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OBJECTIVES Lung volume reduction surgery (LVRS) is an established therapeutic option for advanced emphysema. To improve patients' safety and reduce complications, an enhanced recovery protocol (ERP) was implemented. This study aims to describe and evaluate the short-term outcome of this ERP. METHODS This retrospective single-centre study included all consecutive LVRS patients (1 January 2017 until 15 September 2020). An ERP for LVRS was implemented and stepwise optimised from 1 August 2019, it consisted of changes in pre-, peri- and postoperative care pathways. Patients were compared before and after implementation of ERP. Primary outcome was incidence of postoperative complications (Clavien-Dindo), and secondary outcomes included chest tube duration, incidence of prolonged air leak (PAL), length of stay (LOS) and 90-day mortality. Lung function and exercise capacity were evaluated at 3 and 6 months post-LVRS. RESULTS Seventy-six LVRS patients were included (pre-ERP: n =41, ERP: n =35). The ERP cohort presented with lower incidence of postoperative complications (42% vs 83%, P =0.0002), shorter chest tube duration (4 vs 12 days, P <0.0001) with a lower incidence of PAL (21% vs 61%, P =0.0005) and shorter LOS (6 vs 14 days, P <0.0001). No in-hospital mortality occurred in the ERP cohort versus 4 pre-ERP. Postoperative forced expiratory volume in 1 s was higher in the ERP cohort compared to pre-ERP at 3 months (1.35 vs 1.02 l) and at 6 months (1.31 vs 1.01 l). CONCLUSIONS Implementation of ERP as part of a comprehensive reconceptualisation towards LVRS, demonstrated fewer postoperative complications, including PAL, resulting in reduced LOS. Improved short-term functional outcomes were observed at 3 and 6 months. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide OBJECTIVES Primary graft dysfunction resulting from ischaemia-reperfusion injury remains a major obstacle after lung transplantation (LTx) and is associated with morbidity and mortality. Continuous release of inflammatory cytokines, due to the process of ischaemia and reperfusion, triggers a complex cascade of apoptosis and necrosis resulting in graft dysfunction. Previous studies demonstrated successful graft improvement by cytokine filtration during ex vivo lung perfusion. We hypothesize that plasma cytokine filtration with CytoSorb® during in vivo graft perfusion immediately after implantation may attenuate ischaemia-reperfusion injury after left LTx in a porcine model. METHODS Left porcine LTx was performed with allografts preserved for 24 h at 4°C. In the treatment group [T] (n  = 7), a veno-venous shunt was created to insert the cytokine filter (CytoSorbents, Berlin, Germany). In the sham group [S] (n  = 4), the shunt was created without the filter. Haemodynamic parameters, lung mechanics, blood gases and plasma cytokines were assessed during 6 h in vivo reperfusion. RESULTS During 6 h of reperfusion, significant differences in plasma pro-inflammatory cytokine [interferon (IFN)-α, IFN-γ and interleukin (IL)-6] concentrations were observed between [T] and [S], but surprisingly with higher plasma levels in the [T] group. Plasma concentrations of other pro-inflammatory cytokines (IL-1β, IL-12p40, IL-4, IL-6, IL-8, IFN-α, IFN-γ and tumour necrosis factor-α) and anti-inflammatory cytokines (IL-10) did not find any evidence for a difference. Furthermore, our study failed to show meaningful difference in haemodynamics and blood gases. Also, no statistically significant differences were found between [T] and [S] in biopsies and wet-to-dry ratio at the end of the experiment. CONCLUSIONS In our porcine left LTx model cytokine filtration did not achieve the intended effect. This is in contrast to previous studies with CytoSorb use during ex vivo lung perfusion as a surrogate LTx model. Our findings might highlight the fact that the theoretical benefit of inserting an additional cytokine adsorber to improve graft function in clinical practice should be critically evaluated with further studies. [ABSTRACT FROM AUTHOR]

