Global Longitudinal Assessment of MASLD Using Magnetic Resonance Elastography (GOLDMINE): A Multi‐Center, International Prospective Cohort Study of Imaging Biomarkers in MASLD Clinical Outcomes

Suzanne Sharpton; Luis Antonio Díaz; Kay Pepin; Maral Amangurbanova; Egbert Madamba; Ricki Bettencourt; Seema Singh; Mark Valasek; Mary Dalupang; Kaleb Tesfai; Michael S Middleton; Cynthia Behling; Winston Dunn; Atsushi Nakajima; Kento Imajo; Yuji Ogawa; Cyrielle Caussy; Dina Halegoua‐DeMarzio; Arpan Mohanty; Daniel Q Huang; Michael Fuchs; Bilal Hameed; Jonathan G Stine; Maya Balakrishnan; Meagan Gray; Manuel Rodriguez; Andre DeLeon; Rohit Puskoor; Raj Vuppalanchi; Jaideep Behari; Lars Hansen; Cynthia Miller; Valentina Medici; Souvik Sarkar; Jerome Boursier; Monica Tincopa; Veeral Ajmera; Lisa Richards; Claude B Sirlin; Richard L Ehman; Rohit Loomba; the GOLDMINE consortium

doi:10.1111/apt.70696

. 2026 Apr 22;64(3):334–344. doi: 10.1111/apt.70696

Global Longitudinal Assessment of MASLD Using Magnetic Resonance Elastography (GOLDMINE): A Multi‐Center, International Prospective Cohort Study of Imaging Biomarkers in MASLD Clinical Outcomes

Suzanne Sharpton ¹, Luis Antonio Díaz ^2,³, Kay Pepin ^4,⁵, Maral Amangurbanova ⁶, Egbert Madamba ², Ricki Bettencourt ², Seema Singh ², Mark Valasek ², Mary Dalupang ², Kaleb Tesfai ², Michael S Middleton ⁷, Cynthia Behling ⁸, Winston Dunn ⁹, Atsushi Nakajima ¹⁰, Kento Imajo ¹⁰, Yuji Ogawa ¹⁰, Cyrielle Caussy ¹¹, Dina Halegoua‐DeMarzio ¹², Arpan Mohanty ¹³, Daniel Q Huang ¹⁴, Michael Fuchs ¹⁵, Bilal Hameed ¹⁶, Jonathan G Stine ¹⁷, Maya Balakrishnan ¹⁸, Meagan Gray ¹⁹, Manuel Rodriguez ²⁰, Andre DeLeon ²¹, Rohit Puskoor ²², Raj Vuppalanchi ²³, Jaideep Behari ²⁴, Lars Hansen ¹⁷, Cynthia Miller ²⁵, Valentina Medici ²⁶, Souvik Sarkar ²⁶, Jerome Boursier ²⁷, Monica Tincopa ², Veeral Ajmera ², Lisa Richards ², Claude B Sirlin ⁷, Richard L Ehman ⁴, Rohit Loomba ^2,^28,^29,^✉; the GOLDMINE consortium

^¹Division of Gastroenterology, Hepatology, and Nutrition, Vanderbilt University Medical Center, Nashville, Tennessee, USA

^²MASLD Research Center, University of California San Diego, La Jolla, California, USA

^³Departamento de Gastroenterología, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile

^⁴Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA

^⁵Resoundant, Inc. Rochester, Minnesota, USA

^⁶Icahn School of Medicine at Mount Sinai, NYC Health+Hospitals Queens, New York, New York, USA

^⁷Department of Radiology, University of California San Diego, La Jolla, California, USA

^⁸Department of Pediatrics, University of California San Diego, La Jolla, California, USA

^⁹Division of Gastroenterology, University of Kansas Health System, Kansas City, Kansas, USA

^¹⁰Department of Gastroenterology, Yokohama City University, Yokohama, Japan

^¹¹Hospices Civils de Lyon, Département Endocrinologie, Diabète et Nutrition, Hôpital Lyon Sud, Pierre‐Bénite, France

^¹²Division of Gastroenterology and Hepatology, Thomas Jefferson University, Philadelphia, Pennsylvania, USA

^¹³Division of Gastroenterology, Boston University, Boston, Massachusetts, USA

^¹⁴Division of Gastroenterology and Hepatology, National University of Singapore, Singapore, Singapore

^¹⁵Central Virginia Veterans Affairs Healthcare System and Virginia Commonwealth University, Richmond, Virginia, USA

^¹⁶Division of Gastroenterology, University of California San Francisco, San Francisco, California, USA

^¹⁷Late‐Stage Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden

^¹⁸Division of Gastroenterology, Baylor College of Medicine, Houston, Texas, USA

^¹⁹Division of Gastroenterology and Hepatology, The University of Alabama at Birmingham, Birmingham, Alabama, USA

^²⁰Florida Research Institute, Lakewood Ranch, Florida, USA

^²¹Pinnacle Clinical Research, San Antonio, Texas, USA

^²²Pinnacle Clinical Research, Austin, Texas, USA

^²³Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana, USA

^²⁴Department of Medicine, Division of Gastroenterology, Hepatology, and Nutrition, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA

^²⁵Clinical Trials Manager, Thomas Jefferson University, Philadelphia, Pennsylvania, USA

^²⁶Department of Internal Medicine, Division of Gastroenterology and Hepatology, University of California Davis, Sacramento, California, USA

^²⁷Centre Hospitalier Universitaire D'angers, HIFIH Laboratory, SFR ICAT 4208, Angers University France, Angers, France

^²⁸Division of Gastroenterology, University of California San Diego, La Jolla, California, USA

^²⁹Department of Epidemiology, University of California San Diego, La Jolla, California, USA

Correspondence: Rohit Loomba (roloomba@ucsd.edu)

^✉

Corresponding author.

PMCID: PMC13356296 PMID: 42017265

ABSTRACT

Background

Metabolic dysfunction‐associated steatotic liver disease (MASLD) exhibits marked heterogeneity in fibrosis progression and liver‐related outcomes. Liver biopsy is not feasible for longitudinal risk stratification at scale, creating a need for validated non‐invasive biomarkers, particularly imaging biomarkers, that can predict clinically meaningful disease progression and liver‐related outcomes.

Aims

To describe the design and rationale of the GOLDMINE study, established to determine whether non‐invasive imaging biomarkers predict MASLD progression and liver‐related clinical outcomes.

