This Is What Metabolic Dysfunction–Associated Steatotic Liver Disease Looks Like: Potential of a Multiparametric MRI Protocol

Abstract

Metabolic dysfunction–associated steatotic liver disease (MASLD) is a prevalent condition with a broad spectrum defined by liver biopsy. This gold standard method evaluates three features: steatosis, activity (ballooning and lobular inflammation), and fibrosis, attributing them to certain grades or stages using a semiquantitative scoring system. However, liver biopsy is subject to numerous restrictions, creating an unmet need for a reliable and reproducible method for MASLD assessment, grading, and staging. Noninvasive imaging modalities, such as magnetic resonance imaging (MRI), offer the potential to assess quantitative liver parameters. This review aims to provide an overview of the available MRI techniques for the three criteria evaluated individually by liver histology. Here, we discuss the possibility of combining multiple MRI parameters to replace liver biopsy with a holistic, multiparametric MRI protocol. In conclusion, the development and implementation of such an approach could significantly improve the diagnosis and management of MASLD, reducing the need for invasive procedures and paving the way for more personalized treatment strategies.

 

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Keywords

metabolic dysfunction–associated steatotic liver disease - magnetic resonance imaging - noninvasive tests - liver stiffness - hepatocyte function

The rise of metabolic dysfunction–associated steatotic liver disease (MASLD) globally demands urgent attention and innovative diagnostic approaches to combat its progression and devastating consequences.[1] This surge in MASLD, and its more severe form, metabolic dysfunction–associated steatohepatitis (MASH), is closely linked to the escalating rates of obesity, type 2 diabetes, and metabolic syndrome, further complicated by genetic factors.[2] [3] [4] [5] [6] [7] Moreover, the progressive fibrosis in advanced MASH can lead to cirrhosis and the development of other severe outcomes including hepatocellular carcinoma and portal hypertension.[8] [9] To effectively address this growing health concern, it is crucial to gain a comprehensive understanding of the pathogenesis of MASLD and MASH, as this knowledge will pave the way for the development of novel and targeted treatments. Clinical imaging plays a vital role in elucidating the underlying mechanisms of this disease, enabling researchers and clinicians to identify potential therapeutic targets and monitor treatment efficacy. By focusing on the intricate interplay between disease pathogenesis and innovative diagnostic techniques, the medical community can work toward more effective strategies to manage and ultimately conquer these prevalent and potentially life-threatening liver diseases.

While the disease processes of MASLD/MASH have many systemic manifestations, the ultimate diagnosis relies on a histologic description of a biopsy sample. This assessment is commonly performed using three main semiquantitative scores: steatosis, activity (ballooning and lobular inflammation), and fibrosis.[10] [11] Although considered the “gold standard,” this approach has limitations due to the invasiveness of the procedure, small specimen volume (approximately 1/50,000 of the liver[12]), and the semiquantitative nature of the assessment.[13] These factors contribute to the low agreement rate of paired biopsy samples and complicate diagnosis and the determination of endpoints in late-stage MASH-related clinical trials.[14] [15] [16]

To address these challenges, the United States Food and Drug Administration (FDA) recommends integrating and evaluating noninvasive biomarkers, including clinical imaging biomarkers.[17] [18] Magnetic resonance imaging (MRI) is emerging as a popular choice among imaging techniques due to its versatility and accuracy. However, while histology assesses multiple pathologic features of MASLD (steatosis, activity, and fibrosis), noninvasive imaging techniques are typically limited to assessing one feature at a time. Thus, it is crucial to match the appropriate imaging method with the specific question and location within the MASLD spectrum.

This review aims to provide an overview of available MRI techniques relating to the three histologic features of MASLD, as described earlier and summarized in [Table 1]. MRI offers a diverse array of methodologies, from widely accepted MRI fat quantification (proton density fat fraction [PDFF]) and measurement of the longitudinal relaxation time (T₁) to more exploratory approaches like gadoxetate-based methods. While these acquisition techniques are preinstalled on most clinical scanners, the MRI portfolio is complemented by commercial MRI products, including hardware devices and software imaging analysis methods. For example, magnetic resonance elastography (MRE) enables the assessment of mechanical tissue parameters and requires secondary hardware and the proprietary iron-corrected T₁ (cT₁) method which corrects iron-induced bias and standardizes across scanners and field strengths. In this article, we will discuss these techniques and their applications in greater detail for each disease manifestation. Lastly, we will emphasize the importance of combining multiple methods to capture a comprehensive picture of MASLD and propose a multiparametric MRI acquisition protocol.

