Prospective longitudinal cohort study of quantitative muscle magnetic resonance imaging in a healthy control population.

Quantitative muscle magnetic resonance imaging (qMRI) is a valuable methodology for assessing muscular injuries and neuromuscular disorders. Notably, muscle diffusion tensor imaging (DTI) gives insights into muscle microstructural and macrostructural characteristics. However, the long-term reproducibility and robustness of these measurements remain relatively unexplored. The purpose of this prospective longitudinal cohort study was to assess the long-term robustness and range of variation of qMRI parameters, especially DTI metrics, in the lower extremity muscles of healthy controls under real-life conditions. Twelve volunteers (seven females, age 44.1 ± 12.1 years, body mass index 23.3 ± 2.0 kg/m2) underwent five leg muscle MRI sessions every 20 ± 4 weeks over a total period of 1.5 years. A multiecho gradient-echo Dixon-based sequence, a multiecho spin-echo T2-mapping sequence, and a spin-echo echo planar imaging diffusion-weighted sequence were acquired bilaterally with a Philips 3-T Achieva MR System using a 16-channel torso coil. Fifteen leg muscles were segmented in both lower extremities. qMRI parameters, including fat fraction (FF), water T2 relaxation time, and the diffusion metrics fractional anisotropy (FA) and mean diffusivity (MD), were evaluated. Coefficients of variance (wsCV) and intraclass correlation coefficients (ICCs) were calculated to assess the reproducibility of qMRI parameters. The standard error of measurement (SEM) and the minimal detectable change (MDC) were calculated to determine the range of variation. All tests were applied to all muscles and, subsequently, to each muscle separately. wsCV showed good reproducibility (≤ 10%) for all qMRI parameters in all muscles. The ICCs revealed excellent agreement between time points (FF = 0.980, water T2 = 0.941, FA = 0.952, MD = 0.948). Random measurement errors assessed by SEM and the MDC were low (< 12%). In conclusion, in this study, we showed that qMRI parameters in healthy volunteers living normal lives are stable over 18 months, thereby defining a benchmark for the expected range of variation over time.

Quantitative muscle magnetic resonance imaging in limb-girdle muscular dystrophy type R1 (LGMDR1): A prospective longitudinal cohort study.

Limb-girdle muscular dystrophy (LGMD) type R1 (LGMDR1) is the most common subtype of LGMD in Europe. Prospective longitudinal data, including clinical assessments and new biomarkers such as quantitative magnetic resonance imaging (qMRI), are needed to evaluate the natural course of the disease and therapeutic options. We evaluated eight thigh and seven leg muscles of 13 LGMDR1 patients (seven females, mean age 36.7 years, body mass index 23.9 kg/m2) and 13 healthy age- and gender-matched controls in a prospective longitudinal design over 1 year. Clinical assessment included testing for muscle strength with quick motor function measure (QMFM), gait analysis and patient questionnaires (neuromuscular symptom score, activity limitation [ACTIVLIM]). MRI scans were performed on a 3-T MRI scanner, including a Dixon-based sequence, T2 mapping and diffusion tensor imaging. The qMRI values of fat fraction (FF), water T2 relaxation time (T2), fractional anisotropy, mean diffusivity, axial diffusivity and radial diffusivity were analysed. Within the clinical outcome measures, significant deterioration between baseline and follow-up was found for ACTIVLIM (p = 0.029), QMFM (p = 0.012). Analysis of qMRI parameters of the patient group revealed differences between time points for both FF and T2 when analysing all muscles (FF: p < 0.001; T2: p = 0.016). The highest increase of fat replacement was found in muscles with an FF of between 10% and 50% at baseline. T2 in muscles with low-fat replacement increased significantly. No significant differences were found for the diffusion metrics. Significant correlations between qMRI metrics and clinical assessments were found at baseline and follow-up, while only T2 changes in thigh muscles correlated with changes in ACTIVLIM over time (ρ = -0.621, p < 0.05). Clinical assessments can show deterioration of the general condition of LGMDR1 patients. qMRI measures can give additional information about underlying pathophysiology. Further research is needed to establish qMRI outcome measures for clinical trials.

