We acknowledge grant support from the National Institutes of Health: NIH/NIAMS R01 AR050101 (BMD), NIH/NIAMS R01 AR057091 (BMD/JHP), NIH/NIBEB K25 EB013659 (RDD), and the Vanderbilt CTSA award RR024975. We also thank the reviewers for the comments and the subject for participating in these studies.

NOTE: The reader is reminded that all research involving human subjects must be approved by the local Institutional Review Board (IRB) for the Use of Human Subjects in Research. Research participants must be informed of the purpose, procedures, risks, and benefits of the proposed research; the availability of alternative treatments or procedures; the availability of remuneration; and of their rights to privacy and to withdraw their consent and discontinue their participation. Prior to the MRI testing session, an investigator must present a potential research participant with an IRB-approved informed consent document (ICD), explain its contents, and ask the potential research participant if he/she wishes to participate in the study. If so, the participant will have to sign and date the ICD prior to completing any of the steps of the protocol here.
1. Actions Prior to the Day of Testing
<ol>
	<li>Restrict Lifestyle Habits that Could Confound the Data
	<ol>
		<li>Instruct the participant not to perform moderate or heavy exercise during the 48 h prior to testing. Instruct the participant to abstain from over-the-counter medication and alcohol intake during the 24 h prior to testing. Instruct the participant to refrain from tobacco use or caffeine consumption during the 6 h prior to testing.</li>
		<li>Prior to testing, confirm that the participant has been compliant with these instructions.</li>
	</ol>
	</li>
	<li>Prepare the MRI System
	<ol>
		<li>Ensure the availability of all necessary equipment, as listed in the Table of Materials and Equipment.</li>
		<li>Define an MRI protocol; suggested parameters are found in Tables 1 - 5.</li>
	</ol>
	</li>
</ol>
2. Day of Testing: Prepare for MRI Data Acquisition
<ol>
	<li>Conduct Safety Screening
	<ol>
		<li>Screen for potential hazards in the MRI environment by having an MRI safety-trained healthcare worker present the research participant with a suitable MRI safety form, such as that found at www.mrisafety.com.</li>
		<li>If there any implanted magnetic or magnetically sensitive objects, ensure that they are safe for MRI scanning.</li>
	</ol>
	</li>
	<li>Prepare the MRI System
	<ol>
		<li>Ensure that all personnel have removed all magnetic and magnetically sensitive objects before entering the room that houses the MRI system. Conduct this check every time that someone enters the MRI room.</li>
		<li>Prepare the MRI system by placing the receive coil on the patient bed of the MRI system. Also, place a mattress with sheet and pillow with pillowcase on the bed. Have straps available to place around the thighs and bolsters or pillows to place under the knees.</li>
		<li>Start the software interface, enter patient data, and open the imaging protocol.</li>
	</ol>
	</li>
	<li>Position the Research Participant on the MRI Scanner Table
	<ol>
		<li>Observe the research participant as he/she checks his/her person and clothing for magnetically sensitive objects. Secure these objects outside of the MRI room in a lockable container. Enter the MRI room with the research participant immediately after completing this step.</li>
		<li>Position the participant on the patient bed in a supine, feet-first position. Place the body part to be imaged as close to the midline of the table as practical. Place bolsters or pillows under the knees to provide strain relief for the lower back and place a pillow under the head. To limit motion, gently but effectively secure the thigh, leg, and feet and ensure that the participant is comfortable.</li>
		<li>Place the RF receiver coil around the participant&#39;s thighs and connect it to the MRI system.</li>
	</ol>
	</li>
	<li>Instruct the Participant and Complete Final Pre-testing Steps
	<ol>
		<li>Give instructions about how to communicate with the investigators. Provide the participant with hearing protection and a signaling device that can be used to call for attention if needed. Instruct the participant of the need to stay still during and between all imaging sequences.</li>
		<li>Advance the patient bed into the MRI scanner such that the body part to be imaged is aligned to the center of the MRI scanner.</li>
		<li>After exiting the MRI room, confirm that the patient communication system is working and see that the participant is comfortable. Throughout the protocol, communicate regularly with the participant to ensure his/her comfort and compliance with instructions.</li>
	</ol>
	</li>
</ol>
3. Day of Testing: Acquire the MRI Data
<ol>
	<li>Preparatory Steps
	<ol>
		<li>As the MRI system determines the instrumental settings and calibrations prior to each imaging sequence (center frequency, receiver gain calibration, etc.), supervise these processes and ensure that each step is being performed correctly.</li>