Table 1 MRI methods for evaluation of MASLD

	MRI-PDFF	MRE	Gadoxetate	(c)T1
Description	Relative measure of MR signal originating from triglycerides	Supplemental device that allows the measurement of tissue mechanical properties	Contrast agent that is actively taken up by healthy hepatocytes	MR signal property sensitive to changes in extracellular water
Measurements	Fat fraction (fat/(fat and water))	Tissue mechanical properties	Hepatocyte function	Extracellular water
Assessed MASLD feature(s)	Steatosis, ballooning	Fibrosis, inflammation	Fibrosis, inflammation, hepatocyte function	Fibrosis, inflammation
Strengths	Full organ coverage, accepted/validated biomarker for liver steatosis	Full organ coverage, diagnostic accuracy	Full organ coverage, measure of liver function	Full organ coverage
Challenges	Additional vendor packages required (cost and availability)	Additional hardware required (cost and availability), confounded by  • Edema  • Iron (mainly at 3T)	Contrast injection, exploratory, complex, advanced mathematical model required for dynamic imaging	Confounded by  • Fat load  • Iron (only T1)  • Hydration  • Glycogen  • Edema cT1: patented commercial product (cost and availability)
Opportunities	Differentiation of abdominal adipose tissue compartments and fatty acid composition	Combination with circulating biomarkers, extraction of different measures, 3D MRE, indication for portal hypertension derivable when extending MRE to the spleen	Assessment of liver function, multiple physiological parameters accessible with compartmental analysis, simultaneous screening for hepatocellular carcinomas	Bridging the gap between PDFF and MRE, assessment of inflammatory status of (visceral) adipose tissue

Abbreviations: cT₁, iron-corrected T₁; MASLD, metabolic dysfunction–associated steatotic liver disease; MRE, magnetic resonance elastography; MRI, magnetic resonance imaging; PDFF, proton density fat fraction; T₁, longitudinal relaxation time.

Assessment of Steatosis

The primary characteristic and defining feature of MASLD is the accumulation of triglycerides as fat droplets within hepatocytes. These fatty acids originate from various sources, including serum nonesterified fatty acids (59%), de novo lipogenesis (26%), and dietary fatty acids (15%).[19] [20] Fat droplets can be classified as either microvesicular or macrovesicular steatosis based on their size. In MASLD, macrovesicular steatosis is the predominant pattern, characterized by medium to large fat droplets and the displacement of the hepatocyte nucleus to the periphery.[11] [19] [21] To diagnose MASLD, at least 5% of hepatocytes must exhibit fatty acid accumulation in the form of macrovesicular steatosis.[21]

MRI-PDFF

The signal accessible using conventional ¹H MRI almost exclusively originates from the hydrogen nuclei of either triglycerides or water and the chemical structure of these molecules is characterized by distinct magnetic resonance (MR) frequencies. It was recognized early on that magnetic resonance spectroscopy (MRS) could quantify the proportion of fat molecules relative to the sum of water and fat molecules. However, while MRS shows excellent accuracy and sensitivity for the assessment of fat content and allows for further characterization of the lipids, it is a complicated procedure with limited coverage and is not available in all clinical centers. Hence, researchers devised sophisticated techniques such as multi-echo Dixon methods and advanced fat water separation algorithms, specifically the Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL). These methods have proven effective in achieving robust fat–water separation, eliminating the T₁ or T₂* bias that can affect quantification. This IDEAL-PDFF technique shows excellent performance compared to MRS across magnetic field strengths, MRI manufacturers and reconstruction methods,[22] and a high level of concordance with liver biopsy in multiple studies.[18] [23] [24] [25] [26] [27] A meta-analysis of the published data reveals the greatest combined sensitivity (0.92) and specificity (0.95) of MRI-PDFF in distinguishing steatosis at stage 1 or above, determined histologically, from no steatosis. The reduced sensitivity in detecting more advanced stages aligns with a recent study examining the discrepancy between MRI-PDFF and histology.[28] Here, discrepancy was reported to be primarily due to MRI-PDFF underestimating the advanced stages reported by histology. Forest plots on sensitivity and specificity are summarized in [Fig. 1] for all steatosis stages. In addition to the overall high performance of MRI-PDFF, Noureddin et al reported a higher sensitivity to small, longitudinal changes in hepatic fat compared to liver biopsy.[29] These findings were attributed to the low reproducibility and the broad-grading categories associated with liver biopsy,[29] while a study on the repeatability of MRI-PDFF proposed a threshold of 1.2 to 1.6% to discern real change from measurement error.[30] Furthermore, the inter-reader agreement of MRI-PDFF (ICC = 0.998–0.996)[31] outperforms liver biopsy (ICC = 0.654)[32] and ultrasonography-based methods for liver fat quantification. For these reasons, MRI-PDFF is widely accepted and even recommended for early clinical trials as primary efficacy endpoint especially in drugs suspected to have an antisteatotic effect.[33] FDA- and European Medicines Agency (EMA)-approved MRI sequences with CE-marked on-scanner reconstruction of the PDFF maps are provided for different vendors (GE, Philips, Siemens, and Canon) promoting MRI-PDFF as a widely available technique for precise and noninvasive hepatic steatosis assessment.

