Addressing spontaneous signal voids in repetitive single-shot DWI of musculature: spatial and temporal patterns in the calves of healthy volunteers and consideration of unintended muscle activities as underlying mechanism

Neurophysiological and imaging biomarkers of lower motor neuron dysfunction in motor neuron diseases/amyotrophic lateral sclerosis: IFCN handbook chapter

This chapter discusses comprehensive neurophysiological biomarkers utilised in motor neuron disease (MND) and, in particular, its commonest form, amyotrophic lateral sclerosis (ALS). These encompass the conventional techniques including nerve conduction studies (NCS), needle and high-density surface electromyography (EMG) and H-reflex studies as well as novel techniques. In the last two decades, new methods of assessing the loss of motor units in a muscle have been developed, that are more convenient than earlier methods of motor unit number estimation (MUNE),and may use either electrical stimulation (e.g. MScanFit MUNE) or voluntary activation (MUNIX). Electrical impedance myography (EIM) is another novel approach for the evaluation that relies upon the application and measurement of high-frequency, low-intensity electrical current. Nerve excitability techniques (NET) also provide insights into the function of an axon and reflect the changes in resting membrane potential, ion channel dysfunction and the structural integrity of the axon and myelin sheath. Furthermore, imaging ultrasound techniques as well as magnetic resonance imaging are capable of detecting the constituents of morphological changes in the nerve and muscle. The chapter provides a critical description of the ability of each technique to provide neurophysiological insight into the complex pathophysiology of MND/ALS. However, it is important to recognise the strengths and limitations of each approach in order to clarify utility. These neurophysiological biomarkers have demonstrated reliability, specificity and provide additional information to validate and assess lower motor neuron dysfunction. Their use has expanded the knowledge about MND/ALS and enhanced our understanding of the relationship between motor units, axons, reflexes and other neural circuits in relation to clinical features of patients with MND/ALS at different stages of the disease. Taken together, the ultimate goal is to aid early diagnosis, distinguish potential disease mimics, monitor and stage disease progression, quantify response to treatment and develop potential therapeutic interventions.

Whole-body fasciculation detection in amyotrophic lateral sclerosis using motor unit MRI

OBJECTIVE

Compare fasciculation rates between amyotrophic lateral sclerosis (ALS) patients and healthy controls in body regions relevant for diagnosing ALS using motor unit MRI (MUMRI) at baseline and 6 months follow-up, and relate this to single-channel surface EMG (SEMG).

METHODS

Tongue, biceps brachii, paraspinals and lower legs were assessed with MUMRI and biceps brachii and soleus with SEMG in 10 healthy controls and 10 patients (9 typical ALS, 1 primary lateral sclerosis [PLS]).

RESULTS

MUMRI-detected fasciculation rates in typical ALS patients were higher compared to healthy controls for biceps brachii (2.40 ± 1.90 cm-3min-1vs. 0.04 ± 0.10 cm-3min-1, p = 0.004), paraspinals (1.14 ± 1.61 cm-3min-1vs. 0.02 ± 0.02 cm-3min-1, p = 0.016) and lower legs (1.42 ± 1.27 cm-3min-1vs. 0.13 ± 0.10 cm-3min-1, p = 0.004), but not tongue (1.41 ± 1.94 cm-3min-1vs. 0.18 ± 0.18 cm-3min-1, p = 0.556). The PLS patient showed no fasciculation. At baseline, 6/9 ALS patients had increased fasciculation rates compared to healthy controls in at least 2 body regions. At follow-up every patient had increased fasciculation rates in at least 2 body regions. The MUMRI-detected fasciculation rate correlated with SEMG-detected fasciculation rates (τ = 0.475, p = 0.006).

CONCLUSION

MUMRI can non-invasively image fasciculation in multiple body regions and appears sensitive to disease progression in individual patients.

SIGNIFICANCE

MUMRI has potential as diagnostic tool for ALS.