Methods

GOLDMINE is an investigator‐initiated, multi‐centre, international longitudinal cohort enrolling up to 1000 adults with either biopsy‐proven MASLD or MASLD cirrhosis across the full fibrosis spectrum. Participants are recruited from 15 sites in the US and 4 international sites (Japan, Singapore and France). At baseline, participants undergo clinical phenotyping, vibration‐controlled transient elastography, and advanced magnetic resonance imaging (MRI), including proton‐density‐fat‐fraction and magnetic resonance elastography (MRE). MRI (and biospecimen banking) is repeated at 2‐year intervals (years 2 and 4), with annual follow‐up visits for up to 10 years. Baseline liver histology is centrally processed, digitized and reviewed by a single expert hepatopathologist; all MRI/MREs are centrally interpreted.

Results

The prespecified clinical outcomes include progression to cirrhosis, clinically significant portal hypertension, major adverse liver‐related outcomes (ascites, hepatic encephalopathy, portal hypertensive bleeding, liver transplantation/qualification), hepatocellular carcinoma, major adverse cardiovascular events, and all‐cause mortality, with independent central adjudication of all events.

Conclusions

GOLDMINE establishes a rigorously phenotyped MASLD cohort integrating centralized histology, advanced MRI‐based biomarkers, longitudinal biobanking, and adjudicated outcomes, providing a platform to validate imaging and blood‐based prognostic biomarkers in MASLD.

Keywords: fatty liver, metabolic dysfunction‐associated steatotic liver disease, NAFLD, non‐alcoholic fatty liver disease, non‐alcoholic steatohepatitis

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Abbreviations

AUDIT: Alcohol Use Disorders Identification Test
AUDIT‐C: Alcohol Use Disorders Identification Test–Consumption
CAP: controlled attenuation parameter
CSPH: clinically significant portal hypertension
CT: computed tomography
DNA: deoxyribonucleic acid
EGD: esophagogastroduodenoscopy
GOLDMINE: Global Longitudinal Assessment of MASLD using Magnetic Resonance Elastography
HCC: hepatocellular carcinoma
HIPAA: Health Insurance Portability and Accountability Act
HIV: human immunodeficiency virus
HVPG: hepatic venous pressure gradient
IRB: Institutional Review Board
MACE: major adverse cardiovascular event
MALO: major adverse liver‐related event
MASH: metabolic dysfunction‐associated steatohepatitis
MASLD: metabolic dysfunction‐associated steatotic liver disease
MELD: Model for End‐Stage Liver Disease
MRE: magnetic resonance elastography
MRI: magnetic resonance imaging
PDFF: proton density fat fraction
PNPLA3: patatin‐like phospholipase domain–containing protein 3
US: United States
VCTE: vibration‐controlled transient elastography

1. Introduction

Metabolic dysfunction‐associated steatotic liver disease (MASLD) is recognized as the most prevalent cause of chronic liver disease worldwide [1, 2]. MASLD is estimated to affect approximately one‐third of the adult population in the United States (US) and is currently the second leading indication for liver transplantation [3, 4]. Its prevalence is strongly associated with metabolic syndrome, obesity and type 2 diabetes mellitus [5, 6]. Moreover, MASLD can lead to progressive liver disease, including cirrhosis and hepatocellular carcinoma (HCC) [7, 8]. Although advanced fibrosis and cirrhosis have been identified as the main risk factors for liver‐related mortality [9, 10], the natural history of MASLD and factors associated with its progression remain incompletely understood. For example, MASLD exhibits substantial heterogeneity in disease severity and fibrosis progression, and only a subset of adults with MASLD ultimately develop liver‐related complications [7, 10].

For many years, liver biopsy has been considered the gold standard for staging liver fibrosis in MASLD. However, liver biopsy is not suitable for use as a population‐wide screening tool because of its cost, limited availability and associated risks [11]. Thus, identification of those individuals with MASLD who are at risk for progressive liver disease and liver‐related morbidity and mortality through non‐invasive means is a major priority [12]. To date, biomarkers of interest have been identified based on the current understanding of the pathogenesis of MASLD and include markers of oxidative stress, inflammation, hepatocyte apoptosis and hepatic fibrosis. Furthermore, newer technologies are now being applied to MASLD biomarker development, including lipidomics, proteomics, metabolomics, metagenomics and genomics, which may contribute to the identification of novel biomarkers of disease [13]. Although most of these biomarkers cannot reliably identify individuals with significant fibrosis and steatohepatitis, others, such as chemical shift–encoding magnetic resonance imaging (MRI)–derived proton density fat fraction (PDFF) and magnetic resonance elastography (MRE), yield high sensitivity and specificity for identifying steatohepatitis and liver fibrosis, respectively [14, 15]. Both PDFF and MRE can be useful not only for diagnostic purposes but also for ongoing monitoring of disease progression and response to treatment [16, 17, 18, 19].

Here we present the protocol for the Global Longitudinal Assessment of MASLD using Magnetic Resonance Elastography (GOLDMINE) study, an international multicenter prospective cohort study enrolling adults with biopsy‐proven MASLD and MASLD‐related cirrhosis. This study will facilitate the needed evaluation of the following: (1) Further elucidation of the natural history of MASLD and its different histological subtypes; (2) Understanding of MASLD disease variation occurring in different segments of the population by enrolling a racially and ethnically diverse group of patients; (3) Characterization of the prognostic factors for progression of MASLD and liver‐related clinical outcomes; (4) Development of novel predictive non‐invasive imaging and non‐imaging biomarkers of MASLD progression, and for longitudinal follow‐up of MASLD. (5) Interpretation of dynamic changes in non‐invasive markers, such as changes in liver stiffness on MRE between years 1 and 2, in relation to long‐term clinical outcomes.

2. Methods

2.1. Overview

GOLDMINE is an investigator‐initiated, multicenter, international longitudinal study that includes a well‐characterized cohort of up to 1000 adults with either biopsy‐proven MASLD or MASLD‐related cirrhosis (Figure 1). The full spectrum of MASLD is represented, including all stages of fibrosis. This is a clinicopathologic condition‐based study designed primarily to allow the compilation of data and collection of specimens for the study of the epidemiology and natural history of MASLD. Participants undergo contemporaneous MRI (PDFF and MRE) at the time of enrollment, followed by two subsequent MRI studies at 2‐year intervals. Biobanking occurs at baseline and at 2‐year intervals to coincide with advanced MRI imaging. Histologic assessment of baseline liver biopsies is systematically performed by one central experienced liver pathologist. Participants return annually for up to 10 years of follow‐up. The sample size calculation is outlined in the Data S1.

Overview of the Global Longitudinal Assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD) using Magnetic Resonance (GOLDMINE) study procedures.