[Expert recommendations for magnetic resonance imaging of muscle disorders]. / Expertenempfehlung zur Magnetresonanztomographie bei Muskelerkrankungen.

BACKGROUND: Magnetic resonance (MRI) imaging of the skeletal muscles (muscle MRI for short) is increasingly being used in clinical routine for diagnosis and longitudinal assessment of muscle disorders. However, cross-centre standards for measurement protocol and radiological assessment are still lacking. OBJECTIVES: The aim of this expert recommendation is to present standards for the application and interpretation of muscle MRI in hereditary and inflammatory muscle disorders. METHODS: This work was developed in collaboration between neurologists, neuroradiologists, radiologists, neuropaediatricians, neuroscientists and MR physicists from different university hospitals in Germany. The recommendations are based on expert knowledge and a focused literature search. RESULTS: The indications for muscle MRI are explained, including the detection and monitoring of structural tissue changes and oedema in the muscle, as well as the identification of a suitable biopsy site. Recommendations for the examination procedure and selection of appropriate MRI sequences are given. Finally, steps for a structured radiological assessment are presented. CONCLUSIONS: The present work provides concrete recommendations for the indication, implementation and interpretation of muscle MRI in muscle disorders. Furthermore, it provides a possible basis for the standardisation of the measurement protocols at all clinical centres in Germany.

Compositional and Functional MRI of Skeletal Muscle: A Review.

Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.

Quantitative muscle magnetic resonance imaging depicts microstructural abnormalities but no signs of inflammation or dystrophy in post-COVID-19 condition.

BACKGROUND AND PURPOSE: Post-COVID-19 condition (PCC) has high impact on quality of life, with myalgia and fatigue affecting at least 25% of PCC patients. This case-control study aims to noninvasively assess muscular alterations via quantitative muscle magnetic resonance imaging (MRI) as possible mechanisms for ongoing musculoskeletal complaints and premature exhaustion in PCC. METHODS: Quantitative muscle MRI was performed on a 3 Tesla MRI scanner of the whole legs in PCC patients compared to age- and sex-matched healthy controls, including a Dixon sequence to determine muscle fat fraction (FF), a multi-echo spin-echo sequence for quantitative water mapping reflecting putative edema, and a diffusion-weighted spin-echo echo-planar imaging sequence to assess microstructural alterations. Clinical examination, nerve conduction studies, and serum creatine kinase were performed in all patients. Quantitative muscle MRI results were correlated to the results of the 6-min walk test and standardized questionnaires assessing quality of life, fatigue, and depression. RESULTS: Twenty PCC patients (female: n = 15, age = 48.8 ± 10.1 years, symptoms duration = 13.4 ± 4.2 months, body mass index [BMI] = 28.8 ± 4.7 kg/m2 ) were compared to 20 healthy controls (female: n = 15, age = 48.1 ± 11.1 years, BMI = 22.9 ± 2.2 kg/m2 ). Neither FF nor T2 revealed signs of muscle degeneration or inflammation in either study groups. Diffusion tensor imaging (DTI) revealed reduced mean, axial, and radial diffusivity in the PCC group. CONCLUSIONS: Quantitative muscle MRI did not depict any signs of ongoing inflammation or dystrophic process in the skeletal muscles in PCC patients. However, differences observed in muscle DTI depict microstructural abnormalities, which may reflect potentially reversible fiber hypotrophy due to deconditioning. Further longitudinal and interventional studies should prove this hypothesis.

Robustness and stability of volume-based tractography in a multicenter setting.

