Abstract: Abnormal or excessive excess of intraperitoneal fat at different anatomical sites (heart, kidneys, liver, etc.) alters the metabolic profile by generating diseases causing cardiovascular complications. These include hepatic steatosis, which requires being increased surveillance before its severe progression to cirrhosis and its complications. Our objective in this study (in-vivo) was to propose a new approach to characterize and quanti-fy hepatic fat. Then, differentiated patients with metabolic dis-eases, obesity, Type 2 diabetes (T2D), metabolic syndrome and healthy subjects. This distinction was not only according to tradi-tional measurement tools such as body mass index (BMI) and waist circumference, but also according to the amount of fat from magnetic resonance imaging (MRI) DIXON image and T1-mapping at 1.5 Tesla (T). The evaluation results show that our proposed approach is reproducible, fast and robust. The distri-bution of the amount of hepatic fat in a cohort of data composed of four groups shows that hepatic fat is able to differentiate the metabolic population on the study chest. Relationship study of hepatic fat and cardiovascular parameters shows that hepatic fat is able to differentiate the metabolic population on the study chest. The relationship study of hepatic fat and cardiovascular parameters shows that hepatic fat has a negative influence on the heart if the amount it increases.

Khouloud AFFI and Mnaouer KACHOUT, “Automated Measurement of Hepatic Fat in T1-Mapping and DIXON MRI as a Powerful Biomarker of Metabolic Profile and Detection of Hepatic Steatosis” International Journal of Advanced Computer Science and Applications(IJACSA), 11(3), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110362

@article{AFFI2020,
title = {Automated Measurement of Hepatic Fat in T1-Mapping and DIXON MRI as a Powerful Biomarker of Metabolic Profile and Detection of Hepatic Steatosis},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110362},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110362},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {3},
author = {Khouloud AFFI and Mnaouer KACHOUT}
}