Background

Ex vivo lung perfusion (EVLP) is an advanced platform for isolated lung assessment and treatment. Radiographs acquired during EVLP provide a unique opportunity to assess lung injury. The purpose of our study was to define and evaluate EVLP radiographic findings and their association with lung transplant outcomes.

Methods

We retrospectively evaluated 113 EVLP cases from 2020-21. Radiographs were scored by a thoracic radiologist blinded to outcome. Six lung regions were scored for five radiographic features (consolidation, infiltrates, atelectasis, nodules, and interstitial lines) on a scale of 0 to 3 to derive a score. Spearman’s correlation was used to correlate radiographic scores to biomarkers of lung injury. Machine learning models were developed using radiographic features and EVLP functional data. Predictive performance was assessed using the area under the curve.

Results

Consolidation and infiltrates were the most frequent findings at 1h EVLP (radiographic lung score 2.6 (3.3) and 4.6 (4.3)). Consolidation (r=-0.536 and -0.608, p<0.0001) and infiltrates (r=-0.492 and -0.616, p<0.0001) were inversely correlated with oxygenation (∆pO₂) at 1h and 3h of EVLP. First-hour consolidation and infiltrate lung scores predicted transplant suitability with an area under the curve of 87% and 88%, respectively. Prediction of transplant outcomes using a machine learning model yielded an area under the curve of 80% in the validation set.

Conclusions

EVLP radiographs provide valuable insight into donor lungs being assessed for transplantation. Consolidation and infiltrates were the most common abnormalities observed in EVLP lungs, and radiographic lung scores predicted the suitability of donor lungs for transplant.

中文翻译：

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人类供体肺离体肺灌注的放射学评分可预测移植结果

背景

离体肺灌注 (EVLP) 是用于离体肺评估和治疗的先进平台。EVLP 期间获得的射线照片提供了评估肺损伤的独特机会。我们研究的目的是定义和评估 EVLP 影像学结果及其与肺移植结果的关联。

方法

我们回顾性评估了 2020-21 年间的 113 例 EVLP 病例。X光片由对结果不知情的胸部放射科医生进行评分。对六个肺部区域的五种放射学特征（实变、浸润、肺不张、结节和间质线）进行评分，评分范围为 0 到 3。斯皮尔曼相关性用于将放射学评分与肺损伤的生物标志物相关联。机器学习模型是使用射线照相特征和 EVLP 功能数据开发的。使用曲线下面积评估预测性能。

结果

实变和浸润是 1 小时 EVLP 时最常见的发现（放射学肺部评分 2.6 (3.3) 和 4.6 (4.3)）。EVLP 1 小时和 3 小时时，实变（r=-0.536 和 -0.608，p<0.0001）和浸润（r=-0.492 和 -0.616，p<0.0001）与氧合（ΔpO ₂ ）呈负相关。第一小时巩固和浸润肺评分预测移植适宜性，曲线下面积分别为 87% 和 88%。使用机器学习模型预测移植结果在验证集中产生了 80% 的曲线下面积。

结论

EVLP X 线照片为评估移植供体肺提供了宝贵的见解。实变和浸润是 EVLP 肺中最常见的异常，放射学肺评分可以预测供体肺是否适合移植。