Lung cancer probability and prognostic prediction using a large-scale CT image database

2016 Fiscal Year Final Research Report

• Project/Area Number: 26280107
• Research Category: Grant-in-Aid for Scientific Research (B)
• Allocation Type: Partial Multi-year Fund
• Section: 一般
• Research Field: Life / Health / Medical informatics
• Research Institution: The University of Tokushima
• Principal Investigator: Kawata yoshiki 徳島大学, 大学院理工学研究部, 准教授 (70274264)
• Co-Investigator(Kenkyū-buntansha): 仁木 登 徳島大学, ソシオテクノサイエンス研究部, 教授 (80116847) ; 大松 広伸 国立研究開発法人国立がん研究センター, 東病院, 副科長 (40415518)
• Project Period (FY): 2014-04-01 – 2017-03-31
• Keywords: 肺がんの画像診断法 / 肺がんの画像診断法 / 肺がん病態の時空間的な解析法 / 肺がん候補の悪性度推定法 / 肺がん候補の予後予測法

Outline of Final Research Achievements

Purpose of this research was to develop prediction models for lung cancer probability and prognosis through quantitative analyses of a large-scale CT image database. We strove to the following three major research issues: (1) establishment of a large-scale CT image database in which thoracic CT images with a large field-of-view, clinicopathological information, and prognostic information were included, (2) development of CT features which can represent tumor phenotypes quantitatively, (3) development of prediction models for lung cancer probability and prognosis. Our achievements may accelerate the identification of reliable and meaningful quantitative imaging biomarkers to develop the core technologies of estimating lung cancer probability and prognosis using preoperative CT images.

Free Research Field

医用画像工学