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| Liver cT1 (Corrected T1) (ms) | Disease Activity Level |
|---|---|
| < 800 |
Low likelihood of disease activity |
| ≥ 800 |
Elevated level of disease activity Increased risk of cardiovascular and/or liver-related hospitalization 1, 2 |
Roca-Fernandez A, Banerjee R, Thomaides-Brears H, Telford A, Sanyal A, Neubauer S, Nichols TE, Raman B, McCracken C, Petersen SE, Ntusi NA, Cuthbertson DJ, Lai M, Dennis A, Banerjee A | Liver disease is a significant risk factor for cardiovascular outcomes | JHEP Reports (2023)
Jackson E, Dennis A, Alkhouri N, Samala N, Vuppalanchi R, Sanyal AJ, Muthiah M, Banerjee R, Banerjee A. | Cardiac and liver impairment on multi-organ MRI and risk of major adverse cardiovascular and liver events | Nature Medicine (2025)
A non-invasive, quantitative MRI solution providing comprehensive assessment of liver disease activity, fat, and iron; enabling identification, risk stratification, prognostication, and monitoring of treatment response in the liver1–11
Quantifies 3 metrics providing a comprehensive assessment of the liver in a single scan6
Liver Disease Activity (cT1)1
Liver Fat Fraction (PDFF)
Liver Iron Concentration (LIC)
Viable Alternative to Biopsy
A safe, quick, non-invasive, and non-contrast method for liver assessment1,2,3,10,12
Early Detection
LiverMultiScan enables early identification of at-risk individuals1, guiding preventative strategies
Enables timely intervention
Reliable Monitoring
Enables early detection of clinically meaningful change13
Supports longitudinal monitoring of treatment response10,11,14,15
Prognostic
Prognostic of clinical liver related outcomes and cardiovascular outcomes2,9,16
Easy-To-Read Reports
Delivers intuitive, and visually rich reports
Increases understanding and patient engagement5
Andersson A, et al. | Clinical Utility of MRI Biomarkers for Identifying NASH Patients at High Risk of Progression: A Multicenter Pooled Data and Meta-Analysis | Clinical Gastroenterology and Hepatology (2022)
Jayaswal ANA, et al. | Prognostic value of multiparametric MRI, transient elastography and blood-based fibrosis markers in patients with chronic liver disease | Liver International (2020)
Imajo K, et al. | Quantitative multiparametric MRI can aid NASH diagnosis in a Japanese cohort | World J. Gastroenterol. (2021)
Beyer C, et al. | Comparison between MR and ultrasound-derived indicators of hepatic steatosis in a pooled NAFLD cohort | PLoS One (2021)
McKay A, et al. | Patient understanding and experience of non-invasive imaging diagnostic techniques and the liver patient pathway | J. Patient. Rep. Outcomes (2021)
Banerjee R, et al. | Multiparametric MR for the non-invasive diagnosis of liver disease | J. Hepatol. (2014)
Bassett ML, Halliday JW, Powell LW | Value of Hepatic Iron Measurements in Early Hemochromatosis and Determination of the Critical Iron Level Associated With Fibrosis | Hepatology (1986)
Heneghan MA, et al. | Quantitative MRI to aid clinical decision making in autoimmune hepatitis | EClinicalMedicine (2022)
Roca-Fernandez A, et al. | Liver disease is a significant risk factor for cardiovascular outcomes – A UK Biobank study | J. Hepatol. (2023)
Alkhouri N, et al. | Decreases in cT1 and liver fat content reflect treatment-induced histological improvements in MASH | J. Hepatol. (2025)
Beyer C, et al. | Quantitative MRI for Monitoring MASLD: A Test–Retest Repeatability Study | Journal of Magnetic Resonance Imaging (2025)
Dennis A, et al. | Correlations Between MRI Biomarkers PDFF and cT1 With Histopathological Features of NASH | Front. Endocrinol. (2021)
Harrison SA, et al. | Effect of pemvidutide, a GLP-1/glucagon dual receptor agonist, on MASLD: A randomized, double-blind, placebo-controlled study | J. Hepatol. (2025)
