Nan Bin, Pan Yukun, Ge Yinghui, Sun Minghua, Cai Jin, Kan Xiaojing
Department of Radiology, Fuwai Central China Cardiovascular Hospital, Henan Provincial Key Laboratory of Cardiology Medical Imaging, Zhengzhou, Henan 450003, China.
Curr Med Imaging. 2025 Aug 26. doi: 10.2174/0115734056392707250818063540.
This study aims to evaluate the diagnostic value of extracellular volume fraction (ECV) and spectral CT parameters in assessing the pathological grading of lung invasive adenocarcinoma (IAC) presenting as solid or subsolid nodules.
A retrospective collection of patients who were pathologically confirmed as IAC with solid or subsolid pulmonary nodules at our hospital from March 2023 to November 2024 was conducted. Relevant data were recorded, and the patients were divided into two groups: intermediate/high differentiation and low differentiation. The parameters including arterial phase iodine concentration (IC), arterial phase normalized iodine concentration (NIC), arterial phase normalized effective atomic number (nZef), arterial phase extracellular volume fraction (ECV), venous phase iodine concentration (IC), venous phase Normalized Iodine Concentration (NIC), venous phase normalized effective atomic number (nZeff), and venous phase extracellular volume fraction (ECV) were compared between the two groups. Parameters with statistical significance were evaluated for their diagnostic performance using Receiver Operating Characteristic (ROC) curves.
A total of 61 patients were included, comprising 40 in the intermediate to high differentiation group and 21 in the low differentiation group. The intermediate/high differentiation group had higher values of ECV, NIC, ECV, IC, NIC, and nZeff than the low differentiation group (P < 0.05). The AUC values for these parameters were 0.679, 0.620, 0.757, 0.688, 0.724, and 0.693, respectively. Among these, ECV had the largest AUC, with a sensitivity and specificity of 72.5% and 71.4%, respectively. Through binary logistic regression analysis, five features were identified: the maximum diameter of the lesion, bronchus encapsulated air sign, lobulation sign, spiculation sign, and pleural traction sign. The integration of these imaging features with ECV resulted in a model with enhanced diagnostic performance, characterized by an AUC of 0.886, a sensitivity of 85.7%, and a specificity of 80.0%.
ECVV outperforms other spectral parameters in differentiating IAC grades, reflecting changes in the tumor microenvironment. Combining ECV with imaging features enhances diagnostic accuracy, though the study's single-center design and small sample size limit generalizability.
Extracellular volume fraction can provide more information for the pathological grading assessment of invasive adenocarcinoma of the lung. Compared to other spectral parameters, ECV exhibits the highest diagnostic performance, and its combination with conventional imaging features can further enhance diagnostic accuracy.
本研究旨在评估细胞外容积分数（ECV）和光谱CT参数在评估表现为实性或亚实性结节的肺浸润性腺癌（IAC）病理分级中的诊断价值。
回顾性收集2023年3月至2024年11月在我院经病理证实为IAC且有实性或亚实性肺结节的患者。记录相关数据，并将患者分为两组：中/高分化组和低分化组。比较两组之间的参数，包括动脉期碘浓度（IC）、动脉期标准化碘浓度（NIC）、动脉期标准化有效原子序数（nZef）、动脉期细胞外容积分数（ECV）、静脉期碘浓度（IC）、静脉期标准化碘浓度（NIC）、静脉期标准化有效原子序数（nZeff）和静脉期细胞外容积分数（ECV）。使用受试者操作特征（ROC）曲线评估具有统计学意义的参数的诊断性能。
共纳入61例患者，其中中高分化组40例，低分化组21例。中/高分化组的ECV、NIC、ECV、IC、NIC和nZeff值高于低分化组（P<0.05）。这些参数的AUC值分别为0.679、0.620、0.757、0.688、0.724和0.693。其中，ECV的AUC最大，敏感性和特异性分别为72.5%和71.4%。通过二元逻辑回归分析，确定了五个特征：病变最大直径、支气管包绕空气征、分叶征、毛刺征和胸膜牵拉征。将这些影像特征与ECV相结合，得到了一个诊断性能增强的模型，其AUC为0.886，敏感性为85.7%，特异性为80.0%。
ECV在区分IAC分级方面优于其他光谱参数，反映了肿瘤微环境的变化。将ECV与影像特征相结合可提高诊断准确性，不过本研究的单中心设计和小样本量限制了其可推广性。
细胞外容积分数可为肺浸润性腺癌的病理分级评估提供更多信息。与其他光谱参数相比，ECV具有最高的诊断性能，其与传统影像特征相结合可进一步提高诊断准确性。