Motor Unit Magnetic Resonance Imaging (MUMRI) In Skeletal Muscle

Magnetic resonance imaging (MRI) is routinely used in the musculoskeletal system to measure skeletal muscle structure and pathology in health and disease. Recently, it has been shown that MRI also has promise for detecting the functional changes, which occur in muscles, commonly associated with a range of neuromuscular disorders. This review focuses on novel adaptations of MRI, which can detect the activity of the functional sub-units of skeletal muscle, the motor units, referred to as "motor unit MRI (MUMRI)." MUMRI utilizes pulsed gradient spin echo, pulsed gradient stimulated echo and phase contrast MRI sequences and has, so far, been used to investigate spontaneous motor unit activity (fasciculation) and used in combination with electrical nerve stimulation to study motor unit morphology and muscle twitch dynamics. Through detection of disease driven changes in motor unit activity, MUMRI shows promise as a tool to aid in both earlier diagnosis of neuromuscular disorders and to help in furthering our understanding of the underlying mechanisms, which proceed gross structural and anatomical changes within diseased muscle. Here, we summarize evidence for the use of MUMRI in neuromuscular disorders and discuss what future research is required to translate MUMRI toward clinical practice. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

Whole Muscle and Single Motor Unit Twitch Profiles in a Healthy Adult Cohort Assessed With Phase Contrast Motor Unit MRI (PC-MUMRI)

BACKGROUND

Motor units (MUs) control the contraction of muscles and degenerate with age. It is therefore of interest to measure whole muscle and MU twitch profiles in aging skeletal muscle.

PURPOSE

Apply phase contrast MU MRI (PC-MUMRI) in a cohort of healthy adults to measure whole anterior compartment, individual muscles, and single MU twitch profiles in the calf. Assess the effect of age and sex on contraction and relaxation times.

STUDY TYPE

Prospective cross-sectional study.

SUBJECTS

Sixty-one healthy participants (N = 32 male; age 55 ± 16 years [range: 26-82]).

FIELD STRENGTH/SEQUENCES

3 T, velocity encoded gradient echo and single shot spin echo pulsed gradient spin echo, echo-planar imaging.

ASSESSMENT

Anterior shin compartment (N = 47), individual muscle (tibialis anterior, extensor digitorum longus, peroneus longus; N = 47) and single MU (N = 34) twitch profiles were extracted from the data to calculate contraction and relaxation times.

STATISTICAL TESTS

Multivariable linear regression to investigate relationships between age, sex and contraction and relaxation times of the whole anterior compartment. Pearson correlation to investigate relationships between age and contraction and relaxation times of individual muscles and single MUs. A P value <0.05 was considered statistically significant.

RESULTS

Age and sex predicted significantly increased contraction and relaxation time for the anterior compartment. Females had significantly longer contraction times than males (females 86 ± 8 msec, males 80 ± 9 msec). Relaxation times were longer, not significant (females 204 ± 36 msec, males 188 ± 34 msec, P = 0.151). Contraction and relaxation times of single MUs showed no change with age (P = 0.462, P = 0.534, respectively).

DATE CONCLUSION

Older participants had significantly longer contraction and relaxation times of the whole anterior compartment compared to younger participants. Females had longer contraction and relaxation times than males, significant for contraction time.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Feature-guided deep learning reduces signal loss and increases lesion CNR in diffusion-weighted imaging of the liver

PURPOSE

This research aims to develop a feature-guided deep learning approach and compare it with an optimized conventional post-processing algorithm in order to enhance the image quality of diffusion-weighted liver images and, in particular, to reduce the pulsation-induced signal loss occurring predominantly in the left liver lobe.

METHODS

Data from 40 patients with liver lesions were used. For the conventional approach, the best-suited out of five examined algorithms was chosen. For the deep learning approach, a U-Net was trained. Instead of learning "gold-standard" target images, the network was trained to optimize four image features (lesion CNR, vessel darkness, data consistency, and pulsation artifact reduction), which could be assessed quantitatively using manually drawn ROIs. A quality score was calculated from these four features. As an additional quality assessment, three radiologists rated different features of the resulting images.

RESULTS

The conventional approach could substantially increase the lesion CNR and reduce the pulsation-induced signal loss. However, the vessel darkness was reduced. The deep learning approach increased the lesion CNR and reduced the signal loss to a slightly lower extent, but it could additionally increase the vessel darkness. According to the image quality score, the quality of the deep-learning images was higher than that of the images obtained using the conventional approach. The radiologist ratings were mostly consistent with the quantitative scores, but the overall quality ratings differed among the readers.

CONCLUSION

Unlike the conventional algorithm, the deep-learning algorithm increased the vessel darkness. Therefore, it may be a viable alternative to conventional algorithms.

Deep Learning-Guided Weighted Averaging for Signal Dropout Compensation in DWI of the Liver

PURPOSE

To develop an algorithm for the retrospective correction of signal dropout artifacts in abdominal DWI resulting from cardiac motion.