Fig. 1 (A, B) Forest plots of pooled diagnostic sensitivity and specificity for the prediction of different steatosis stages using MRI-PDFF. Data were processed using Met DiSc 2.0. MRI, magnetic resonance imaging; PDFF, proton density fat fraction.

The main advantage of MRI-PDFF over both biopsy and MRS is the whole organ coverage and the additional possibility for spatial assessment, enabling evaluation of heterogeneity within and between liver segments. The heterogeneity in this context necessitates a reliable and consistent segmentation process for extracting features. To address this, recent investigations focus on automated liver segmentation and processing of median PDFF.[25]

In addition to the spatial distribution, characterization of the spectral information might allow future advantages such as triglyceride differentiation. Due to its complex chemical structure (hydrogen atoms are residing at different sites in the molecule), the MR signal of triglycerides contains multiple MR frequencies, and the spectral frequency pattern can possibly be used to quantify the underlying fatty acid composition. Current techniques (i.e., IDEAL) predefine the fatty acid composition and ignore potential deviations, but different approaches are currently under investigation which provide additional information on the share of saturated, mono- and polyunsaturated fatty acids.[34] [35] [36] Since recent studies suggest an interdependence of the fatty acid composition and the severity of MASLD, linking severe phenotypes to an increased share of saturated fatty acids, the characterization of the triglyceride signal pattern might allow for patient segmentation or stratification.[37]

In conclusion, MRI-PDFF is a widely available and accepted method for the quantification of liver fat that still has the potential to generate additional characterization and benefit in the near future by application of new yet experimental postprocessing techniques.

 

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Assessment of Activity

Simple steatosis is the most common form of MASLD, and the majority of patients remain at this low end of the broad MASLD spectrum for several years. However, it has been reported that approximately one-third progresses to the more severe form of MASH.[2] [5] [38] In MASH, hepatocyte activity is disrupted due to the presence of inflammation and liver cell damage (hepatocyte ballooning). These factors can lead to impaired liver function and, in severe cases, progress to liver fibrosis, cirrhosis, or liver cancer.[20] [21] The inflammation and ballooning features are separately assessed by histology and are often collectively referred to as activity.[10] [11] [21]

Currently, the most challenging aspect of MASLD to evaluate using MRI is assessing activity.[39] At present, no specific approach is designed for differentiating activity grades; instead, existing techniques for steatosis and fibrosis assessment are extended to encompass this aspect of the disease. This is partly due to the simultaneous development and progression of various pathological features in hepatic tissue. Additionally, ballooning and inflammation have distinct effects on different MRI methods, making a combination of multiple techniques potentially the most promising approach for assessing activity.

