung Function Initiative (GLI) model are used in pulmonary disease detection and monitoring. It is unknown how well the predicted lung volume corresponds with computed tomography (CT) derived total lung volume (TLV). The aim of this study was to compare the GLI-2021 model predictions of total lung capacity (TLC) with CT-derived TLV. 151 female and 139 male healthy participants (age 45-65 years) were consecutively selected from a Dutch general population cohort, the Imaging in Lifelines (ImaLife) cohort. In ImaLife, all participants underwent low-dose, inspiratory chest CT. TLV was measured by an automated analysis, and compared to predicted TLC based on the GLI-2021 model. Bland-Altman analysis was performed for analysis of systematic bias and range between limits of agreement. To further mimic the GLI-cohort all analyses were repeated in a subset of never-smokers (51% of the cohort). Mean±SD of TLV was 4.7±0.9 L in women and 6.2±1.2 L in men. TLC overestimated TLV, with systematic bias of 1.0 L in women and 1.6 L in men. Range between limits of agreement was 3.2 L for women and 4.2 L for men, indicating high variability. Performing the analysis with never-smokers yielded similar results. In conclusion, in a healthy cohort, predicted TLC substantially overestimates CT-derived TLV, with low precision and accuracy. In a clinical context where an accurate or precise lung volume is required, measurement of lung volume should be considered.

Primary graft dysfunction following lung transplantation: From pathogenesis to future frontiers

Lung transplantation is the treatment of choice for patients with end-stage lung disease. Currently, just under 5000 lung transplants are performed worldwide annually. However, a major scourge leading to 90-d and 1-year mortality remains primary graft dysfunction. It is a spectrum of lung injury ranging from mild to severe depending on the level of hypoxaemia and lung injury post-transplant. This review aims to provide an in-depth analysis of the epidemiology, pathophysiology, risk factors, outcomes, and future frontiers involved in mitigating primary graft dysfunction. The current diagnostic criteria are examined alongside changes from the previous definition. We also highlight the issues surrounding chronic lung allograft dysfunction and identify the novel therapies available for ex-vivo lung perfusion. Although primary graft dysfunction remains a significant contributor to 90-d and 1-year mortality, ongoing research and development abreast with current technological advancements have shed some light on the issue in pursuit of future diagnostic and therapeutic tools.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSION

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.