Rohit L, et al. | Tirzepatide for MASH with Liver Fibrosis | New England Journal of Medicine (2024)
Andersson A, et al. | Change in cT1 Following Interventions in MASLD: A Systematic Review and Meta-Analysis | Clinical Gastroenterology and Hepatology (2026)
Jackson E, et al. | Cardiac and liver impairment on multiorgan MRI and risk of major adverse cardiovascular and liver events | Nat. Med. (2025)
A non-invasive MRI solution that provides 3D visualization alongside precise quantitative assessment of the biliary system1,2 to aid healthcare professionals in the diagnosis and monitoring of diseases that affect the pancreatobiliary system3–7
Biliary Tree Volume (mL)1,2
Maximum Common Bile Duct Diameter (mm)1
Total Number of Ducts, Strictures, Dilatations & Ducts with Stricture OR Dilatation1,2
Percent of Ducts with Median Width greater than 3mm up to 5mm (%)1,6
Repeatable Monitoring
Precise metrics enable reliable monitoring of disease1,2
Clinically Meaningful
Provides quantitative metrics unavailable from standard MRCP1,2,7
MRCP+ metrics are reliable and outperformed standard MRCP3
Prognostic
Demonstrated strong prognostic value in PSC4,5,6
Enhanced Visualization
Enhances MRCP data to support diagnostic decisions3,8,9,10
Enhanced visualization of the pancreatobiliary tree including heat mapping of duct diameters1,2
Goldfinger MH, et al. | Quantitative MRCP Imaging: Accuracy, Repeatability, Reproducibility, and Cohort-Derived Normative Ranges | Journal of Magnetic Resonance Imaging (2020)
Harisinghani M, et al. | Accuracy, repeatability, reproducibility and reference ranges of primary sclerosing cholangitis specific biomarkers from quantitative MRCP | Abdominal Radiology (2025)
Selvaraj EA, et al. | A Quantitative MRCP Metric of Intrahepatic Biliary Dilatation Severity Detects High-Risk Primary Sclerosing Cholangitis | Hepatol Commun (2022)
Vuppalanchi V, et al. | A Composite score using quantitative MRCP predicts clinical outcomes in primary sclerosing cholangitis | JHEP Reports (2023)
Cristoferi L, et al. | A quantitative MRCP-derived score for medium-term outcome prediction in primary sclerosing cholangitis | Dig Liver Dis (2022)
Cazzagon N, et al. | Quantitative MRCP metrics are associated with disease severity and outcomes in people with primary sclerosing cholangitis | JHEP Rep (2022)
Trivedi PJ, et al. | Quantitative MRCP and metrics of bile duct disease over time in patients with primary sclerosing cholangitis: A prospective study | Aliment Pharmacol Ther (2024)
Mahalingam N, et al. | Associations between MRI T1 mapping, liver stiffness, quantitative MRCP, and laboratory biomarkers in children and young adults with autoimmune liver disease | Abdominal Radiology (2022)
Janowski K, et al. | Quantitative multiparametric MRI as a non-invasive stratification tool in children and adolescents with autoimmune liver disease | Scientific Reports (2021)
Gilligan LA, et al. | Differentiating pediatric autoimmune liver diseases by quantitative MRCP | Abdominal Radiology (2020)
A non-invasive, quantitative assessment of liver disease activity, liver fat, and liver volume on the global and individual Couinaud segment levels; allowing accurate prediction of the health and volume of the post-surgical future liver remnant1
Provides quantitative biomarkers of liver health and volume on the global and individual Couinaud segment levels2
Liver Disease Activity (cT1)
Liver Fat Fraction (PDFF)
Volumetry
Risk-Assessment
Supports in identifying patients at risk of poor outcomes who would benefit from more conservative treatments3
May help improve overall outcomes and reduce post-operative hospital stays3
Intervention Monitoring
Assess the success of intermediate procedures such as parenchymal sparing techniques5
Pre-Surgical Planning
Supports estimation of the health and volume of the future liver remnant (FLR)