2.2. Study Objectives

The primary objective of the GOLDMINE study is to create a multicenter longitudinal cohort to investigate whether non‐invasive imaging biomarkers predict disease progression and clinical outcomes in MASLD. Secondary objectives include: (1) to define clinically significant changes in non‐invasive imaging biomarkers and compare the diagnostic accuracy of MRI and ultrasound‐based modalities, (2) create a biospecimen bank [serum, plasma, urine, DNA and liver tissue] suitable for development of prognostic non‐imaging biomarkers and (3) to provide a resource for ancillary studies of MASLD pathogenesis including genomic, proteomic and lipidomic characterization.

2.3. Organization and Oversight

Coordination of the GOLDMINE study is performed by the MASLD Research Center at the University of California, San Diego (La Jolla, California, US). Responsibilities of the coordinating site include creation of the protocol, defining standard operating procedures, data management of all centralized MRI data and management of the web‐based REDCap database. GOLDMINE participants are enrolled from 15 sites in the US and 4 international sites. International sites are in Japan, Singapore and France. Participating GOLDMINE sites are shown in Figures 2 and 3. Site principal investigators are experienced hepatologists and clinical researchers with expertise in MASLD (Table 1).

Map of participant sites for the Global Longitudinal Assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD) using Magnetic Resonance (GOLDMINE) study in the United States.

Map of international participant sites for the Global Longitudinal Assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD) using the Magnetic Resonance (GOLDMINE) study.

TABLE 1.

The Global Longitudinal Assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD) using Magnetic Resonance (GOLDMINE) participant sites with active recruitment.

Country	Site name	Site principal investigator
USA	University of California San Diego	Rohit Loomba
USA	University of California San Francisco	Bilal Hameed
USA	University of California Davis	Valentina Medici
USA	Mayo Clinic	Alina Allen
USA	Kansas University	Winston Dunn
USA	Arizona Liver Health	Naim Alkhouri
USA	Pinnacle Clinical Research	Jacques Benun
USA	Baylor Medicine	Maya Balakrishnan
USA	Thomas Jefferson University	Dina Halegoua‐DeMarzio
USA	Vanderbilt University Medical Center	Suzanne Sharpton
USA	University of Alabama	Meagan Grey
USA	Central Virginia VA Health Care Center	Michael Fuchs
USA	University of Pittsburgh Medical Center	Jaideep Bahari
USA	Boston University	Arpan Mohanty
USA	Indiana University	Raj Vuppalanchi
France	Angers University Hospital	Jerome Boursier
France	Hospices Civils de Lyon	Cyrielle Caussy
Japan	Yokohama University	Atsushi Nakajima
Singapore	University of Singapore	Daniel Huang

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2.4. Ethical Practice and Confidentiality

Prior to implementation of this protocol, the principal investigator must have the protocol and consent form approved by the Institutional Review Board for Human Research (IRB) at his/her institution. Once a candidate for the GOLDMINE study entry has been identified, details are carefully discussed with the participant. The participant is asked to read and sign the IRB‐approved consent form. There is a separate consent for the collection, storage and use of DNA for genetic research. Consent for screening and Health Insurance Portability and Accountability Act (HIPAA) authorization to disclose protected health information with the GOLDMINE Study must be obtained from the participant prior to initiating any data collection. HIPAA authorization forms are prepared according to the clinical center IRB requirements and guidelines. Data is held within the registry in an anonymized form to avoid identifiable data transfer or processing outside of the participant's care team at the recruiting center. All laboratory specimens, data, reports and other records that are part of the study data collection and entry materials are identified by a coded number to maintain subject confidentiality.

2.5. Biorepository

All biosamples are processed at participating sites according to standardized protocols. Samples are then stored at the Altman Clinical and Translational Institute, which is a state‐of‐the‐art biobanking facility at the University of California San Diego (La Jolla, California, USA).

2.6. Study Inclusion and Exclusion Criteria

Adults (age ≥ 18 years) with biopsy‐proven MASLD or MASLD‐related cirrhosis are eligible for study inclusion. Liver biopsy must be performed within 180 days prior to study enrollment but is not required for participants with MASLD‐related cirrhosis. MASLD is defined by steatosis involving at least 5% of hepatocytes on routine stains in the absence of evidence of any other acute or chronic liver disease. Cirrhosis may be defined based on histology or a clinical diagnosis of cirrhosis by a board‐certified gastroenterologist based on the combination of imaging, physical examination and laboratory findings.

Patients meeting any of the following criteria were excluded from the study: significant alcohol consumption (defined as ≥ 14 drinks/week for men or ≥ 7 drinks/week for women) within the previous 2‐year period; underlying liver disease including hepatitis B, hepatitis C, hemochromatosis, Wilson's disease, alpha‐1 antitrypsin deficiency, glycogen storage disease, autoimmune hepatitis and cholestatic or vascular liver disease; clinical or laboratory evidence of secondary causes or chronic conditions associated with hepatic steatosis including nutritional disorders, human immunodeficiency virus (HIV) infection and use of steatogenic drugs such as amiodarone, glucocorticoids, methotrexate, l‐asparaginase and valproic acid; major systemic illnesses; contraindications to MRI, including metallic implants, claustrophobia and body circumference exceeding the imaging chamber capacity; pregnancy or attempting to become pregnant. All patients undergo etiologic tests at baseline, including hepatitis B surface antigen, hepatitis C antibody, HIV antigen/antibody, ceruloplasmin and alpha‐1 antitrypsin. Clinically significant portal hypertension (CSPH) is not an exclusion criterion and is evaluated for at both baseline and at annual follow‐up. Inclusion and exclusion criteria are further detailed in Table 2.

TABLE 2.

Inclusion and exclusion criteria for the Global Longitudinal Assessment of metabolic dysfunction‐associated steatotic liver disease (MASLD) using Magnetic Resonance (GOLDMINE).

Key inclusion criteria

Age at least 18 years at time of initial screening

Written informed consent to participate

Willingness to be followed for up to a minimum of 4 years

Minimal or no alcohol use history consistent with MASLD (see exclusion criteria)

Clinical diagnosis of MASLD‐cirrhosis or evidence of MASLD on a liver biopsy within 180 days of enrollment

Key exclusion criteria

Clinical or histological evidence of alcoholic liver disease:

Participant with biopsy‐proven MASLD without cirrhosis: regular and excessive use of alcohol within the 2 years prior to interview, defined as alcohol intake > 14 standard drinks on average per week for men and > 7 standard drinks on average per week for women
Participant with MASLD‐related cirrhosis: any current alcohol consumption

Total parenteral nutrition for more than 1 month within a 6‐month period before enrollment

Short bowel syndrome

History of gastric or jejunoileal bypass or bariatric surgery procedure prior to enrollment

