UNLABELLED: Nonalcoholic fatty liver disease (NAFLD) is highly prevalent and being overweight is a significant risk factor. The aim was to build an algorithm along with a scoring system for histopathologic classification of liver lesions that covers the entire spectrum of lesions in morbidly obese patients. A cohort of 679 obese patients undergoing liver biopsy at the time of bariatric surgery was studied. An algorithm for segregating lesions into normal liver, NAFLD, or nonalcoholic steatohepatitis (NASH) was built based on semiquantitative evaluation of steatosis, hepatocellular ballooning, and lobular inflammation. For each case, the SAF score was created including the semiquantitative scoring of steatosis (S), activity (A), and fibrosis (F). Based on the algorithm, 230 obese patients (34%) were categorized as NASH, 291 (43%) as NAFLD without NASH, and 158 (23%) as not NAFLD. The activity score (ballooning + lobular inflammation) enabled discriminating NASH because all patients with NASH had A ≥ 2, whereas no patients with A < 2 had NASH. This score was closely correlated with both alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (P < 0.0001, analysis of variance [ANOVA]). Comparison of transaminase levels between patients with normal liver and pure steatosis did not reveal significant differences, thus lending support to the proposal not to include steatosis in the activity score but to report it separately in the SAF score. In the validation series, the interobserver agreement for the diagnosis of NASH was excellent (κ = 0.80) between liver pathologists. There was no discrepancy between the initial diagnosis and the diagnosis proposed using the algorithm. CONCLUSION: We propose a simple but robust algorithm for categorizing liver lesions in NAFLD patients. Because liver lesions in obese patients may display a continuous spectrum of histologic lesions, we suggest describing liver lesions using the SAF score.
UNLABELLED: Nonalcoholic fatty liver disease (NAFLD) is highly prevalent and being overweight is a significant risk factor. The aim was to build an algorithm along with a scoring system for histopathologic classification of liver lesions that covers the entire spectrum of lesions in morbidly obesepatients. A cohort of 679 obesepatients undergoing liver biopsy at the time of bariatric surgery was studied. An algorithm for segregating lesions into normal liver, NAFLD, or nonalcoholic steatohepatitis (NASH) was built based on semiquantitative evaluation of steatosis, hepatocellular ballooning, and lobular inflammation. For each case, the SAF score was created including the semiquantitative scoring of steatosis (S), activity (A), and fibrosis (F). Based on the algorithm, 230 obesepatients (34%) were categorized as NASH, 291 (43%) as NAFLD without NASH, and 158 (23%) as not NAFLD. The activity score (ballooning + lobular inflammation) enabled discriminating NASH because all patients with NASH had A ≥ 2, whereas no patients with A < 2 had NASH. This score was closely correlated with both alanine aminotransferase (ALT) and aspartate aminotransferase (AST) (P < 0.0001, analysis of variance [ANOVA]). Comparison of transaminase levels between patients with normal liver and pure steatosis did not reveal significant differences, thus lending support to the proposal not to include steatosis in the activity score but to report it separately in the SAF score. In the validation series, the interobserver agreement for the diagnosis of NASH was excellent (κ = 0.80) between liver pathologists. There was no discrepancy between the initial diagnosis and the diagnosis proposed using the algorithm. CONCLUSION: We propose a simple but robust algorithm for categorizing liver lesions in NAFLD patients. Because liver lesions in obesepatients may display a continuous spectrum of histologic lesions, we suggest describing liver lesions using the SAF score.
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Authors: Anthony Petrick; Peter Benotti; G Craig Wood; Christopher D Still; William E Strodel; John Gabrielsen; David Rolston; Xin Chu; George Argyropoulos; Anna Ibele; Glenn S Gerhard Journal: Obes Surg Date: 2015-12 Impact factor: 4.129
Authors: Quentin Raas; Malu-Clair van de Beek; Sonja Forss-Petter; Inge Me Dijkstra; Abigail Deschiffart; Briana C Freshner; Tamara J Stevenson; Yorrick Rj Jaspers; Liselotte Nagtzaam; Ronald Ja Wanders; Michel van Weeghel; Joo-Yeon Engelen-Lee; Marc Engelen; Florian Eichler; Johannes Berger; Joshua L Bonkowsky; Stephan Kemp Journal: J Clin Invest Date: 2021-04-15 Impact factor: 14.808