		<li>Using a suitable software interface, acquire a set of localizer images (also known as pilot or scout images); using suggested parameters presented in Table 2.</li>
		<li>Determine where to place the center slice for qMRI data acquisitions, by identifying areas of damage and/or by referencing the slice position relative to reproducible anatomical landmarks.</li>
	</ol>
	</li>
	<li>Transmit and Receive Coil Calibration Steps
	<ol>
		<li>For these steps as well as all of the subsequent imaging steps, define region of anatomy in which to optimize the homogeneity of the static magnetic field (B0), a process known as &#34;shimming&#34;. See Figure 1A for the typical placement of the shimming volume of interest (VOI) used in the present studies.</li>
		<li>If the MRI scanner has a multi-element transmission coil, acquire an RF calibration dataset.</li>
		<li>If the MRI scanner has a multi-element receive coil, acquire a spatial sensitivity map of the coils.</li>
	</ol>
	</li>
	<li>Acquire Structural MRI Data
	<ol>
		<li>Acquire high resolution, multi-slice, T1-weighted images using a fast spin-echo (FSE) sequence; the imaging parameters used in the present studies are provided in Table 1.</li>
		<li>Acquire high resolution, multi-slice, T2-weighted images using an FSE sequence; the imaging parameters used in the present studies are provided in Table 2.</li>
	</ol>
	</li>
	<li>Acquire Data for Real-time Quality Control and Making Post-processing Corrections
	<ol>
		<li>Acquire three-dimensional (3D) multiple gradient-echo data for the calculation of B0 field maps. The imaging parameters used in the present studies are provided in Table 3.</li>
		<li>Examine the field maps to ensure that there are no deviations of greater than &#177;60 Hz (approximately 0.5 parts per million at 3 Tesla) across the image. If there are, adopt an alternative approach to shimming (different method, different placement of VOI, etc.).</li>
		<li>Acquire 3D data for the calculation of nutation angle maps. The imaging parameters used in the present studies are provided in Table 2.</li>
		<li>Examine the field maps to ensure that there are no areas that deviate excessively from the nominal nutation angle. For the RF pulses that are used in this protocol, deviations greater than &#177; 30% of the nominal nutation angle are considered excessive.</li>
	</ol>
	</li>
	<li>Acquire the qMRI Data
	<ol>
		<li>Acquire 3D images for calculation of the T1, using an inversion recovery sequence. The imaging parameters used in the present studies are presented in Table 3.</li>
		<li>Repeat the T1 measurement in the presence of fat signal suppression (FS; this parameter is abbreviated T1,FS).</li>
		<li>Acquire single-slice images for calculation of the T2, using a multiple spin-echo sequence.&#160;Use the imaging parameters presented in Table 3.</li>
		<li>Repeat the T2 measurement in the presence of FS (T2,FS).</li>
		<li>Acquire 3D images for calculation of qMT parameters, using a pulsed saturation sequence with FS and the imaging parameters given in Table 4.</li>
		<li>Acquire multi-slice data for calculation of diffusion-tensor parameters, using a series of diffusion-weighted images. The imaging parameters used in these studies are given in Table 4.</li>
		<li>Acquire 3D data for calculation of fat/water images, using a series of six gradient-echo images. The imaging parameters used in these studies are given in Table 5.</li>
	</ol>
	</li>
	<li>After Completing the qMRI Protocol
	<ol>
		<li>Ensure that all images are of suitable quality by examining them for potentially correctable artifacts and by measuring the sufficient signal-to-noise ratio.</li>
		<li>For each qMRI dataset, define several regions of interest (ROIs) in the image series and examine the signal as a function of the relevant parameter (for example, for the T1-dependent data acquired in steps 3.5.1 and 3.5.2, plot the signal as a function of TI and ensure that the data follow the inversion-recovery function listed below in step 4.1.2).</li>
		<li>After completing a personal screening for magnetically sensitive objects, enter the MRI room. Remove the participant from the magnet, remove all straps and padding, and assist the participant in exiting the MRI scanner and the MRI room.</li>
		<li>Transfer the data, using methods compliant with local health privacy laws, to a local workstation for processing; data may be exported as Digital Imaging Communications in Medicine (DICOM) files or in the vendor&#39;s proprietary format (the method used in this protocol).</li>
	</ol>
	</li>
</ol>
4. Analyze the qMRI Data
<ol>
	<li>Calculate the Parametric Maps
	<ol>
		<li>Use a computer program designed for scientific computing and image analysis. By examining a histogram of the signal intensities in the image, form a signal threshold-based image mask that delineates areas of signal from areas of noise. Complete the steps below for every pixel in the signal portions of the images.</li>
		<li>Analyze the T1 data by measuring the signal intensity S for each inversion time (TI). Then, fit the values for S to an inversion-recovery with reduced pre-delay model: 
		 
