Shahzadi Iram, Zwanenburg Alex, Frohwein Lynn Johann, Schramm Dominik, Meyer Hans Jonas, Hinnerichs Mattes, Moenninghoff Christoph, Niehoff Julius Henning, Kroeger Jan Robert, Borggrefe Jan, Surov Alexey
Department of Radiology, Neuroradiology and Nuclear Medicine, Johannes Wesling University Hospital, Ruhr University Bochum, Bochum, Germany.
Siemens Healthineers GmbH, Erlangen, Germany.
J Cachexia Sarcopenia Muscle. 2024 Aug;15(4):1430-1440. doi: 10.1002/jcsm.13488. Epub 2024 Jun 10.
Acute pulmonary embolism (APE) is a potentially life-threatening disorder, emphasizing the importance of accurate risk stratification and survival prognosis. The exploration of imaging biomarkers that can reflect patient survival holds the potential to further enhance the stratification of APE patients, enabling personalized treatment and early intervention. Therefore, in this study, we develop computed tomography pulmonary angiography (CTPA) radiomic signatures for the prognosis of 7- and 30-day all-cause mortality in patients with APE.
Diagnostic CTPA images from 829 patients with APE were collected. Two hundred thirty-four features from each skeletal muscle (SM), intramuscular adipose tissue (IMAT) and both tissues combined (SM + IMAT) were calculated at the level of thoracic vertebra 12. Radiomic signatures were derived using 10 times repeated three-fold cross-validation on the training data for SM, IMAT and SM + IMAT for predicting 7- and 30-day mortality independently. The performance of the radiomic signatures was then evaluated on held-out test data and compared with the simplified pulmonary embolism severity index (sPESI) score, a well-established biomarker for risk stratification in APE. Predictive accuracy was assessed by the area under the receiver operating characteristic curve (AUC) with a 95% confidence interval (CI), sensitivity and specificity.
The radiomic signatures based on IMAT and a combination of SM and IMAT (SM + IMAT) achieved moderate performance for the prediction of 30-day mortality on test data (IMAT: AUC = 0.68, 95% CI [0.57-0.78], sensitivity = 0.57, specificity = 0.73; SM + IMAT: AUC = 0.70, 95% CI [0.60-0.79], sensitivity = 0.74, specificity = 0.54). Radiomic signatures developed for predicting 7-day all-cause mortality showed overall low performance. The clinical signature, that is, sPESI, achieved slightly better performance in terms of AUC on test data compared with the radiomic signatures for the prediction of both 7- and 30-day mortality on the test data (7 days: AUC = 0.73, 95% CI [0.67-0.79], sensitivity = 0.92, specificity = 0.16; 30 days: AUC = 0.74, 95% CI [0.66-0.82], sensitivity = 0.97, specificity = 0.16).
We developed and tested radiomic signatures for predicting 7- and 30-day all-cause mortality in APE using a multicentric retrospective dataset. The present multicentre work shows that radiomics parameters extracted from SM and IMAT can predict 30-day all-cause mortality in patients with APE.
急性肺栓塞（APE）是一种潜在的危及生命的疾病，凸显了准确风险分层和生存预后的重要性。探索能够反映患者生存情况的影像学生物标志物，有可能进一步优化APE患者的分层，实现个性化治疗和早期干预。因此，在本研究中，我们开发了计算机断层扫描肺动脉造影（CTPA）影像组学特征，用于预测APE患者7天和30天全因死亡率。
收集了829例APE患者的诊断性CTPA图像。在第12胸椎水平计算每个骨骼肌（SM）、肌内脂肪组织（IMAT）以及两者组合（SM + IMAT）的234个特征。使用训练数据对SM、IMAT和SM + IMAT进行10次重复的三倍交叉验证，独立得出用于预测7天和30天死亡率的影像组学特征。然后在留出的测试数据上评估影像组学特征的性能，并与简化肺栓塞严重程度指数（sPESI）评分进行比较，sPESI是一种成熟的APE风险分层生物标志物。通过受试者操作特征曲线下面积（AUC）及95%置信区间（CI）、敏感性和特异性评估预测准确性。
基于IMAT以及SM和IMAT组合（SM + IMAT）的影像组学特征在测试数据上对30天死亡率的预测表现中等（IMAT：AUC = 0.68，95% CI [0.57 - 0.78]，敏感性 = 0.57，特异性 = 0.73；SM + IMAT：AUC = 0.70，95% CI [0.60 - 0.79]，敏感性 = 0.74，特异性 = 0.54）。为预测7天全因死亡率而开发的影像组学特征总体表现较差。临床特征即sPESI在测试数据上的AUC方面，相比影像组学特征对测试数据上7天和30天死亡率的预测表现略好（7天：AUC = 0.73，95% CI [0.67 - 0.79]，敏感性 = 0.92，特异性 = 0.16；30天：AUC = 0.74，95% CI [0.66 - 0.82]，敏感性 = 0.97，特异性 = 0.16）。
我们使用多中心回顾性数据集开发并测试了用于预测APE患者7天和30天全因死亡率的影像组学特征。目前的多中心研究表明，从SM和IMAT中提取的影像组学参数可以预测APE患者30天全因死亡率。