MRI-PDFF to Assess Ballooning

Ballooning is the histologic term for swelling and rounding of the hepatocyte due to a manifestation of cell injury and altered accumulation of fat droplets.[40] Since MRI-PDFF is a measure of liver fat content, investigators have tried, with varying degrees of success, to link MRI-PDFF to ballooning grade. Although studies investigating the interplay of ballooning and MRI markers are sparse, some report a correlation of PDFF and histologic ballooning grade and changes thereof[41] [42] [43] while others do not find a correlation.[44] However, it must be emphasized that the status of liver biopsy as a reference is particularly questionable for this MASLD feature since inter-reader agreement is very low (ICC = 0.012)[32] and only moderate agreement can be obtained between paired liver biopsy samples.[14]

 

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MRE to Assess Inflammation

Elastography is the objective and quantitative evolution of palpation, which for many decades was the only opportunity to assess mechanical properties of abdominal organs. Nowadays, different imaging technologies quantitatively capture these features by accessing the propagation characteristics of shear waves in tissues. The most objective and reproducible among these techniques is MRE. Briefly, this approach uses a commercially available external driver to generate vibrations at 60 Hz and acquires complex MR raw data under application of an additional motion encoding gradient.[45] Since the speed of shear waves differs significantly across different types of soft tissues, this variation is used to distinguish between tissues and to assess pathophysiological changes.[46] The behavior of the shear waves is determined by the shear modulus which refers to the deformability of the tissue in response to shear stress. The magnitude of the shear modulus (shear stiffness) is the quantity most frequently assessed by MRE and is often also designated as stiffness. However, it represents the combined effect of two distinct material properties: elasticity and viscosity.[46] The former is attributable to the characteristics of solids and refers to a reversible deformation resulting in a storage of energy (storage modulus), while the latter is associated with the behavior of fluids and represents an irreversible deformation and dissipation of energy (loss modulus). Hepatic inflammation is associated with the accumulation of free fluids in the interhepatic space, which would, in theory, result in an alteration of shear stiffness due to a changed loss modulus (viscosity). While there is, therefore, great interest in the application of MRE for the assessment of inflammation, the shear stiffness in the liver is largely determined by the elasticity-related storage modulus component. Thus, changes in the shear modulus are strongly dominated by fibrotic processes. Hence, it is not surprising that while some studies demonstrate a correlation between inflammation status and shear modulus,[47] [48] [49] other studies do not.[50] In this context, hope is placed on the development of new three-dimensional (3D) MRE techniques which allow the separate assessment of the viscous tissue characteristics. For example, while there are limited data in the MASH population, a recent 3D MRE study of hepatitis B and C patients retrieved AUROCs of 0.86 to 0.90 for different stages of inflammation.[51] However, it must be noted that at this point, 3D MRE is still an experimental technique.

 

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MRI-PDFF and MRE—Yin and Yang of Activity Assessment?

Leveraging the described correlation of MRI-PDFF and hepatic ballooning, as well as inflammation and MRE, various studies have been conducted in both mice[48] and humans[41] [47] [52] combining these two techniques. This approach demonstrated increased performance in diagnosing MASH and assessing activity scores. The enhanced effectiveness can be attributed to the sensitivity of MRI-PDFF to hepatic ballooning and of MRE to lobular inflammation, which together define histology-based activity.[41] Consequently, MRI-PDFF and MRE can be viewed as two contrasting techniques that, when used in tandem, provide a holistic picture of hepatic activity.

 

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(c)T₁ and Gadoxetate—Alternatives to MRE for Inflammation Assessment?

Fluid in the interhepatic space impacts the relaxation behavior of the MR signal. In particular, T₁ increases with fluid content and has been associated with inflamed hepatic tissue. However, multiple other factors such as fibrosis, fat fraction, hydration, iron content, glucose, ascites, and edema impact this relaxation constant. Thus, the ambiguity of the results obtained by T₁ relaxometry in relation to inflammation grade assessed by histology is not surprising: while most studies report a positive correlation of T₁ and inflammation grade,[43] [50] [53] [54] some conclude no relation,[55] and one study in rats found a negative correlation.[56]

For these reasons, investigators have tried to quantify extracellular volume using contrast-enhanced MRI. In hepatic MRI, two classes of contrast agents are applied: extracellular and hepatobiliary contrast agents which differ regarding their pharmacokinetics.[57] While both initially accumulate in the extracellular space, hepatobiliary contrast agents (i.e., gadoxetate disodium) are subsequently in part actively taken up by healthy hepatocytes and excreted via the biliary system (the dual function of these contrast agents is described in more detail in the section on fibrosis). Based on a dynamic acquisition and a multicompartment model, insights on extracellular volume can be derived from gadoxetate-enhanced MRI.[58] However, this approach requires advanced mathematical models and is still experimental. There is interesting data that suggest an impact of steatohepatitis on the liver kinetics underlying hepatobiliary contrast agents,[59] [60] but currently there is a lack of information regarding the performance of this technique correlating extracellular volume and inflammation.

