Muscle fat infiltration: a narrative review of the magnetic resonance (MR)-based evaluation methods and their clinical applications

Introduction

Muscle fat infiltration (MFI) is known to occur with the normal process of aging or in the presence of specific pathologies (1,2). These pathologies may be of varied origins, including neuromuscular, endocrinological, or musculoskeletal etiologies (3-5).

Two main processes have been identified that lead to the accumulation of fat in muscle tissue. The first process includes a direct route of accumulation of fat in myocytes, known as intra-muscular fat infiltration. This was shown to lead to a decrease in insulin sensitivity, increased inflammation, and decreased functional ability of the muscle tissue (6,7). The second process happens via the accumulation of adipocytes within the muscle fibers, also known as inter-muscular fat infiltration. This process might be caused by different conditions, such as muscle damage or glucocorticoid treatment. Both may lead to the differentiation of specific stem cells within the muscle, known as fibro/adipogenic progenitors, into adipocytes (8,9).

In both research and clinical settings, fat infiltration in skeletal muscle is mainly evaluated via medical imaging, such as magnetic resonance imaging (MRI), computed tomography (CT-scan), and ultrasonography (US). MRI represents the most efficient imaging modality in visualizing the soft tissues, especially the muscle, compared to CT-scans and US (10), while US allows dynamic assessment of the muscles. Furthermore, MRI is a non-irradiating imaging modality, unlike CT-scans, and can better visualize both superficial and deep muscles than US.

Several qualitative and quantitative methods have been implemented for the assessment of the degree of MFI. Qualitative grading methods have been used in the literature, such as the Goutallier classification which is mainly applied to assess the MFI of the rotator cuff (11), the Mercuri Classification in neuromuscular disorders (12), the Kjaer classification in paraspinal muscles (13,14), or the Bal-Lowe and Quartile classifications for hip muscles (15,16). Quantitative methods, such as pixel intensity-based thresholding, mean pixel-intensity or the Dixon technique, are used to better evaluate and quantify MFI.

The quantification of MFI was shown to be indicative of both the progression of disease and the response to treatment in different pathologies. For instance, a higher degree of fat infiltration has been shown to be associated with more severe symptoms in neuromuscular diseases, a worse clinical and functional status in neuromuscular disorders, and a higher risk of post-surgery complications during both the correction of spinal deformities and total hip replacement (16-22).

This review aimed to provide an overview of the different MRI applications for MFI assessment, their clinical relevance, and the techniques used for these evaluations. We present this article in accordance with the Narrative Review reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-177/rc).

Methods

Search strategy

The literature search was performed on the PubMed database for articles published between 2010 and end of January 2023. The keywords used were: (Fat infiltration of the muscle) AND [magnetic resonance imaging (MRI)].

Study selection

Articles were included if they were written in English, were full text, on human species, and included fat infiltration assessment of skeletal muscles regardless of the disease and system or muscle groups. Cross-sectional, retrospective, prospective and randomized controlled trials were included. Excluded studies were abstracts, reviews, systematic reviews, case studies, in vitro or animal studies, and articles not related to the research topic.

Study data extraction

For each included study, the main characteristics were extracted including the MFI evaluation method, the target pathology, the muscle(s) of interest, the size of the cohort, the software used (if applicable), the MRI sequences, and the magnet strength. The strategy of the narrative review is displayed in Table 1.

Results

Literature search

Two researchers conducted an independent screening of the literature, based on the aforementioned inclusion and exclusion criteria. 615 publications were found on PubMed dated between January 2010 and January 2023. After applying the exclusion criteria, 471 articles were pre-selected. The two researchers independently underwent a screening of all titles and abstracts, then a detailed reading of full articles, effectively narrowing the literature down to a total of 159 papers. The detailed results of MFI evaluation methods and the associated conditions are presented hereafter. The search methodology was summarized in a flow chart (Figure 1) and a detailed table was added in https://cdn.amegroups.cn/static/public/qims-24-177-1.xlsx.

Figure 1 Flow chart of the inclusion and exclusion criteria. MRI, magnetic resonance imaging.

MFI evaluation methods

The 159 selected papers involved MFI evaluation methods that could be classified as qualitative or quantitative (Figure 2). Within the 159 papers, some of them included more than one method, resulting in 168 studies.

Figure 2 Pie chart of MFI evaluation methods. MFI, muscle fat infiltration; PDFF, proton density fat fraction.

Qualitative methods (33 studies)

Goutallier classification (17 studies)

The Goutallier classification includes five grades. Grade 0: absence of fat infiltration in the muscle tissue; grade 1: some fat streaks in the muscle tissue; grade 2: lean muscle tissue exceeding the fat tissue; grade 3: lean muscle tissue equal to fat tissue; grade 4: fat deposits in the muscle tissue exceeding the lean muscle mass (Figure 3) (23).

