Creating a new plaster model of coronary artery calcification utilizing optical frequency domain imaging (OFDI) and developing treatment devices.

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K08142
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 52040:Radiological sciences-related
• Research Institution: Iwate Medical University
• Principal Investigator: Ishida Masaru 岩手医科大学, 医学部, 准教授 (20400484)
• Co-Investigator(Kenkyū-buntansha): 伊藤 智範 岩手医科大学, 医学部, 教授 (30347851) ; 土井 章男 岩手県立大学, ソフトウェア情報学部, 教授 (60271839) ; 森野 禎浩 岩手医科大学, 医学部, 教授 (90408063)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 血管内イメージング / 冠動脈 / 石灰化 / 光干渉断層法 / 機械学習

Outline of Final Research Achievements

Initially, we had planned to conduct research using optical frequency domain imaging (OFDI) images of coronary artery calcification, which prospectively obtained from our department. The goal was to create plaster models of coronary artery calcification and explore the optimal devices for treating calcified coronary lesions. However, due to the COVID-19 pandemic, it became impossible to carry out the research as planned. Therefore, we decided to change our research approach and explore methods.
As a result, we succeeded in creating an algorithm that can automatically diagnose calcification lesions using coronary artery OFDI by developing a machine learning model. Furthermore, we revealed diagnostic accuracy as follows; sensitivity, specificity, positive predictive value, and negative predictive value for calcified plaque extraction using our program were 83.2%, 85.5%, 76.6%, and 89.9%, respectively.

Free Research Field

冠動脈インターベンション、血管内イメージング

Academic Significance and Societal Importance of the Research Achievements

本研究成果が実用化された際には、経験が浅い術者でも冠動脈石灰化プラークの重症度診断が簡便にできる様になると思われる。また、治療中に取得した画像を用いた際も石灰化プラークの定量化が容易に可能となり、治療のデバイスの選択及び評価も簡便かつ単純に行うことができる様になる。