 

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Assessment of Fibrosis

Inflammation is a necessary component of healing processes.[61] However, in 20% of MASH patients, protracted wound healing of liver tissue eventually culminates in liver fibrosis.[20] [62] [63] [64] This accumulation of extracellular matrix proteins is the direct result of an imbalance of fibrogenesis and fibrolysis due to an uncompensated shift toward a reparative, anti-inflammatory immune response which is initiated by signaling from damaged or stressed hepatocytes and activated macrophages.[20] [62] [65] Given the close link of inflammation and fibrosis, it is not surprising that they are driven by comparable factors such as genetic predisposition and interaction with intestine and adipose tissue.[3] [62] [66] [67] [68] However, the severity of fibrosis rather than the degree of steatosis or activity predicts liver-related and overall morbidity and mortality in MASLD patients.[38] [69] For this reason, fibrosis is staged independently of activity based on location and amount of extracellular matrix proteins[10] [11] and noninvasive fibrosis biomarkers are also of interest for the prediction of liver-related outcomes. In summary, fibrosis describes the remodeling of hepatic tissue by extracellular matrix proteins—mainly type I/III collagen.[70]

MRE

The increasingly organized structure of the collagen fibers results in a reduction of the elasticity of the liver which dominates the storage modulus assessed by MRE. For this reason, MRE is considered the most promising MR technique to assess liver fibrosis. Standard clinical MRE generates two-dimensional elastograms representing the magnitude of the shear modulus which is used to calculate liver stiffness. Multiple studies applied this standardized approach to evaluate its performance to differentiate biopsy-accessed fibrosis stages.[18] [23] [27] [71] [72] [73] [74] [75] A meta-analyses based on the pooled data of these studies revealed the best performance for the detection of a fibrosis stage of 3 or above with a combined sensitivity of 0.86 and specificity of 0.90. The detection of at least fibrosis stage 1 yielded the lowest summary sensitivity (0.71) and a specificity of 0.88. A detailed overview of the results of the meta-analysis is provided in [Fig. 2]. Overall, the AUROC of MRE increases with advancing fibrosis and is reported to outperform ultrasonography-based techniques in advanced stages.[71] Furthermore, inter-reader agreement of MRE (ICC[71] = 0.948 and ICC[76] = 0.84) is higher than those acquired for vibration-controlled transient elastography (ICC = 0.790)[71] and biopsy (ICC = 0.504).[32] It is suggested that a threshold of 0.75 kPa represents a significant change in MRE.[30] The main limitations of MRE, aside from the limited availability of the MRE hardware, are the sensitivity of MRE to early stages of fibrosis and a reduced reliability in the presence of iron. Specifically, the elastograms are provided with an area of confidence representing a region of sufficient signal intensity. In cases of iron overload, particularly at 3T, this area might shrink. In rare occasions, this could culminate in technical failure.[77] Therefore, alternative techniques such as the usage of spin-echo based echo planar imaging sequences especially at 3T to reduce the impact of iron[78] and 3D MRE, which allows for the extraction of additional variables (discussed in more detail in the previous section on activity), are increasingly being applied with novel automated analysis techniques to improve the sensitivity of MRE in all conditions.

Fig. 2 (A, B) Forest plots of pooled diagnostic sensitivity and specificity for the prediction of different fibrosis stages using MRE. Data were processed using Met DiSc 2.0. MRE, magnetic resonance elastography.

 

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(c)T₁

The most prominent alternative to MRE is the measurement of the longitudinal relaxation time T₁. As previously mentioned, T₁ is a multidependent MR signal property and initially gained attention in cardiac MRI. Common applications of MRI involved acquiring images using T₁-weighted contrast sequences which display grey scale values that are closely related to the T₁ relaxation time. However, these techniques are less sensitive to small changes in T₁, particularly in cardiac MRI, and do not allow the proper assessment of fibrosis. While the extraction of actual T₁ values was thought to be valuable, this technique required multiple breath-holds which limited applicability in cardiac MRI. This limitation led to the development of new acquisition sequences and post-processing algorithms that enabled the acquisition of T₁ maps in a single breath-hold displaying the actual T₁ values, measured in milliseconds.[79] This significant advancement catalyzed the application of T₁ quantification in other organ systems such as the liver. However, it is worth noting that T₁ also depends on both tissue characteristics such as the presence of edema, fatty acids, and iron, as well as scanner characteristics like the field strength. Therefore, caution is required when interpreting T₁ maps, especially in organs such as the liver where confounding features are frequently present. For these reasons, it is not surprising that fibrosis staging by T₁ was outperformed by MRE despite a high inter-reader agreement of ICC = 0.94–0.993.[50] [76]

