Quantitative magnetic resonance imaging of paraspinal muscles for assessing chronic non-specific low back pain in young adults: a prospective case-control study

PURPOSE

This study aimed to investigate the application of quantitative magnetic resonance imaging of paraspinal muscles in assessing the young CNLBP with unilateral symptom.

METHODS

This prospective study enrolled 107 young individuals with unilateral symptomatic CNLBP (56 cases) and a normal cohort (51 cases). All subjects underwent conventional lumbar sequences, T2 mapping, and IDEAL-IQ scans at 3T. T2 values and fat fraction (FF) of bilateral multifidus (mid-levels of L2-L5 vertebrae) and erector spinae (mid-levels of L1-L4 vertebrae) were measured. CNLBP severity, Japanese Orthopedic Association (JOA) score, and Visual Analogue Scale (VAS) score were recorded. Wilcoxon signed-rank tests were used to compare parameter differences between painful and non-painful sides in the case group. Mann-Whitney U tests were employed to evaluate differences between the case and normal group. Logistic regression analysis was conducted to identify predictive factors and to establish a combined model.

RESULTS

In the case group, erector spinae FF values (L4 level), erector spinae T2 values (L1, L2, and L4 levels), and multifidus T2 values (L4 and L5 levels) were higher on the painful side (P<0.05). Multifidus T2 values (L5 level) and FF values (L2-L5 levels) were higher in the case group compared to the normal group (P<0.05). The optimal performance in differentiating young CNLBP was the combination of L5 level multifidus T2 value with FF (AUC = 91.81%). Negative correlation existed between T2 values and FF of multifidus at L5 level and JOA scores (r=-0.41, P < 0.05), and positive correlation with VAS scores (r = 0.46, P < 0.05).

CONCLUSION

The combination of T2 value and FF may provide deeper insights into the pathological alterations of paraspinal muscles in young CNLBP, providing an important imaging basis for clinical judgment and preventive treatment of non-painful side in unilateral symptomatic patients.

Advancements in sarcopenia diagnosis: from imaging techniques to non-radiation assessments

Sarcopenia is a prevalent condition with significant clinical implications, and it is expected to escalate globally, demanding for effective diagnostic strategies, possibly at an early stage of the disease. Imaging techniques play a pivotal role in comprehensively evaluating sarcopenia, offering insights into both muscle quantity and quality. Among all the imaging techniques currently used for the diagnosis and follow up of sarcopenia, it is possible to distinguish two classes: Rx based techniques, using ionizing radiations, and non-invasive techniques, which are based on the use of safe and low risk diagnostic procedures. Dual-energy x-ray Absorptiometry and Computed Tomography, while widely utilized, entail radiation exposure concerns. Ultrasound imaging offers portability, real-time imaging, and absence of ionizing radiation, making it a promising tool Magnetic Resonance Imaging, particularly T1-weighted and Dixon sequences, provides cross- sectional and high-resolution images and fat-water separation capabilities, facilitating precise sarcopenia quantification. Bioelectrical Impedance Analysis (BIA), a non-invasive technique, estimates body composition, including muscle mass, albeit influenced by hydration status. Standardized protocols, such as those proposed by the Sarcopenia through Ultrasound (SARCUS) Working Group, are imperative for ensuring consistency across assessments. Future research should focus on refining these techniques and harnessing the potential of radiomics and artificial intelligence to enhance diagnostic accuracy and prognostic capabilities in sarcopenia.

Positional contrastive learning for improved thigh muscle segmentation in MR images