Muscle diffusion tensor imaging (mDTI)-based tractography is a promising tool with which to detect subclinical changes in muscle injuries and to evaluate pathophysiology in neuromuscular diseases. Classic region of interest (ROI)-based tractography is very time-consuming and requires an examiner with extensive experience. (Semi)automatic approaches such as volume-based tractography (VBT) can diminish this problem but its robustness and stability are unknown. The aim of the current study was to assess the performance of VBT in a multicenter setting and to evaluate semiautomatic segmentation approaches in the analysis of VBT-derived data in terms of the comparability of the outcome measures. Five traveling volunteers underwent 3-T mDTI of seven calf muscles of both legs at six different MR sites. Tract properties and diffusion metrics were calculated using VBT. Within-subject coefficients of variance (wsCVs) and intraclass correlation coefficients (ICCs) were calculated to assess the multicenter reproducibility of tract properties such as tract density (TD), mean tract length, volume and tract propagation angle, and diffusion metrics such as fractional anisotropy, mean diffusivity, axial diffusivity (λ1 ) and radial diffusivity in traveling subjects. Furthermore, 50 individual datasets from five different centers (10 datasets per center) were pooled to assess the feasibility of VBT with manual and semiautomatic segmentation. To assess the differences of tract properties and diffusion metrics between segmentation approaches an ANOVA was performed, and ICC and Bland-Altman plots were analyzed. wsCVs and ICCs showed good reproducibility of the tract properties TD and volume, as well as diffusion metrics. ANOVA showed no significant differences between manual and semiautomatic approaches. ICCs were excellent (≥ 0.992) and Bland-Altman analysis did not reveal any systemic bias between the methods. Tract properties and diffusion metrics derived from VBT showed good comparability among centers. Semiautomatic approaches revealed excellent agreement with gold standard of manual segmentation. These findings suggest that pooling data from different centers to construct a reference database for tractography results is feasible using semiautomatic segmentation approaches.

Modulations of Insular Projections by Prior Belief Mediate the Precision of Prediction Error during Tactile Learning.

Awareness for surprising sensory events is shaped by prior belief inferred from past experience. Here, we combined hierarchical Bayesian modeling with fMRI on an associative learning task in 28 male human participants to characterize the effect of the prior belief of tactile events on connections mediating the outcome of perceptual decisions. Activity in anterior insular cortex (AIC), premotor cortex (PMd), and inferior parietal lobule (IPL) were modulated by prior belief on unexpected targets compared with expected targets. On expected targets, prior belief decreased the connection strength from AIC to IPL, whereas it increased the connection strength from AIC to PMd when targets were unexpected. Individual differences in the modulatory strength of prior belief on insular projections correlated with the precision that increases the influence of prediction errors on belief updating. These results suggest complementary effects of prior belief on insular-frontoparietal projections mediating the precision of prediction during probabilistic tactile learning.SIGNIFICANCE STATEMENT In a probabilistic environment, the prior belief of sensory events can be inferred from past experiences. How this prior belief modulates effective brain connectivity for updating expectations for future decision-making remains unexplored. Combining hierarchical Bayesian modeling with fMRI, we show that during tactile associative learning, prior expectations modulate connections originating in the anterior insula cortex and targeting salience-related and attention-related frontoparietal areas (i.e., parietal and premotor cortex). These connections seem to be involved in updating evidence based on the precision of ascending inputs to guide future decision-making.

Evaluation of interrater reliability of different muscle segmentation techniques in diffusion tensor imaging.