Recently, postprocessing algorithms have been developed to minimize the impact of the competing influences on T₁. The technique to correct for the effect of iron load in the liver is based on the transverse relaxation time (T₂*) and is referred to as iron-corrected T₁ (cT₁).[80] This correction was further extended to standardize to a specific scanner from a specific vendor at a specific field strength to obtain a reproducible, scanner-independent MRI marker to assess extracellular water content.[80] [81] This approach has been commercialized and is available through the patent holder.

Multiple studies have reported an increase in cT₁ with fibrosis stage, particularly in the early stages of the fibrotic process.[43] [55] [82] However, due to the effect of inflammation on T₁, which also raises cT₁ values,[82] this measure is collectively referred to as fibroinflammation. Additionally, steatosis grade is positively associated with cT₁ and is the strongest among multiple confounding factors in MASLD.[78] [80] [81] Since steatosis is the key feature of MASLD across the disease spectrum and often decreases in advanced stages of fibrosis, the confounding of cT₁ by changes in fat content is a significant concern. Consequently, it becomes challenging to determine whether a decrease in cT₁ is primarily caused by fibrosis, inflammation, or steatosis regression.

While T₁ quantification is available on most MR scanners, the availability of cT₁ is restricted since it requires an additional commercial product and might be inconclusive for high iron overload (>5 mg Fe/g dry tissue) and high fat content (>35%: no cT₁ reported).[83] Importantly though, cT₁ and T₁ both cover the entire organ and should allow regional disease assessment.

 

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Gadoxetate-Enhanced Imaging

As previously mentioned in the section on inflammation, gadoxetate, also known as gadoxetic acid, is a liver-specific contrast agent used in MRI to enhance the visualization of liver lesions. Gadoxetate is partly taken up by hepatocytes through an active transport mechanism involving the organic anion transporting polypeptides (OATPs). Once inside the hepatocytes, gadoxetate is excreted into the bile canaliculi through the multidrug resistance-associated protein 2 (MRP2). Under normal condition, 50% of the contrast agent follows the described hepatobiliary route while the other 50% are removed via the systemic circulation. The hepatobiliary route of the contrast agent allows for the enhancement of healthy liver parenchyma and enables the assessment of hepatocyte function as the gadoxetate is transported only into the biliary system by functional hepatocytes.[57]

The bifunctional pharmacokinetic pattern of gadoxetate allows for the extraction of different contrasts depending on the delay after contrast injection. The assessment of the contrast agent within the intra- and extracellular space is accomplished by measuring the MR signal throughout the late arterial (30–35 seconds after contrast injection) and portal phase (60–75 seconds). The active transport by hepatocytes starts in the translational phase (3–5 minutes) and reaches maximum parenchymal enhancement during the hepatobiliary phase (15–20 minutes).[57] This pharmacokinetic pattern allows for both static and dynamic approaches to derive measures of hepatocyte health. Static techniques are usually performed with high spatial resolution at a single time point during hepatobiliary phase and are evaluated either for a region of interest or the whole liver. The most common static technique compares MR signal intensity (T₁-weighted) obtained in the hepatobiliary phase (usually 20 minutes after injection) to precontrast values. This relative liver enhancement yielded the highest inter-reader repeatability (ICC = 0.979)[84] among all static techniques and has an AUROC of 0.93 to 0.98 for the differentiation of histologically determined fibrosis stages.[85] Moreover, in a study in 98 participants, these data showed a decrease in signal intensity in advanced liver fibrosis.[85] Other static techniques use reference tissues as muscle or spleen, or calculate T₁ relaxation time to provide a less scanner-dependent measure.[60]