METHODS

Given a set of image repetitions for a slice, a locally adaptive weighted averaging is proposed that aims to suppress the contribution of image regions affected by signal dropouts. Corresponding weight maps were estimated by a sliding-window algorithm, which analyzed signal deviations from a patch-wise reference. In order to ensure the computation of a robust reference, repetitions were filtered by a classifier that was trained to detect images corrupted by signal dropouts. The proposed method, named Deep Learning-guided Adaptive Weighted Averaging (DLAWA), was evaluated in terms of dropout suppression capability, bias reduction in the ADC, and noise characteristics.

RESULTS

In the case of uniform averaging, motion-related dropouts caused signal attenuation and ADC overestimation in parts of the liver, with the left lobe being affected particularly. Both effects could be substantially mitigated by DLAWA while preventing global penalties with respect to SNR due to local signal suppression. Performing evaluations on patient data, the capability to recover lesions concealed by signal dropouts was demonstrated as well. Further, DLAWA allowed for transparent control of the trade-off between SNR and signal dropout suppression by means of a few hyperparameters.

CONCLUSION

This work presents an effective and flexible method for the local compensation of signal dropouts resulting from motion and pulsation. Because DLAWA follows a retrospective approach, no changes to the acquisition are required.

Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography

Spontaneous muscular activities can be studied by simultaneous recordings of surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI). For reliable assessment of the spontaneous activity rate in sEMG data during active MR imaging, it is necessary to have a decent gradient artifact (GA) correction algorithm enabling the detection of small spontaneous activities with an amplitude of few microvolts. In this work, a neural network with weak label annotations during the training process is utilized for enhanced correction of GA residuals in the sEMG recordings. Based on sEMG signal decomposition and class-activation maps from the neural network classification, the amount of GA residuals is iteratively decreased in the sEMG signal. This leads to a reduction of the false-positive rate in automated spontaneous activity detection. Quality of GA residual correction is therefore estimated by using a specialized second neural network model. Clinical relevance- This work establishes an improved GA residual correction for simultaneously recorded sEMG data during MRI to enhance the ability for small spontaneous activity detection.

Effect of compression garments on muscle perfusion in delayed-onset muscle soreness: A quantitative analysis using intravoxel incoherent motion MR perfusion imaging

The aim of this prospective cohort study was to evaluate the effect of compression garments under resting conditions and after the induction of delayed-onset muscle soreness (DOMS) by MR perfusion imaging using intravoxel incoherent motion (IVIM). Magnetic resonance imaging of both lower legs of 16 volunteers was performed before and after standardized eccentric exercises that induced DOMS. A compression garment (21-22 mmHg) was worn during and for 6 h after exercise on one randomly selected leg. IVIM MR imaging, represented as total muscle perfusion D*f, perfusion fraction f and tissue diffusivity D, were compared between baseline and directly, 30 min, 6 h and 48 h after exhausting exercise with and without compression. Creatine kinase levels and T2-weighted images were acquired at baseline and after 48 h. DOMS was induced in the medial head of the gastrocnemius muscle (MGM) in all volunteers. Compression garments did not show any significant effect on IVIM perfusion parameters at any time point in the MGM or the tibialis anterior muscle (p > 0.05). Microvascular perfusion in the MGM increased significantly in both the compressed and noncompressed leg between baseline measurements and those taken directly after and 30 min after the exercise: the relative median f increased by 31.5% and 24.7% in the compressed and noncompressed leg, respectively, directly after the exercise compared with the baseline value. No significant change in tissue perfusion occurred 48 h after the induction of DOMS compared with baseline. It was concluded that compression garments (21-22 mmHg) do not alter microvascular muscle perfusion at rest, nor do they have any significant effect during the regeneration phase of DOMS. In DOMS, only a short-term effect of increased muscle perfusion (30 min after exercise) was observed, with normalization occurring during regeneration after 6-48 h. The normalization of perfusion independently of compression after 6 h may have implications for diagnostic and therapeutic strategies and for the better understanding of pathophysiological pathways in DOMS.

