Quantification of liver fat infiltration by magnetic resonance

• Published in: Revista medíca de Chile Vol. 147; no. 7; p. 821
• Main Authors: Herrera, Rodrigo, Peñaloza, Francisco, Arrieta, Cristóbal, Zacconi, Flavia, Saavedra, Víctor, Saavedra, Carla, Brañes, Cecilia, Hack, Thomas, Uribe, Sergio
• Format: Journal Article
• Language: Spanish
• Published: Chile 01.07.2019
• Subjects: Adipose Tissue - diagnostic imaging; Adipose Tissue - pathology; Adult; Aged; Humans; Liver - diagnostic imaging; Liver - pathology; Magnetic Resonance Imaging; Middle Aged; Non-alcoholic Fatty Liver Disease - diagnostic imaging; Non-alcoholic Fatty Liver Disease - pathology; Severity of Illness Index; Ultrasonography
• ISSN: 0717-6163; 0717-6163
• DOI: 10.4067/S0034-98872019000700821

A simple and inexpensive method is required to assess fatty infiltration of the liver non-invasively. To develop and compare different methods to quantify liver fat by magnetic resonance and compare it against ultrasound. Three algorithms were implemented: region growing (RG), graph cuts (GC) and hierarchical (HR), all based on the IDEAL method to obtain water and fat images. Using these images, the proton density fat fraction (PDFF) was calculated. The three methods were tested in phantoms with known fat percentages and later on we acquired images from 20 volunteers with an ultrasound diagnosis of fatty liver disease in different stages. For everyone, the PDFF of the nine liver segments was determined. In phantoms, the mean error between the real fat percentage and the value obtained through the three methods was -1,26, -1 and -0,8 for RG, GC and HR, respectively. The hierarchical method was more precise and efficient to obtain PDFF. The results in volunteers revealed that ultrasound showed errors categorizing the severity of hepatic steatosis in more than 50% of volunteers. We developed a tool for magnetic resonance, which allows to quantify fat in the liver. This method is less operator dependent than ultrasound and describes the heterogeneity in the fat distribution along the nine hepatic segments.