Figure 3 Goutallier classification. Grade 0, no intramuscular fat; grade 1, some fatty streaks present; grade 2, fat evident, but less than muscle tissue; grade 3, amounts of fat equal to amount of muscle; grade 4, more fat than muscle tissue. MM: red; ES blue; PS: yellow. The figure was reprinted from a previously published open access journal article by Guan et al. (23) under the terms of the Creative Commons CC BY license. PS, psoas; ES, erector spinae; MM, multifidus muscle.

This classification was created to assess the MFI in rotator cuff pathologies using CT-scans (11). It was later modified for use in MRI studies and extended to other muscles, especially in the spine. The Goutallier classification is applied on T2 sequences.

Kjaer classification (9 studies)

The Kjaer classification is mainly used for the evaluation of the paraspinal muscles, especially the multifidus muscle, and includes three grades (Figure 4) (13,14,24). Grade 0: muscle with fat infiltration less than 10%; grade 1: fat infiltration between 10% and 50%; grade 2: muscle with fat infiltration more than 50%.

Figure 4 T2 weighted axial MR magnetic resonance (images of the lumbar spine). Images represent Kjaer grades: 0 (A), 1 (B), and 2 (C) muscles of the lumbar spine. All images are from patients undergoing surgery for low back pain related pathology. The figure was reprinted from a previously published open access journal article by Berry et al. (24) under the terms of the Creative Commons CC BY license. MR, magnetic resonance.

Mercuri grading scale (5 studies)

The Mercuri classification is mainly used for the assessment of thigh muscles in neuromuscular diseases and categorizes MFI into four grades (12). Grade 1: muscles with a normal appearance; grade 2: muscles with mild fatty infiltration (less than 30% of the volume of the original muscles); grade 3: muscles with moderate fatty infiltration (30% to 60% of the volume of the original muscles); grade 4: muscles with severe fatty infiltration (greater than 60% of the volume of the original muscles).

Bal Lowe classification (1 study)

The Bal Lowe classification aims to evaluate hip muscles after minimally invasive total hip arthroplasty (THA) and includes four grades (15,16). Grade 0: muscle with a normal appearance; grade 1: muscle with less than 30% of fatty infiltration; grade 2: muscle with fatty infiltration between 30% and 70%; grade 3: muscle with more than 70% of fatty infiltration.

Quartile classification (1 study)

The Quartile classification was first used to assess fat infiltration in the hip muscles and includes four grades. Grade 1: MFI less than 25%; grade 2: MFI between 25% and 50%; grade 3: MFI between >50% and 75%, grade 4: MFI more than 75% (25).

Table 2 displays the different qualitative methods used to evaluate MFI.

Within the 168 studies, these 5 qualitative MIF classifications accounted for 20% of all MIF evaluation methods, with the Goutallier classification being the most represented.

Validity and reliability studies on these techniques were scarcely evaluated in the screened literature. Klemt et al. reported that the Bal Lowe, Goutallier and Quartile classifications demonstrated good reproducibility in assessing hip muscles with better results for the Quartile classification (16).

Quantitative methods (135 studies)

All the quantitative methods described hereafter involve the segmentation of the muscles of interest and the computation of the pixel intensity histogram.

Dixon method (68 studies)

Unlike other fat suppression methods, the Dixon acquisition principle takes advantage of a convenient fat and water chemical shift to generate fat-only and water-only images. Sequence terminology depends on the manufacturer: IDEAL (GE Healthcare, Waukesha, MI, USA); Dixon (Siemens Healthcare, Erlangen, Germany); mDIXON (Philips Medical Systems, Best, the Netherlands); and FatSep (Hitachi, Tokyo, Japan) (26,27).

Since the invention of this technique, numerous variations have been proposed to improve the quantification of the water and fat components.

The original 2-point Dixon (2PD) depends on two image acquisitions [in T1, T2, proton density weighted; spin echo (SE) or fast spin echo (FSE)] at two different echo times (TEs), where the water and fat magnetizations are in-phase and out-of-phase, respectively. Then, the water-only image is obtained by the sum of the in-phase and out-of-phase images, while the fat-only image is obtained by subtracting the out-of-phase from the in-phase images (26). This formulation is prone to misquantification caused by B0 inhomogeneities and ignores additional image weighting (T2* relaxation, diffusion, and flow) and other phase shift biases (eddy currents and B1 receive-field non-uniformity) (28).

To overcome 2PD sequence drawbacks, the original technique was modified to involve a third TE point to sample a second out-of-phase state. In the so-called three-point Dixon (3PD), B0 inhomogeneity can be removed using the two out-of-phase acquisitions for estimating the phase error. A generalized 3-point method was proposed in the late 90s, showing that pure in-phase and out-of-phase imaging was not required when 3 echoes were acquired (29). The 3PD technology provides more effective fat quantification, resulting in a better signal-to-noise ratio (SNR) and optimal spatial resolution. The fat fraction (FF) image is calculated as follows: I_FF = I_f/ (I_f + I_w) × 100, where I_f, I_w, and I_FF are the fat, water, and FF images, respectively.