The muscle twitch profile assessed with motor unit magnetic resonance imaging

Localised signal voids in diffusion-weighted (DW) images of skeletal muscle have been postulated to occur as a result of muscle fibre contraction and relaxation. We investigated the contrast mechanism of these signal voids using a combination of modelling and experimental measurements by employing DW and phase contrast (PC) imaging sequences. The DW signal and PC signal were simulated for each time point of a theoretical muscle twitch. The model incorporated compaction (simulating actively contracting muscle fibres) and translation (simulating passively moving surrounding fibres). The model suggested that the DW signal depended on contraction time and compaction whereas the PC signal depended on contraction time, compaction and translation. In a retrospective study, we tested this model with subgroup analyses on 10 healthy participants. Electrical nerve stimulation was used to generate muscle twitches in lower leg muscles; the resulting force was measured using an MR-compatible force transducer. At current levels causing a visible muscle twitch (~13 mA), the width of the first signal drop in the DW signal (mean ± SD: 103 ± 20 ms) was comparable with the force contraction time (93 ± 34 ms; intraclass correlation coefficient [ICC] = 0.717, P = .010). At current levels activating single motor units (~9 mA), the contraction time determined from the DW signal was 75 ± 13 ms and comparable with the PC contraction time (81 ± 15 ms; ICC = 0.925, P = .001). The maximum positive velocity was 0.55 ± 0.26 cm/s and the displacement was 0.20 ± 0.10 mm. Voxel-wise analysis revealed localised DW changes occurring together with more widespread phase changes. In conclusion, local signal attenuations in DW images following muscle fibre activation are primarily caused by compaction. The PC sequence also detects translating muscle tissue being passively pulled. The magnitude of the changes in DW and PC images depends on the twitch's contractile properties and percentage contraction. DW imaging and PC imaging can therefore measure twitch profiles of skeletal muscle fibres.

Diffusion Tensor Imaging of Skeletal Muscle Contraction Using Oscillating Gradient Spin Echo

Diffusion tensor imaging (DTI) measures water diffusion in skeletal muscle tissue and allows for muscle assessment in a broad range of neuromuscular diseases. However, current DTI measurements, typically performed using pulsed gradient spin echo (PGSE) diffusion encoding, are limited to the assessment of non-contracted musculature, therefore providing limited insight into muscle contraction mechanisms and contraction abnormalities. In this study, we propose the use of an oscillating gradient spin echo (OGSE) diffusion encoding strategy for DTI measurements to mitigate the effect of signal voids in contracted muscle and to obtain reliable diffusivity values. Two OGSE sequences with encoding frequencies of 25 and 50 Hz were tested in the lower leg of five healthy volunteers with relaxed musculature and during active dorsiflexion and plantarflexion, and compared with a conventional PGSE approach. A significant reduction of areas of signal voids using OGSE compared with PGSE was observed in the tibialis anterior for the scans obtained in active dorsiflexion and in the soleus during active plantarflexion. The use of PGSE sequences led to unrealistically elevated axial diffusivity values in the tibialis anterior during dorsiflexion and in the soleus during plantarflexion, while the corresponding values obtained using the OGSE sequences were significantly reduced. Similar findings were seen for radial diffusivity, with significantly higher diffusivity measured in plantarflexion in the soleus muscle using the PGSE sequence. Our preliminary results indicate that DTI with OGSE diffusion encoding is feasible in human musculature and allows to quantitatively assess diffusion properties in actively contracting skeletal muscle. OGSE holds great potential to assess microstructural changes occurring in the skeletal muscle during contraction, and for non-invasive assessment of contraction abnormalities in patients with muscle diseases.

The role of novel motor unit magnetic resonance imaging to investigate motor unit activity in ageing skeletal muscle

Sarcopenia is a progressive and generalized disease, more common in older adults, which manifests as a loss of muscle strength and mass. The pathophysiology of sarcopenia is still poorly understood with many mechanisms suggested. Age associated changes to the neuromuscular architecture, including motor units and their constituent muscle fibres, represent one such mechanism. Electromyography can be used to distinguish between different myopathies and produce counts of motor units. Evidence from electromyography studies suggests that with age, there is a loss of motor units, increases to the sizes of remaining units, and changes to their activity patterns. However, electromyography is invasive, can be uncomfortable, does not reveal the exact spatial position of motor units within muscle and is difficult to perform in deep muscles. We present a novel diffusion-weighted magnetic resonance imaging technique called 'motor unit magnetic resonance imaging (MUMRI)'. MUMRI aims to improve our understanding of the changes to the neuromuscular system associated with ageing, sarcopenia and other neuromuscular diseases. To date, we have demonstrated that MUMRI can be used to detect statistically significant differences in fasciculation rate of motor units between (n = 4) patients with amyotrophic lateral sclerosis (mean age ± SD: 53 ± 15) and a group of (n = 4) healthy controls (38 ± 7). Patients had significantly higher rates of fasciculation compared with healthy controls (mean = 99.1/min, range = 25.7-161.0 in patients vs. 7.7/min, range = 4.3-9.7 in controls; P < 0.05. MUMRI has detected differences in size, shape, and distribution of single human motor units between (n = 5) young healthy volunteers (29 ± 2.2) and (n = 5) healthy older volunteers (65.6 ± 14.8). The maximum size of motor unit territories in the older group was 12.4 ± 3.3 mm and 9.7 ± 2.7 mm in the young group; P < 0.05. MUMRI is an entirely non-invasive tool, which can be used to detect physiological and pathological changes to motor units in neuromuscular diseases. MUMRI also has the potential to be used as an intermediate outcome measure in sarcopenia trials.