Gives confidence to perform more radical curative procedures4,5
Seamless Integration
Seamless integration into standard imaging workflow for pre-surgical planning
Welsh F, et al. | Precision medicine for liver tumours with quantitative MRI and whole genome sequencing (Precision1 trial): study protocol for observational cohort study | BMJ Open (2022)
Mojtahed A, et al. | Repeatability and reproducibility of deep-learning-based liver volume and Couinaud segment volume measurement tool | Abdominal Radiology (2021)
Mole DJ, et al. | Magnetic resonance imaging predicts individual future liver performance after liver resection for cancer | PLOS ONE (2020)
Sethi P, et al. | Quantitative multiparametric MRI allows safe surgical planning in patients undergoing liver resection for colorectal liver metastases: report of two patients | BJR Case Reports (2021)
Sundaravadanan S, et al. | Novel multiparametric MRI detects improved future liver remnant quality post-dual vein embolization | (2024)
CoverScan is a non-invasive, multi-organ MRI solution that assesses six key organs (heart, lungs, liver, kidneys, spleen, and pancreas) in a single scan without the need for contrast agents. It provides a comprehensive and intuitive report that detects organ abnormalities, enabling personalized treatment and optimized patient care.1,22,23,25,26
Heart2,3,4,13,14,15,24
Cardiac function
Atrial and ventricular measurements
Strain
T1 & T2 Mapping
Abdominal & Ascending Aorta
Lungs23
Fractional Area Change
Liver16,17,18,19,20,21
cT1, fat & liver iron concentration
Kidney5,6,7,8
Cortical T1 & length
Pancreas9,10,11,12
srT1 & fat
Spleen23
Length
Key Benefits
Early detection & patient stratification: identifies organ damage early to enable personalized treatments and optimized care pathways1
Identifies and monitors multi-organ impairment23,26
Rationalized imaging pathway to avoid additional testing. Fewer patient visits and quicker diagnosis to prevent progression to chronic disease or hospitalisation24,26,27
Time to diagnosis is days
CoverScan improves coordinated patient care to allow early detection of organ abnormalities and prevent further damage17,23,24,26
Reed S, et al. | Multi-organ abnormalities assessed by a single MRI scan in individuals with blood cancer | European Journal of Internal Medicine (2024)
Bull S, et al. | Human non-contrast T1 values and correlation with histology in diffuse fibrosis | Heart (2013)
Ferreira VM, et al. | Native T1-mapping detects the location, extent and patterns of acute myocarditis without the need for gadolinium contrast agents | Journal of Cardiovascular Magnetic Resonance (2014)
Messroghli DR, et al. | Clinical recommendations for cardiovascular magnetic resonance mapping of T1, T2, T2* and extracellular volume: A consensus statement by SCMR endorsed by EACVI | Journal of Cardiovascular Magnetic Resonance (2017)
Buchanan CE, et al. | Quantitative assessment of renal structural and functional changes in chronic kidney disease using multi-parametric MRI | Nephrology Dialysis Transplantation (2020)
Berchtold L, et al. | Validation of the corticomedullary difference in MRI-derived apparent diffusion coefficient for kidney fibrosis detection: a cross-sectional study | Nephrology, Dialysis, Transplantation (2020)
Makvandi K, et al. | Multiparametric MRI allows non-invasive functional and structural evaluation of diabetic kidney disease | Clinical Kidney Journal (2022)
Graham-Brown MP, et al. | Association between native T1 mapping of the kidney and renal fibrosis in patients with IgA nephropathy | BMC Nephrology (2019)
Zhu L, et al. | Native T1 mapping of autoimmune pancreatitis as a quantitative outcome surrogate | European Radiology (2019)
Wang L, et al. | Multiparametric Mapping MRI of Pancreatic Disease | Frontiers in Physiology (2020)