INTRODUCTION: Muscle diffusion tensor imaging (mDTI) is a quantitative MRI technique that can provide information about muscular microstructure and integrity. Ultrasound and DTI studies have shown intramuscular differences, and therefore separation of different muscles for analysis is essential. The commonly used methods to assess DTI metrics in muscles are manual segmentation and tract-based analysis. Recently methods such as volume-based tractography have been applied to optimize muscle architecture estimation, but can also be used to assess DTI metrics. PURPOSE: To evaluate diffusion metrics obtained using three different methods-volume-based tractography, manual segmentation-based analysis and tract-based analysis-with respect to their interrater reliability and their ability to detect intramuscular variance. MATERIALS AND METHODS: 30 volunteers underwent an MRI examination in a 3 T scanner using a 16-channel Torso XL coil. Diffusion-weighted images were acquired to obtain DTI metrics. These metrics were evaluated in six thigh muscles using volume-based tractography, manual segmentation and standard tractography. All three methods were performed by two independent raters to assess interrater reliability by ICC analysis and Bland-Altman plots. Ability to assess intramuscular variance was compared using an ANOVA with muscle as a between-subjects factor. RESULTS: Interrater reliability for all methods was found to be excellent. The highest interrater reliability was found for volume-based tractography (ICC ≥ 0.967). Significant differences for the factor muscle in all examined diffusion parameters were shown in muscles using all methods (main effect p < 0.001). CONCLUSIONS: Diffusion data can be assessed by volume tractography, standard tractography and manual segmentation with high interrater reliability. Each method produces different results for the investigated DTI parameters. Volume-based tractography was superior to conventional manual segmentation and tractography regarding interrater reliability and detection of intramuscular variance, while tract-based analysis showed the lowest coefficients of variation.

MRI of Skeletal Muscles in Participants with Type 2 Diabetes with or without Diabetic Polyneuropathy.

BackgroundDiabetic polyneuropathy (DPN) is associated with loss of muscle strength. MRI including diffusion-tensor imaging (DTI) may enable detection of muscle abnormalities related to type 2 diabetes mellitus (DM2) and DPN.PurposeTo assess skeletal muscle abnormalities in participants with DM2 with or without DPN by using MRI.Materials and MethodsThis prospective cross-sectional study included participants with DM2 and DPN (DPN positive), participants with DM2 without DPN (DPN negative), and healthy control (HC) participants enrolled between August 2017 and June 2018. Muscle strength at the knee and ankle was determined with isokinetic dynamometry. MRI of the lower extremities included the Dixon sequence, multicomponent T2 mapping, and DTI calculated fat fractions (FFs), T2 relaxation of muscle (T2water), fractional anisotropy (FA), and diffusivity (mean, axial, and radial). One-way analysis of variance and Tukey honestly significant difference were applied for comparison between groups, and multivariate regression models were used for association between MRI parameters, nerve conduction, strength, and body mass index (BMI).ResultsTwenty participants with DPN (mean age, 65 years ± 9 [standard deviation]; 70% men; mean BMI, 34 kg/m2 ± 5), 20 participants without DPN (mean age, 64 years ± 9; 55% men; mean BMI, 30 kg/m2 ± 6), and 20 HC participants (mean age, 61 years ± 10; 55% men; mean BMI, 27 kg/m2 ± 5) were enrolled in this study. Muscle strength adjusted for age, sex, and BMI was lower in participants with DPN than in DPN-negative and HC participants in the upper and lower leg (plantar flexors [PF], 62% vs 78% vs 89%; P < .001; knee extensors [KE], 73% vs 95% vs 93%; P < .001). FF was higher in leg muscle groups of participants with DPN than in DPN-negative and HC participants (PF, 20% vs 10% vs 8%; P < .001; KE, 13% vs 8% vs 6%; P < .001). T2water was prolonged in leg muscle groups of participants with DPN when compared with HC participants (PF, 33 msec vs 31 msec; P < .001; KE, 32 msec vs 31 msec; P = .002) and in the lower leg when compared with participants without DPN (PF, 33 msec vs 32 msec; P = .03). In multivariate regression models, strength was associated with FA (b = -0.0004), T2water (b = -0.03 msec), and FF (b = -0.1%) at thigh level (P < .001). Furthermore, FA (b = -0.007), T2water (b = -0.53 msec), and FF (b = -4.0%) were associated with nerve conduction at calf level (P < .001).ConclusionMRI of leg muscle groups revealed fat accumulation, differences in water composition, and structural changes in participants with type 2 diabetes mellitus and neuropathy. Abnormalities were most pronounced in the plantar flexors.© RSNA, 2020Online supplemental material is available for this article.See also the editorial by Sneag and Tan in this issue.

