Mayoral Maria, Araujo-Filho Jose Arimateia Batista, Tan Kay See, Ortiz Eduardo, Adusumilli Prasad S, Rusch Valerie, Zauderer Marjorie, Ginsberg Michelle S
Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA.
Medical Imaging Department, Hospital Clinic of Barcelona, 170 Villarroel street, Barcelona, 08036, Spain.
Eur Radiol. 2025 Feb;35(2):806-814. doi: 10.1007/s00330-024-10963-6. Epub 2024 Aug 15.
The current clinical staging of pleural mesothelioma (PM) is often discordant with the pathologic staging. This study aimed to identify clinical and radiological features that could help predict unresectability in PM.
Twenty-two descriptive radiologic features were retrospectively evaluated on preoperative computed tomography (CT) and/or positron emission tomography/CT (PET/CT) performed in patients with presumably resectable PM who underwent surgery. Measurements of maximum and sum pleural thickness at three levels of the thorax (upper, middle, and lower) were taken and stratified based on the cutpoints provided by the International Association for the Study of Lung Cancer (IASLC). Clinical and radiological features, including clinical-stage, were compared between resectable and unresectable tumors by univariate analysis and logistic regression modeling.
Of 133 patients, 69/133 (52%) had resectable and 64/133 (48%) had unresectable PM. Asbestos exposure (p = 0.005), neoadjuvant treatment (p = 0.001), clinical T-stage (p < 0.0001), all pleural thickness measurements (p < 0.05), pleural thickness pattern (p < 0.0001) and degree (p = 0.033), lung invasion (p = 0.004), extrapleural space obliteration (p < 0.0001), extension to subphrenic space (p = 0.0004), and two combination variables representing extensive diaphragmatic contact and/or chest wall involvement (p = 0.002) and mediastinal invasion (p < 0.0001) were significant predictors at univariate analysis. At multivariable analysis, all models achieved a strong diagnostic performance (area under the curve (AUC) > 0.8). The two best-performing models were one that included the upper-level maximum pleural thickness, extrapleural space obliteration, and mediastinal infiltration (AUC = 0.876), and another that integrated clinical variables and radiological assessment through the clinical T-stage (AUC = 0.879).
Selected clinical and radiologic features, including pleural thickness measurements, appear to be strong predictors of unresectability in PM.
A more accurate prediction of unresectability in the preoperative assessment of patients with pleural mesothelioma may avoid unnecessary surgery and prompt initiation of nonsurgical treatments.
About half of pleural mesothelioma patients are reported to receive an incorrect disease stage preoperatively. Eleven features identified as predictors of unresectability were included in strongly performing predictive models. More accurate preoperative staging will help clinicians and patients choose the most appropriate treatments.
目前胸膜间皮瘤（PM）的临床分期常与病理分期不一致。本研究旨在确定有助于预测PM不可切除性的临床和放射学特征。
对拟行手术切除的PM患者术前计算机断层扫描（CT）和/或正电子发射断层扫描/CT（PET/CT）进行回顾性评估，分析22项描述性放射学特征。测量胸部三个水平（上、中、下）的最大胸膜厚度和胸膜厚度总和，并根据国际肺癌研究协会（IASLC）提供的切点进行分层。通过单因素分析和逻辑回归模型比较可切除和不可切除肿瘤的临床和放射学特征，包括临床分期。
133例患者中，69/133（52%）为可切除性PM，64/133（48%）为不可切除性PM。单因素分析显示，石棉暴露（p = 0.005）、新辅助治疗（p = 0.001）、临床T分期（p < 0.0001）、所有胸膜厚度测量值（p < 0.05）、胸膜厚度模式（p < 0.0001）和程度（p = 0.033）、肺侵犯（p = 0.004）、胸膜外间隙闭塞（p < 0.0001）、膈下间隙扩展（p = 0.0004）以及两个代表广泛膈肌接触和/或胸壁受累（p = 0.002）和纵隔侵犯（p < 0.0001）的组合变量是显著的预测因素。多因素分析中，所有模型均具有较强的诊断性能（曲线下面积（AUC）> 0.8）。表现最佳的两个模型，一个包括上层最大胸膜厚度、胸膜外间隙闭塞和纵隔浸润（AUC = 0.876），另一个通过临床T分期整合临床变量和放射学评估（AUC = 0.879）。
选定的临床和放射学特征，包括胸膜厚度测量，似乎是PM不可切除性的有力预测因素。
在胸膜间皮瘤患者的术前评估中更准确地预测不可切除性，可避免不必要的手术，并促使启动非手术治疗。
据报道，约一半的胸膜间皮瘤患者术前疾病分期错误。在表现强大的预测模型中纳入了11个被确定为不可切除性预测因素的特征。更准确的术前分期将有助于临床医生和患者选择最合适的治疗方法。