		<img alt="Equation1" src="/files/ftp_upload/52352/52352equation1.jpg" /> 
		 
		where M0 is a signal intensity representing the magnetization at the equilibrium state, Sf is the inversion ratio, and TD is the pre-delay time. Then, fit the data with FS to the same model, allowing determination of the longitudinal relaxation time constant with FS, T1,FS.</li>
		<li>Analyze theT2 data by measuring S at each TE. Then, fit the data to a mono-exponential decay model: 
		 
		<img alt="Equation2" src="/files/ftp_upload/52352/52352equation2.jpg" /> 
		 
		where N is the signal offset at baseline. The reader may also decide to fit the data to a multi-exponential model, such as that below: 
		 
		<img alt="Equation3" src="/files/ftp_upload/52352/52352equation3.jpg" /> 
		 
		where J is the number of exponential components and f and T2,j are the signal fraction and T2 values associated with the jth component. Or, the reader may use a non-negative least squares (NNLS) method3. In the latter case, the Multi-exponential Relaxation Analysis (MERA) toolbox33 is freely available; other programs are available too. Repeat these analyses for the data with and without FS.</li>
		<li>To analyze the qMT data, measure S for each irradiation power and frequency offset. Correct the nominal irradiation powers (represented by &#969;1 in the equation below) using the nutation angle maps. Correct the frequency offsets (&#916;f in the equation below) by using the B0 maps to adjust the applied offset frequencies. Then, fit the data to the following model34,35 
		 
		<img alt="Equation4" src="/files/ftp_upload/52352/52352equation4.jpg" /> 
		 
		where is the exchange rate from the macromolecular pool to the free water pool, is the longitudinal relaxation rate of the free water pool, is the longitudinal relaxation rate of the macromolecular pool (assumed to be 1 s-1), is the PSR, is the T2 of the free water pool, and &#969;1CWPE is the average power of the saturation pulse. The saturation rate of the longitudinal magnetization of the macromolecular pool, is described by a super-Lorentzian model, as described in work by Henkelman and colleagues34,35.</li>
		<li>To analyze the DTI data, first use an affine transformation algorithm36 to register each diffusion-weighted image to the corresponding non-diffusion weighted image. Then, for each pixel, measure the values for S in the non-diffusion weighted image and in each diffusion-weighted direction. Form a matrix composed of the diffusion encoding directions. Using multivariate, weighted least squares regression, regress the signal data on the diffusion encoding matrix and form D. Diagonalize D and perform a magnitude-sorting of the eigenvalues and their eigenvectors. Then calculate the mean diffusivity (MD) as: 
		 
		<img alt="Equation5" src="/files/ftp_upload/52352/52352equation5.jpg" /> 
		 
		where &#955;1, &#955;2, and &#955;3 are the eigenvalues of the diffusion tensor. Also calculate the fractional anisotropy (FA) as: 
		 
		<img alt="Equation6" src="/files/ftp_upload/52352/52352equation6.jpg" /> 
		&#160;</li>
		<li>Analyze the FWMRI data using a quantitative approach that separates water and fat signals based on chemical shift (such as the FattyRiot algorithm, available for free download from https://github.com/welcheb/FattyRiot).</li>
	</ol>
	</li>
	<li>Define Regions of Interest for Analysis
	<ol>
		<li>Specify ROIs on the anatomical images (by defining the boundaries of each muscle of interest). An example is shown in Figure 1.</li>
		<li>Resize the ROIs to match the matrix size of the qMRI images. As necessary, adjust the alignment of the ROIs to match the qMRI map (for example, if the participant moved between acquisitions, a translation of the ROI position might be required to avoid overlapping the muscle boundaries).</li>
		<li>Examine each ROI. If necessary, ensure that no pixels are included that contain partial volume artifacts, non-contractile tissue, and flow artifacts; please see Figure 1 for examples.</li>
		<li>Calculate the mean and standard deviation of the qMRI values in all pixels within the selected ROIs.</li>
	</ol>
	</li>
</ol>

None of the authors has a financial conflict of interest to report.

Muscle diseases such as the muscular dystrophies and idiopathic inflammatory myopathies constitute of group of diseases that are heterogeneous in etiology and, as individual entities, rare in their incidence. For example, Duchenne muscular dystrophy &#8212; the most common form of muscular dystrophy &#8212; has an incidence of 1 in 3,500 live male births37,38; dermatomyositis, to which this protocol has been applied, has an incidence of 1 in 100,00039. The higher collective incidence of these diseas...