The last two decades produced significant improvements due to advanced chemical shift imaging processes enabling the correction of some major confounding factors. First, the independence of T1 relaxation between fat and water can be avoided with very low flip angle values, less than 6 degrees (30). Second, the effect of T2*-related signal loss is corrected by using images acquired at flexible and multiple TEs (31,32), from 3 to up to 6 different TEs that can be exploited to fit the signal decay. Indeed, iron deposition in certain organs and tissues shortens T2* values. Finally, accurate water and fat separation requires a more sophisticated model including a fat multifrequency spectrum with the use of up to 6 fat peaks, rather than just a single methylene peak (32,33). Such quantitative Dixon sequences and the associated post-processing constitute a reliable method for fat quantification. Up to 6 quantitative images may be produced: fat-only, water-only, in-phase, and out-of-phase images, as well as proton density fat fraction (PDFF), and R2* maps (R2*=1/T2*) (Figure 5) (34). One can notice that the earlier signal FF refers to the fraction of MR signal attributable to fat. Conversely, the PDFF is the ratio of the density of mobile triglycerides to the total density of mobile triglycerides and mobile water and has an acute correlation with histological findings (35).

Figure 5 Illustration on the Dixon method. (A) A multi-echo acquisition illustrated in the case of 6 echoes Dixon sequence at 3T (Canon Medical System, Fat Iron Quantification). Signal intensity decay is sampled at several time points corresponding to partially in-phase and opposed-phase spin states as shown in image numbers 1−6 acquired at a starting time of 1.2 ms and an ending time of 6.2 ms. (B) Native multi-echo Dixon images in the case of 6-echo Dixon sequence (Canon Medical System, Fat Iron Quantification): IP, OP, fat, water, PDFF, iron (R2*). These images were constructed a posteriori using the multi-echo images (A) and thanks to dedicated algorithms dealing with field inhomogeneity corrections, fat/water signal contribution separation, and specific image reconstruction for each one. The figure was reprinted from a previously published open access journal article by Arango-Lievano et al. (34) under the terms of the Creative Commons CC BY license. IP, in-phase; OP, opposed-phase; PDFF, proton density fat fraction.

Thus, the quantification of the MFI is based on FF or PDFF images depending on the Dixon sequence available with the imaging system. The operator determines a region of interest (ROI) using segmentation software. The MFI is computed as the PDFF voxel average in the ROI.

The most frequently used software employing the Dixon technique are ImageJ (36,37), Osirix (38,39), MITK (40-44), ITK-SNAP (1,45-47), SiemensSyngo (48,49), AMRA (50), IntelliSpace (51), Mimics (52), MIPAV (53), MIAF (54,55), Analyzedirect-v11 (56-59), Aquarius-iNtuition-Edition (60), 3Dslicer (61), Horos (62), Muscl’X (5,63,64), PRIDE (3,65), Advantage-Window (4), Interactive Data Language (66), Intellispace (51), NiftyNet (67), Display1 (68), FSL software (69), IDEAL-IQ (18), MeVisLab (70), Myrian (71,72), Radionet (73) and Simple Ware (74-76).

Hiba et al. reported that the Dixon technique showed high reproducibility when measuring fat infiltration of the tibialis anterior in the setting of Myotonic Dystrophy type 1 (MD1) (77). Two research groups developed an automated thigh muscle segmentation using Dixon sequences. It was found to exhibit excellent accuracy and high reproducibility in FF estimation compared to manual segmentation (37,78).

Threshold-defined method (48 studies)

Three main methodologies were identified in order to define the cutoff between fat and muscle tissue, all applied on either T1 or T2 sequences without fat saturation.

• Fixed threshold: all pixels with a signal value higher than 120 (for pixels intensity ranging from 0 to 660) on the grayscale are defined as fatty tissue, while those lower than 120 are muscle tissue (79). The value of 120 was defined when the gray scale of muscle, fat, and bone tissues of the lower back muscles of 6 subjects were averaged, and this specific value was found to delimit the fat tissue from muscle and bones (80).
• Gaussian modeling: two Gaussian models are fitted on the pixel intensity histogram in order to identify the peaks of fat and muscle. The threshold between fat and muscle is then defined as the intersection between the two Gaussian models and used to classify pixels as fat or muscle tissue. This method is subject-specific (Figure 6) (81-84).
• Visual assessment: the operator is asked to specify the threshold to separate fat from muscle tissue on the histogram. The fat-muscle separation threshold is determined by locating the lower limit of the region-growing threshold at the base of the muscle peak. This is a subject-specific, but operator-dependent method (85,86).

Figure 6 MRI image processing. Multifidus cross-sectional area and fat fraction were determined using custom MatLab code to differentiate between muscle and fat. Regions of interest were drawn around the right and left multifidus in T2-weighted axial MRIs of the lumbar spine (A). Right and left multifidus were evaluated for muscle size (B), then, a bi-gaussian distribution of voxel intensity (C) was used to determine the intercept (red circle) between water (blue line) and fat (green line). The intercept is used as a threshold; greater voxel intensities are designated as fat and lower voxel intensities are designated as muscle. This analysis highlights muscle as teal and fat as yellow (D) and provides a calculation for both right and left multifidus cross-sectional area and fat fraction (D, table). The figure was reprinted from a previously published open access journal article by Anderson et al. (81) under the terms of the Creative Commons CC BY license. R, right; L, left; CSA, cross sectional area; MRI, magnetic resonance imaging.