Monte-Carlo Analysis for Quality Estimation of Gradient Correction Algorithms in Simultaneous Surface EMG-MRI Measurements using Signal Synthesis and Class Probability

Simultaneous measurements by surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI) enable studies of small muscular activities in resting human musculature. Induced signal disturbances can hamper the evaluation of small amplitude myoelectric signals despite the application of gradient artifact correction (GAC) methods. Systematic evaluation of the quality of GAC methods is difficult due to the unknown real sEMG signal during simultaneous measurements. Therefore, a new concept for GAC quality estimation is investigated based on sEMG sample generation and classification. Signal synthesis and classification is based on a Dense-Bidirectional-Long-Short-Term-Memory (DBLSTM)-based auxiliary classifier generative adversarial network (AC-GAN). Quality of GAC and ability to detect small myoelectric activities is exemplary investigated on two common DW-MRI sequences.

Intravoxel Incoherent Motion Magnetic Resonance Imaging with Integrated Slice-specific Shimming for old myocardial infarction: A Pilot Study

Currently, little is known regarding the value of quantitative parameters derived from the intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) with integrated slice-specific shimming (iShim) sequence in detecting old myocardial infarction and myocardial fibrosis. This study was to investigate the value of IVIM-MRI with iShim sequence in diagnosing old myocardial infarction and fibrosis. Thirty-five patients with both old myocardial infarction and myocardial fibrosis and 12 healthy volunteers were prospectively enrolled to undergo cardiac diffusion-weighted imaging (DWI) using seven b-values (0, 20, 60, 80, 120, 200 and 600 s/mm²). The iShim sequence was used for IVIM data acquisition, and the diffusion parameters, D, D* and f values for IVIM, and conventional apparent diffusion coefficient (ADC) were evaluated on the anterior, posterior and lateral walls of the ventricular septum using the short axis of the heart. Significant differences were found in the D, D* and f values between healthy subjects and patients with old myocardial infarction and myocardial fibrosis (P = 0.000), with the median value of the D and f significantly smaller in the myocardial infarction and fibrosis than in the normal control but the median value of D* significantly greater in the myocardial infarction and fibrosis than in the normal control. In the receiver operating curve analysis, the areas under the curve were 0.939, 0.988 and 0.959 for the D, D* and f values, respectively. The sensitivities and specificities were 84.6% and 94.4% for D, 88.9% and 84.6% for D* and 100% and 93.1% for the f values, respectively. In conclusion, the IVIM-derived parameters (D, D* and f) obtained using the iShim DWI technique showed high capacity in diagnosing old myocardial infarction and myocardial fibrosis by providing diffusion and perfusion information, which may have great importance in future clinical practice.

Functional magnetic resonance imaging of human motor unit fasciculation in amyotrophic lateral sclerosis

A novel diffusion-weighted magnetic resonance imaging protocol sensitive to contraction of individual skeletal motor units was developed. We applied this technique to the lower limb muscles of 4 patients with confirmed amyotrophic lateral sclerosis (ALS) and 6 healthy controls. A 3-minute scan revealed florid fasciculation in ALS patients, involving both superficial and deep muscles, and at a frequency higher than in healthy controls. This novel imaging technique reveals hitherto unobtainable information on human motor unit structure and function, which may allow earlier diagnosis and recruitment to clinical trials. ANN NEUROL 2019;85:455-459.

A Surface Electromyography-Driven Magnetic Resonance Sequence Controller for Real-Time Myoelectric Triggered Imaging

Combination of surface electromyography (EMG) with diffusion-weighted magnetic resonance imaging (DW-MRI) enables improved studies of spontaneous mechanical contractions in resting human musculature (SMAM). Mechanical muscular activities follow characteristic electrical neuromuscular activities after a delay of several tens of milliseconds. A low-cost standalone system for simultaneous surface EMG measurements during DW-MRI with a real-time model-based surface EMG activity detection is demonstrated which controls the MR sequence. Therefore, a multilayer perceptron (MLP) with sequential forward selection (SFS) was investigated. MLP achieved an area under curve (AUC) of 0.933 in the detection of small surface EMG activities based on five time-domain features. Integration on a microcontroller system enabled fast real-time surface EMG activity detection with highly flexible trigger time settings. Small deviations with only 7.2±1.7 ms time delay between decision of MLP activity detection and onset of MR sequence were measured.