Liu C, et al. | Evaluation of Pancreatic Fibrosis Grading by Multiparametric Quantitative MRI | Journal of Magnetic Resonance Imaging (2021)
Ashihara N, et al. | Correlation of Pancreatic T1 Values Using Modified Look-Locker Inversion Recovery Sequence (MOLLI) with Pancreatic Exocrine and Endocrine Function | Journal of Clinical Medicine (2020)
Fontana M, et al. | Native T1 mapping in ATTR cardiac amyloidosis – comparison with AL cardiac amyloidosis – a 200 patient study | Journal of Cardiovascular Magnetic Resonance (2014)
Dass S, et al. | Myocardial Tissue Characterization Using MR Noncontrast T1 Mapping in Hypertrophic and Dilated Cardiomyopathy | Circulation: Cardiovascular Imaging (2012)
Piechnik SK, et al. | Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold | Journal of Cardiovascular Magnetic Resonance (2010)
Dennis A, et al. | Correlations Between MRI Biomarkers PDFF and cT1 With Histopathological Features of NASH | Frontiers in Endocrinology (2021)
Roca-Fernandez A, et al. | Liver disease is a significant risk factor for cardiovascular outcomes – A UK Biobank study | Journal of Hepatology (2023)
Jayaswal ANA, et al. | Prognostic value of multiparametric MRI, transient elastography and blood-based fibrosis markers in patients with chronic liver disease | Liver International (2020)
Andersson A, et al. | Clinical Utility of MRI Biomarkers for Identifying NASH Patients at High Risk of Progression: A Multicenter Pooled Data and Meta-Analysis | Clinical Gastroenterology and Hepatology (2022)
Bachtiar V, et al. | Repeatability and reproducibility of multiparametric MRI of the liver | PLoS One (2019)
Harrison SA, et al. | NGM282 Improves Liver Fibrosis and Histology in 12 Weeks in Patients With NASH | Hepatology (2020)
Diamond C, et al. | Quantitative imaging reveals steatosis and fibro-inflammation in multiple organs in people with type 2 diabetes: a real-world study | Diabetes (2024)
Dennis A, et al. | Multi-organ impairment and long COVID: a 1-year prospective, longitudinal cohort study | Journal of the Royal Society of Medicine (2023)
Jackson E, et al. | Cardiac and liver impairment on multiorgan MRI and risk of major adverse cardiovascular and liver events | Nature Medicine (2025)
Bradley CR, et al. | Multi-organ assessment of compensated cirrhosis patients using quantitative MRI | Journal of Hepatology (2018)
Roca-Fernandez A, et al. | Cardiac abnormalities in Long COVID 1-year post-SARS-CoV-2 infection | Open Heart (2023)
Roca-Fernández A, et al. | Hepatic Steatosis, Rather Than Underlying Obesity, Increases the Risk of Infection and Hospitalization for COVID-19 | Frontiers in Medicine (2021)
Our Body Composition is a fast, non-invasive MRI add-on for body composition assessment, requiring only one 12-second breath-hold. It seamlessly integrates with any MRI protocol, providing quantitative measurements of fat and muscle in a visually engaging report to support metabolic health, weight management, and sarcopenia assessment.1,2,3,4
Quantitative measurements
Visceral Adipose Tissue (VAT)4–10
Subcutaneous Adipose Tissue (SAT)11
VAT/SAT ratio
Skeletal muscle12–18
Psoas muscle19–22
Fast & Efficient
Requires only one breath-hold (12 seconds) for scanning1,2,3,4
Comprehensive Body Composition Analysis
Measures visceral and subcutaneous adipose tissue and skeletal muscle1,2,3,4
Clinically Relevant Insights
Supports the management of weight loss, sarcopenia, and metabolic health1,2,4
BodyComp provided critical insights into sarcopenic obesity, enabling tailored interventions1,2
Nowak M, et al. | Repeatability, reproducibility, and observer variability of body composition assessment with single-slice lumbar MRI | Discover Imaging (2025)
Nowak M, et al. | Automated volumetric MRI quantification of body fat and skeletal muscle in the UK Biobank: technical validation against expert manual segmentations and comparison with single-slice techniques | Abdominal Radiology (2026)
