Automated assessment of malignant degree of small peripheral adenocarcinomas using volumetric CT data: Correlation with pathologic prognostic factors

作者：Yanagawa Masahiro^*; Tanaka Yuko; Kusumoto Masahiko; Watanabe Shunichi; Tsuchiya Ryosuke; Honda Osamu; Sumikawa Hiromitsu; Inoue Atsuo; Inoue Masayoshi; Okumura Meinoshin; Tomiyama Noriyuki; Johkoh Takeshi

来源：Lung Cancer, 2010, 70(3): 286-294.

DOI：10.1016/j.lungcan.2010.03.009

• Computed tomography (CT)
• Volumetric CT
• Small peripheral pulmonary
• adenocarcinoma
• Ground-glass opacity
• Pathological prognostic factors

Purpose: To evaluate a custom-developed software for analyzing malignant degrees of small peripheral adenocarcinomas on volumetric CT data compared to pathological prognostic factors.
Materials and methods: Forty-six adenocarcinomas with a diameter of 2 cm or less from 46 patients were included. The custom-developed software can calculate the volumetric rates of solid parts to whole nodules even though solid parts show a punctate distribution, and automatically classify nodules into the following six types according to the volumetric rates of solid parts: type 1, pure ground-glass opacity (GGO); type 2, semiconsolidation; type 3, small solid part with a GGO halo; type 4, mixed type with an area that consisted of GGO and solid parts which have air-bronchogram or show a punctate distribution; type 5, large solid part with a GGO halo; and type 6, pure solid type. The boundary between solid portion and GGO on CT was decided using two threshold selection methods for segmenting gray-scale images. A radiologist also examined two-dimensional rates of solid parts to total opacity (2D%solid) which was already confirmed with previous reports.
Results: There were good agreements between the classification determined by the software and radiologists (weighted kappa = 0.778-0.804). Multivariate logistic regression analyses showed that both 2D%solid and computer-automated classification were significantly useful in estimating lymphatic invasion (p = 0.0007, 0.0027), vascular invasion (p = 0.003, 0.012), and pleural invasion (p = 0.021, 0.025).
Conclusion: Using our custom-developed software, it is feasible to predict the pathological prognostic factors of small peripheral adenocarcinomas.

• 出版日期2010-12