Volumetric assessment of spontaneous mechanical activities by simultaneous multi-slice MRI techniques with correlation to muscle fiber orientation

The purpose of this work was assessment of volumetric characteristics of spontaneous mechanical activities in musculature (SMAMs) by diffusion-weighted simultaneous multi-slice (DW-SMS) imaging and spatial correlation to anatomical structure, as revealed by fusion to fiber tractographic information derived from diffusion-tensor imaging (DTI). The feasibility of using DW-SMS to image spontaneous events in human musculature was assessed by phantom measurements. Series of DW-SMS images and DTI datasets were recorded from the resting calf of three human subjects. Simultaneously recorded SMAMs in multiple slices were analyzed regarding spatial extension by the Kolmogorov-Smirnov test. Direct correlation of spatial distribution of SMAMs and fiber orientation was investigated by mapping of muscle fibers to multi-slice SMAM datasets. The DW-SMS strategy allows simultaneous assessment of SMAMs in several slices of resting skeletal musculature, since 73.9% of SMAM-affected volumes have shown SMAMs in multiple DW-SMS slices. Spatial extension of SMAMs was highly correlated over different simultaneously recorded DW-SMS slices, and affected areas followed the orientation of muscle fibers with a connectivity ratio up to 57.18 ± 14.80% based on event count and connectivity count maps. In 89.2% of all SMAM-affected datasets muscle fiber connectivity was shown in at least two adjacent slices. Direct correlation between SMAMs in human lower leg musculature and underlying anatomical structure was revealed by high muscle fiber connectivity (89.2%). SMAMs have shown a wide distribution along the longitudinal muscle direction (73.9% in multiple DW-SMS slices) with direct involvement of muscle fibers. Correlation between SMAMs in multiple DW-SMS slices and crossing muscular fiber tracts provides evidence that SMAMs result from physiological processes in musculature. Fusion of DW-SMS with DTI facilitates non-invasive studies of muscle fiber involvement in SMAMs in resting muscle.

STROBE-A preliminary investigation of IVIM-DWI in cardiac imaging

This study aims to explore the possibility to apply intravoxel incoherent motion-magnetic resonance imaging (IVIM-MRI) in cardiac imaging.Multi-b-value diffusion-weighted imaging (DWI) sequence scanning was performed on 12 healthy volunteers. A double exponential model was adopted, and the b-value sequence was 0, 20, 60, 80, 120, 200, and 600 second/mm. The D-value, D*-value, and f-value of the anterior posterior and lateral walls of the ventricular septum were respectively measured on the short axis section of the heart, the parameters of the myocardium in different blood supply areas in each segment were recorded, and the measured data of these different segments were compared using analysis of variance.Among these 12 healthy volunteers, the D-value, D*-value, and f-value of these 72 segments were not exactly equal, the D-values of the myocardium in the 5th and 11th segment were lower than those in the 2nd, 3rd, 8th, and 9th segments, and the pairwise differences were statistically significant (P < .001). Furthermore, the difference in D-value between the 5th and 11th segments was not statistically significant (P = 1.000). The D*-value and f-value of the myocardium in the 5th and 11th segment were higher than those in the 2nd, 3rd, 8th, and 9th segments, and the pairwise differences were statistically significant (P < .001). Furthermore, the differences in D*-value and f-value between the 5th and 11th segments was not statistically significant (P = .214, .787).The intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) technique can quantitatively reflect the diffusion and blood perfusion status of the myocardium.

Weighted Mean of Signal Intensity for Unbiased Fiber Tracking of Skeletal Muscles: Development of a New Method and Comparison With Other Correction Techniques

OBJECTIVES

The aim of this study was to investigate the origin of random image artifacts in stimulated echo acquisition mode diffusion tensor imaging (STEAM-DTI), assess the role of averaging, develop an automated artifact postprocessing correction method using weighted mean of signal intensities (WMSIs), and compare it with other correction techniques.

