Challenging study to develop a diagnostic support technique of amyotrophic lateral sclerosis (ALS) by image processing approach

2017 Fiscal Year Final Research Report

• Project/Area Number: 16K15346
• Research Category: Grant-in-Aid for Challenging Exploratory Research
• Allocation Type: Multi-year Fund
• Research Field: Medical Physics and Radiological Technology
• Research Institution: Gifu University
• Principal Investigator: FUJITA Hiroshi 岐阜大学, 大学院医学系研究科, 教授 (10124033)
• Co-Investigator(Kenkyū-buntansha): 神谷 直希 愛知県立大学, 情報科学部, 講師 (00580945)
• Co-Investigator(Renkei-kenkyūsha): HARA Takeshi 岐阜大学, 工学部, 准教授 (10283285) ; ZHOU Xiangrong 岐阜大学, 工学部, 助教 (00359738) ; YAMADA Megumi 岐阜大学, 医学部附属病院 (50452157) ; INUZUKA Takashi 岐阜大学, 大学院医学系研究科 (50184734)
• Project Period (FY): 2016-04-01 – 2018-03-31
• Keywords: 医用画像処理・解析 / 筋肉画像解析 / 医用画像診断支援 / ALS / 全身CT画像

Outline of Final Research Achievements

In this research project, by image engineering approach, we aimed at support of diagnosis of amyotrophic lateral sclerosis (ALS), which is one of designated intractable diseases. We realized an automatic recognition of whole-body skeletal muscles and an automatic analysis of fat in skeletal muscle region. Here, we fully automated the recognition of skeletal muscles in whole-body CT images and developed the site-specific automated analytical technique for patients with muscle diseases accompanied by ALS and muscular atrophy. Automatic recognition of surface muscle by modeling the body cavity was performed, and the whole body was divided into 22 areas, and also three dimensional analysis of skeletal muscles was achieved. As a result, significant differences were found in multiple image features between the ALS and the myogenic disease group in the upper arm, thigh and lower leg.

Free Research Field

医用画像処理工学