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of living systems. QMRI requires that one adopt a biophysical model for the system, composed of the tissue of interest and an MRI pulse sequence. The pulse sequence is designed to sensitize the images&#39; signal intensities to the parameter of interest in the model. MRI signal properties (signal magnitude, frequency, and/or phase) are measured and analyzed according to the model. The goal is to produce an unbiased, quantitative estimate of a physical or biological parameter having continuously distributed, physical units of measurement. Often the equations describing the system are analyzed and fitted on a pixel-by-pixel basis, producing an image whose pixel values directly reflect the values of the variable. Such an image is referred to as a parametric map.
A common use of qMRI is the development and application of biomarkers. Biomarkers can be used to investigate a disease mechanism, establish a diagnosis, determine a prognosis, and/or assess a therapeutic response. They may take the form of the concentrations or activities of endogenous or exogenous molecules, a histological specimen, a physical quantity, or an internal image. Some general requirements of biomarkers are that they objectively measure a continuously distributed variable using physical units of measurement; have a clear, well understood relationship with the pathology of interest; are sensitive to improvement to and worsening of clinical state; and can be measured with suitable accuracy and precision. Non-invasive or minimally invasive biomarkers are particularly desirable, as they promote patient comfort and minimally disturb the pathology of interest.
A goal for developing image-based biomarkers for muscle disease is to reflect muscle disease in ways that are complementary to, more specific than, more spatially selective than, and/or less invasive than existing approaches. One particular advantage of qMRI in this regard is that it has the potential to integrate multiple types of information and thus potentially characterize many aspects of the disease process. This ability is very important in muscle diseases, which frequently exhibit a spatially variable, complex pathology that includes inflammation, necrosis and/or atrophy with fat replacement, fibrosis, disruption of the myofilament lattice (&#34;Z-disk streaming&#34;), and membrane damage. Another advantage of qMRI methods is that qualitative or semi-quantitative descriptions of contrast-based MR images reflect not just pathology, but also differences in image acquisition parameters, hardware, and human perception. An example of this last issue was demonstrated by Wokke et al., who showed that semi-quantitative assessments of fat infiltration are highly variable and frequently incorrect, when compared with quantitative fat/water MRI (FWMRI)1.
The protocol described here includes pulse sequences for measuring the longitudinal (T1) and transverse (T2) relaxation time constants, quantitative magnetization transfer (qMT) parameters, water diffusion coefficients using diffusion tensor MRI (DT-MRI), and muscle structure using structural images and FWMRI. T1 is measured by using an inversion recovery sequence, in which the net magnetization vector is inverted and its magnitude is sampled as the system returns to equilibrium. T2 is measured by repeatedly refocusing transverse magnetization using a train of refocusing pulses, such as the Carr-Purcell Meiboom-Gill (CPMG) method, and sampling the resulting spin-echoes. T1 and T2 data can be analyzed using non-linear curve-fitting methods that either assume a number of exponential components a priori (typically between one and three) or by using a linear inverse approach which fits the observed data to the sum of a large number of decaying exponentials, resulting in a spectrum of signal amplitudes. This approach requires a non-negative least square (NNLS) solution3, and typically includes additional regularization to produce stable results. T1 and T2 measurements have been widely used to study muscle diseases and injury4-9. T1 values are typically decreased in fat-infiltrated regions of muscle and elevated in inflamed regions4-6; T2 values are elevated in both fat-infiltrated and inflamed regions10.
QMT-MRI characterizes the free water and solid-like macromolecular proton pools in tissues by estimating the ratio of macromolecular to free water protons (the pool size ratio, PSR); the intrinsic relaxation rates of these pools; and the rates of exchange between them. Common qMT approaches include pulsed saturation11 and selective inversion recovery12,13 methods. The protocol below describes use of the pulsed saturation approach, which exploits the broad linewidth of the macromolecular proton signal, relative to the narrow linewidth of the water proton signal. By saturating the macromolecular signal at resonance frequencies sufficiently different from the water signal, the water signal is reduced as a result of magnetization transfer between the solid and free water proton pools. The data are analyzed using a quantitative biophysical model. QMT has been developed and applied in healthy muscles14,15, and a recent abstract appeared describing its implementation in muscle disease16. QMT has been used to study small animal models of muscle inflammation, wherein it has been shown that inflammation decreases the PSR17. Inasmuch as MT reflects both macromolecular and water contents, MT data may also reflect fibrosis18,19.
DT-MRI is used to quantify the anisotropic diffusion behavior of water molecules in tissues with ordered, elongated cells. In DT-MRI, water diffusion is measured in six or more different directions; these signals are then fitted to a tensor model20. The diffusion tensor, D, is diagonalized to obtain three eigenvalues (which are the three principal diffusivities) and three eigenvectors (which indicate the directions corresponding to the three diffusion coefficients). These and other quantitative indices derived from D provide information about tissue structure and orientation at a microscopic level. The diffusion properties of muscle, especially the third eigenvalue of D and the degree of diffusion anisotropy, reflect muscle inflammation17 and muscle damage due to experimental injury21, strain injury22, and disease23,24. Other potential influences on the diffusion properties of muscle include changes in cell diameter25 and membrane permeability changes.
Lastly, muscle atrophy, without or without macroscopic fat infiltration, is a pathological component of many muscle diseases. Muscle atrophy can be evaluated by using structural images to measure muscle cross-sectional area or volume and FW-MRI to assess fatty infiltration. Fat infiltration can be qualitatively described in T1- and T2-weighted images26, but fat and water signals are best measured by forming images that exploit the different resonance frequencies of fat and water protons27-29. Quantitative fat/water imaging methods have been applied in muscle diseases such as muscular dystrophy1,30,31, and can predict the loss of ambulation in these patients31.
The qMRI protocol described here uses all of these measurements to characterize muscle condition in the autoimmune inflammatory myopathies dermatomyositis (DM) and polymyositis (PM). Further details of the protocol, including its reproducibility, have been published previously32. The protocol includes standard pulse sequences as well as radiofrequency (RF) and magnetic field gradient objects specifically programmed on our systems. The authors anticipate that the protocol is also applicable in other neuromuscular disorders characterized by muscle atrophy, inflammation, and fat infiltration (such as the muscular dystrophies).

