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medRxiv : the preprint server for health sciences · 2025

AI-based Hepatic Steatosis Detection and Integrated Hepatic Assessment from Cardiac CT Attenuation Scans Enhances All-cause Mortality Risk Stratification: A Multi-center Study.

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Yi Jirong, Patel Krishna K, Miller Robert J H, Marcinkiewicz Anna M, Shanbhag Aakash, Hijazi Waseem, Dharmavaram Naga, Lemley Mark, Zhou Jianhang, Zhang Wenhao, Liang Joanna X, Ramirez Giselle, Builoff Valerie, Slipczuk Leandro, Travin Mark, Alexanderson Erick, Carvajal-Juarez Isabel, Packard René R S, Al-Mallah Mouaz, Ruddy Terrence D, Einstein Andrew J, Feher Attila, Miller Edward J, Acampa Wanda, Knight Stacey, Le Viet T, Mason Steve, Calsavara Vinicius F, Chareonthaitawee Panithaya, Wopperer Samuel, Kwan Alan, Wang Lixia, Berman Daniel S, Dey Damini, Carli Marcelo Di, Slomka Piotr J

Аннотация

BACKGROUND: Hepatic steatosis (HS) is a common cardiometabolic risk factor frequently present but under-diagnosed in patients with suspected or known coronary artery disease. We used artificial intelligence (AI) to automatically quantify hepatic tissue measures for identifying HS from CT attenuation correction (CTAC) scans during myocardial perfusion imaging (MPI) and evaluate their added prognostic value for all-cause mortality prediction.

METHODS: This study included 27039 consecutive patients [57% male] with MPI scans from nine sites. We used an AI model to segment liver and spleen on low dose CTAC scans and quantify the liver measures, and the difference of liver minus spleen (LmS) measures. HS was defined as mean liver attenuation < 40 Hounsfield units (HU) or LmS attenuation < -10 HU. Additionally, we used seven sites to develop an AI liver risk index (LIRI) for comprehensive hepatic assessment by integrating the hepatic measures and two external sites to validate its improved prognostic value and generalizability for all-cause mortality prediction over HS.

FINDINGS: Median (interquartile range [IQR]) age was 67 [58, 75] years and body mass index (BMI) was 29.5 [25.5, 34.7] kg/m2, with diabetes in 8950 (33%) patients. The algorithm identified HS in 6579 (24%) patients. During median [IQR] follow-up of 3.58 [1.86, 5.15] years, 4836 (18%) patients died. HS was associated with increased mortality risk overall (adjusted hazard ratio (HR): 1.14 [1.05, 1.24], p=0.0016) and in subpopulations. LIRI provided higher prognostic value than HS after adjustments overall (adjusted HR 1.5 [1.32, 1.69], p<0.0001 vs HR 1.16 [1.02, 1.31], p=0.0204) and in subpopulations.

INTERPRETATIONS: AI-based hepatic measures automatically identify HS from CTAC scans in patients undergoing MPI without additional radiation dose or physician interaction. Integrated liver assessment combining multiple hepatic imaging measures improved risk stratification for all-cause mortality.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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