For all the previous methodologies, the MFI is computed as the proportion of the area of fat infiltration relative to the total area of the segmented muscle.

The software used in the 48 selected studies were 3Dslicer (87), AequitasIA (88), ImageJ (21,79,89-105), INFINIT (106), iSix (107), Osirix(17,24,82,84,108-111), ITK-SNAP (112-114), MIPAV (115), MIAF (55), Mimics (116), Surgimap (117,118), SliceOmatic (86,119), pMRI (120) and PiView (121).

Signal intensity (10 studies)

In this method, the mean signal intensity (MSI) of the segmented muscle is calculated. The intensity of this averaged grayscale increases (hypersignal) with the degree of fat infiltration in the region. For instance, Tabaraee et al. quantified multifidus fat infiltration following a 1-level minimally invasive lumbar discectomy to show the advantage of such interventions in reducing muscle degeneration compared to traditional open surgery (122).

The software used included PiView (123), OpaL (122), ImageJ (124,125), IDL (126,127) and MaZda (128).

Signal intensity/subQ (9 studies)

After computing the MSI of the segmented muscle, a region from the subcutaneous adipose tissue is selected and its MSI is calculated as well. MFI is then evaluated as the proportion of MSI of the muscle relative to the MSI of the subcutaneous adipose tissue (Figure 7) (129).

Figure 7 T2 weighted MRI showing segmentation for CSA and MFI analysis. The violet line represents the measurement of psoas muscle obtained using OsiriX software, while the green line represents the measurement of MF and ES muscles as a unit bilaterally and the red circle represents the measurement of a pure fat ROI. The figure was reprinted from a previously published open access journal article by Yang et al. (129) under the terms of the Creative Commons CC BY license. MRI, magnetic resonance imaging; CSA, cross sectional area; MFI, muscle fat infiltration; MF, multifidus; ES, erector spinae; ROI, region of interest.

Software used for this method include Image J (20,130,131), PACS (132), OsiriX (129,133), AMIRA (134), ITK-SNAP (2) and Mimics (135).

Within the 168 studies, these 4 quantitative MFI evaluations accounted for 80% of all MIF evaluation methods, with the Dixon method being the most represented.

MFI applications in diseases

The most common diseases where MFI was explored were mainly neuromuscular disorders and musculoskeletal pathologies at the level of the spine, shoulders, hips and knees, in addition to studies in healthy subjects (Figure 8).

Figure 8 Pie chart of MFI applications. MFI, muscle fat infiltration; AIS, adolescent idiopathic scoliosis; ASD, adult spinal deformity; OVCF, osteoporotic vertebral compression fracture; LBP/LDH, low back pain/lumbar disc herniation; WAD, whiplash-associated disorder.

Neuromuscular disorders (37 studies)

Duchenne muscular dystrophy (DMD) (8 studies)

DMD is an X-linked, inherited disorder with an incidence of 4.8 per 100,000 (136). It is caused by mutations in the dystrophin gene, which lead to progressive weakening of skeletal muscle, loss of ambulation in adolescence, and death by early adulthood (137). DMD is first suspected by muscle biopsy and confirmed through genetic screening for the dystrophin gene mutation. The use of MRI is essential to assess disease progression and response to treatment. Pelvic, thigh, and calf muscles were the most studied muscles in this disease. Although patients with DMD present with hypertrophied calf muscles, studies reported an increased MFI that was found to be correlated to patient dysfunctional levels (such as the Gower’s sign, time to climb up four steps, and time to run 30 feet) (3,4,17). Three muscles showed the highest degree of MFI: adductor magnus and gluteus medius and magnus (138). The MFI of these muscles was positively correlated to age, height, and weight (138). Moreover, it was reported that using the intensity/subQ method for MFI quantification can show the multistep process of involvement of muscles in the lower limbs of DMD patients and allow the monitoring of disease progression (134).

Limb girdle muscular dystrophy type II (LGMD2) (10 studies)

LGMD2 is the most common form of heterogenous and genetically inherited LGMD. It is characterized by predominant proximal muscle weakness (hip girdle), elevated serum creatinine kinase, and muscle dystrophy on biopsy. LGMD2 is a recessive-autosomal form of LGMD, with a prevalence of 1.63 per 100,000 (139). Two studies have reported the quantification of MFI in this disease by evaluating its reliability (18,19). Thigh muscles were the most studied regions using Dixon sequences. MFI of thigh muscles in patients with LGMD2 correlated with clinical and functional status, such as the British medical research council scales, the motor function measure, muscle strength measurement using a dynamometer, the “timed up and go” test, and the 6-minute walk distance test (18,19).