<table><tbody><tr><td>3T human MRI system</td><td>Philips Medical Systems (Best, the Netherlands)</td><td></td><td>Achieva/Intera</td></tr><tr><td>Cardiac phased array receive coil</td><td>Philips Medical Systems</td><td></td><td></td></tr><tr><td>Pillows, straps, bolsters, and other positioning devices</td><td></td><td></td><td></td></tr><tr><td>Computer with MATLAB software</td><td>The Mathworks, Inc (Natick, MA)</td><td></td><td>r. 2014</td></tr></tbody></table>

quantitative magnetic resonance imaging of skeletal muscle disease

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of living systems. Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using qMRI methods. The MRI acquisition protocol begins with localizer images (used to locate the position of the body and tissue of interest within the MRI system), quality control measurements of relevant magnetic field distributions, and structural imaging for general anatomical characterization. The qMRI portion of the protocol includes measurements of the longitudinal and transverse relaxation time constants (T1 and T2, respectively). Also acquired are diffusion-tensor MRI data, in which water diffusivity is measured and used to infer pathological processes such as edema. Quantitative magnetization transfer imaging is used to characterize the relative tissue content of macromolecular and free water protons. Lastly, fat-water MRI methods are used to characterize fibro-adipose tissue replacement of muscle. In addition to describing the data acquisition and analysis procedures, this paper also discusses the potential problems associated with these methods, the analysis and interpretation of the data, MRI safety, and strategies for artifact reduction and protocol optimization.

Figure 1 shows representative axial anatomical images acquired at the mid-thigh of a patient with polymyositis. Also shown is the location of the in-plane projection of the shim volume. Representative parameter maps for each qMRI method, all obtained from this same patient, are provided from Figures 2 - 7.
Figures 2A and 2B show the &#916;B0 ...

Watch this Scientific Journal Video about Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease at JoVE.com

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Neuromuscular diseases often exhibit a temporally varying, spatially heterogeneous, and multi-faceted pathology. The goal of this protocol is to characterize this pathology using non-invasive magnetic resonance imaging methods.

Quantitative magnetic resonance imaging (qMRI) describes the development and use of MRI to quantify physical, chemical, and/or biological properties of ...

quantitative-magnetic-resonance-imaging-of-skeletal-muscle-disease

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Medicine

19.4K Views.  Vanderbilt University.  Neuromusculaire aandoeningen vertonen vaak een tijdelijk wisselend, ruimtelijk heterogene en veelzijdige pathologie. Het doel van dit protocol is om deze pathologie niet-invasieve magnetische resonantie beeldvorming te karakteriseren. 

Video: Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking 

Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF. Current technologies for CMR are time consuming and difficult to implement in clinical practice. Feature tracking is a technology that can lead to more automization and robustness of quantitative analysis of medical images with less time consumption than comparable methods.
Methods: An automatic or manual input in a single phase serves as an initialization from which the system starts to track the displacement of individual patterns representing anatomical structures over time. The specialty of this method is that the images do not need to be manipulated in any way beforehand like e.g. tagging of CMR images.
Results: The method is very well suited for tracking muscular tissue and with this allowing quantitative elaboration of myocardium and also blood flow.
Conclusions: This new method offers a robust and time saving procedure to quantify myocardial tissue and blood with displacement, velocity and deformation parameters on regular sequences of CMR imaging. It therefore can be implemented in clinical practice.