The accurate segmentation of individual muscles is essential for quantitative MRI analysis of thigh images. Deep learning methods have achieved state-of-the-art results in segmentation, but they require large numbers of labeled data to perform well. However, labeling individual thigh muscles slice by slice for numerous volumes is a laborious and time-consuming task, which limits the availability of annotated datasets. To address this challenge, self-supervised learning (SSL) emerges as a promising technique to enhance model performance by pretraining the model on unlabeled data. A recent approach, called positional contrastive learning, exploits the information given by the axial position of the slices to learn features transferable on the segmentation task. The aim of this work was to propose positional contrastive SSL for the segmentation of individual thigh muscles from MRI acquisitions in a population of elderly healthy subjects and to evaluate it on different levels of limited annotated data. An unlabeled dataset of 72 T1w MRI thigh acquisitions was available for SSL pretraining, while a labeled dataset of 52 volumes was employed for the final segmentation task, split into training and test sets. The effectiveness of SSL pretraining to fine-tune a U-Net architecture for thigh muscle segmentation was compared with that of a randomly initialized model (RND), considering an increasing number of annotated volumes (S = 1, 2, 5, 10, 20, 30, 40). Our results demonstrated that SSL yields substantial improvements in Dice similarity coefficient (DSC) when using a very limited number of labeled volumes (e.g., for S  = 1, DSC 0.631 versus 0.530 for SSL and RND, respectively). Moreover, enhancements are achievable even when utilizing the full number of labeled subjects, with DSC = 0.927 for SSL and 0.924 for RND. In conclusion, positional contrastive SSL was effective in obtaining more accurate thigh muscle segmentation, even with a very low number of labeled data, with a potential impact of speeding up the annotation process in clinics.

Use of two-point and six-point Dixon MRI for fat fraction analysis in the lumbar vertebral bodies and paraspinal muscles in healthy dogs: comparison with magnetic resonance spectroscopy

Introduction

Fatty degeneration of the vertebral bodies and paravertebral muscles is associated with the presence, severity, and prognosis of spinal disease such as intervertebral disc degeneration. Therefore, the fat fraction (FF) of the vertebral bodies and paraspinal muscles has been considered a potential biomarker for assessing the pathophysiology, progression, and treatment response of spinal disease. Magnetic resonance spectroscopy (MRS) is considered the reference standard for fat quantification; however, it has limitations of a long acquisition time and is technically demanding. Chemical shift-encoding water-fat imaging, called the Dixon method, has recently been applied for rapid fat quantification with high spatial resolution. However, the Dixon method has not been validated in veterinary medicine, and we hypothesized that the Dixon method would provide a comparable assessment of the FF to MRS but would be faster and easier to implement in dogs.

Methods

In this prospective study, we assessed the FF of the lumbar vertebral bodies and paravertebral muscles from the first to sixth lumbar vertebrae using MRS, the two-point Dixon method (LAVA-FLEX), and the six-point Dixon method (IDEAL-IQ) and compared these techniques.

Results and discussion

The FFs of vertebral bodies and paravertebral muscles derived from LAVA-FLEX and IDEAL-IQ showed significant correlations and agreement with those obtained with MRS. In particular, the FFs obtained with IDEAL-IQ showed higher correlations and better agreement with those obtained with MRS than those derived by LAVA-FLEX. Both Dixon methods showed excellent intra- and interobserver reproducibility for FF analysis of the vertebral bodies and paraspinal muscles. However, the test-retest repeatability of vertebral body and paraspinal muscle FF analysis was low for all three sequences, especially for the paraspinal muscles. The results of this study showed that LAVA-FLEX and IDEAL-IQ have high reproducibility and that their findings were highly correlated with the FFs of the lumber vertebral bodies and paraspinal muscles determined by MRS in dogs. The FF analysis could be performed much more easily and quickly using LAVA-FLEX and IDEAL-IQ than using MRS. In conclusion, LAVA-FLEX and IDEAL-IQ can be used as routine procedures in spinal magnetic resonance imaging in dogs for FF analysis of the vertebral bodies and paraspinal muscles.

Magnetic Resonance Imaging Biomarkers of Muscle

This review is focused on the current status of quantitative MRI (qMRI) of skeletal muscle. The first section covers the techniques of qMRI in muscle with the focus on each quantitative parameter, the corresponding imaging sequence, discussion of the relation of the measured parameter to underlying physiology/pathophysiology, the image processing and analysis approaches, and studies on normal subjects. We cover the more established parametric mapping from T1-weighted imaging for morphometrics including image segmentation, proton density fat fraction, T2 mapping, and diffusion tensor imaging to emerging qMRI features such as magnetization transfer including ultralow TE imaging for macromolecular fraction, and strain mapping. The second section is a summary of current clinical applications of qMRI of muscle; the intent is to demonstrate the utility of qMRI in different disease states of the muscle rather than a complete comprehensive survey.