Quantitative MRI of skeletal muscle in a cross-sectional cohort of patients with spinal muscular atrophy types 2 and 3.

The aim of this study was to document upper leg involvement in spinal muscular atrophy (SMA) with quantitative MRI (qMRI) in a cross-sectional cohort of patients of varying type, disease severity and age. Thirty-one patients with SMA types 2 and 3 (aged 29.6 [7.6-73.9] years) and 20 healthy controls (aged 37.9 [17.7-71.6] years) were evaluated in a 3 T MRI with a protocol consisting of DIXON, T2 mapping and diffusion tensor imaging (DTI). qMRI measures were compared with clinical scores of motor function (Hammersmith Functional Motor Scale Expanded [HFMSE]) and muscle strength. Patients exhibited an increased fat fraction and fractional anisotropy (FA), and decreased mean diffusivity (MD) and T2 compared with controls (all P < .001). DTI parameters FA and MD manifest stronger effects than can be accounted for the effect of fatty replacement. Fat fraction, FA and MD show moderate correlation with muscle strength and motor function: FA is negatively associated with HFMSE and Medical Research Council sum score (τ = -0.56 and -0.59; both P < .001) whereas for fat fraction values are τ = -0.50 and -0.58, respectively (both P < .001). This study shows that DTI parameters correlate with muscle strength and motor function. DTI findings indirectly indicate cell atrophy and act as a measure independently of fat fraction. Combined these data suggest the potential of muscle DTI in monitoring disease progression and to study SMA pathogenesis in muscle.

Diffusion tensor imaging reveals changes in non-fat infiltrated muscles in late onset Pompe disease.

MRI is a helpful tool for monitoring disease progression in late-onset Pompe disease (LOPD). Our study aimed to evaluate if muscle diffusion tensor imaging (mDTI) shows alterations in muscles of LOPD patients with <10% fat-fraction. We evaluated 6 thigh and 7 calf muscles (both legs) of 18 LOPD and 29 healthy controls (HC) with muscle diffusion tensor imaging (mDTI), T1w, and mDixonquant sequences in a 3T MRI scanner. The quantitative mDTI-values axial diffusivity (λ1 ), mean diffusivity (MD), radial diffusivity (RD), and fractional anisotropy (FA) as well as fat-fraction were analyzed. 6-Minute Walk Test (6-MWT) data were correlated to diffusion metrics. We found that mDTI showed significant differences between LOPD and HC in diffusion parameters (P < .05). Thigh muscles with <10% fat-fraction showed significant differences in MD, RD, and λ1-3 . MD positively correlated with 6-MWT (P = .06). To conclude, mDTI reveals diffusion restrictions in muscles of LOPD with and without fat-infiltration and reflects structural changes prior to fatty degeneration.

Diffusion tensor imaging of the human thigh: consideration of DTI-based fiber tracking stop criteria.

OBJECTIVES: To consider the tract-based analysis of DTI parameters in human muscle by assessing different fiber tracking stop criteria settings on diffusion parameters. MATERIALS AND METHODS: 30 healthy volunteers underwent a 3 T MRI. Diffusion-weighted images were acquired to perform DTI and fiber tracking analysis for six thigh muscles. Whole thigh muscles were evaluated by fiber tractography using different fiber tracking stop parameters [FA (0.01-0.15) to (0.4-0.99); angle 10°-30°, step size 0.75 mm, 1.5 mm, 3 mm]. Diffusion and tractography-derived parameters per stop criterion were compared using a repeated measure ANOVA including Bonferroni-corrected post hoc tests. RESULTS: We found significant differences in all examined diffusion parameters between different stop criteria (main effect p < 0.001). We showed different influence of tracking parameters on diffusion parameters in examined muscles (main effect p ≤ 0.001). CONCLUSIONS: Statistically significant differences in fiber tracking results using different stop criteria were shown. Fiber tracking stop criteria do have an important influence on study results and should be considered in the development of study protocols and comparison of studies. We recommend a FA minimum of 0.10 and a step size lower than voxel size, e.g., a half with a constant ratio between step size and angle of 10°/mm.