The potential advantage of gadoxetate imaging is to move beyond static techniques and examine the dynamic uptake of gadoxetate by functional hepatocytes. Instead of acquiring a single image during hepatobiliary phase and comparing it to precontrast, a continuous acquisition of images is performed starting from the contrast injection and continuing until the hepatobiliary phase. This extended acquisition process lasts approximately 20 minutes for individuals with normal liver function. However, in advanced stages or when there is a need to capture additional variables related to biliary excretion, an extension of the acquisition duration might be necessary.[86] A complete data set allows quantitative measures of hepatocyte transport and perfusion to be derived using multicompartment analysis or deconvolution models.[60] Unfortunately, due to the demanding mathematical models for extraction of the desired variables, studies applying dynamic techniques are sparse and mostly restricted to animal models,[87] [88] although a study in chronic hepatitis patients yielded an AUROC of 0.701 for the differentiation of no versus mild fibrosis.[89]

While gadoxetate is an accepted contrast agent in the detection and characterization of focal liver lesions, its application in staging liver fibrosis is currently considered investigational.[90] However, the increasing prevalence of MASLD combined with the possibility of simultaneous screening for hepatocellular carcinomas, the prevalence of which is increased in MASLD,[8] and the promising results of recent studies might set the stage for a broader field of clinical application.

 

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Multiparametric MRI Protocol: Challenges and Limitations

MRI techniques are powerful multifaceted techniques that allow the assessment of histologic features of MASLD/MASH. Studies have shown that MRI captures a whole organ holistic picture of the liver structure and function. However, there is not one MRI technique that allows quantification of all the different features of MASLD/MASH. Therefore, multiple techniques may be needed to get the whole picture of the disease process. For example, a “suite” of MRI imaging that quantifies tissue composition (i.e., fat content by MRI-PDFF and extracellular water by (c)T₁) and tissue mechanical properties (MRE) will cover the grading of steatosis, activity, and fibrosis usually only assessed using histology ([Fig. 3]). Additionally, MRI allows for the assessment of hepatocyte function using gadoxetic acid. This yet experimental gadoxetate imaging approach captures a further color of the MASLD spectrum not accounted for by histology ([Fig. 4]), as it allows for the quantification of both liver structure and function.

Fig. 3 Schematic illustration of the applicability of different MRI modalities (PDFF, (c)T₁, and MRE) throughout the MASLD spectrum. The figure shows that while there is overlap between the applicability of each modality, each has its own strengths and weaknesses depending on the stage of the disease. cT₁, iron-corrected T₁; MASH, metabolic dysfunction–associated steatohepatitis; MASLD, metabolic dysfunction–associated steatotic liver disease; MRE, magnetic resonance elastography; MRI, magnetic resonance imaging; PDFF, proton density fat fraction; T₁, longitudinal relaxation time.

Fig. 4 Illustration of how a multiparametric MRI protocol covering tissue composition (i.e., fat content and extracellular water), tissue mechanical properties, and hepatocyte function evaluation of the liver (outer ring) can cover the features accessed by histology (center: steatosis, activity and fibrosis). Thereby adding an additional measure by the assessment of hepatocyte function. MRI, magnetic resonance imaging.

However, it is important to note that not every question necessitates the complete range of MRI techniques. The most valuable MRI method largely depends on the specific stage within the MASLD spectrum or question that is being investigated. For instance, in the early stages, MRI-PDFF for steatosis assessment and (c)T₁ for steatohepatitis detection may be adequate. These techniques can also be utilized for screening MASLD or identifying at-risk MASH in large cohort studies.[91] Additionally, MRI-PDFF is used in early clinical trials to assess treatment response.[92] [93] [94] On the other hand, lower liver fat in individuals with advanced fibrosis or cirrhosis was associated with worse outcome.[95] Therefore, MRE and gadoxetic acid–enhanced MRI may be more advisable for more advanced stages. While gadoxetic acid–enhanced MRI is a yet experimental technique in the context of MASLD, MRE alone or in combination with other clinical indicators was reported by different studies to be a predictor of liver-related events.[96] [97] [98] In conclusion, it is important to fully understand the disease process within the MASLD spectrum, the expected histological changes, and the reason for the imaging technique before applying it. [Fig. 5A] is intended to assist in the selection of the appropriate MRI technique(s). The netplot provides an overview of the performance of the covered MRI techniques for different MASLD features in comparison to biopsy. It is important to keep in mind that even though biopsy-based histology is considered the “gold standard,” it still shows limited performance due to sampling error, limited organ coverage, and low reproducibility.[32] These criteria and the higher acceptance and quantitative nature represent the strongest advantages of a multiparametric MRI protocol over liver biopsy as is visualized in [Fig. 5B]. Importantly, due to its noninvasiveness, multiparametric MRI is well suited to screening and follow-up settings in clinical trials.