MATERIALS AND METHODS

Institutional review board approval and written informed consent were obtained. The right calf and thigh of 10 volunteers were scanned on a 3 T magnetic resonance imaging scanner using a STEAM-DTI sequence.Artifacts (ie, signal loss) in STEAM-based DTI, presumably caused by involuntary muscle contractions, were investigated in volunteers and ex vivo (ie, human cadaver calf and turkey leg using the same DTI parameters as for the volunteers). An automated postprocessing artifact correction method based on the WMSI was developed and compared with previous approaches (ie, iteratively reweighted linear least squares and informed robust estimation of tensors by outlier rejection [iRESTORE]). Diffusion tensor imaging and fiber tracking metrics, using different averages and artifact corrections, were compared for region of interest- and mask-based analyses. One-way repeated measures analysis of variance with Greenhouse-Geisser correction and Bonferroni post hoc tests were used to evaluate differences among all tested conditions. Qualitative assessment (ie, images quality) for native and corrected images was performed using the paired t test.

RESULTS

Randomly localized and shaped artifacts affected all volunteer data sets. Artifact burden during voluntary muscle contractions increased on average from 23.1% to 77.5% but were absent ex vivo. Diffusion tensor imaging metrics (mean diffusivity, fractional anisotropy, radial diffusivity, and axial diffusivity) had a heterogeneous behavior, but in the range reported by literature. Fiber track metrics (number, length, and volume) significantly improved in both calves and thighs after artifact correction in region of interest- and mask-based analyses (P < 0.05 each). Iteratively reweighted linear least squares and iRESTORE showed equivalent results, but WMSI was faster than iRESTORE. Muscle delineation and artifact load significantly improved after correction (P < 0.05 each).

CONCLUSIONS

Weighted mean of signal intensity correction significantly improved STEAM-based quantitative DTI analyses and fiber tracking of lower-limb muscles, providing a robust tool for musculoskeletal applications.

Normalized STEAM-based diffusion tensor imaging provides a robust assessment of muscle tears in football players: preliminary results of a new approach to evaluate muscle injuries

Objectives

To assess acute muscle tears in professional football players by diffusion tensor imaging (DTI) and evaluate the impact of normalization of data.

Methods

Eight football players with acute lower limb muscle tears were examined. DTI metrics of the injured muscle and corresponding healthy contralateral muscle and of ROIs drawn in muscle tears (ROI_tear) in the corresponding healthy contralateral muscle (ROI_{hc_t}) in a healthy area ipsilateral to the injury (ROI_hi) and in a corresponding contralateral area (ROI_{hc_i}) were compared. The same comparison was performed for ratios of the injured (ROI_tear/ROI_hi) and contralateral sides (ROI_{hc_t}/ROI_{hc_i}). ANOVA, Bonferroni-corrected post-hoc and Student’s t-tests were used.

Results

Analyses of the entire muscle did not show any differences (p>0.05 each) except for axial diffusivity (AD; p=0.048). ROI_tear showed higher mean diffusivity (MD) and AD than ROI_{hc_t} (p<0.05). Fractional anisotropy (FA) was lower in ROI_tear than in ROI_hi and ROI_{hc_t} (p<0.05). Radial diffusivity (RD) was higher in ROI_tear than in any other ROI (p<0.05). Ratios revealed higher MD and RD and lower FA and reduced number and length of fibre tracts on the injured side (p<0.05 each).

Conclusions

DTI allowed a robust assessment of muscle tears in athletes especially after normalization to healthy muscle tissue.

Key Points

• STEAM-based DTI allows the investigation of muscle tears affecting professional football players.

• Fractional anisotropy and mean diffusivity differ between injured and healthy muscle areas.

• Only normalized data show differences of fibre tracking metrics in muscle tears.

• The normalization of DTI-metrics enables a more robust characterization of muscle tears.

Spontaneous mechanical and electrical activities of human calf musculature at rest assessed by repetitive single-shot diffusion-weighted MRI and simultaneous surface electromyography

PURPOSE

Assessment of temporal and spatial relations between spontaneous mechanical activities in musculature (SMAM) at rest as revealed by diffusion-weighted imaging (DWI) and electrical muscular activities in surface EMG (sEMG). Potential influences of static and radiofrequency magnetic fields on muscular activity on sEMG measurements at rest were examined systematically.

METHODS

Series of diffusion-weighted stimulated echo planar imaging were recorded with concurrent sEMG measurements. Electrical activities in sEMG were analyzed by non-parametric Friedman and two-sample Kolmogorov-Smirnov test. Direct correlation of both modalities was investigated by temporal mapping of electrical activity in sEMG to DWI repetition interval.