One article studied muscle FF in calpainopathy, another type of LGMD (61).

MD1 (2 studies)

MD1 is an autosomal dominant multisystemic disorder and is one of the most frequently encountered muscular dystrophies in adults (140,141). It includes a wide range of symptoms such as myotonia, progressive muscle weakness and wasting, cardiac conduction defects, and endocrine and cognitive dysfunctions. In DM1 patients, motor impairment at the extremities progresses from distal to proximal. Although MRI has no role in the diagnosis of DM1, it is still used in research. Several studies have quantified the MFI of muscles in DMI patients using MRI, especially in the lower limbs. The use of the Dixon technique in the tibialis anterior muscle was capable of monitoring disease progression, as well as response to therapy (77). Other studies evaluated the MFI of trunk muscles using the Mercuri classification and indicated that MFI may be negatively correlated to muscle strength, trunk mobility, and balance. High MFI was also associated with decreased lung function (142).

Facioscapulohumeral muscular dystrophy (FSHD) (10 studies)

FSHD is the third most common inherited muscular disorder with an incidence of 3.95 per 100,000 (139). FSHD is characterized by a loss of repression of the DUX4 (protein that has toxic effects on muscle cells) (143). The decrease in muscle function during disease progression is strongly related to fat infiltration and muscle cell atrophy (36,144). MRI is mainly used in order to better understand the natural distribution of MFI, correlation with the disease, clinical status, severity, progression, and attenuation of specific muscle groups. The most commonly studied muscles in FSHD are thigh and leg muscles (145). Studies have shown that fatty infiltration begins in the distal end of affected muscles (49). The MFI was strongly correlated to the clinical status of FSHD and negatively correlated with manual testing of muscles and measures of muscle function (146,147). Furthermore, MFI measurement was shown to be a reproducible and sensitive biomarker to monitor the responsiveness of FSHD during aerobic exercise therapy (126).

Amyotrophic lateral sclerosis (ALS) (3 studies)

ALS is a rapidly progressive and fatal disease characterized by upper and lower motor neuron dysfunction, which leads to muscle degeneration (148). Its incidence ranges between 2.4 and 2.7 per 100,000 person per year (149). The initial clinical presentation may affect every segment of the body. The most common presentation is the asymmetric weakness of upper or lower limbs (148). Musculoskeletal MRI is not used for the diagnosis of ALS, but rather for research purposes. The MFI of shoulder muscles was shown to be correlated with the degree of brachial plexus alteration (150). In addition, the MFI of thigh and leg muscles using the quantitative Dixon technique was shown to be negatively correlated with disease functional status (ALS functional rating scale-revised). Also, MFI was shown to be a useful tool to differentiate between ALS and spino-bulbar muscular atrophy, another type of motor neuron disorder (45).

Four articles studied MFI in rare neuromuscular disorders: Becker muscular dystrophy (53), occulopharyngeal muscular dystrophy (151), Charcot-Marie-Tooth type 2 F (152), GNE myopathy (153).

Studies focusing on the MFI in neuromuscular disorders used mainly the Dixon and PDFF quantitative techniques. The qualitative Mercuri and Goutallier classifications were less used.

Endocrinological disorders (2 studies)

MFI has been used in the setting of two endocrinological disorders, acromegaly (65) and Cushing syndrome (3).

Acromegaly is characterized by elevated growth hormone (GH) secretion and insulin-like growth factor 1 (IGF1). Despite their lipolytic effects, the excess of GH and IGF1 is associated with increased MFI in skeletal muscles, which persists even after hormone levels have been controlled or the disease managed surgically (154,155). MFI of thigh muscles in patients with acromegaly is negatively correlated with muscle function (65).

Cushing syndrome is caused by hypercortisolism, which is associated with proximal myopathy and especially lower limb weakness (156). Musculoskeletal MRI has been used to evaluate muscle tissue evolution after blood cortisol levels have been controlled, and to search for relationships with muscle function. MFI of thigh muscles was negatively correlated with muscle strength and patient functional status. It was also shown that MFI remained elevated after blood cortisol levels were controlled (3).

The Dixon technique was used in these two pathologies.

Spine pathologies (72 studies)

Adolescent idiopathic scoliosis (AIS) (2 studies)

AIS is one of the most common 3D spinal deformities affecting adolescents, with a prevalence ranging between 1 to 4% with a female predominance (157). Despite many research efforts, the direct etiology behind AIS remains unclear. Many causes are involved, such as vertebral body deformation, paraspinal muscle defects leading to asymmetrical contractions, as well as biochemical and histopathological muscle alterations. Studies aimed to quantify the MFI of the multifidus and erector spinae muscles, mainly at the level of the apical vertebrae (83,89). Studies have found no correlations between increased MFI in multifidus and erector spinae muscles, the severity of radiographic scoliosis parameters, and curvature flexibility (83). However, a predominance of MFI on the concave side of the curvature has been reported (83,89). Furthermore, there was no significant difference regarding MFI of the multifidus and erector spinae muscles between subjects with AIS and controls.

