2022 Fiscal Year Final Research Report

Development of an artificial intelligence diagnostic system and useful biomarkers for lower urinary tract dysfunction in men

Research Project

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Project/Area Number	20K09523
Research Category	Grant-in-Aid for Scientific Research (C)
Allocation Type	Multi-year Fund
Section	一般
Review Section	Basic Section 56030:Urology-related
Research Institution	Nagoya University
Principal Investigator	Matsukawa Yoshihisa 名古屋大学, 医学部附属病院, 講師 (30378145)
Co-Investigator(Kenkyū-buntansha)	山本徳則名古屋大学, 医学系研究科, 特任教授 (20182636) 亀谷由隆名城大学, 理工学部, 准教授 (60361789)
Project Period (FY)	2020-04-01 – 2023-03-31
Keywords	排尿筋低活動 / 人工知能 / 下部尿路機能障害 / オミックス / 低活動膀胱 / 診断システム
Outline of Final Research Achievements	Detrusor underactivity (DU) and bladder outlet obstruction (BOO) are the main pathophysiology of lower urinary tract symptoms (LUTS) in men and the differentiation between DU and BOO is important for therapeutic decision-making. However, a pressure-flow study, which is invasive and complex, is required for the precise diagnosis of both DU and BOO. In this study, we established an artificial intelligence (AI) diagnostic system for lower urinary tract function in men with LUTS using only uroflowmetry data and to evaluate its usefulness. The sensitivity and specificity for DU diagnosis by this AI system were 79.7% and 88.7%, respectively, and the sensitivity and specificity for BOO diagnosis were 76.8% and 84.7%, respectively. In conclusion, our AI diagnostic system developed using only UFM waveforms could distinguish between DU and BOO with high sensitivity and specificity in men with LUTS.
Free Research Field	下部尿路機能障害
Academic Significance and Societal Importance of the Research Achievements	非侵襲的検査により、高い精度で下部尿路機能障害（排尿筋低活動、膀胱出口部閉塞）を診断できたことで、下部尿路症状に対する病態診断が簡便に可能となった。超高齢化社会を迎えてますまず増加する下部尿路症状症例に対して、正確な病態診断は正しい治療選択につながり、治療満足度や医療費の効率化に貢献できるものと考えている。また、今回、非侵襲的検査から下部尿路機能障害の病態が診断可能になったことから、これまで診断の難しさから治療法の開発が遅れていた排尿筋低活動に対して、新規治療の開発促進につながることが予想され、下部尿路症状に対する診療の充実化につながることが予想される。