Diagnosing lung injury is a challenge in lung transplantation. It has been unclear if a single biopsy specimen is truly representative of the entire organ. Our objective was to investigate lung inflammatory biomarkers using human lung tissue biopsies and ex vivo lung perfusion perfusate. Eight human donor lungs declined for transplantation were air inflated, flash frozen, and partitioned from apex to base. Biopsies were then sampled throughout the lung. Perfusate was sampled from 4 lung lobes in 8 additional donor lungs subjected to ex vivo lung perfusion. The levels of interleukin-6, interleukin-8, interleukin-10, and interleukin-1β were measured using quantitative reverse transcription polymerase chain reaction from lung biopsies and enzyme-linked immunosorbent assay from ex vivo lung perfusion perfusate. The median intra-biopsy equal-variance P value was.50 for messenger RNA biomarkers in tissue biopsies. The median intra-biopsy coefficient of variance was 18%. In donors with no apparent focal injuries, the biopsies in each donor showed no difference in various lung slices, with a coefficient of variance of 20%. The exception was biopsies from the lingula and injured focal areas that demonstrated larger differences. Cytokines in ex vivo lung perfusion perfusate showed minimal variation among different lobes (coefficient of variance = 4.9%). Cytokine gene expression in lung biopsies was consistent, and the biopsy analysis reflects the whole lung, except when specimens were collected from the lingula or an area of focal injury. Ex vivo lung perfusion perfusate also provides a representative measurement of lung inflammation from the draining lobe. These results will reassure clinicians that a lung biopsy or an ex vivo lung perfusion perfusate sample can be used to inform donor lung selection. [Display omitted] [ABSTRACT FROM AUTHOR]

To clarify the relationship between the use of extracorporeal life support during lung transplantation and severe primary graft dysfunction (PGD), we developed and analyzed a novel multicenter international registry. The Extracorporeal Life Support in Lung Transplantation Registry includes double-lung transplants performed at 8 high-volume centers (>40/year). Multiorgan transplants were excluded. We defined severe PGD as grade 3 PGD (PGD3) observed 48 or 72 hours after reperfusion. Modes of support were no extracorporeal life support (off-pump), extracorporeal membrane oxygenation (ECMO), and cardiopulmonary bypass (CPB). To assess the association between mode of support and PGD3, we adjusted for demographic and intraoperative factors with a stepwise, mixed selection, multivariable regression model, ending with 10 covariates in the final model. We analyzed 852 transplants performed between January 2016 and March 2020: 422 (50%) off-pump, 273 (32%) ECMO, and 157 (18%) CPB cases. PGD3 rates at time point 48-72 were 12.1% (51 out of 422) for off-pump, 28.9% for ECMO (79 out of 273), and 42.7% (67 out of 157) for CPB. The adjusted model resulted in the following risk profile for PGD3: CPB versus ECMO odds ratio, 1.89 (95% CI, 1.05-3.41; P =.033), CPB versus off-pump odds ratio, 4.24 (95% CI, 2.24-8.04; P <.001), and ECMO versus off-pump odds ratio, 2.24 (95% CI, 1.38-3.65; P =.001). Venoarterial ECMO is increasingly used at high-volume centers to support complex transplant recipients during double-lung transplantation. This practice is associated with more risk of PGD3 than off-pump transplantation but less risk than CPB. When extracorporeal life support is required during lung transplantation, ECMO may be the preferable approach when feasible. [Display omitted] [ABSTRACT FROM AUTHOR]

Background Interstitial lung abnormalities (ILAs) reflect imaging features on lung CT scans that are compatible with (early) interstitial lung disease. Despite accumulating evidence regarding the incidence, risk factors, and prognosis of ILAs, the histopathologic correlates of ILAs remain elusive. Purpose To determine the correlation between radiologic and histopathologic findings in CT-defined ILAs in human lung explants. Materials and Methods Explanted lungs or lobes from participants with radiologically documented ILAs were prospectively collected from 2010 to 2021. These specimens were air-inflated, frozen, and scanned with CT and micro-CT (spatial resolution of 0.7 mm and 90 μm, respectively). Subsequently, the lungs were cut and sampled with core biopsies. At least five samples per lung underwent micro-CT and subsequent histopathologic assessment with semiquantitative remodeling scorings. Based on area-specific radiologic scoring, the association between radiologic and histopathologic findings was assessed. Results Eight lung explants from six donors (median age at explantation, 71 years [range, 60-83 years]; four men) were included (unused donor lungs, n = 4; pre-emptive lobectomy for oncologic indications, n = 2). Ex vivo CT demonstrated ground-glass opacification, reticulation, and bronchiectasis. Micro-CT and histopathologic examination demonstrated that lung abnormalities were frequently paraseptal and associated with fibrosis and lymphocytic inflammation. The histopathologic results showed varying degrees of fibrosis in areas that appeared normal on CT scans. Regions of reticulation on CT scans generally had greater fibrosis at histopathologic analysis. Vasculopathy and bronchiectasis were also often present at histopathologic examination of lungs with ILAs. Fully developed fibroblastic foci were rarely observed. Conclusion This study demonstrated direct histologic correlates of CT-defined interstitial lung abnormalities. © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Jeudy in this issue.

Background: Assessment and selection of donor lungs remains largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo CT images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs prior to transplantation., Methods: Clinical measures and ex-situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner prior to transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning , which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures., Results: Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) prior to CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the ICU and were at 19 times higher risk of developing CLAD within 2 years post-transplant., Conclusions: We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of post-transplant complications.