PDFF diagnoses MASH in patients with severe obesity but without known liver disease

Motivation: To address the pressing need for non-invasive diagnosis of metabolic dysfunction-associated steatohepatitis (MASH). Goal(s): To evaluate the potential of proton-density fat-fraction (PDFF), corrected T1 (cT1), liver enzymes, and fibrosis scores to assist in the diagnosis of MASH. Approach: The study included study participants with obesity and at risk for MASH, undergoing bariatric surgery with intraoperative liver biopsy. Potential predictors and predictor combinations were evaluated as classifiers for MASH and steatosis. Results: PDFF distinguished MASH from non-MASH (AUC=0.85; 95%CI 0.79-0.91, p<0.0001). A cutoff of PDFF≥13.9% detected MASH with 90% specificity and 59% sensitivity. Neither cT1, liver enzymes, nor fibrosis scores significantly improved diagnostic performance. Impact: Our results suggest that PDFF alone may be sufficient for non-invasive detection of metabolic dysfunction-associated steatohepatitis (MASH). This novel use case for an established method has the potential to transform the diagnostic approach to MASH which currently necessitates invasive biopsy.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2024-11-26
DOI
https://doi.org/10.58530/2024/4746
Citations
1
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PDFF diagnoses MASH in patients with severe obesity but without known liver disease

Thekla Oechtering, Eduardo Grunvald, Claude B. Sirlin, Gavin Hamilton et al.
1 citations
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Liver Disease Diagnosis and Treatment
0.39
article

PDFF diagnoses MASH in patients with severe obesity but without known liver disease

Thekla Oechtering, Eduardo Grunvald, Claude B. Sirlin, Gavin Hamilton, Garth R. Jacobsen, Anne O. Lidor, Scott B. Reeder, Daiki Tamada, Yesenia Covarrubias, Michael S. Middleton, Lael Ceriani, Rashmi Agni, Luke M. Funk, Danielle Batakis, James R. Goodman, Tanya Wolfson, Nikolaos Panagiotopoulos, David Harris, Santiago Horgan, Ryan Sappenfield
article en
1 citations

Abstract

Motivation: To address the pressing need for non-invasive diagnosis of metabolic dysfunction-associated steatohepatitis (MASH). Goal(s): To evaluate the potential of proton-density fat-fraction (PDFF), corrected T1 (cT1), liver enzymes, and fibrosis scores to assist in the diagnosis of MASH. Approach: The study included study participants with obesity and at risk for MASH, undergoing bariatric surgery with intraoperative liver biopsy. Potential predictors and predictor combinations were evaluated as classifiers for MASH and steatosis. Results: PDFF distinguished MASH from non-MASH (AUC=0.85; 95%CI 0.79-0.91, p<0.0001). A cutoff of PDFF≥13.9% detected MASH with 90% specificity and 59% sensitivity. Neither cT1, liver enzymes, nor fibrosis scores significantly improved diagnostic performance. Impact: Our results suggest that PDFF alone may be sufficient for non-invasive detection of metabolic dysfunction-associated steatohepatitis (MASH). This novel use case for an established method has the potential to transform the diagnostic approach to MASH which currently necessitates invasive biopsy.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Good health and well-being
Openalex Percentile: Top 32%
Liver Disease Diagnosis and Treatment
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.