On the sensitivity of the diffusion MRI signal to brain activity in response to a motor cortex paradigm.

Diffusion functional magnetic resonance imaging (dfMRI) is a promising technique to map functional activations by acquiring diffusion-weighed spin-echo images. In previous studies, dfMRI showed higher spatial accuracy at activation mapping compared to classic functional MRI approaches. However, it remains unclear whether dfMRI measures result from changes in the intracellular/extracellular environment, perfusion, and/or T2 values. We designed an acquisition/quantification scheme to disentangle such effects in the motor cortex during a finger-tapping paradigm. dfMRI was acquired at specific diffusion weightings to selectively suppress perfusion and free-water diffusion, then time series of the apparent diffusion coefficient (ADC-fMRI) and of intravoxel incoherent motion (IVIM) effects were derived. ADC-fMRI provided ADC estimates sensitive to changes in perfusion and free-water volume, but not to T2 /T2 * values. With IVIM modeling, we isolated the perfusion contribution to ADC, while suppressing T2 effects. Compared to conventional gradient-echo blood oxygenation level-dependent fMRI, activation maps obtained with dfMRI and ADC-fMRI had smaller clusters, and the spatial overlap between the three techniques was below 50%. Increases of perfusion fractions were observed during task in both dfMRI and ADC-fMRI activations. Perfusion effects were more prominent with ADC-fMRI than with dfMRI but were significant in less than 25% of activation regions. IVIM modeling suggests that the sensitivity to task of dfMRI derives from a decrease of intracellular/extracellular diffusion and an increase of the pseudo-diffusion signal fraction, leading to different, more confined spatial activation patterns compared to classic functional MRI.

Multi-center evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles.

The purpose of this study was to evaluate temporal stability, multi-center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle. Quantitative T2, quantitative diffusion and four-point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty-five healthy volunteers (31 females) were included in one of eight 3-T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water-T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two-way random intraclass correlation coefficient (ICC). Multi-center reproducibility of traveling volunteers was assessed by a two-way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance. ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water-T2 relaxation decreased significantly (P < 10-3 ) within one hour by ~ 1 ms. Multi-center reproducibility showed ICCs within 0.879-0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20-40% of variance for observed parameters. Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.

Diffusion tensor imaging of the human calf: Variation of inter- and intramuscle-specific diffusion parameters.

PURPOSE: To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). MATERIALS AND METHODS: Whole calf muscles of 18 healthy volunteers were evaluated. Magnetic resonance imaging (MRI) was performed using a 3T scanner and a 16-channel Torso XL coil. Diffusion-weighted images were acquired to perform fiber tractography and diffusion tensor imaging (DTI) analysis for each muscle of both legs. Fiber tractography was used to separate seven lower leg muscles. Associations between DTI parameters and confounds were evaluated. All muscles were additionally separated in seven identical segments along the z-axis to evaluate intramuscular differences in diffusion parameters. RESULTS: Fractional anisotropy (FA) and mean diffusivity (MD) were obtained for each muscle with low standard deviations (SDs) (SDFA : 0.01-0.02; SDMD : 0.07-0.14(10-3 )). We found significant differences in FA values of the tibialis anterior muscle (AT) and extensor digitorum longus (EDL) muscles between men and women for whole muscle FA (two-sample t-tests; AT: P = 0.0014; EDL: P = 0.0004). We showed significant intramuscular differences in diffusion parameters between adjacent segments in most calf muscles (P < 0.001). Whereas muscle insertions showed higher (SD 0.03-0.06) than muscle bellies (SD 0.01-0.03), no relationships between FA or MD with age or BMI were found. CONCLUSION: Inter- and intramuscular variations in diffusion parameters of the calf were shown, which are not related to age or BMI in this age group. Differences between muscle belly and insertion should be considered when interpreting datasets not including whole muscles. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1137-1148.

