MASLD: What We Have Learned and Where We Need to Go-A Call to Action

Abstract

Since its introduction in 1980, fatty liver disease (now termed metabolic dysfunction-associated steatotic liver disease [MASLD]) has grown in prevalence significantly, paralleling the rise of obesity worldwide. While MASLD has been the subject of extensive research leading to significant progress in the understanding of its pathophysiology and progression factors, several gaps in knowledge remain. In this pictorial review, the authors present the latest insights into MASLD, covering its recent nomenclature change, spectrum of disease, epidemiology, morbidity, and mortality. The authors also discuss current qualitative and quantitative imaging methods for assessing and monitoring MASLD. Last, they propose six unsolved challenges in MASLD assessment, which they term the proliferation, reproducibility, reporting, needle-in-the-haystack, availability, and knowledge problems. These challenges offer opportunities for the radiology community to proactively contribute to their resolution. The authors conclude with a call to action for the entire radiology community to claim a seat at the table, collaborate with other societies, and commit to advancing the development, validation, dissemination, and accessibility of the imaging technologies required to combat the looming health care crisis of MASLD.

Graphical abstract

Figure 1.

History of MASLD literature. Graph shows the number of NAFLD (MASLD) publications per year from 1980 to 2023. Those highlighted are the first publication to describe NAFLD in 1980 (four authors from one institution) and the consensus paper in 2023 announcing the new MASLD nomenclature (236 contributors from 56 countries and representing seven scientific societies). (Embedded maps created with and adapted and reprinted under a CC BY-SA 4.0 license from MapChart [https://www.mapchart.net/].)

Figure 2.

SLD nomenclature. Steatotic liver disease is an umbrella term that encompasses various disorders associated with excess fat accumulation in the liver, including MASLD and MASLD with increased alcohol intake (MetALD). Although MASLD can coexist with other causes of SLD such as viral hepatitis, this article focuses on MASLD in the absence of other steatogenic conditions. (Reprinted under a CC BY-NC-ND license from reference .)

Figure 3.

MASLD cardiometabolic diagnostic criteria. ALD = alcohol-associated/related liver disease, BMI = body mass index, BP = blood pressure, CMRF = cardiometabolic risk factors, DILI = drug-induced liver disease, F = female, HbA1c = hemoglobin A_1c, HDL = high-density lipoprotein, M = male, WC = waist circumference. (Reprinted under a CC BY-NC-ND license from reference .)

Figure 4.

MASLD spectrum. Conventional histologic images show steatosis with fat droplets within hepatocytes (*), steatohepatitis with ballooned hepatocytes (B), early-stage fibrotic liver with pericellular fibrosis (black arrow), and cirrhotic liver with fibrotic scars (yellow arrow) surrounding a regenerative nodule (N). MASL refers to steatosis without inflammation or cell injury. MASH refers to steatosis with inflammation and cell injury. Fibrosis refers to excess collagen deposition in the extracellular matrix and is a marker of cumulative liver damage. Cirrhosis is a late stage of disease in which fibrotic scars have carved the liver into regenerative nodules. At-risk MASH is defined by the combination of MASH, an NAFLD activity score of 4 or greater, and a fibrosis score of 2 or greater. NAFLD activity score is the sum of the steatosis grade (0–3), lobular inflammation grade (0–3), and ballooning score (0–2). (Hematoxylin-eosin stain [two left images] and trichrome stain [two right images].)

Figure 5.

Prevalence of MASLD, MASH, and at-risk MASH. Diagram shows the prevalence of the MASLD spectrum in the general population (left) and in patients with MASLD (right).

Figure 6.

MASLD prevalence worldwide. South and Central America has the highest prevalence of MASLD (44%) and western Europe has the lowest (25%) (10). (Map created with and adapted and reprinted under a CC BY-SA 4.0 license from MapChart [https://www.mapchart.net/].)

Figure 7.

MASLD estimated annual percentage change worldwide. The four areas with the highest rate of increase are Oman (2.1%), Finland (1.7%), Equatorial Guinea (1.7%), and Nicaragua (1.6%). There are no areas in which the prevalence is decreasing. (Adapted and reprinted under a CC BY-NC 4.0 license from reference . Map created with and adapted and reprinted under a CC BY-SA 4.0 license from MapChart [https://www.mapchart.net/].)