Nowak M, et al. | Weight-related changes in MRI-derived measures of body composition and liver steatosis: a large-scale analysis for obesity trial design | International Journal of Obesity (2026)
Waddell T, et al. | Greater ectopic fat deposition and liver fibroinflammation, and lower skeletal muscle mass in people with type 2 diabetes | Obesity (2022)
Kranendonk MEG, et al. | Inflammatory characteristics of distinct abdominal adipose tissue depots relate differently to metabolic risk factors for cardiovascular disease | Atherosclerosis (2015)
Verkouter I, et al. | Adult weight change in relation to visceral fat and liver fat at middle age: The Netherlands epidemiology of obesity study | International Journal of Obesity (2018)
Bamberg F, et al. | Subclinical Disease Burden as Assessed by Whole-Body MRI in Subjects With Prediabetes, Subjects With Diabetes, and Normal Control Subjects From the General Population: The KORA-MRI Study | Diabetes (2016)
Miyazaki Y, et al. | Effect of pioglitazone on abdominal fat distribution and insulin sensitivity in type 2 diabetic patients | The Journal of Clinical Endocrinology and Metabolism (2002)
Linge J, et al. | Body Composition Profiling in the UK Biobank Imaging Study | Obesity (2018)
Stefan N | Causes, consequences, and treatment of metabolically unhealthy fat distribution | The Lancet Diabetes & Endocrinology (2020)
van den Munckhof ICL, et al. | Sex-specific association of visceral and subcutaneous adipose tissue volumes with systemic inflammation and innate immune cells in people living with obesity | International Journal of Obesity (2023)
Nachit M, et al. | AI-based CT Body Composition Identifies Myosteatosis as Key Mortality Predictor in Asymptomatic Adults | Radiology (2023)
Hirani V, et al. | Longitudinal associations between body composition, sarcopenic obesity and outcomes of frailty, disability, institutionalisation and mortality in community-dwelling older men: The Concord Health and Ageing in Men Project | Age and Ageing (2016)
Jauffret C, et al. | Association Between Sarcopenia and Fracture Risk in a Population From the UK Biobank Database | Journal of Bone and Mineral Research (2023)
Knowles R, et al. | Associations of Skeletal Muscle Mass and Fat Mass With Incident Cardiovascular Disease and All-Cause Mortality: A Prospective Cohort Study of UK Biobank Participants | Journal of the American Heart Association (2021)
Wang H, et al. | Skeletal Muscle Mass as a Mortality Predictor among Nonagenarians and Centenarians: A Prospective Cohort Study | Scientific Reports (2019)
Wilkinson TJ, et al. | Association of sarcopenia with mortality and end-stage renal disease in those with chronic kidney disease: a UK Biobank study | Journal of Cachexia, Sarcopenia and Muscle (2021)
Wei L, et al. | Associations between handgrip strength and skeletal muscle mass with all-cause mortality and cardiovascular mortality in people with type 2 diabetes: A prospective cohort study of the UK Biobank | Journal of Diabetes (2023)
Cankurtaran RE, et al. | Sarcopenia and Myosteatosis Assessed by Magnetic Resonance Enterography May Predict Negative Outcomes in Patients with Crohn’s Disease | Turkish Journal of Gastroenterology (2023)
Han Y-A, et al. | Impact of Sarcopenia on Percutaneous Epidural Balloon Neuroplasty in Patients with Lumbar Spinal Stenosis: A Retrospective Analysis | Medicina (2023)
Wu C-H | Effects of transjugular intrahepatic portosystemic shunt on abdominal muscle mass in patients with decompensated cirrhosis | Journal of the Formosan Medical Association (2023)
Paternostro R, et al. | Prognostic impact of sarcopenia in cirrhotic patients stratified by different severity of portal hypertension | Liver International (2020)