Quantifying fat and lean muscle in the lower legs of women with knee osteoarthritis using two different MRI systems

Utility of multidetector computed tomography quantitative measurements in identifying sarcopenia: a propensity score matched study

OBJECTIVE

To evaluate the utility of multidetector computed tomography MDCT quantitative measurements in identifying sarcopenia.

MATERIALS AND METHODS

The clinical data and MDCT images of 64 patients of sarcopenia and 184 non-sarcopenic participants between October 2020 and January 2021were retrospectively analyzed. Propensity score matching was used to match the sarcopenic patients with the non-sarcopenic participants. Two radiologists independently measured the cross-sectional area (CSA) of skeletal muscle and intramuscular fat tissue and CT density of skeletal muscle at the middle L3 vertebral level on CT images of all participants. Intra-observer agreement was evaluated via intraclass correlation coefficients (ICC). A receiver operating characteristic (ROC) curve was built for each variable. Correlations between CT parameters and clinical data were assessed via Pearson or Spearman correlation coefficient.

RESULTS

A total of 74 participants (mean age 72 ± 4 years, range 66-85 years; 38 men and 36 women) were included, comprising 37 sarcopenic patients and 37 non-sarcopenic participants. There were no significant intergroup differences regarding age, sex ratio, and body mass index (BMI) (P < 0.05). The CSA and density of skeletal muscle measured by two radiologists were reliable (ICC ≥ 0.75, P < 0.001). Compared with the sarcopenic group, the non-sarcopenic group had a significantly greater CSA and CT density of the total skeletal muscle (TSM) and paraspinal skeletal muscle (PSM) and skeletal muscle index at L3 level (L3 SMI) (P < 0.05). The fat infiltration ratio (FIR) of TSM, PSM, and psoas muscle was significantly higher in the sarcopenic group than that in non-sarcopenic participants (P < 0.05). ROC curve analysis showed the PSM FIR + PSM CT density (PSM D) had the best predictive value for sarcopenia (AUC = 0.836). The PSM FIR and age were moderately positively correlated (r = 0.410, P < 0.001).

CONCLUSION

Fat infiltration of skeletal muscle had better predictive value than L3 SMI in the diagnosis of sarcopenic. The PSM FIR + PSMD had the best predictive value for sarcopenia, which was moderately positively correlated with age.

A Valid and Precise Semiautomated Method for Quantifying Intermuscular Fat Intramuscular Fat in Lower Leg Magnetic Resonance Images

The accumulation of INTERmuscular fat and INTRAmuscular fat (IMF) has been a hallmark of individuals with diabetes, those with mobility impairments such as spinal cord injuries and is known to increase with aging. An elevated amount of IMF has been associated with fractures and frailty, but the imprecision of IMF measurement has so far limited the ability to observe more consistent clinical associations. Magnetic resonance imaging has been recognized as the gold standard for portraying these features, yet reliable methods for quantifying IMF on magnetic resonance imaging is far from standardized. Previous investigators used manual segmentation guided by histogram-based region-growing, but these techniques are subjective and have not demonstrated reliability. Others applied fuzzy classification, machine learning, and atlas-based segmentation methods, but each is limited by the complexity of implementation or by the need for a learning set, which must be established each time a new disease cohort is examined. In this paper, a simple convergent iterative threshold-optimizing algorithm was explored. The goal of the algorithm is to enable IMF quantification from plain fast spin echo (FSE) T1-weighted MR images or from water-saturated images. The algorithm can be programmed into Matlab easily, and is semiautomated, thus minimizing the subjectivity of threshold-selection. In 110 participants from 3 cohort studies, IMF area measurement demonstrated a high degree of reproducibility with errors well within the 5% benchmark for intraobserver, interobserver, and test-retest analyses; in contrast to manual segmentation which already yielded over 20% error for intraobserver analysis. This algorithm showed validity against manual segmentations (r > 0.85). The simplicity of this technique lends itself to be applied to fast spin echo images commonly ordered as part of standard of care and does not require more advanced fat-water separated images.

Bone Marrow and Muscle Fat Infiltration Are Correlated among Postmenopausal Women With Osteoporosis: The AMBERS Cohort Study

Bone and muscle have shown to interact, but little is known about fat within bone and muscle. Clinical studies have isolated fat within bone and muscle using MRI. In this cross-sectional study, we hypothesized that bone marrow adiposity and muscle adiposity are related and that this relationship is associated with osteoporosis. Postmenopausal women aged 60 to 85 years were recruited as part of the Appendicular Muscle and Bone Extension Research Study (AMBERS). Participants completed dual-energy X-ray absorptiometry (DXA) of the hip and spine to diagnose osteoporosis. Muscle adiposity was measured with MRI at the 66% site of the leg. Fat segmentation was achieved using a semi-automated iterative threshold-optimizing algorithm (error < 5%). Peripheral quantitative computed tomography measured marrow density of the 4% distal tibia (surrogate for marrow fat) by threshold-based, edge-detection segmentations and by examining residuals from trabecular bone density regressed on trabecular tissue mineral density. Muscle adiposity from MRI was regressed on marrow density using linear regression. Models were further examined with an interaction with osteoporosis status. Among 312 women (aged 75.4 ± 5.9 years, body mass index [BMI] 29.5 ± 5.7 kg/m² ), a larger amount of muscle fat was associated with lower marrow density at the 66% mid-tibia (B = 84.08 [27.56], p = 0.002) and at the 4% distal tibia (B = 129.17 [55.96], p = 0.022) after accounting for age, height, weight, average daily energy expenditure, hypertension, and diabetes. Interactions of this relationship with osteoporosis status were also significant. Upon probing these interactions, the relationships were significant only in women with osteoporosis but not in those without osteoporosis. Fat from bone marrow and muscle may be related to one another through the same phenomenon, which is likely also responsible for osteoporosis, but independent of hypertension and diabetes. More research should focus on the potential abnormalities in muscle and bone fat metabolism and mesenchymal cell commitment to fat within patients with osteoporosis. © 2019 American Society for Bone and Mineral Research.

