The Use of LiverMultiScan to identify, stratify and predict clinical outcomes of NASH.

The utility of imaging biomarkers in NASH is the focus of several abstracts accepted for presentation at the American Association for the Study of Liver Disease’s The Liver Meeting® 2018, November 9-13, 2018 .  Three abstracts – two selected as Posters of Distinction – highlight the use of Perspectum Diagnostics’ LiverMultiScan to identify, stratify and predict clinical outcomes of NASH.

The study, “Liver cT1 predicts clinical outcomes in patients with chronic liver disease, equivalent to liver biopsy,” demonstrates the performance of multiparametric MRI imaging in predicting clinical outcomes in liver disease. Research demonstrated further evidence that corrected T1 (cT1) can predict clinical outcomes in a larger cohort of patients with varying liver disease etiologies. Patients underwent multiparametric imaging (T1, T2* mapping (iron) and MR spectroscopy (fat). LiverMultiScan software was used to obtain cT1 maps of the liver and calculate the mean cT1 value from three regions of interest. cT1 significantly differentiated between all-cause mortality, liver-related mortality and liver event-free survival. Results showed that cT1 was as predictive for liver-related events as histology.

“Identifying high risk NASH patients using reliable, cost-effective non-invasive markers is critical for streamlining care pathways, enriching populations for clinical trials, and eventually prioritising patients for approved therapies. Multiparametric MRI, combining key phenotypic measurements in a single test, has the potential to fulfil a number of diagnostic purposes,” said Professor Jonathan Fallowfield, University of Edinburgh.

Professor Fallowfield is the clinical lead for the Innovate UK funded NASH Data Commons project

 

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Steatosite

The creation of the NASH Data Commons will provide a unified data system that promotes sharing of genomic and clinical data, forming the basis for a comprehensive knowledge system that centralises, standardises and makes accessible data. These datasets will lead to a much deeper understanding of which therapies are most effective for individual patients. With each new dataset added e.g. additional ‘omics’ data, it will evolve into a smarter, more comprehensive knowledge system that will foster important discoveries in chronic liver disease and increase the success of treatments for patients.

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