2022 Fiscal Year Final Research Report
Development of a diagnostic method for cardiomyopathy using pathological images reproduced from myocardial MRI delayed contrast images.
Project/Area Number |
19K17188
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 52040:Radiological sciences-related
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Research Institution | National Cardiovascular Center Research Institute |
Principal Investigator |
Ohta Yasutoshi 国立研究開発法人国立循環器病研究センター, 病院, 医長 (90388570)
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Project Period (FY) |
2019-04-01 – 2023-03-31
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Keywords | MRI / 心臓 / 高分解能 / ディープラーニング / スマートフォン |
Outline of Final Research Achievements |
We developed an imaging technique capable of higher-resolution cardiac delayed enhancement imaging to create a dataset resembling pathological images. We confirmed the achievement of high-resolution imaging in phantoms and validated improved resolution in clinical settings.
For accurate determination of inversion time in cardiac delayed enhancement imaging, we created a program using deep learning to correct for precise inversion time. We successfully implemented this program on a smartphone, confirming its clinical applicability for accurate correction using images displayed on a monitor.
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Free Research Field |
放射線科学
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Academic Significance and Societal Importance of the Research Achievements |
本研究において、心臓MRI撮像になれていない操作者でも正しく心臓MRI撮像が可能で、心筋病変観察もより高分解能にできる。この画像を蓄積した上で、病理画像と対比、更に心筋病理画像類似画像が作成できれば疾患の非侵襲的診断精度の向上が期待出来る。
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