Magnetic Resonance Derived Myocardial Strain Assessment Using Feature Tracking

An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that strain is a more sensitive and earlier marker for contractile dysfunction than the frequently used parameter EF.

Purpose: An accurate and practical method to measure parameters like strain in myocardial tissue is of great clinical value, since it has been shown, that ...

An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery

Muscle strains are one of the most common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and physical exam alone, however the clinical presentation can vary greatly depending on the extent of injury, the patient's pain tolerance, etc. In patients with muscle injury or muscle disease, assessment of muscle damage is typically limited to clinical signs, such as tenderness, strength, range of motion, and more recently, imaging studies. Biological markers, such as serum creatine kinase levels, are typically elevated with muscle injury, but their levels do not always correlate with the loss of force production. This is even true of histological findings from animals, which provide a "direct measure" of damage, but do not account for all the loss of function. Some have argued that the most comprehensive measure of the overall health of the muscle in contractile force. Because muscle injury is a random event that occurs under a variety of biomechanical conditions, it is difficult to study. Here, we describe an in vivo animal model to measure torque and to produce a reliable muscle injury. We also describe our model for measurement of force from an isolated muscle in situ. Furthermore, we describe our small animal MRI procedure.

An in vivo Rodent Model of Contraction-induced Injury and Non-invasive Monitoring of Recovery

An in vivo animal model of injury is described. The method takes advantage of the subcutaneous position of the fibular nerve. Velocity, timing of muscle activation, and arc of motion are all pre-determined and synchronized using commercial software. Post injury changes are monitored in vivo using MR imaging/spectroscopy.

Muscle strains are one of the most  common complaints treated by physicians. A muscle injury is typically diagnosed from the patient history and  physical ...

X-ray Diffraction of Intact Murine Skeletal Muscle as a Tool for Studying the Structural Basis of Muscle Disease

Transgenic mouse models have been important tools for studying the relationship of genotype to phenotype for human diseases including those of skeletal muscle. Mouse skeletal muscle has been shown to produce high quality X-ray diffraction patterns on third generation synchrotron beamlines providing an opportunity to link changes at the level of the genotype to functional phenotypes in health and disease by determining the structural consequences of genetic changes. We present detailed protocols for preparation of specimens, collecting the X-ray patterns and extracting relevant structural parameters from the X-ray patterns that may help guide experimenters wishing to perform such experiments for themselves.

We present detailed protocols for performing small-angle X-ray diffraction experiments using intact mouse skeletal muscles. With the wide availability of transgenic mouse models for human diseases, this experimental platform can form a useful test bed for elucidating the structural basis of genetic muscle diseases

Transgenic mouse models have been important tools for studying the relationship of genotype to phenotype for human diseases including those of skeletal ...

Developmental Biology

Noninvasive Assessment of Cardiac Abnormalities in Experimental Autoimmune Myocarditis by Magnetic Resonance Microscopy Imaging in the Mouse

Myocarditis is an inflammation of the myocardium, but only ~10% of those affected show clinical manifestations of the disease. To study the immune events of myocardial injuries, various mouse models of myocarditis have been widely used. This study involved experimental autoimmune myocarditis (EAM) induced with cardiac myosin heavy chain (Myhc)-&#945; 334-352 in A/J mice; the affected animals develop lymphocytic myocarditis but with no apparent clinical signs. In this model, the utility of magnetic resonance microscopy (MRM) as a non-invasive modality to determine the cardiac structural and functional changes in animals immunized with Myhc-&#945; 334-352 is shown. EAM and healthy mice were imaged using a 9.4 T (400 MHz) 89 mm vertical core bore scanner equipped with a 4 cm millipede radio-frequency imaging probe and 100 G/cm triple axis gradients. Cardiac images were acquired from anesthetized animals using a gradient-echo-based cine pulse sequence, and the animals were monitored by respiration and pulse oximetry. The analysis revealed an increase in the thickness of the ventricular wall in EAM mice, with a corresponding decrease in the interior diameter of ventricles, when compared with healthy mice. The data suggest that morphological and functional changes in the inflamed hearts can be non-invasively monitored by MRM in live animals. In conclusion, MRM offers an advantage of assessing the progression and regression of myocardial injuries in diseases caused by infectious agents, as well as response to therapies.