Figure 8.

Liver and systemic MASLD outcomes. Patients with at-risk MASH have the highest likelihood of developing liver-related outcomes (left), while all patients with MASLD have an increased likelihood for developing systemic outcomes (right).

Figure 9.

Survival is worse with development of hepatic fibrosis. Graph demonstrates all-cause (total) and liver-related (brown) mortality rates by hepatic fibrosis stage (7). As fibrosis stage increases, both liver and nonliver-related mortality rates increase. Note that nonliver-related mortality exceeds liver-related mortality at every stage until stage 4 (cirrhosis), when nonliver and liver-related mortality rates are about the same. PYF = patient years of follow-up.

Figure 10.

MASLD is an integral component of metabolic syndrome, as shown on the diagram. Note the complex bidirectional relationships between all components of metabolic syndrome, including MASLD.

Figure 11.

Chart shows conventional US images for SLD in four different pediatric patients (each column shows images in one patient), each with three B-mode US views. The corresponding PDFF percentage value for each patient’s liver is noted in the last row. In all three cases with steatosis, the liver is brighter than the kidney and there is blurring of the vessels. While qualitative assessment of B-mode US images can help identify patients with steatosis, it cannot discriminate the severity of steatosis. Bunny = bunny waveform.

Figure 12.

SLD by noncontrast CT in a 66-year-old man. Axial noncontrast CT image shows the liver with attenuation of 20.7 HU and the spleen with attenuation of 43.6 HU. Note that the vessels appear to have more attenuation than the liver due to elevated fat deposition within the liver tissue. In extreme cases, the vessels may appear so bright compared with the liver that it can resemble a contrast-enhanced image.

Figure 13.

SLD by conventional MRI in a 59-year-old woman. Axial out-of-phase MR image (left) shows that the liver is hypointense compared with the liver on the in-phase MR image (right). Note that fat deposition is heterogeneous throughout the liver.

Figure 14.

Identification and management of at-risk MASH with FIB-4. Flowchart shows how patients with MASLD should be categorized and where they should follow up according to the FIB-4 score (41).

Figure 15.

Quantitative imaging biomarkers for the MASLD spectrum. On the MR elastographic images, the dashed white lines outline the liver. Classification of “clinical” or “investigational” reflects how these modalities are used at the authors’ institutions.

Figure 16.

MRI for assessment of hepatic steatosis and fibrosis in a 48-year-old woman with biopsy-proven nonfibrotic MASH. Axial MRI PDFF map (left) shows a fat fraction of 31.9%, and the axial two-dimensional (2D) MR elastography (MRE) stiffness map (right) shows a stiffness of 2.0 kPa. Note the visibility of the hepatic vessels on the MRI PDFF map due to elevated fat deposition within the liver. Cardiometabolic factors for MASLD diagnosis included elevated body mass index (39.8 kg/m²), elevated hemoglobin A1c levels, and hypertriglyceridemia. The patient’s alcohol use was less than one drink per week. Serum asparate aminotransferase (AST) and alanine aminotransferase (ALT) levels were elevated, and the FIB-4 score was 0.90.

Figure 17.

MRI for assessment of hepatic steatosis and fibrosis in a 60-year-old woman with biopsy-proven at-risk MASH. Axial MRI PDFF map (left) shows a fat fraction of 12%, and axial 2D MRE stiffness map (right) shows a stiffness of 3.4 kPa. Cardiometabolic factors for MASLD diagnosis included elevated body mass index (26.9 kg/m²) and elevated fasting blood glucose levels. The patient’s alcohol use was less than one drink per week. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels were elevated, and the FIB-4 score was 2.0. Note that as fibrosis increases, steatosis can decrease (compared with Figure 16).

Figure 18.