RESULTS

Electrical activities in sEMG and number of visible SMAMs in DWI showed a strong correlation (ρ = 0.9718). High accordance between sEMG activities and visible SMAMs in DWI in a near-surface region around sEMG electrodes was achieved. Characteristics of sEMG activities were almost similar under varying magnetic field conditions.

CONCLUSION

Visible SMAMs in DWI have shown a close and direct relation to concurrent signals recorded by sEMG. MR-related magnetic fields had no significant effects on findings in sEMG. Hence, appearance of SMAMs in DWI should not be considered as imaging artifact or as effects originating from the special conditions of MR examinations. Spatial and temporal distributions of SMAMs indicate characteristics of spontaneous (microscopic) mechanical muscular action at rest. Therefore, DWI techniques should be considered as non-invasive tools for studying physiology and pathophysiology of spontaneous activities in resting muscle. Magn Reson Med 79:2784-2794, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

In vivo measurement of membrane permeability and myofiber size in human muscle using time-dependent diffusion tensor imaging and the random permeable barrier model

The time dependence of the diffusion coefficient is a hallmark of tissue complexity at the micrometer level. Here we demonstrate how biophysical modeling, combined with a specifically tailored diffusion MRI acquisition performing diffusion tensor imaging (DTI) for varying diffusion times, can be used to determine fiber size and membrane permeability of muscle fibers in vivo. We describe the random permeable barrier model (RPBM) and its assumptions, as well as the details of stimulated echo DTI acquisition, signal processing steps, and potential pitfalls. We illustrate the RPBM method on a few pilot examples involving human subjects (previously published as well as new), such as revealing myofiber size derived from RPBM increase after training in a calf muscle, and size decrease with atrophy in shoulder rotator cuff muscle. Finally, we comment on the potential clinical relevance of our results. Copyright © 2016 John Wiley & Sons, Ltd.

Effects of perfusion on DTI and DKI estimates in the skeletal muscle

PURPOSE

In this study, we evaluated the effects of perfusion of the skeletal muscle on diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) parameters and their reproducibility.

METHODS

Diffusion tensor imaging and DKI models, with and without intravoxel incoherent motion (IVIM) correction, were applied to simulated data at different physiological conditions and signal-to-noise ratio levels. Next, the same models were applied to data of the right calf of five healthy volunteers, acquired twice at 3 telsa. For six muscles, we evaluated the correlation of the perfusion signal fraction, with parameters derived from DTI and DKI, and performed repeatability analysis with and without IVIM correction. Additionally, the IVIM correction was compared to a multishell acquisition approach that minimizes perfusion effects on DTI estimates.

RESULTS

Simulations and acquired data showed that DTI and DKI estimates were biased proportionally to the perfusion signal fraction, and that IVIM correction was needed for accurate estimation of the DTI and DKI parameters. However, taking perfusion into account did not improve repeatability.

CONCLUSION

Blood perfusion has an effect on DTI and DKI estimations, but it can be minimized with IVIM correction or multishell acquisition strategies. Magn Reson Med 78:233-246, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Diffusional kurtosis MRI of the lower leg: changes caused by passive muscle elongation and shortening

Diffusional kurtosis MRI (DKI) quantifies the deviation of water diffusion from a Gaussian distribution. We investigated the influence of passive elongation and shortening of the lower leg muscles on the DKI parameters D (diffusion coefficient) and K (kurtosis). After approval by the local ethics committee, eight healthy volunteers (age, 29.1 ± 2.9 years) underwent MRI of the lower leg at 3 T. Diffusion-weighted images were acquired with 10 different b values at three ankle positions (passive dorsiflexion 10°, neutral position 0°, passive plantar flexion 40°). Parametrical maps of D and K were obtained by voxel-wise fitting of the signal intensities using a non-linear Levenberg-Marquardt algorithm. D and K were measured in the tibialis anterior, medial and lateral gastrocnemius, and soleus muscles. In the neutral position, D and K values were in the range between 1.66-1.79 × 10(-3) mm(2) /s and 0.21-0.39, respectively. D and K increased with passive shortening, and decreased with passive elongation, which could also be illustrated on the parametrical maps. In dorsiflexion, D (p < 0.01) and K (p = 0.036) were higher in the tibialis anterior than in the medial gastrocnemius. In plantar flexion, the opposite was found for K (p = 0.035). DKI parameters in the lower leg muscles are significantly influenced by the ankle joint position, indicating that the diffusion of water molecules in skeletal muscle deviates from a Gaussian distribution depending on muscle tonus. Copyright © 2016 John Wiley & Sons, Ltd.