Literature DB >> 17879633

A validated method for quantifying macrovesicular hepatic steatosis in chronic hepatitis C.

Tom H Boyles1, Sarah Johnson, Nigel Garrahan, Andrew R Freedman, Gerraint T Williams.   

Abstract

Hepatic steatosis is increasingly seen as an important prognostic factor in chronic hepatitis C infection (HCV). The commonly used semiquantitative method of measuring steatosis is based on a study that excluded patients with HCV. Several potentially useful methods of quantifying steatosis using computer-assisted morphometric analysis have been proposed, but none has been validated against a proposed gold standard other than the method they were intended to replace. We present a novel method and propose a gold standard based on manual measurements. The manual method is time consuming but shows little interobserver error, and the mean value of 3 observations by separate investigators is proposed as the gold standard. The computer-assisted method is fast, with a single interactive step that shows minimal interobserver variation. It accurately identifies biopsies with <1% steatosis (7 of 7) and predicts the gold standard value for biopsies with > 1% steatosis with narrow CIs (geometric mean ratio 0.85 with 95% CIs 0.77-0.95). This novel method of computer-assisted morphometric analysis is fast, reliable, and suitable for future research in HCV steatosis. It may be used to reanalyze previous studies. The semiquantitative method of assessing steatosis remains appropriate for clinical purposes.

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Year:  2007        PMID: 17879633

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  5 in total

1.  Digital quantification is more precise than traditional semiquantitation of hepatic steatosis: correlation with fibrosis in 220 treatment-naïve patients with chronic hepatitis C.

Authors:  Sekou R Rawlins; Ola El-Zammar; J Michael Zinkievich; Nancy Newman; Robert A Levine
Journal:  Dig Dis Sci       Date:  2010-05-12       Impact factor: 3.199

2.  Automated image analysis method for detecting and quantifying macrovesicular steatosis in hematoxylin and eosin-stained histology images of human livers.

Authors:  Nir I Nativ; Alvin I Chen; Gabriel Yarmush; Scot D Henry; Jay H Lefkowitch; Kenneth M Klein; Timothy J Maguire; Rene Schloss; James V Guarrera; Francois Berthiaume; Martin L Yarmush
Journal:  Liver Transpl       Date:  2013-12-12       Impact factor: 5.799

3.  Liver steatosis in pre-transplant liver biopsies can be quantified rapidly and accurately by nuclear magnetic resonance analysis.

Authors:  Stefanie Bertram; Cathrin Myland; Sandra Swoboda; Anja Gallinat; Thomas Minor; Nils Lehmann; Michael Thie; Julia Kälsch; Leona Pott; Ali Canbay; Thomas Bajanowski; Henning Reis; Andreas Paul; Hideo A Baba
Journal:  Virchows Arch       Date:  2016-12-03       Impact factor: 4.064

4.  Quantification of hepatic steatosis with 3-T MR imaging: validation in ob/ob mice.

Authors:  Catherine D G Hines; Huanzhou Yu; Ann Shimakawa; Charles A McKenzie; Thomas F Warner; Jean H Brittain; Scott B Reeder
Journal:  Radiology       Date:  2010-01       Impact factor: 11.105

5.  Efficiency of Machine Learning Algorithms for the Determination of Macrovesicular Steatosis in Frozen Sections Stained with Sudan to Evaluate the Quality of the Graft in Liver Transplantation.

Authors:  Fernando Pérez-Sanz; Miriam Riquelme-Pérez; Enrique Martínez-Barba; Jesús de la Peña-Moral; Alejandro Salazar Nicolás; Marina Carpes-Ruiz; Angel Esteban-Gil; María Del Carmen Legaz-García; María Antonia Parreño-González; Pablo Ramírez; Carlos M Martínez
Journal:  Sensors (Basel)       Date:  2021-03-12       Impact factor: 3.576

  5 in total

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