Adult spinal deformity (ASD) (27 studies)

ASD encompasses a heterogeneous spectrum of deformities affecting the lumbar and thoracolumbar spine and includes de-novo scoliosis, degenerative thoracic kyphosis, degenerative lumbar lordosis, and spondylolisthesis (158). The incidence of ASD increases throughout the aging process, with a prevalence in individuals older than 65 years of age ranging from 38% to 68% (159,160). It is the result of complex-degenerative processes affecting the vertebral bodies, intervertebral discs, and paraspinal muscles, leading to spinal malalignment in the three planes, especially the sagittal plane with patients known to lean forward.

The most commonly studied muscles in ASD were the multifidus, erector spinae, psoas, and quadratus lumborum. Female patients with ASD tended to have an increased MFI of paraspinal muscles with increasing age, compared to their healthy counterparts (99,161).

Several studies investigated the correlation between MFI of paraspinal muscles and the severity of changes in radiographic parameters (96,97,123).

In degenerative lumbar scoliosis, the average MFI in the multifidus muscle was found to be higher on the concave than the convex side at the level of the apical vertebra. Additionally, the MFI of multifidus and erector spinae was found to be positively correlated to the Cobb angle and frontal malalignment (96,97). Furthermore, the MFI of paraspinal muscles showed a significant positive correlation with pelvic tilt and sagittal vertical axis, two radiographic parameters of sagittal alignment (114). Finally, spinopelvic sagittal malalignment could be predicted with a threshold of 43.9% of fat infiltration of multifidus and erector spinae (sensitivity =61.2%; specificity =59.4%) (112).

In degenerative lumbar lordosis patients, the increased MFI of paraspinal extensor muscles was found to be negatively correlated to the magnitude of the lumbar lordosis. Furthermore, the MFI of paraspinal extensor muscles was more correlated to dynamic parameters during walking than static parameters evaluated on radiographs (123).

Posterior interbody fusion is a very common treatment strategy in patients with ASD. The MFI of paravertebral muscles is considered a risk factor for post-operative complications. After lumbar fusion, the degree of MFI and the cross-sectional area of paravertebral muscles at the L4–L5 and L5–S1 levels were found to be important risk factors for the occurrence of adjacent segment disease (Figure 9) (20). Moreover, the MFI of paraspinal muscles preoperatively was found to be correlated to the loss of lumbar lordosis post-operatively (21).

Figure 9 A 63-year-old female underwent L4–5 transforaminal lumbar interbody fusion surgery in 2016 for lumbar spondylolisthesis and lumbar spinal stenosis and underwent L3–4 revision surgery for adjacent segment disease 4 years later. (A) The lumbar lateral plain radiograph before the first surgery. (B) Suggests significant fatty infiltration of the multifidus muscle at the L4–5 segment before the first surgery. (C) The lumbar lateral plain radiograph after the first surgery. (D,E) Pre- and postoperative radiographs of the revision surgery, respectively. The figure was reprinted from a previously published open access journal article by Gong et al. (20) under the terms of the Creative Commons CC BY license.

Osteoporotic vertebral compression fracture (OVCF) (6 studies)

The most common type of osteoporotic fracture is vertebral compression fracture (162). It generally results from minor trauma to the spine. This most commonly occurs at the midthoracic (T7–T8) and the thoracolumbar junctions (T12–L1). Many risk factors can cause OVCF, like aging, osteopenia, osteoporosis, corticosteroid treatment, weight loss, smoking, vitamin D deficiency, and depression (163,164).

OVCFs can lead to severe back pain, restricted physical activities, and impairments in activities of daily living, leading to a loss of independence, depression, chronic pain, and, in severe cases, spinal cord compression. Evaluation of OVCF is primarily done through clinical examination and X-rays with MRI being important diagnostic tool to help differentiate between malignant and benign fractures, and between chronic and acute fractures. Additionally, it is a useful tool to identify the MFI of paraspinal muscles or to evaluate the severity of vertebral fractures in the presence of posterior wall protrusion, posterior column extension, or spinal cord compression (165).

OVCFs result in a decrease in cross-sectional area and volume, and an increase in MFI of erector spinae and multifidus muscles, aggravating the risk of falling and occurrence of new OVCF (121,166,167).

Treatment can vary from conservative management (medications, bracing, physical therapy, and exercise) to percutaneous vertebroplasty or kyphoplasty (168). The MFI of paravertebral muscles correlated with radiographic parameters 6 months post-kyphoplasty (132). It was shown that, along with the increase in MFI of the erector spinae at L4, pelvic retroversion increased. Moreover, lower lumbar lordosis decreased with the increase of MFI of erector spinae and multifidus muscles at the L5 level.