Proliferation problem. Word cloud illustration shows the conglomeration of circulating- (orange), imaging- (black), and “-omics”- (brown) based diagnostic tests currently available for MASLD. In this figure, -omics refers to genomics, proteomics, metabolomics, and lipidomics. Radiomics are considered imaging biomarkers for the purpose of this figure. (Reprinted with permission from and generated using Wordclouds.com [https://www.wordclouds.com/].)

Figure 19.

Reproducibility problem. Reproducibility plots on the left show poor agreement among US vendors for measuring the same US-based biomarkers in adults with known or suspected MASLD (left) including attenuation coefficient (AC) (top left) and shear wave speed (bottom left) in a study by Pierce et al (65). Different colors correspond to paired comparison of values achieved from two different vendors for the same research participants. For AC, four leading vendors were compared, with an intraclass correlation coefficient (ICC) ranging from -0.04 to 0.49. For shear wave speed, five leading vendors were compared, with an ICC ranging from -0.09 to 0.68. For comparison, reproducibility plots on the right show good agreement among MRI vendors for measuring MRI-based biomarkers in adults with known or suspected MASLD including PDFF (top right) and two-dimensional (2D) MRE stiffness (bottom right) in a study by Fowler et al (64). For PDFF, three leading vendors were compared at two field strengths (3 T and 1.5 T), with ICC ranging from 0.97 to 0.98. For 2D MRE stiffness, three leading vendors were compared at two field strengths (3 T and 1.5 T), with ICC ranging from 0.96 to 0.99. Perfect agreement would be ICC of 1.0.

Figure 20.

Proportion of HCC attributable to MASLD worldwide. India has the highest proportion of HCC attributable to MASLD (38%) and China has the lowest (1%) (70). (Map created with and adapted and reprinted under a CC BY-SA 4.0 license from MapChart [https://www.mapchart.net/].)

Figure 21.

In about one-third of HCC cases attributed to MASLD, patients do not have cirrhosis. Charts show the attributable proportion of HCC in patients with MASLD (left) versus other liver diseases (eg, viral hepatitis, alcohol-associated liver disease) (right) (71,72).

Figure 22.

Availability problem chart. Multiple interrelated barriers reduce the use of imaging in the diagnosis and management of MASLD, spanning from individual to institutional and societal levels.

Figure 23.

Solutions to access and affordability barriers: point-of-care US and MRI. (A) Diagram shows point-of-care US with AI-assisted guidance for acquisition and AI-facilitated analysis of liver steatosis and fibrosis. QUS = quantitative US. (B) Illustration shows point-of-care MRI for liver PDFF measurement.

Figure 24.

Solutions to site technology barrier: AI-derived liver fat and stiffness measurements obtained from other sequences. Diagram shows examples of AI-derived PDFF measurements from in-phase (IP) and out-of-phase (OP) MR images (top row) and AI-derived stiffness measurements from conventional MR images (T1- and T2-weighted MR images shown) (bottom row).

Figure 25.

Solutions to site experience barrier: automated PDFF and MRE analysis. Axial images show liver fat (outlines) PDFF (left) and liver stiffness from MRE (right) analyzed automatically from PDFF and MRE stiffness maps, respectively. IQR = interquartile range, ROI = region of interest. (Image courtesy of Richard Ehman, MD, Mayo Clinic, Rochester, Minnesota, and Resoundant.)

Figure 26.

Solutions to patient tolerance barrier: motion-robust PDFF acquisitions to enable free breathing. A child with MASLD was unable to hold their breath during a 15-second conventional PDFF acquisition (left). Repeat PDFF was performed using an investigational motion-robust sequence during free breathing (right). Image degradation by motion artifact on the axial conventional PDFF image is substantially improved on the axial motion-robust image.

Figure 27.

Historical exclusion of radiologists and radiology societies from MASLD clinical practice guidelines and clinical consensus statements. Four hundred and fifty-nine unique authors have contributed to 30 clinical practice consensus statements since 2010. Only two were radiologists. No radiology society participated. NIH = National Institutes of Health.

Figure 28.

A call to action: moving forward, more active integration by the house of radiology with efforts by existing stakeholders is needed to advance the development, validation, dissemination, and accessibility of the technologies to improve clinical practice and research in MASLD.