A Comparison of Peripheral Imaging Technologies for Bone and Muscle Quantification: A Review of Segmentation Techniques

Musculoskeletal science has developed many overlapping branches, necessitating specialists from 1 area of focus to often require the expertise in others. In terms of imaging, this means obtaining a comprehensive illustration of bone, muscle, and fat tissues. There is currently a lack of a reliable resource for end users to learn about these tissues' imaging and quantification techniques together. An improved understanding of these tissues has been an important progression toward better prediction of disease outcomes and better elucidation of their interaction with frailty, aging, and metabolic disorders. Over the last decade, there have been major advances into the image acquisition and segmentation of bone, muscle, and fat features using computed tomography (CT), magnetic resonance imaging (MRI), and peripheral modules of these systems. Dedicated peripheral quantitative musculoskeletal imaging systems have paved the way for mobile research units, lower cost clinical research facilities, and improved resolution per unit cost paid. The purpose of this review was to detail the segmentation techniques available for each of these peripheral CT and MRI modalities and to describe advances in segmentation methods as applied to study longitudinal changes and treatment-related dynamics. Although the peripheral CT units described herein have established feasible standardized protocols that users have adopted globally, there remain challenges in standardizing MRI protocols for bone and muscle imaging.

MRI quantitation of abdominal skeletal muscle correlates with CT-based analysis: implications for sarcopenia measurement

Sarcopenia is associated with poor outcomes in a variety of conditions, including malignancy. Abdominal skeletal muscle area (SMA) segmentation using computed tomography (CT) has been shown to be an accurate surrogate for identifying sarcopenia. While magnetic resonance imaging (MRI) segmentation of SMA has been validated in cadaver limbs, few studies have validated abdominal SMA segmentation using MRI at lumbar level mid-L3. Our objective was to assess the reproducibility and concordance of CT and MRI segmentation analyses of SMA at mid-L3. This retrospective analysis included a random sample of 10 patients with renal cell carcinoma (RCC) and CT abdomen/pelvis, used to assess intra-observer variability of SMA measurements using CT. An additional sample of 9 patients with RCC and both CT and T2-weighted (T2w) MRI abdomen/pelvis was used to assess intra-observer variability of SMA using MRI and concordance of SMA between MRI and CT. SMA was segmented using Slice-O-Matic. SMA reproducibility was assessed using intraclass correlation coefficient (ICC). SMA concordance was analyzed using Bland-Altman plot and Pearson correlation coefficient. The intra-observer variability of CT and MRI SMA at mid-L3 was low, with ICC of 0.998 and 0.985, respectively. Bland-Altman analysis revealed bias of 0.74% for T2w MRI over CT. The Pearson correlation coefficient was 0.997 (p < 0.0001), demonstrating strong correlation between CT and T2w MRI. Abdominal SMA at mid-L3 is reproducibly segmented for both CT and T2w MRI, with strong correlation between the 2 modalities. T2w MRI can be used interchangeably with CT for assessment of SMA and sarcopenia. This finding has important clinical implications.

Changes in intra- and extramyocellular lipids in morbidly obese patients after non-surgical weight loss-a pilot study using magnetic resonance spectroscopy

BACKGROUND & AIMS

Lipid accumulation in muscles is common in obesity and associated with increased risks for insulin resistance. However, the impact of weight loss and exercise on muscle fat content is not clear due to inconsistent data. We used magnetic resonance spectroscopy (MRS) to compare the intra- (IMCL) and extramyocellular lipid (EMCL) proportions in the musculus tibialis anterior of extremely obese patients before and after weight loss.

METHODS

Nineteen non-diabetic patients with a Body Mass Index (BMI) ≥ 40 kg/m² who participated in a non-surgical multimodal weight loss program were recruited. Metabolite ratios of IMCL and EMCL (metabolite/creatine) were assessed using 3 T ¹H-MRS before therapy and after 6 months. The primary outcome comprised changes in IMCL and body cell mass. Additionally, changes of IMCL and EMCL were compared with changes in standard clinical measures, i.e., BMI, body composition, blood pressure and functional exercise capacity.

RESULTS

After 6 months the relative weight loss was 24.8% (127.6 kg, 48.5 kg/m² vs. 96 kg, 36.5 kg/m²). All standard clinical measures were significantly improved. MRS data from 10 patients provided complete and evaluable data sets. IMCL was reduced by nearly 50% (p < .05). The reduction of EMCL was not significant (p = .106). An explorative correlation analysis between changes of IMCL and changes of the standard measures did not reveal any significance.

CONCLUSIONS

Significant reductions of IMCL following a successful conservative weight loss intervention are detectable by using MRS. These changes may have the potential to serve as an additional marker of clinically meaningful obesity treatment.