Fig. 5 Net plots providing an overview of the performance of the determination of different features of MASLD (A) and methodological criteria (B) comparing the MRI techniques (PDFF, (c)T₁, MRE, and Gadoxetate) to liver biopsy. Inspired by Nogami et al.[99] cT₁, iron-corrected T₁; MASLD, metabolic dysfunction–associated steatotic liver disease; MRE, magnetic resonance elastography; MRI, magnetic resonance imaging; PDFF, proton density fat fraction; T₁, longitudinal relaxation time.

However, as [Fig. 5B] further indicates, MRI is also facing challenges. The most obvious and often quoted challenges are availability and cost, albeit the costs are still lower than those associated with liver biopsy.[55] [73] [99] [100] Ultrasonography-based techniques are noninvasive alternatives that benefit from low costs and relatively broad availability.[71] While ultrasonography is a commonly applied approach within MASLD/MASH, these techniques do not achieve the accuracy and reproducibility of MRI.[18] [23] [71] [72] Therefore, cost-effectiveness analyses predominantly rule in favor of MRI[101] and this should only become better as the availability of MRI increases in the future.[99]

 

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Concluding Remarks

It is important to keep in mind that the histologic evaluation of a liver biopsy limits investigators to a single snapshot in time of an extremely small sample of the liver. Moreover, biopsy is not an easy procedure and includes risk to the participant. MRI, on the other hand, allows full organ coverage, which strengthens the results in a complex disease such as MASLD. Furthermore, experts agree that there need to be validated and useful noninvasive tests for this disease. Recently, there is a growing interest in composite biomarkers that combine imaging with nonimaging biomarkers. One example is the prediction of treatment response by a combination of MRI-PDFF with blood-based biomarkers.[102] [103] Other composite markers which include MRE are mainly intended to predict outcome in more advanced stages. The most established among them is the MAST score which includes aspartate aminotransferase measured in blood with MRI-PDFF and MRE.[104] A second recent score is the MEFIB which combines MRE and FIB-4 score for MASH and advanced fibrosis detection.[105] Both composites were shown to be associated with liver-related events, while MEFIB was reported statistically superior in predicting hepatic decompensation.[106] Other studies confirm the performance of MEFIB for the prediction of decompensation and death.[96] [97] Additionally MRI opens the possibility of analyzing the spatial distribution of certain features throughout the organ. Nonetheless, examining the entire liver does not fully encompass the scope of the issue, as MASLD represents the hepatic manifestation of metabolic syndrome and is significantly impacted by other organs, such as various adipose tissue compartments or the intestine. Therefore, one benefit of MRI is the simultaneous accessibility of multiple organs. For example, PDFF-maps or T₁ images of the abdomen allow the volumetric quantification of different abdominal adipose tissue compartments. Recent studies have shown that the prevalence of MASLD and MASH was found to increase with visceral adipose tissue volume, while no difference was observed for subcutaneous adipose tissue.[107] [108] In addition, inflammation of visceral adipose tissue which might be revealed by T₁ increase is associated with hepatic fibroinflammation.[109]

Furthermore, a potential complication of hepatic cirrhosis is portal hypertension caused by increased intrahepatic resistance and representing a necessary condition for multiple MASLD-associated comorbidities (i.e., esophageal varices and ascites).[110] Recent studies suggest that the simultaneous assessment of spleen stiffness (shear or loss modulus) during 3D MRE examination of the liver is a reliable noninvasive indicator for portal hypertension.[51] [111] Thus, the coverage of the spleen in addition to the liver by MRE might allow for risk stratification of certain comorbidities in advanced fibrosis.

In conclusion, a multiparametric MRI protocol not only covers the entire liver volume and MASLD spectrum with additional information on hepatocyte function but also allows for segmentation of disease based on related extrahepatic alterations. We argue that this is clearly better than the histological assessment of unviable liver fragments and can be applied across multiple centers in multiple studies and provides investigators with a method to assess disease pathogenesis and response to therapy.

 

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Conflict of Interest

A.M.F., N.L., and H.O.C. are employees of Boehringer Ingelheim Pharma GmbH & Co. KG.

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Publication History

Accepted Manuscript online:
28 May 2024

Article published online:
19 June 2024