History of biliopancreatic diversion

Evidence of chronic hepatitis B as marked by the presence of HBsAg

Evidence of chronic hepatitis C as marked by the presence of anti‐HCV or HCV RNA

Low alpha‐1‐antitrypsin level and/or AAT ZZ phenotype

Wilson's disease

Known glycogen storage disease

Known dysbetalipoproteinemia

Hereditary hemochromatosis or known hepatic iron overload

Acute or chronic Budd‐Chiari

Known HIV positivity

Polycystic liver disease

Congenital hepatic fibrosis

Other metabolic or congenital liver disease

Disseminated or advanced malignancy

Evidence of systemic infectious disease

Documented history of hepatocellular carcinoma

Concomitant severe underlying systemic illness that, in the opinion of the investigator, would interfere with completion of follow‐up

Active drug use or dependence that, in the opinion of the study investigator, would interfere with adherence to study requirements

Any other condition which, in the opinion of the investigator, would impede compliance or hinder completion of study

Inability to provide informed consent

Pregnancy at the time of initial screening

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Abbreviations: AAT, alpha‐1 antitrypsin; anti‐HCV, hepatitis C virus antibody; HBsAg, hepatitis B surface antigen; HCV, hepatitis C virus; HIV, human immunodeficiency virus; MASLD, metabolic dysfunction‐associated steatotic liver disease; RNA, ribonucleic acid.

2.7. Central Histologic Interpretation and Digitization of Liver Biopsies

Liver biopsy is required for study enrollment in all patients, unless there is a clinical diagnosis of cirrhosis confirmed by the site principal investigator. All liver biopsies are accessioned, processed and stained (haematoxylin & eosin and trichrome) through a centralized process overseen by AcelaBio (San Diego, CA, USA) to minimize variation of slide preparation. High‐resolution images from whole slides are digitized and transferred to an imaging management system to facilitate central pathology secondary review and interpretation.

One expert hepatopathologist reviews all liver biopsies for GOLDMINE participants, and the central pathologist confirms that the biopsy is not exclusionary. This process was chosen given concerns regarding interobserver variability in assessment. The standardized central GOLDMINE histology form is included in the Data S1 and includes capture of many exploratory features.

2.8. Baseline and Annual Follow‐Up

All GOLDMINE participants present for a baseline evaluation and follow‐up visits are scheduled at one‐year intervals after enrollment. An overview of study procedures is included in Figure 1.

A comprehensive dataset is collected at each visit (Table 3). The following assessments occur at every study visit: (1) medical history including data on key events or intervention, surgeries, hospital admissions, new diagnoses of co‐morbidities; (2) medication history: specific medications queried include those taken for the treatment of liver disease (i.e., resmetirom and/or glucagon‐like peptide‐1 receptor agonists), diabetes, insulin resistance, hypertension and hyperlipidemia; (3) physical examination including vital signs, anthropometrics and general and liver‐specific signs (jaundice, spider angiomata, palmar erythema, hepatomegaly, splenomegaly, asterixis); (4) standardized questionnaires to assess alcohol use history, including the Alcohol Use Disorders Identification Test (AUDIT) and Skinner Lifetime Drinking history at baseline and the interim drinking history (AUDIT‐C) at annual follow‐up visits; (5) screening etiologic tests for chronic liver disease at baseline and phlebotomy for routine fasting laboratory tests (haematology, glucose and insulin, clinical chemistry, hepatic panel, glycated haemoglobin and lipid profile); (6) ultrasound and vibration‐controlled transient elastography (VCTE) with controlled attenuation parameter (CAP) performed by a certified technician according to the manufacturer's protocol; (7) documentation of any esophagogastroduodenoscopy (EGD) findings performed for routine clinical care; and (8) documentation of any additional liver biopsies performed as part of standard of care or during participation in other research trials.

TABLE 3.

Summary of clinical data collected by study time point.

Clinical data	Baseline	Annual follow‐up
Liver biopsy (for study inclusion in non‐cirrhotic MASLD) ^a	x
Medical history, including data on key outcomes, hospital admissions and co‐morbidities	x	x
Comprehensive medication use history	x	x
Focused physical examination	x	x
Anthropometric measurements	x	x
Skinner Lifetime drinking history	x
Alcohol Use Disorders Identification Test (AUDIT) questionnaire	x
Interim drinking history (AUDIT‐C)		x
Screening etiologic tests ^b	x
Fasting laboratory data: clinical blood count, clinical chemistry, hepatic panel, glycated haemoglobin, lipid panel, international normalized ratio (INR) and insulin	x	x
Vibration‐controlled transient elastography (VCTE)	x	x
Review of interim liver biopsy or endoscopy results ^a		x
Biobanking collection (for central biobank) ^c	Collected at 3 time‐points during the study: baseline, year 2, year 4
Magnetic resonance elastography and PDFF ^d

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^{^a}

Liver biopsy is only performed at baseline per protocol; if subsequent liver biopsies are performed for clinical care purposes, this information is collected. Endoscopy is not included in the GOLDMINE protocol, but esophagogastroduodenoscopy (EGD) data is collected if performed for clinical care.

^{^b}

Required serum etiologic tests include hepatitis B surface antigen, hepatitis C antibody, alpha‐1‐antitrypsin, ceruloplasmin, ferritin and iron indices, anti‐mitochondrial antibody (AMA), anti‐smooth muscle antibody (ASMA) and anti‐nuclear antibody (ANA).

^{^c}

According to a central standardized operating procedure. Biobanking specimens collected include plasma, serum, whole blood and urine.

^{^d}

Women of reproductive age undergo a urine pregnancy test prior to magnetic resonance imaging. MRE protocol is further outlined in the Table S1.

In addition to the above procedures, the following are performed at baseline and every 2 years, for 2 additional occurrences (years 2 and 4): MRI per study protocol and biospecimen banking (serum, plasma, urine, DNA and liver tissue samples if available). Blood samples are drawn in a fasting state. Standardized methods are utilized for serum, plasma, peripheral blood mononuclear cells and DNA isolation that allow for maximal preservation of banked specimens and storage in designated −80°C freezers. We estimated that approximately 20% of the patient population at any stage of MASLD (no fibrosis, mild/moderate fibrosis, advanced fibrosis) will exhibit fibrosis progression within a 2‐year span [20], which was our reasoning for obtaining MRI and biospecimens at 2‐year intervals during this 10‐year study.

