Development and validation of automated assessment of liver fibrosis using second harmonic generation microscopy in patients with non-alcoholic fatty liver disease
Author(s): ,
Jason Chang
Affiliations:
Gastroenterology & Hepatology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
,
George Boon-Bee Goh
Affiliations:
Gastroenterology & Hepatology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
,
Wei Qiang Leow
Affiliations:
Department of Anatomical Pathology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
,
Yayun Ren
Affiliations:
,HistoIndex Pte Ltd,Singapore,Singapore
,
Wei Keat Wan
Affiliations:
Department of Anatomical Pathology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
,
Kiat Hon Lim
Affiliations:
Department of Anatomical Pathology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
Chee Kiat Tan
Affiliations:
Gastroenterology & Hepatology,Singapore General Hospital,Singapore,Singapore;,Duke-NUS Medical School,Singapore,Singapore
EASL LiverTree™. Chang J. Apr 20, 2017; 168816
Topic: Diagnosis
Dr. Jason Chang
Dr. Jason Chang

Access to Privileged content is an EASL members and LiverTree™ Privileged Users benefit.


Click here to join EASL or renew your membership.

Abstract
Discussion Forum (0)
Rate & Comment (0)

THU-364

Topic: Fatty liver disease: Clinical aspects

Background and aims
Assessment of liver fibrosis is essential in the management of patients with non-alcoholic fatty liver disease (NAFLD). Second Harmonic Generation (SHG) microscopy is a novel optical tissue imaging system that provides reliable automated quantification of fibrosis based on unique architectural features of collagen. SHG has been validated against METAVIR fibrosis grading in chronic hepatitis B patients. However, the utility of SHG in assessment of NAFLD fibrosis has not been explored.

The aim of this study is to develop and validate unique SHG-based characteristics for the automated assessment of fibrosis stage in patients with NAFLD.

Methods
SHG microscopy using GenesisTM(HistoIndex®, Singapore) was performed on archived liver biopsy specimens from 43 patients with NAFLD (training group). Unique algorithms were developed to identify specific SHG collagen characteristics that stage the severity of fibrosis. This was compared against the histological grading by expert liver histopathologists using Brunt fibrosis staging. The accuracy of the algorithm to stage NAFLD fibrosis was then assessed in a separate group of 40 NAFLD patients (validation group) using AUROC analysis.

Results
The training group consisted of 43 patients (mean age 52.1±12.0 years, 38% males) with NAFLD. A fibrosis index (B-index) was developed, comprising 6 unique SHG-based collagen parameters related to NAFLD fibrosis. The SHG-derived B-index was correlated well with Brunt fibrosis staging by the histopathologist (Spearman’s correlation 0.820, p<0.001) with AUROCs of 0.895, 0.982, 0.989, 0.964 for prediction of B1, B2, B3 and B4 fibrosis respectively.  The validation group comprised of 40 patients (mean age 51.2±11.6 years, 45% males). There were no significant differences in age, gender, liver function, platelet count and liver stiffness between the training and validation groups. In the validation group, B-index predicted Brunt fibrosis stage with AUROCs of 0.740, 0.865, 0.967, 0.886. A B-index score of >1.9 had an overall diagnostic accuracy of 92.5% for prediction of presence of bridging fibrosis (B≥3) with sensitivity of 83.3%, specificity 96.4%, positive likelihood ratio 23.3 and negative likelihood ratio of 0.17.

Conclusions
We have developed and subsequently validated a unique SHG-based fibrosis index that provides highly reliable automated assessment of fibrosis in NAFLD patients.

 

Code of conduct/disclaimer available in General Terms & Conditions
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.



Google Analytics is used for user behavior tracking/reporting. Google Analytics works in parallel and independently from MLG’s features. Google Analytics relies on cookies and these cookies can be used by Google to track users across different platforms/services.


Save Settings