Publication of a paper on automated measurement of native T1 and extracellular volume fraction in cardiac magnetic resonance imaging using a commercially available deep learning algorithm: This paper proposes a method for automatically measuring the extracellular volume fraction and native T1 in cardiac magnetic resonance imaging. The study estimates the extracellular volume fraction and native T1 values in cardiac magnetic resonance imaging using a commercially available deep learning algorithm. It has been proven that the algorithm provides more accurate and consistent results than human interpretation. This automated measurement method enables fast and accurate diagnosis, and is expected to greatly assist in predicting and tracking the prognosis of patients with heart disease.

To diagnose and treat heart muscle diseases such as myocardial infarction and hypertrophic cardiomyopathy accurately using cardiac MRI, it is important to diagnose the degree of fibrosis and the characteristics of the myocardial tissue. T1 mapping images of cardiac MRI can be used to measure the T1 relaxation time and the extracellular volume fraction, which are indicators of myocardial damage. However, different MRI machines and imaging methods in different hospitals can lead to different measurement values, making it difficult to compare data and establish normal range data for each hospital. Professor Choi Byung-Wook has developed a method to standardize MRI measurement values across hospitals, allowing for the application of common data for disease diagnosis and enabling the use of big data-based accurate diagnosis using cardiac MRI. This research was supported by the Korea Research Foundation's Biomedical Technology Development Project, the Ministry of SMEs and Startups' BIG3 Startup Commercialization Support Project, and sponsored by Dong-A University Life Science. The research was conducted in collaboration with Professor Park Eun-Ah's team from Seoul National University Hospital's Department of Radiology, Professor Jung Jung-Im's team from Seoul St. Mary's Hospital's Department of Radiology, and Phantomics Co., Ltd. The research results were published in the recent issue of European Radiology (IF 7.034).