2.9. MRI and MRE With Central Imaging Repository and Interpretation

MRI examinations include four research sequences (three imaging sequences and one single‐voxel spectroscopy sequence), allowing for the measurement of liver fat fraction and newer candidate MRI‐based biomarkers for future MASLD studies (Figure 4 and Table S1). MRE is performed according to previously described methods on commercially available software and hardware (Developed by Resoundant Inc., Rochester, MN and available from the major MRI manufacturers). No more than a maximum of 180 days is permitted to elapse between liver biopsy and imaging assessments, including ultrasound, VCTE and MRI‐based imaging. Image acquisition at expiration is required. To assess sequence repeatability, two sequences per subject, block randomized, will be run three times. All MRIs are transferred and interpreted by the central imaging team at Resoundant Inc. (Rochester, MN, USA). MRI images are transferred to Mayo via AMBRA, a secure, cloud‐based, medical imaging transfer and storage solution. AMBRA performs client‐side metadata de‐identification before upload. For analyses comparing ultrasound with MRI‐based modalities, paired examinations obtained within the prespecified 180‐day imaging window will be used, and site‐related heterogeneity in ultrasound acquisition will be accounted for analytically by stratifying analyses according to center (central coordinating site vs. other sites).

Hepatogram results of a 31‐year old male participant with a history of metabolic dysfunction‐associated steatotic liver disease (MASLD), type 2 diabetes and hyperlipidemia. Imaging showed a liver stiffness of 4.04 kPa, fat fraction 18.2% and R2* 30 s⁻¹. Representative images from each acquisition are shown in the summary report, with the region of interest used for measurement shown in white. The mean value was calculated from four slices.

3. Results

3.1. Expected Clinical Outcomes

Key outcomes assessed in the GOLDMINE study include the following: (1) progression to cirrhosis, (2) asymptomatic CSPH, (3) major adverse liver‐related events (MALOs), (4) HCC, cardiovascular events and (5) all‐cause mortality (including liver‐related and non‐liver‐related mortality) (Table 4).

TABLE 4.

Clinical outcomes to be assessed during 10‐year longitudinal follow‐up.

Clinical outcome ^a	Definition
Progression to cirrhosis	Defined by histopathology, radiologic evidence of cirrhosis (combined with clinical criteria), elastography measures of cirrhosis ^b , or development of CSPH
Asymptomatic clinically significant portal hypertension (CSPH)	High risk varices (large or ‘red‐wale’ signs) requiring treatment
	Elastography measures (LSM ≥ 25 kPa on VCTE)
	HVPG ≥ 10 mmHg
Major adverse liver‐related outcomes (MALOs)	Clinically apparent ascites requiring treatment (diuretics, paracentesis and/or TIPS)
	Hepatic encephalopathy, grade 2 or above according to West Haven criteria and requiring treatment
	Portal hypertension‐related upper gastrointestinal bleeding identified by endoscopy and requiring hospitalization
	Liver transplantation or qualification for liver transplantation (defined by MELD score ≥ 15 on two separate occasions at least 2 weeks apart)
Hepatocellular carcinoma	Hepatocellular carcinoma confirmed on histology or imaging
Major adverse cardiovascular events (MACEs)	Coronary events (unstable angina, myocardial infarction, or coronary intervention or surgery), ischemic or hemorrhagic stroke, heart failure, or cardiovascular death
All‐cause mortality	Liver‐related and non‐liver‐related mortality

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Abbreviations: HVPG, hepatic venous pressure gradient; MELD, Model for End‐Stage Liver Disease; TIPS, transjugular intrahepatic portosystemic shunt.

^{^a}

All outcomes, including all deaths, are reviewed by an adjudication committee according to a standardized protocol.

^{^b}

Elastography measures of cirrhosis include LSM ≥ 20 kPa (VCTE) and/or LSM ≥ 5 kPa (MRE).

Progression to cirrhosis is defined by any of the following: histopathology, clinical evidence of cirrhosis (combined radiologic and clinical criteria), non‐invasive and elastography measures of cirrhosis, or development of CSPH. MALO is defined by any of the following: clinically apparent ascites requiring treatment (with paracentesis, diuretics and/or transjugular intrahepatic portosystemic shunt), hepatic encephalopathy, grade 2 or above according to the West Haven criteria and requiring treatment documented by a gastroenterologist, progression to large gastric or oesophageal varices and/or ‘red‐wale’ signs or endoscopic treatment, portal hypertension‐related upper gastrointestinal bleeding identified by EGD and requiring hospitalization, including events of bleeding from oesophageal varices or gastric varices, and liver transplantation or qualification for liver transplantation, defined as Model for End‐Stage Liver Disease (MELD) score ≥ 15 on at least 2 consecutive occasions at least 2 weeks apart. HCC must be confirmed by histology or by characteristic appearance on multiphasic, contrast‐enhanced ultrasound, computed tomography (CT), or MRI.

We will collect cardiovascular events, including coronary heart disease and/or cerebrovascular accident (stroke). In particular, we will assess major adverse cardiovascular events (MACEs), which will be composed of coronary events (unstable angina, myocardial infarction, or coronary intervention or surgery), ischemic or hemorrhagic stroke, heart failure, or cardiovascular death.

3.2. Adjudication of Clinical Outcomes

All clinical outcomes and deaths are reviewed by an adjudication committee. The adjudication committee is an independent committee composed of three physician members who have expertise in hepatology. For outcomes including progression to cirrhosis and MALOs, sites provide the central adjudication committee with a clinical description of the event, including signs and symptoms and information on treatment (e.g., discharge summary, hospital notes and relevant hospital records related to the event). Pertinent laboratory results (with reference ranges, if available, and including MELD scores), imaging results, and pathology reports are also provided to the committee. All deaths in the study are reviewed by the adjudication committee to determine if liver‐related, cardiovascular‐related, or related to another cause.

4. Discussion

We have presented the protocol for GOLDMINE, which is a prospective, international multi‐center study including up to 1000 adults with biopsy‐proven MASLD enrolled across 20 sites in North America, Europe and Asia. Numerous strengths of the GOLDMINE study design include: (1) enrollment of a diverse patient population from sites across multiple continents; (2) central histologic interpretation for study entry by a single experienced liver pathologist; (3) standardized prospective biobanking; (4) novel imaging protocol with central imaging interpretation of all MRI‐based studies; (5) extended follow‐up of all participants up to 10 years after initial enrollment; and (6) adjudication of all liver‐related outcomes by a central adjudication committee comprised of experienced hepatologists.

Due to these innovative aspects of the study protocol, the GOLDMINE study affords outstanding opportunities to explore the natural history of MASLD and its different histological subtypes. In particular, MRE outperforms VCTE and ultrasound‐based elastography techniques (point shear‐wave elastography and 2D shear‐wave elastography) for staging liver fibrosis [21]. An individual‐participant‐data meta‐analysis of 798 participants with MASLD showed that MRE achieves higher sensitivity and specificity, with areas under the receiver operating characteristic curve for detecting significant fibrosis (≥ F2), advanced fibrosis (≥ F3) and cirrhosis (F4) within the range of 0.92–0.94 [15]. Moreover, MRE is less affected by technical limitations such as obesity, ascites, or challenging anatomy, and demonstrates superior intra‐ and inter‐observer reproducibility compared to ultrasound‐based methods [22, 23]. In addition, MRE can better identify changes in liver stiffness than VCTE, in which changes in kPa do not follow a linear pattern and are associated with higher intra‐ and inter‐observer variability [24].