Chronic low back pain (LBP) and lumbar disc disorders (28 studies)

LBP represents an important health problem. Approximately 80% of adults have experienced at least one episode of LBP, with degenerative disc disorders and lumbar disc herniation (LDH) being the most common causes (169). MRI remains the best imaging modality for the visualization and evaluation of intervertebral disc degeneration, using Pfirrmann classification (170,171). Several studies investigated the correlation between MFI in paravertebral muscles and spinal symptoms, such as radiculopathy, clinical presentation, and post-operative outcomes in patients with intervertebral disc disorders and LDH (103,105,109-111,122,125,172-174). In these studies, the MFI of the multifidus muscle at the same level of a herniated disc was found to be correlated with the severity of nerve compression and symptom duration. Moreover, the MFI of erector spinae and multifidus muscles was correlated with the Pfirrmann grade.

Whiplash-associated disorder (WAD) (9 studies)

Motor vehicle collisions may cause whiplash, which arises from rapid multiplanar acceleration/deceleration of the head and neck (175). WAD is a multifactorial clinical presentation (176) including neck movement disability, sensorimotor disturbances, distress, and cervical soft tissue degeneration (177). Deep extensor muscles, such as cervical multifidus and semispinalis cervicis, play an important role in maintaining cervical spine stability and postural control. Their degeneration, quantified by MFI, alters postural stability (Figure 10) (178-180). Many studies have shown the association between the increase of MFI and the increase of neck pain disability scores, proprioceptive deficits, chronic pain, and other functional impairments such as altered motor control and stiffness (57,58,67,178,181,182).

Figure 10 Fat/water MRI of the deep cervical extensors from C4 through C7 cervical vertebrae. Red circles represent the multifidus muscle. The figure was reprinted from a previously published open access journal article by Smith et al. (178) under the terms of the Creative Commons CC BY license. MRI, magnetic resonance imaging.

In spine pathologies, the main method used for MFI evaluation was the threshold method, except for the WAD investigation, where the Dixon technique was most frequent (Figure 10) (178).

Shoulder rotator cuff tears (20 studies)

The rotator cuff includes four muscles: supraspinatus, infraspinatus, teres minor, and subscapularis muscles. The supraspinatus is the most affected muscle in the rotator cuff. Rotator cuff tears affect around 20% to 30% of the population after the age of 60 (11). MFI represents the degenerative process of rotator cuff muscles (11). The analysis of MFI is primordial since the distribution of fat content of the supraspinatus muscle becomes heterogeneous once the global fat content of the muscle exceeds 10% (183). Several studies showed that MFI in the rotator cuff correlates with symptomatology, shoulder range of motion, and post-operative failure after tendon repair (60,184-186). One notable benefit when using the Dixon technique is its ability to perform a volumetric analysis of the muscle by analyzing several slices (187). In contrast, the Goutallier classification has limited reproducibility and it is restricted to a single slice (188).

The Goutallier classification was mainly used in the evaluation of MFI in the rotator cuff muscles in 9 studies. The Dixon technique was also applied (9 studies) for this muscle group and showed higher reliability and accuracy than the Goutallier classification (189).

Knee osteoarthritis (OA) (2 studies)

Knee OA is a painful degenerative disease affecting up to 6% of adults. Its prevalence increases with age, with over 40% of people aged over 75 years old being affected (190). Knee OA is associated with reduced strength of knee extensors and loss of muscle mass (191). It was shown that these patients have increased MFI of thigh muscles. It was thus suggested that the MFI of the quadriceps muscle may serve as a marker of the symptomatic and structural severity of the degenerative process (192). One study showed that sporting activities and lifestyle changes may decrease the MFI of the vastus medialis muscle, which is directly associated with a reduction in annual loss of cartilage volume and a reduction of the risk of knee OA (193).

Hip pain and arthroplasty (6 studies)

Hip muscles have a crucial role in maintaining hip joint mobility and stability, and in accomplishing activities of daily living such as standing, running, and walking (194). Hip muscle degeneration and especially the gluteus maximus can lead to hip joint diseases and accidental falls in the elderly (195,196). It was shown that a high MFI of hip muscles is associated with hip pain after physical activity. In addition, high fat infiltration of gluteus maximus was found to be associated with low physical activity, female gender, and obesity, even in healthy subjects (75). THA represents one of the most common procedures in patients with hip pain due to a variety of conditions. It can relieve pain, restore hip joint function, and improve quality of life (197). Patients with a history of high MFI of hip muscles presented a poor post-surgical outcome following THA (16,22).

Sarcopenia (2 studies)

Sarcopenia refers to the progressive loss of both muscle mass and function (198), appears commonly with aging and leads to an increased risk of falling and fractures among elderly patients. High intensity resistance training (HIRT) is strongly recommended by international guidelines, as it can improve muscle function and strength (199). MFI in thigh muscles after HIRT in elderly subjects was evaluated and was found to reduce sarcopenia and build lean muscle mass (54,200). Although only two studies have explicitly explored sarcopenia, investigations of the increase of MFI with age have been explored in healthy subjects.

Healthy subjects (27 studies)

Studies involving healthy subjects assessed the evolution of MFI either during the aging process, between young and older adults, or between genders. The association between bone mass density (BMD) and MFI as well as the integration of new automated algorithms for muscle segmentation were studied.