Significant age-related differences between lower leg muscles of older and younger female subjects detected by ultrashort echo time magnetization transfer modeling

Magnetization transfer (MT) magnetic resonance imaging (MRI) can be used to estimate the fraction of water and macromolecular proton pools in tissues. MT modeling paired with ultrashort echo time acquisition (UTE-MT modeling) has been proposed to improve the evaluation of the myotendinous junction and fibrosis in muscle tissues, which the latter increases with aging. This study aimed to determine if the UTE-MT modeling technique is sensitive to age-related changes in the skeletal muscles of the lower leg. Institutional review board approval was obtained, and all recruited subjects provided written informed consent. The legs of 31 healthy younger (28.1 ± 6.1 years old, BMI = 22.3 ± 3.5) and 20 older (74.7 ± 5.5 years old, BMI = 26.7 ± 5.9) female subjects were imaged using UTE sequences on a 3 T MRI scanner. MT ratio (MTR), macromolecular fraction (MMF), macromolecular T2 (T2-MM), and water T2 (T2-W) were calculated using UTE-MT modeling for the anterior tibialis (ATM), posterior tibialis (PTM), soleus (SM), and combined lateral muscles. Results were compared between groups using the Wilcoxon rank sum test. Three independent observers selected regions of interest (ROIs) and processed UTE-MRI images separately, and the intraclass correlation coefficient (ICC) was calculated for a reproducibility study. Significantly lower mean MTR and MMF values were present in the older compared with the younger group in all studied lower leg muscles. T2-MM showed significantly lower values in the older group only for PTM and SM muscles. In contrast, T2-W showed significantly higher values in the older group. The age-related differences were more pronounced for MMF (-17 to -19%) and T2-W (+20 to 47%) measurements in all muscle groups compared with other investigated MR measures. ICCs were higher than 0.93, indicating excellent consistency between the ROI selection and MRI measurements of independent readers. As demonstrated by significant differences between younger and older groups, this research emphasizes the potential of UTE-MT MRI techniques in evaluating age-related skeletal muscle changes.

Computed tomography (CT)-based skeletal muscle vertebral-related index to assess low muscle mass in patients with non-small cell lung cancer

Background

Patients with lung cancer accompanied by sarcopenia may have a poor prognosis. Normally, low muscle mass associated with sarcopenia is assessed using the skeletal muscle index (SMI). It remains unclear whether the standardized skeletal muscle area (SMA) using 2-dimensional (2D) vertebral metrics (called the skeletal muscle vertebral related index, SMVI) could substitute for SMI when it is missing. The aim of this study was to investigate the feasibility of SMVI as an alternative to SMI, and their associations with overall survival (OS) in patients with non-small cell lung cancer (NSCLC).

Methods

In this single-center study, a retrospective analysis was conducted on 433 NSCLC patients who underwent computed tomography (CT) scans. At the third lumbar vertebra (L3) level, measurements were taken for SMA, vertebral body area, transverse vertebral diameter (TVD), longitudinal vertebral diameter (LVD), and vertebral height (VH). The 4 SMVIs were skeletal muscle vertebral ratio (SMVR) (SMA/vertebral body area), skeletal muscle transverse vertebral diameter index (SMTVDI) (SMA/TVD2), skeletal muscle longitudinal vertebral diameter index (SMLVDI) (SMA/LVD2), and skeletal muscle vertebral height index (SMVHI) (SMA/VH2). The patients were categorized into low and high muscle mass groups based on SMI, and the differences in SMVIs between the 2 groups were compared to assess their correlation with SMI. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were utilized to assess the discriminatory ability. Kaplan-Meier curves were employed to compare the survival disparity between the 2 groups.