We will also be able to better understand variation in MASLD disease burden occurring in different segments of the population by enrolling a racially and ethnically diverse group of patients. For example, the US exhibits a high burden of cardiometabolic risk factors, with an obesity prevalence of 45.6% in women and 41.5% in men [25], and a diabetes prevalence of 15.8% [26]. In contrast, other populations, such as the Japanese population, may exhibit lower prevalence, with obesity (BMI ≥ 25 kg/m²) prevalence of 27.2% in men and 10.6% in women [27], and a diabetes prevalence of about 8% [28]. Specific differences in ethnicities across the US are also expected. For example, Hispanic individuals constitute approximately 45%–50% of the population in Southern California but around 9% of the population in Pennsylvania [29]. Also, the Hispanic population from Southern California is predominantly of Mexican heritage, while in Pennsylvania, the Hispanic population is smaller and more diverse in origin. Considering that Hispanics carry a higher frequency of patatin‐like phospholipase domain–containing protein 3 (PNPLA3) I148M genetic risk variant, more severe phenotypes are expected in this population [30]. Therefore, these differing exposures may help to identify comparative risks associated with cardiometabolic risk factors and specific susceptibility among races and ethnicities.

We expect to further characterize the prognostic factors that drive progression of MASLD, ranging from simple steatosis to advanced fibrosis, cirrhosis and liver‐related events. Using large, well‐phenotyped and diverse cohorts, we will evaluate how clinical, metabolic, lifestyle and genetic determinants interact over time to influence these trajectories. In parallel, we aim to develop and validate novel predictive non‐invasive biomarkers of MASLD progression by integrating cutting‐edge technologies, including genomics, metagenomics, metabolomics, lipidomics and proteomics. Finally, we will also investigate innovative imaging technologies for the non‐invasive longitudinal follow‐up of MASLD, enabling dynamic monitoring of disease activity and treatment response.

In conclusion, the GOLDMINE study establishes a rigorously designed, prospective, international cohort of adults with biopsy‐proven MASLD across all fibrosis stages, integrating centralized histologic assessment, advanced MRI‐based phenotyping and longitudinal clinical follow‐up. By combining MRE—one of the most accurate and reproducible non‐invasive tools for fibrosis assessment—with detailed clinical, laboratory and histologic data, GOLDMINE is uniquely positioned to delineate the natural history of MASLD across the full spectrum of disease severity.

Author Contributions

Suzanne Sharpton: conceptualization, writing – original draft, data curation, writing – review and editing, formal analysis. Kay Pepin: writing – review and editing, data curation. Luis Antonio Díaz: conceptualization, writing – original draft, writing – review and editing, data curation, formal analysis. Egbert Madamba: writing – review and editing, data curation. Mary Dalupang: writing – review and editing, data curation. Ricki Bettencourt: writing – review and editing, formal analysis, data curation. Seema Singh: writing – review and editing, data curation. Atsushi Nakajima: writing – review and editing, data curation. Maral Amangurbanova: writing – review and editing, data curation. Cynthia Behling: writing – review and editing, data curation. Cyrielle Caussy: writing – review and editing, data curation. Kento Imajo: writing – review and editing, data curation. Michael S. Middleton: writing – review and editing, data curation. Yuji Ogawa: writing – review and editing, data curation. Winston Dunn: writing – review and editing, data curation. Andre DeLeon: writing – review and editing, data curation. Valentina Medici: writing – review and editing, data curation. Dina Halegoua‐DeMarzio: writing – review and editing, data curation. Maya Balakrishnan: writing – review and editing, data curation. Bilal Hameed: writing – review and editing, data curation. Arpan Mohanty: writing – review and editing, data curation. Cynthia Miller: writing – review and editing, data curation. Jerome Boursier: writing – review and editing, data curation. Meagan Gray: writing – review and editing, data curation. Daniel Q. Huang: writing – review and editing, data curation. Raj Vuppalanchi: writing – review and editing, data curation. Rohit Puskoor: writing – review and editing, data curation. Monica Tincopa: writing – review and editing, data curation. Lisa Richards: writing – review and editing, data curation. Lars Hansen: writing – review and editing, data curation. Jonathan G. Stine: writing – review and editing, data curation. Souvik Sarkar: writing – review and editing, data curation. Jaideep Behari: writing – review and editing, data curation.

Funding

The GOLDMINE study is funded by AstraZeneca.

Conflicts of Interest

Suzanne Sharpton serves on an advisory board for Takeda Pharmaceuticals and her institution has received research funding from Takeda, AstraZeneca and Boehringer Ingelheim. Michael Middleton reports current or prior consultation to Alimentiv, Arrowhead, Ascelia, AutonomUS, Glympse, Immunobrain, Image Analysis Group, Kowa, Livivos, Median, Novo Nordisk and PharmaNest; current or prior lab service agreements under auspices of UCSD from Alexion, AstraZeneca, Bristol‐Myers Squibb, Celgene, Enanta, Galmed, Genzyme, Gilead, Guerbet, Intercept, Ionis, Janssen, Livivos, NuSirt, Organovo, Pfizer, Roche, Sanofi, Shire, Synageva and Takeda; stockholder Pfizer; stock options AutonomUS and Livivos; co‐founder Quantix Bio. Jonathan G. Stine received research support within the past 24 months from AstraZeneca, Galectin, Novo Nordisk, Zydus, Regeneron. Employment with AstraZeneca, Ad board for Madrigal. Jaideep Behari has received research grant support from Pfizer, AstraZeneca, Madrigal and Gilead. His institution has research contracts with Madrigal, Akero, Rhythm and Inventiva. Valentina Medici serves as consultant for Arbormed, Eton Pharmaceuticals, Orphalan, Prime Medicine; is site PI for Orphalan, Prime Medicine, Ultragenix, Vivet; received an unrestricted gift from Mars Inc. Veeral Ajmera has consulted for Madrigal Pharmaceuticals. Richard L. Ehman and the Mayo Clinic have intellectual property rights and a financial interest in magnetic resonance elastography technology. Rohit Loomba serves as a consultant to Aardvark Therapeutics, Altimmune, Anylam/Regeneron, Amgen, Arrowhead Pharmaceuticals, AstraZeneca, Bristol‐Myer Squibb, CohBar, Eli Lilly, Galmed, Gilead, Glympse bio, Hightide, Inipharma, Intercept, Inventiva, Ionis, Janssen Inc., Madrigal, Metacrine Inc., NGM Biopharmaceuticals, Novartis, Novo Nordisk, Merck, Pfizer, Sagimet, Theratechnologies, 89 bio, Terns Pharmaceuticals and Viking Therapeutics. In addition, his institutions received research grants from Arrowhead Pharmaceuticals, AstraZeneca, Boehringer‐Ingelheim, Bristol‐Myers Squibb, Eli Lilly, Galectin Therapeutics, Galmed Pharmaceuticals, Gilead, Hanmi, Intercept, Inventiva, Ionis, Janssen, Madrigal Pharmaceuticals, Merck, NGM Biopharmaceuticals, Novo Nordisk, Merck, Pfizer, Sonic Incytes and Terns Pharmaceuticals. He is a co‐founder of LipoNexus Inc.