This study demonstrates the successful establishment of magnetic resonance microscopy imaging as a non-invasive tool to assess the cardiac abnormalities in mice affected with autoimmune myocarditis. The data indicate that the technique can be used to monitor the disease-progression in live animals.

Myocarditis is an inflammation of the myocardium, but only ~10% of those affected show clinical manifestations of the disease. To study the immune events ...

Phosphorus-31 Magnetic Resonance Spectroscopy: A Tool for Measuring In Vivo Mitochondrial Oxidative Phosphorylation Capacity in Human Skeletal Muscle

Skeletal muscle mitochondrial oxidative phosphorylation (OXPHOS) capacity, which is critically important in health and disease, can be measured in vivo and noninvasively in humans via phosphorus-31 magnetic resonance spectroscopy (31PMRS). However, the approach has not been widely adopted in translational and clinical research, with variations in methodology and limited guidance from the literature. Increased optimization, standardization, and dissemination of methods for in vivo 31PMRS would facilitate the development of targeted therapies to improve OXPHOS capacity and could ultimately favorably impact cardiovascular health. 31PMRS produces a noninvasive, in vivo measure of OXPHOS capacity in human skeletal muscle, as opposed to alternative measures obtained from explanted and potentially altered mitochondria via muscle biopsy. It relies upon only modest additional instrumentation beyond what is already in place on magnetic resonance scanners available for clinical and translational research at most institutions. In this work, we outline a method to measure in vivo skeletal muscle OXPHOS. The technique is demonstrated using a 1.5 Tesla whole-body MR scanner equipped with the suitable hardware and software for 31PMRS, and we explain a simple and robust protocol for in-magnet resistive exercise to rapidly fatigue the quadriceps muscle. Reproducibility and feasibility are demonstrated in volunteers as well as subjects over a wide range of functional capacities.

Phosphorus-31 Magnetic Resonance Spectroscopy: A Tool for Measuring In Vivo Mitochondrial Oxidative Phosphorylation Capacity in Human Skeletal Muscle

This work demonstrates the feasibility of an in vivo phosphorus-31 magnetic resonance spectroscopy (31PMRS) technique to quantify mitochondrial oxidative phosphorylation (OXPHOS) capacity in human skeletal muscle.

Skeletal muscle mitochondrial oxidative phosphorylation (OXPHOS) capacity, which is critically important in health and disease, can be measured in vivo ...

Measurements of Motor Function and Other Clinical Outcome Parameters in Ambulant Children with Duchenne Muscular Dystrophy

While the number of new treatment options tested in patients with Duchenne muscular dystrophy (DMD) is increasing, there is still no defining of the most reliable assessments regarding therapeutic efficacy. We present clinical and radiological outcome measures used in ambulatory patients participating in our trial &#34;Treatment with L-citrulline and metformin in Duchenne muscular dystrophy&#34;. The motor function measure is a validated test in patients with neuromuscular disorders that consists of 32 items and assesses all three dimensions of motor performance including standing and transfer (D1 subscore), axial and proximal motor function (D2 subscore), and distal motor function (D3 subscore). The test shows high intra- and inter-rater variability but only when strictly following guidelines of the materials, examination steps, and calculation of scores. The 6-minute walk test, timed 10-meter walk/run test, and supine-up time are commonly used timed functional tests that also sufficiently monitor changes in muscle function; however, they strongly depend on patient collaboration. Quantitative MRI is an objective and sensitive biomarker to detect subclinical changes, though the examination costs may be a reason for its limited use. In this study, a high correlation between all clinical assessments and quantitative MRI scans was found. The combinational use of these methods provides a better understanding about disease progression; however, longitudinal studies are needed to validate their reliability.

The aim of this study is to present the most reliable clinical outcome measures and their correlations with quantitative muscle MRI in ambulant patients with Duchenne muscular dystrophy.

While the number of new treatment options tested in patients with Duchenne muscular dystrophy (DMD) is increasing, there is still no defining of the most ...

