Cargando…
An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials
Background: Many clinical trials with potential drug treatment options for non-alcoholic fatty liver disease (NAFLD) are focused on patients with non-alcoholic steatohepatitis (NASH) stages 2 and 3 fibrosis. As the histological features differentiating stage 1 (F1) from stage 2 (F2) NASH fibrosis ar...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554942/ https://www.ncbi.nlm.nih.gov/pubmed/32872090 http://dx.doi.org/10.3390/diagnostics10090643 |
_version_ | 1783593891542335488 |
---|---|
author | Leow, Wei-Qiang Bedossa, Pierre Liu, Feng Wei, Lai Lim, Kiat-Hon Wan, Wei-Keat Ren, Yayun Chang, Jason Pik-Eu Tan, Chee-Kiat Wee, Aileen Goh, George Boon-Bee |
author_facet | Leow, Wei-Qiang Bedossa, Pierre Liu, Feng Wei, Lai Lim, Kiat-Hon Wan, Wei-Keat Ren, Yayun Chang, Jason Pik-Eu Tan, Chee-Kiat Wee, Aileen Goh, George Boon-Bee |
author_sort | Leow, Wei-Qiang |
collection | PubMed |
description | Background: Many clinical trials with potential drug treatment options for non-alcoholic fatty liver disease (NAFLD) are focused on patients with non-alcoholic steatohepatitis (NASH) stages 2 and 3 fibrosis. As the histological features differentiating stage 1 (F1) from stage 2 (F2) NASH fibrosis are subtle, some patients may be wrongly staged by the in-house pathologist and miss the opportunity for enrollment into clinical trials. We hypothesized that our refined artificial intelligence (AI)-based algorithm (qFibrosis) can identify these subtle differences and serve as an assistive tool for in-house pathologists. Methods: Liver tissue from 160 adult patients with biopsy-proven NASH from Singapore General Hospital (SGH) and Peking University People’s Hospital (PKUH) were used. A consensus read by two expert hepatopathologists was organized. The refined qFibrosis algorithm incorporated the creation of a periportal region that allowed for the increased detection of periportal fibrosis. Consequently, an additional 28 periportal parameters were added, and 28 pre-existing perisinusoidal parameters had altered definitions. Results: Twenty-eight parameters (20 periportal and 8 perisinusoidal) were significantly different between the F1 and F2 cases that prompted a change of stage after a careful consensus read. The discriminatory ability of these parameters was further demonstrated in a comparison between the true F1 and true F2 cases as 26 out of the 28 parameters showed significant differences. These 26 parameters constitute a novel sub-algorithm that could accurately stratify F1 and F2 cases. Conclusion: The refined qFibrosis algorithm incorporated 26 novel parameters that showed a good discriminatory ability for NASH fibrosis stage 1 and 2 cases, representing an invaluable assistive tool for in-house pathologists when screening patients for NASH clinical trials. |
format | Online Article Text |
id | pubmed-7554942 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75549422020-10-14 An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials Leow, Wei-Qiang Bedossa, Pierre Liu, Feng Wei, Lai Lim, Kiat-Hon Wan, Wei-Keat Ren, Yayun Chang, Jason Pik-Eu Tan, Chee-Kiat Wee, Aileen Goh, George Boon-Bee Diagnostics (Basel) Article Background: Many clinical trials with potential drug treatment options for non-alcoholic fatty liver disease (NAFLD) are focused on patients with non-alcoholic steatohepatitis (NASH) stages 2 and 3 fibrosis. As the histological features differentiating stage 1 (F1) from stage 2 (F2) NASH fibrosis are subtle, some patients may be wrongly staged by the in-house pathologist and miss the opportunity for enrollment into clinical trials. We hypothesized that our refined artificial intelligence (AI)-based algorithm (qFibrosis) can identify these subtle differences and serve as an assistive tool for in-house pathologists. Methods: Liver tissue from 160 adult patients with biopsy-proven NASH from Singapore General Hospital (SGH) and Peking University People’s Hospital (PKUH) were used. A consensus read by two expert hepatopathologists was organized. The refined qFibrosis algorithm incorporated the creation of a periportal region that allowed for the increased detection of periportal fibrosis. Consequently, an additional 28 periportal parameters were added, and 28 pre-existing perisinusoidal parameters had altered definitions. Results: Twenty-eight parameters (20 periportal and 8 perisinusoidal) were significantly different between the F1 and F2 cases that prompted a change of stage after a careful consensus read. The discriminatory ability of these parameters was further demonstrated in a comparison between the true F1 and true F2 cases as 26 out of the 28 parameters showed significant differences. These 26 parameters constitute a novel sub-algorithm that could accurately stratify F1 and F2 cases. Conclusion: The refined qFibrosis algorithm incorporated 26 novel parameters that showed a good discriminatory ability for NASH fibrosis stage 1 and 2 cases, representing an invaluable assistive tool for in-house pathologists when screening patients for NASH clinical trials. MDPI 2020-08-28 /pmc/articles/PMC7554942/ /pubmed/32872090 http://dx.doi.org/10.3390/diagnostics10090643 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Leow, Wei-Qiang Bedossa, Pierre Liu, Feng Wei, Lai Lim, Kiat-Hon Wan, Wei-Keat Ren, Yayun Chang, Jason Pik-Eu Tan, Chee-Kiat Wee, Aileen Goh, George Boon-Bee An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title | An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title_full | An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title_fullStr | An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title_full_unstemmed | An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title_short | An Improved qFibrosis Algorithm for Precise Screening and Enrollment into Non-Alcoholic Steatohepatitis (NASH) Clinical Trials |
title_sort | improved qfibrosis algorithm for precise screening and enrollment into non-alcoholic steatohepatitis (nash) clinical trials |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554942/ https://www.ncbi.nlm.nih.gov/pubmed/32872090 http://dx.doi.org/10.3390/diagnostics10090643 |
work_keys_str_mv | AT leowweiqiang animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT bedossapierre animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT liufeng animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT weilai animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT limkiathon animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT wanweikeat animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT renyayun animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT changjasonpikeu animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT tancheekiat animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT weeaileen animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT gohgeorgeboonbee animprovedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT leowweiqiang improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT bedossapierre improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT liufeng improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT weilai improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT limkiathon improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT wanweikeat improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT renyayun improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT changjasonpikeu improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT tancheekiat improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT weeaileen improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials AT gohgeorgeboonbee improvedqfibrosisalgorithmforprecisescreeningandenrollmentintononalcoholicsteatohepatitisnashclinicaltrials |