Supporting information

Table S1: Magnetic resonance imaging and elastography protocol.

Data S1: Liver Biopsy Histology Worksheet.

APT-64-334-s001.docx^{(33.5KB, docx)}

Acknowledgements

The authors would like to sincerely thank all individuals and institutions who contributed to this work. We gratefully acknowledge the valuable contributions of the investigators, research coordinators and clinical staff at all study sites for their dedication to participant recruitment, data collection and study oversight: University of California, Davis—Davis, CA, USA (Abigail Caron, Sandeep Dhaliwal and Sean Romeo); University of Yokohoma—Yokohoma, Japan (Takashi Kobayashi); Boston Medical Center—Boston, MA, USA (Deepika Chilumula, Karolina Muszyńska and Amalia Holmberg); University of Kansas Medical Center—Kansas City, KS, USA (Wamda Ahmed, Michelle Springer, Ziad Etorki and Sage Robert); University of California, San Francisco—San Francisco, CA, USA (Jacqueline Lam and Rohan Ravirala); Lyon South University Hospital—Lyon, FR (Dominique Delaunay and Stephanie Auboussier); Thomas Jefferson University—Philadelphia, PA, USA (Michael Matthews and Hannah Ott); Central Virginia VA Health Care System—Richmond, VA, USA (Jill Edwards); Pinnacle Clinical Research, Austin—Austin, TX, USA (Mustafa Khan); University of Pittsburgh Medical Center—Pittsburgh, PA, USA (Jessica Izenas and Trevor Dean); Indiana University—Indianapolis, IN, USA (Kate Scheetz and Faith Swindle); Pinnacle Clinical Research, San Antonio—San Antonio, TX, USA (Ariana Torres, Sydney Duran, Sarah Merchant and LaTonda Eubanks); Baylor College of Medicine—Houston, TX, USA (Paola Martinez and Ximena Vargas); Florida Research Institute—Lakewood Ranch, FL, USA (Mandy Burdine); Centre Hospitalier Universitaire Angers—Angers, France (Pierre Celea and Sandra Girre); University of California, San Diego—La Jolla, CA, USA (Wathnita Sarik and Darryl Contrano).

Sharpton S., Díaz L. A., Pepin K., et al., “Global Longitudinal Assessment of MASLD Using Magnetic Resonance Elastography (GOLDMINE): A Multi‐Center, International Prospective Cohort Study of Imaging Biomarkers in MASLD Clinical Outcomes,” Alimentary Pharmacology & Therapeutics 64, no. 3 (2026): 334–344, 10.1111/apt.70696.

Handling Editor: Grace Wong

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1: Magnetic resonance imaging and elastography protocol.

Data S1: Liver Biopsy Histology Worksheet.