Results

We included 191 male and 242 female patients in this study. Compared to the high muscle mass group, patients in the low muscle mass group exhibited significantly lower SMVR, SMTVDI, SMLVDI, and SMVHI (all P<0.05). All 4 SMVIs showed a positive correlation with SMI, with Spearman correlation coefficients of 0.83, 0.76, 0.75, and 0.67, respectively (all P<0.001). The AUC for diagnosing low muscle mass was higher than 0.8 for all 4 SMVI parameters. The Kaplan-Meier curve revealed that the low-risk group had a better survival probability than the high-risk group in the SMVR, SMTVDI, and SMLVDI.

Conclusions

The SMVI functions as an alternative metric for evaluating skeletal muscle mass in the assessment of NSCLC based on SMI.

Non invasive techniques for direct muscle quality assessment after exercise intervention in older adults: a systematic review

BACKGROUND

The aging process induces neural and morphological changes in the human musculoskeletal system, leading to a decline in muscle mass, strength and quality. These alterations, coupled with shifts in muscle metabolism, underscore the essential role of physical exercise in maintaining and improving muscle quality in older adults. Muscle quality's morphological domain encompasses direct assessments of muscle microscopic and macroscopic aspects of muscle architecture and composition. Various tools exist to estimate muscle quality, each with specific technical requirements. However, due to the heterogeneity in both the studied population and study methodologies, there is a gap in the establishment of reference standards to determine which are the non-invasive and direct tools to assess muscle quality after exercise interventions. Therefore, the purpose of this review is to obtain an overview of the non-invasive tools used to measure muscle quality directly after exercise interventions in healthy older adults, as well as to assess the effects of exercise on muscle quality.

MAIN TEXT

To address the imperative of understanding and optimizing muscle quality in aging individuals, this review provides an overview of non-invasive tools employed to measure muscle quality directly after exercise interventions in healthy older adults, along with an assessment of the effects of exercise on muscle quality.

RESULTS

Thirty four studies were included. Several methods of direct muscle quality assessment were identified. Notably, 2 studies harnessed CT, 20 utilized US, 9 employed MRI, 2 opted for TMG, 2 adopted myotonometry, and 1 incorporated BIA, with several studies employing multiple tests. Exploring interventions, 26 studies focus on resistance exercise, 4 on aerobic training, and 5 on concurrent training.

CONCLUSIONS

There is significant diversity in the methods of direct assessment of muscle quality, mainly using ultrasound and magnetic resonance imaging; and a consistent positive trend in exercise interventions, indicating their efficacy in improving or preserving muscle quality. However, the lack of standardized assessment criteria poses a challenge given the diversity within the studied population and variations in methodologies.. These data emphasize the need to standardize assessment criteria and underscore the potential benefits of exercise interventions aimed at optimizing muscle quality.

Unveiling the Intricate Dance: How Cancer Orchestrates Muscle Wasting and Sarcopenia

Sarcopenia is a prevalent and clinically significant condition, particularly among older age groups and those with chronic disease. Patients with cancer frequently suffer from sarcopenia and progressive loss of muscle mass, strength, and function. The complex interplay between cancer and its treatment, including medical therapy, radiotherapy, and surgery, significantly contributes to the onset and worsening of sarcopenia. Cancer induces muscle wasting through inflammatory processes, metabolic alterations, and hormonal imbalance. Moreover, medical and radiation therapies exert direct toxic effects on muscles, contributing to the impairment of physical function. Loss of appetite, malnutrition, and physical inactivity further exacerbate muscle wasting in cancer patients. Imaging techniques are the cornerstones for sarcopenia diagnosis. Magnetic resonance imaging, computed tomography, and dual-energy X-ray absorptiometry provide valuable insights into muscle structure and quality. Although each modality has advantages and limitations, magnetic resonance imaging produces high-resolution images and provides dynamic information about muscle function. Despite these challenges, addressing sarcopenia is essential for optimizing treatment outcomes and improving survival rates in patients with cancer. This review explored the factors contributing to sarcopenia in oncologic patients, emphasizing the importance of early detection and comprehensive management strategies.

Factors influencing diffusion tensor imaging of knee cartilage in children ages 6-12 years: a prospective study

BACKGROUND

Magnetic resonance diffusion tensor imaging (DTI) has recently been used to evaluate the developing cartilage of children, but the influencing factors have not been well studied.