Through the aging process, MFI was found to increase mainly in the thigh and spine muscles (1,2,55,73,102,115). It was found to depend on gender and muscle groups (2,73). Higher MFI was more frequent in women than men and was found to be correlated to bone density loss (51,129). In thigh muscles, the muscles with most infiltration were the gracilis, the sartorius and the short head of biceps femoris (73).

Discussion

The evaluation of MFI using MRI is useful to establishing an accurate diagnosis, monitor disease progression, predict the severity of the disease, or to evaluate treatments in the setting of endocrinological diseases and neuromuscular or musculoskeletal disorders. This study presents a review of the methods available to evaluate MFI using MRI and their applications in multiple pathologies.

Qualitative methods, such as the Goutallier classification, are largely used in the context of rotator cuff tears and LBP. Based on a 2-to-4 score grading scale, they are known for their ease of use by clinicians. They can be applied to conventional T2-weighted images that are commonly prescribed by physicians for diagnostic purposes. However, they are used in only 20% of the referenced studies and are not subject-specific. Since the validity and reliability of these methods were scarcely evaluated, their clinical application should be approached with caution. Most of the investigations used quantitative methods (80%) requiring muscle segmentation, with the Dixon technique being the most widely used (45%). Studies utilizing the Dixon technique employed various modalities (2PD, 3PD, PDFF, etc.), and several software were used to quantify the percentage of fat signal in a specific ROI. Based on the needs and interests identified in the literature, automated muscle segmentation and calculation of MFI can be of utmost importance for physicians and researchers.

The evaluation of MFI seems to be particularly relevant in neuromuscular diseases, especially when evaluating the response to treatment, or objectively monitoring disease progression. It was also shown that MFI was predictive of the severity of these pathologies.

When evaluated for musculoskeletal diseases, MFI was correlated with the degree of shoulder range of motion in the presence of rotator cuff tears and failure of rotator cuff repair (60,184-186). MFI in the quadriceps was related to knee OA (193,201), whereas MFI in the hip muscles, especially the glutei, was related to post-operative complications after total hip replacement (16,22). Moreover, in the presence of LBP, MFI was more prevalent at the distal lumbar levels in all paraspinal muscles.

It is important to mention that muscles’ evaluation during physical examination is of paramount importance in clinical routine. The evaluation of MFI can give an additional insight, especially in the presence of complicated pathologies. For instance, in the setting of ASD, the MFI of the erector spinae was related to the severity of spinal malalignment both in the coronal and sagittal planes. Increased MFI in the trunk extensors was related to increased anterior shift of the trunk and pelvic retroversion. Complications and failure are known to occur in more than 50% of these cases (202). Several studies have attempted to understand the causes behind surgical failure that might occur due to over-correction of spinal malalignment (203,204). Spinal fusion is usually decided after a clinical examination of the patient and the evaluation of full standing X-rays on which spinopelvic and global alignment parameters are calculated. However, statis evaluations do not accurately represent activities of daily living, which emphasizes the importance of evaluating patients in other functional positions and during movement. More recently, studies have shown interest in quantifying the biomechanics of the spine in ASD patients in the sitting position and during movement (205-207), with recent reports exploring the risk of post-surgical mechanical complications based on the evaluation of spine flexibility (208). In order to complete the biomechanical assessment of the spine in ASD patients, an evaluation of the muscles, and more precisely the quality of the tissue, is important in order to estimate whether spinal fusion can be mechanically supported by the soft tissues. Thus, calculating the MFI can be a valuable predictor of muscle quality in ASD patients. As such, studies showed that increased MFI in the trunk was related to post-operative complications and increased risk of revision surgeries (20,209).

One of the major limitations of this study is related to the fact that the literature search did not use synonymous or Boolean algorithm. This may have resulted in overlooking some relevant articles. However, we believe this study still presents a relatively comprehensive and detailed review on the evaluation methods of MFI using MRI and their clinical applications (detailed literature table available in https://cdn.amegroups.cn/static/public/qims-24-177-1.xlsx). While the main objective of this review was to present the available techniques to evaluate MFI using MRI and the associated pathologies, this study did not focus on the correlation study between MFI and the severity of the pathology. General associations were presented in the text, and more in-depth analysis can be consulted in the listed articles.

Conclusions

The evaluation of MFI is important for diagnosis and can be representative of disease progression in several endocrinological, neuromuscular, or musculoskeletal diseases. The use of MFI assessment tools in the clinical setting seems to be important in spinal disorders, especially in ASD, to predict post-surgical complications. This review also showed the importance of automation of MFI assessment using quantitative MRI images, particularly Dixon sequences. Such automation could democratize the calculation of MFI, make its use easier in clinical settings and open MFI assessment applications to other diseases.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-177/rc

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-177/coif). A.A. is a consultant at Olea Medical. J.R., A.M. and S.C. are employees at Olea Medical in the research and scientific departments. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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