APT-64-334-s001.docx^{(33.5KB, docx)}

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

[apt70696-bib-0001] 1. Younossi Z. M., Golabi P., Paik J. M., Henry A., Van Dongen C., and Henry L., “The Global Epidemiology of Nonalcoholic Fatty Liver Disease (NAFLD) and Nonalcoholic Steatohepatitis (NASH): A Systematic Review,” Hepatology 77, no. 4 (2023): 1335–1347. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0002] 2. Huang D. Q., Wong V. W. S., Rinella M. E., et al., “Metabolic Dysfunction‐Associated Steatotic Liver Disease in Adults,” Nature Reviews. Disease Primers 11, no. 1 (2025): 14. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0003] 3. Díaz L. A., Lazarus J. V., Fuentes‐López E., et al., “Disparities in Steatosis Prevalence in the United States by Race or Ethnicity According to the 2023 Criteria,” Commun Med (Lond) 4, no. 1 (2024): 219. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0004] 4. Ochoa‐Allemant P., Serper M., Wang R. X., et al., “Waitlisting and Liver Transplantation for MetALD in the United States: An Analysis of the UNOS National Registry,” Hepatology 81, no. 2 (2025): 532–545. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0005] 5. Targher G., Valenti L., and Byrne C. D., “Metabolic Dysfunction‐Associated Steatotic Liver Disease,” New England Journal of Medicine 393, no. 7 (2025): 683–698. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0006] 6. Ajmera V., Cepin S., Tesfai K., et al., “A Prospective Study on the Prevalence of NAFLD, Advanced Fibrosis, Cirrhosis and Hepatocellular Carcinoma in People With Type 2 Diabetes,” Journal of Hepatology 78, no. 3 (2023): 471–478. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0007] 7. Hagström H., Shang Y., Hegmar H., and Nasr P., “Natural History and Progression of Metabolic Dysfunction‐Associated Steatotic Liver Disease,” Lancet Gastroenterology & Hepatology 9, no. 10 (2024): 944–956. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0008] 8. Tamaki N., Ahlholm N., Luukkonen P. K., et al., “Risk of Advanced Fibrosis in First‐Degree Relatives of Patients With Nonalcoholic Fatty Liver Disease,” Journal of Clinical Investigation 132, no. 21 (2022): e162513, 10.1172/JCI162513. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0009] 9. Dulai P. S., Singh S., Patel J., et al., “Increased Risk of Mortality by Fibrosis Stage in Nonalcoholic Fatty Liver Disease: Systematic Review and Meta‐Analysis,” Hepatology 65, no. 5 (2017): 1557–1565. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0010] 10. Sanyal A. J., Van Natta M. L., Clark J., et al., “Prospective Study of Outcomes in Adults With Nonalcoholic Fatty Liver Disease,” New England Journal of Medicine 385, no. 17 (2021): 1559–1569. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0011] 11. Hudson D., Afzaal T., Bualbanat H., et al., “Modernizing Metabolic Dysfunction‐Associated Steatotic Liver Disease Diagnostics: The Progressive Shift From Liver Biopsy to Noninvasive Techniques,” Therapeutic Advances in Gastroenterology 17 (2024): 17562848241276334. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0012] 12. Rinella M. E., Neuschwander‐Tetri B. A., Siddiqui M. S., et al., “AASLD Practice Guidance on the Clinical Assessment and Management of Nonalcoholic Fatty Liver Disease,” Hepatology 77, no. 5 (2023): 1797–1835. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0013] 13. Thakral N., Desalegn H., Diaz L. A., et al., “A Precision Medicine Guided Approach to the Utilization of Biomarkers in MASLD,” Seminars in Liver Disease 44, no. 3 (2024): 273–286. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0014] 14. Panagiotopoulos N., Wolfson T., Harris D. T., et al., “Proton Density Fat Fraction for Diagnosis of Metabolic Dysfunction‐Associated Steatotic Liver Disease,” Hepatology 83, no. 1 (2026): 127–141. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0015] 15. Liang J. X., Ampuero J., Niu H., et al., “An Individual Patient Data Meta‐Analysis to Determine Cut‐Offs for and Confounders of NAFLD‐Fibrosis Staging With Magnetic Resonance Elastography,” Journal of Hepatology 79, no. 3 (2023): 592–604. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0016] 16. Tamaki N., Munaganuru N., Jung J., et al., “Clinical Utility of 30% Relative Decline in MRI‐PDFF in Predicting Fibrosis Regression in Non‐Alcoholic Fatty Liver Disease,” Gut 71, no. 5 (2022): 983–990. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0017] 17. Koh B., Xiao J., Ng C. H., et al., “Comparative Efficacy of Pharmacologic Therapies for MASH in Reducing Liver Fat Content: Systematic Review and Network Meta‐Analysis,” Hepatology 83, no. 1 (2026): 117–126. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0018] 18. Loomba R., Amangurbanova M., Bettencourt R., et al., “MASH Resolution Index: Development and Validation of a Non‐Invasive Score to Detect Histological Resolution of MASH,” Gut 73, no. 8 (2024): 1343–1349. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0019] 19. Loomba R., Daniel P. C. Y. N., Amangurbanova M., et al., “Head‐To‐Head Comparison of MASH Resolution Index Versus FAST for Noninvasive Prediction of Resolution of MASH on Biopsy,” Hepatology 83 (2025): 907–914, 10.1097/HEP.0000000000001396. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0020] 20. Singh S., Fujii L. L., Murad M. H., et al., “Liver Stiffness Is Associated With Risk of Decompensation, Liver Cancer, and Death in Patients With Chronic Liver Diseases: A Systematic Review and Meta‐Analysis,” Clinical Gastroenterology and Hepatology 11, no. 12 (2013): 1573–1584.e1–2; quiz e88–9. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0021] 21. Hsu C., Caussy C., Imajo K., et al., “Magnetic Resonance vs Transient Elastography Analysis of Patients With Nonalcoholic Fatty Liver Disease: A Systematic Review and Pooled Analysis of Individual Participants,” Clinical Gastroenterology and Hepatology 17, no. 4 (2019): 630–637.e8. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0022] 22. Sterling R. K., Duarte‐Rojo A., Patel K., et al., “AASLD Practice Guideline on Imaging‐Based Noninvasive Liver Disease Assessment of Hepatic Fibrosis and Steatosis,” Hepatology 81, no. 2 (2025): 672–724. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0023] 23. Chen J., Yin M., Talwalkar J. A., et al., “Diagnostic Performance of MR Elastography and Vibration‐Controlled Transient Elastography in the Detection of Hepatic Fibrosis in Patients With Severe to Morbid Obesity,” Radiology 283, no. 2 (2017): 418–428. [DOI] [PMC free article] [PubMed] [Google Scholar]

[apt70696-bib-0024] 24. Lee Y. j., Lee J. M., Lee J. E., et al., “MR Elastography for Noninvasive Assessment of Hepatic Fibrosis: Reproducibility of the Examination and Reproducibility and Repeatability of the Liver Stiffness Value Measurement,” Journal of Magnetic Resonance Imaging 39, no. 2 (2014): 326–331. [DOI] [PubMed] [Google Scholar]

[apt70696-bib-0025] 25. GBD 2021 US Obesity Forecasting Collaborators , “National‐Level and State‐Level Prevalence of Overweight and Obesity Among Children, Adolescents, and Adults in the USA, 1990–2021, and Forecasts Up to 2050,” Lancet 404 (2024): 2278–2298, 10.1016/S0140-6736(24)01548-4. [DOI] [PMC free article] [PubMed] [Google Scholar]

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PERMALINK

Global Longitudinal Assessment of MASLD Using Magnetic Resonance Elastography (GOLDMINE): A Multi‐Center, International Prospective Cohort Study of Imaging Biomarkers in MASLD Clinical Outcomes

Suzanne Sharpton

Luis Antonio Díaz

Kay Pepin

Maral Amangurbanova

Egbert Madamba

Ricki Bettencourt

Seema Singh

Mark Valasek

Mary Dalupang

Kaleb Tesfai

Michael S Middleton

Cynthia Behling

Winston Dunn

Atsushi Nakajima

Kento Imajo

Yuji Ogawa

Cyrielle Caussy

Dina Halegoua‐DeMarzio

Arpan Mohanty

Daniel Q Huang

Michael Fuchs

Bilal Hameed

Jonathan G Stine

Maya Balakrishnan

Meagan Gray

Manuel Rodriguez

Andre DeLeon

Rohit Puskoor

Raj Vuppalanchi

Jaideep Behari

Lars Hansen

Cynthia Miller

Valentina Medici

Souvik Sarkar

Jerome Boursier

Monica Tincopa

Veeral Ajmera

Lisa Richards

Claude B Sirlin

Richard L Ehman

Rohit Loomba

ABSTRACT

Background

Aims

Methods

Results

Conclusions

Abbreviations

1. Introduction

2. Methods

2.1. Overview

FIGURE 1.

2.2. Study Objectives

2.3. Organization and Oversight

FIGURE 2.

FIGURE 3.

TABLE 1.

2.4. Ethical Practice and Confidentiality

2.5. Biorepository

2.6. Study Inclusion and Exclusion Criteria

TABLE 2.

2.7. Central Histologic Interpretation and Digitization of Liver Biopsies

2.8. Baseline and Annual Follow‐Up

TABLE 3.

2.9. MRI and MRE With Central Imaging Repository and Interpretation

FIGURE 4.

3. Results

3.1. Expected Clinical Outcomes

TABLE 4.

3.2. Adjudication of Clinical Outcomes

4. Discussion

Author Contributions

Funding

Conflicts of Interest

Supporting information

Acknowledgements

Data Availability Statement

References