Kuroda Sanae, Nishikubo Megumi, Haga Nanase, Nishioka Yuki, Shimizu Nahoko, Nishio Wataru
Division of Chest Surgery, Hyogo Cancer Center, 13-70, Kitaoji-Cho, Akashi City, 673-8558, Japan.
Gen Thorac Cardiovasc Surg. 2025 Apr;73(4):235-244. doi: 10.1007/s11748-024-02076-0. Epub 2024 Sep 3.
As the role of segmentectomy expands in managing early-stage lung adenocarcinoma, precise preoperative assessments of tumor invasiveness via computed tomography become crucial. This study aimed to evaluate the effectiveness of solid component analysis of three-dimensional (3D) computed tomography images and establish segmentectomy criteria for early-stage lung adenocarcinomas.
This retrospective study included 101 cases with adenocarcinoma diagnoses, with patients undergoing segmentectomy for clinical stage 0 or IA between 2012 and 2017. The solid component volume (3D-volume) and solid component ratio (3D-ratio) of tumors were calculated using 3D computed tomography. Additionally, based on two-dimensional (2D) computed tomography, the solid component diameter (2D-diameter) and solid component ratio (2D-ratio) were calculated. The area under the receiver-operating characteristic curve (AUC) was calculated for each method, facilitating predictions of mortality and recurrence within 5 years. The AUC of each measurement was compared with those of invasive component diameter (path-diameter) and invasive component ratio (path-ratio) obtained through pathology analysis.
The predictive performance of 3D-volume did not differ significantly from that of path-diameter, whereas 2D-diameter exhibited less predictive accuracy (AUC: 3D-volume, 2D-diameter, and path-diameter: 0.772, 0.624, and 0.747, respectively; 3D-volume vs. path-diameter: p = 0.697; 2D-diameter vs. path-diameter: p = 0.048). Results were similar for the solid component ratio (AUC: 3D-ratio, 2D-ratio, path-ratio: 0.707, 0.534, and 0.698, respectively; 3D-ratio vs. path-ratio: p = 0.882; 2D-ratio vs. path-ratio: p = 0.038).
Solid component analysis using 3D computed tomography offers advantages in prognostic prediction for early-stage lung adenocarcinomas.
随着肺段切除术在早期肺腺癌治疗中的作用不断扩大，通过计算机断层扫描对肿瘤侵袭性进行精确的术前评估变得至关重要。本研究旨在评估三维（3D）计算机断层扫描图像实性成分分析的有效性，并建立早期肺腺癌的肺段切除标准。
这项回顾性研究纳入了101例腺癌诊断病例，这些患者在2012年至2017年间因临床分期为0期或IA期而接受了肺段切除术。使用3D计算机断层扫描计算肿瘤的实性成分体积（3D体积）和实性成分比例（3D比例）。此外，基于二维（2D）计算机断层扫描，计算实性成分直径（2D直径）和实性成分比例（2D比例）。计算每种方法的受试者操作特征曲线（AUC）下面积，以预测5年内的死亡率和复发率。将每种测量的AUC与通过病理分析获得的侵袭性成分直径（病理直径）和侵袭性成分比例（病理比例）的AUC进行比较。
3D体积的预测性能与病理直径的预测性能无显著差异，而2D直径的预测准确性较低（AUC：3D体积、2D直径和病理直径分别为0.