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

The overall goal of this article is to demonstrate a state-of-the-art ultrahigh field (UHF) magnetic resonance (MR) protocol of the brain at 7.0 Tesla in multiple sclerosis (MS) patients. MS is a chronic inflammatory, demyelinating, neurodegenerative disease that is characterized by white and gray matter lesions. Detection of spatially and temporally disseminated T2-hyperintense lesions by the use of MRI at 1.5 T and 3 T represents a crucial diagnostic tool in clinical practice to establish accurate diagnosis of MS based on the current version of the 2017 McDonald criteria. However, the differentiation of MS lesions from brain white matter lesions of other origins can sometimes be challenging due to their resembling morphology at lower magnetic field strengths (typically 3 T). Ultrahigh field MR (UHF-MR) benefits from increased signal-to-noise ratio and enhanced spatial resolution, both key to superior imaging for more accurate and definitive diagnoses of subtle lesions. Hence, MRI at 7.0 T has shown encouraging results to overcome the challenges of MS differential diagnosis by providing MS-specific neuroimaging markers (e.g., central vein sign, hypointense rim structures and differentiation of MS grey matter lesions). These markers and others can be identified by other MR contrasts other than T1 and T2 (T2*, phase, diffusion) and substantially improve the differentiation of MS lesions from those occurring in other neuroinflammatory conditions such as neuromyelitis optica and Susac syndrome. In this article, we describe our current technical approach to study cerebral white and grey matter lesions in MS patients at 7.0 T using different MR acquisition methods. The up-to-date protocol includes the preparation of the MR setup including the radio-frequency coils customized for UHF-MR, standardized screening, safety and interview procedures with MS patients, patient positioning in the MR scanner and acquisition of dedicated brain scans tailored for examining MS.

Here, we present a protocol to acquire magnetic resonance (MR) images of multiple sclerosis (MS) patient brains at 7.0 Tesla. The protocol includes preparation of the setup including the radio-frequency coils, standardized interview procedures with MS patients, subject positioning in the MR scanner and MR data acquisition.

The overall goal of this article is to demonstrate a state-of-the-art ultrahigh field (UHF) magnetic resonance (MR) protocol of the brain at 7.0 Tesla in ...

Quantification of Skeletal Muscle Fatty Infiltration via Decellularization

Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration

Fatty infiltration is the accumulation of adipocytes between myofibers in skeletal muscle and is a prominent feature of many myopathies, metabolic disorders, and dystrophies. Clinically in human populations, fatty infiltration is assessed using noninvasive methods, including computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). Although some studies have used CT or MRI to quantify fatty infiltration in mouse muscle, costs and insufficient spatial resolution remain challenging. Other small animal methods utilize histology to visualize individual adipocytes; however, this methodology suffers from sampling bias in heterogeneous pathology. This protocol describes the methodology to qualitatively view and quantitatively measure fatty infiltration comprehensively throughout intact mouse muscle and at the level of individual adipocytes using decellularization. The protocol is not limited to specific muscles or specific species and can be extended to human biopsy. Additionally, gross qualitative and quantitative assessments can be made with standard laboratory equipment for little cost, making this procedure more accessible across research laboratories.

Author Spotlight: Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration  

The present study describes decellularization-based methodologies for visualizing and quantifying intramuscular adipose tissue (IMAT) deposition through intact muscle volume, as well as quantifying metrics of individual adipocytes that comprise IMAT.

Fatty infiltration is the accumulation of adipocytes between myofibers in skeletal muscle and is a prominent feature of many myopathies, metabolic ...

Biology

Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography

Skeletal muscle size, mass, and composition are critical properties for studying metabolic and muscle-related diseases, as they directly impact the understanding of disease progression and treatment outcomes. Quantifying a live animal's lean, adipose, and skeletal mass is important in metabolic, physiology, pharmacologic, and geroscience studies. However, obtaining accurate body composition measurements, especially of lean mass, remains challenging due to the inherent limitations of conventional assessment techniques. Micro-computed tomography (micro-CT) is a non-invasive radiological technique that enables high-resolution visualization of internal structures in small animal models. A standardized micro-CT method can significantly enhance translational research with more reliable and impactful results, particularly during aging studies or at different time points within the same animal. Despite its potential, the lack of standardization in image acquisition and analysis methods significantly hinders the comparability of results across different studies. Herein, we present a comprehensive and detailed low-cost protocol for lean mass analysis using micro-CT to address these challenges and promote consistency in research involving small animal models.

This protocol uses micro-computed tomography to enable the cost-effective quantification of lean mass, including skeletal muscle and visceral tissue, adipose tissue, and skeletal tissue in small animals. It distinguishes between lean and adipose tissue, which offers significant advantages for biomedical research, particularly in translational research in small animals.

Skeletal muscle size, mass, and composition are critical properties for studying metabolic and muscle-related diseases, as they directly impact the ...

Using 23Na Magnetic Resonance Imaging to Measure Sodium in Muscle Tissues

This video demonstrates the quantification of sodium content in human tissues using sodium magnetic resonance imaging (23Na-MRI). The patient&#39;s lower leg is placed within the radiofrequency (RF) coil of the machine, and a three-dimensional gradient-echo sequence is performed. Multinuclear MRI images are generated using hydrogen and sodium nuclei to quantify sodium levels in various tissues.

All procedures involving human participants have been performed in compliance with the institutional, national, and international guidelines for human ...

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

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