OBJECTIVE

The objective of this study was to investigate the influence of the diffusion gradient strength (b value), diffusion gradient direction, age and sex on knee cartilage DTI in healthy children aged 6-12 years.

MATERIALS AND METHODS

A total of 30 healthy child volunteers, with an average age of 8.9 ± 1.6 (mean ± standard deviation) years, were enrolled in this study. They were categorized into three groups according to their age range: 6-8 years, 8-10 years and 10-12 years, ensuring equal sex distribution in each group (5 boys and 5 girls). These volunteers underwent routine left knee joint magnetic resonance imaging (MRI) and serial DTI scans. DTI parameters were altered as follows: when b value = 600 s/mm2, diffusion gradient direction was set to 6, 15, 25, 35 and 45; and when diffusion gradient direction = 25, b value was set to 300, 600, 900 and 1200 s/mm2. The values of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were separately acquired using image post-processing techniques. The correlation between various b values, diffusion gradient directions, age and sex on the one hand and FA and ADC values on the other, was investigated.

RESULTS

(1) When diffusion gradient direction was fixed and the b value was varied, both FA and ADC exhibited a decreasing trend as the b value increased (P < 0.001). (2) When the b value was fixed and diffusion gradient direction was varied, the FA of knee cartilage showed a decreasing trend with increasing diffusion gradient direction (P < 0.001). (3) The FA value increased with age (P < 0.05).

CONCLUSION

The b value, diffusion gradient direction value and age exert a significant impact on both FA and ADC values in MR DTI of knee cartilage in children aged 6-12 years. In order to obtain a stable DTI, it is recommended to select a b value ≥ 600 s/mm2 and a diffusion gradient direction ≥ 25 during scanning.

Defining and Addressing Research Priorities in Cancer Cachexia through Transdisciplinary Collaboration

For many patients, the cancer continuum includes a syndrome known as cancer-associated cachexia (CAC), which encompasses the unintended loss of body weight and muscle mass, and is often associated with fat loss, decreased appetite, lower tolerance and poorer response to treatment, poor quality of life, and reduced survival. Unfortunately, there are no effective therapeutic interventions to completely reverse cancer cachexia and no FDA-approved pharmacologic agents; hence, new approaches are urgently needed. In May of 2022, researchers and clinicians from Moffitt Cancer Center held an inaugural retreat on CAC that aimed to review the state of the science, identify knowledge gaps and research priorities, and foster transdisciplinary collaborative research projects. This review summarizes research priorities that emerged from the retreat, examples of ongoing collaborations, and opportunities to move science forward. The highest priorities identified include the need to (1) evaluate patient-reported outcome (PRO) measures obtained in clinical practice and assess their use in improving CAC-related outcomes; (2) identify biomarkers (imaging, molecular, and/or behavioral) and novel analytic approaches to accurately predict the early onset of CAC and its progression; and (3) develop and test interventions (pharmacologic, nutritional, exercise-based, and through mathematical modeling) to prevent CAC progression and improve associated symptoms and outcomes.

Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications

Osteoarthritis (OA) is a disabling chronic disease involving the gradual degradation of joint structures causing pain and dysfunction. Magnetic resonance imaging (MRI) has been widely used as a non-invasive tool for assessing OA-related changes. While anatomical MRI is limited to the morphological assessment of the joint structures, quantitative MRI (qMRI) allows for the measurement of biophysical properties of the tissues at the molecular level. Quantitative MRI techniques have been employed to characterize tissues' structural integrity, biochemical content, and mechanical properties. Their applications extend to studying degenerative alterations, early OA detection, and evaluating therapeutic intervention. This article is a review of qMRI techniques for musculoskeletal tissue evaluation, with a particular emphasis on articular cartilage. The goal is to describe the underlying mechanism and primary limitations of the qMRI parameters, their association with the tissue physiological properties and their potential in detecting tissue degeneration leading to the development of OA with a primary focus on basic and preclinical research studies. Additionally, the review highlights some clinical applications of qMRI, discussing the role of texture-based radiomics and machine learning in advancing OA research.