1. Prognostic impact of artificial intelligence-based volumetric quantification of the solid part of the tumor in clinical stage 0-I adenocarcinoma
- Author
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Yohei Kawaguchi, Yoshihisa Shimada, Kotaro Murakami, Tomokazu Omori, Yujin Kudo, Yojiro Makino, Sachio Maehara, Masaru Hagiwara, Masatoshi Kakihana, Takafumi Yamada, Jinho Park, Jun Matsubayashi, Tatsuo Ohira, and Norihiko Ikeda
- Subjects
Pulmonary and Respiratory Medicine ,Cancer Research ,Lung Neoplasms ,Oncology ,Artificial Intelligence ,Humans ,Adenocarcinoma ,Prognosis ,Tomography, X-Ray Computed ,Retrospective Studies - Abstract
The size of the solid part of a tumor, as measured using thin-section computed tomography, can help predict disease prognosis in patients with early-stage lung cancer. Although three-dimensional volumetric analysis may be more useful than two-dimensional evaluation, measuring the solid part of some lesions is difficult using this methods. We developed an artificial intelligence-based analysis software that can distinguish the solid and non-solid parts (ground-grass opacity). This software calculates the solid part volume in a totally automated and reproducible manner. The predictive performance of the artificial intelligence software was evaluated in terms of survival or recurrence-free survival.We analyzed the high-resolution computed tomography images of the primary lesion in 772 consecutive patients with clinical stage 0-I adenocarcinoma. We performed automated measurement of the solid part volume using an artificial intelligence-based algorithm in collaboration with FUJIFILM Corporation. The solid part size, the solid part volume based on traditional three-dimensional volumetric analysis, and the solid part volume based on artificial intelligence were compared.Higher areas under the curve related to the solid part volume were provided by the artificial intelligence-based method (0.752) than by the solid part size (0.722) and traditional three-dimensional volumetric analysis-based method (0.723). Multivariate analysis demonstrated that the solid part volume based on artificial intelligence was independently correlated with overall survival (P = 0.019) and recurrence-free survival (P 0.001).The solid part volume measured by artificial intelligence was superior to conventional methods in predicting the prognosis of clinical stage 0-I adenocarcinoma.
- Published
- 2022