Shared and nonshared neural networks of cognitive and affective theory-of-mind: a neuroimaging study using cartoon picture stories.

Theory of mind (ToM) refers to the ability to represent one's own and others' cognitive and affective mental states. Recent imaging studies have aimed to disentangle the neural networks involved in cognitive as opposed to affective ToM, based on clinical observations that the two can functionally dissociate. Due to large differences in stimulus material and task complexity findings are, however, inconclusive. Here, we investigated the neural correlates of cognitive and affective ToM in psychologically healthy male participants (n = 39) using functional brain imaging, whereby the same set of stimuli was presented for all conditions (affective, cognitive and control), but associated with different questions prompting either a cognitive or affective ToM inference. Direct contrasts of cognitive versus affective ToM showed that cognitive ToM recruited the precuneus and cuneus, as well as regions in the temporal lobes bilaterally. Affective ToM, in contrast, involved a neural network comprising prefrontal cortical structures, as well as smaller regions in the posterior cingulate cortex and the basal ganglia. Notably, these results were complemented by a multivariate pattern analysis (leave one study subject out), yielding a classifier with an accuracy rate of more than 85% in distinguishing between the two ToM-conditions. The regions contributing most to successful classification corresponded to those found in the univariate analyses. The study contributes to the differentiation of neural patterns involved in the representation of cognitive and affective mental states of others.

From perceptual to lexico-semantic analysis--cortical plasticity enabling new levels of processing.

Certain kinds of stimuli can be processed on multiple levels. While the neural correlates of different levels of processing (LOPs) have been investigated to some extent, most of the studies involve skills and/or knowledge already present when performing the task. In this study we specifically sought to identify neural correlates of an evolving skill that allows the transition from perceptual to a lexico-semantic stimulus analysis. Eighteen participants were trained to decode 12 letters of Morse code that were presented acoustically inside and outside of the scanner environment. Morse code was presented in trains of three letters while brain activity was assessed with fMRI. Participants either attended to the stimulus length (perceptual analysis), or evaluated its meaning distinguishing words from nonwords (lexico-semantic analysis). Perceptual and lexico-semantic analyses shared a mutual network comprising the left premotor cortex, the supplementary motor area (SMA) and the inferior parietal lobule (IPL). Perceptual analysis was associated with a strong brain activation in the SMA and the superior temporal gyrus bilaterally (STG), which remained unaltered from pre and post training. In the lexico-semantic analysis post learning, study participants showed additional activation in the left inferior frontal cortex (IFC) and in the left occipitotemporal cortex (OTC), regions known to be critically involved in lexical processing. Our data provide evidence for cortical plasticity evolving with a learning process enabling the transition from perceptual to lexico-semantic stimulus analysis. Importantly, the activation pattern remains task-related LOP and is thus the result of a decision process as to which LOP to engage in.

Microstructural properties of attention-related white matter tracts are associated with the renewal effect of extinction.

The tendency to show the renewal effect of extinction appears as an intra-individually stable, reproducible processing strategy associated with differential patterns of BOLD activation in hippocampus, iFG and vmPFC, as well as differential resting-state functional connectivity between prefrontal regions and the dorsal attention network. Also, pharmacological modulations of the noradrenergic system that influence attentional processing have partially different effects upon individuals with (REN) and without (NoREN) a propensity for renewal. However, it is as yet unknown whether REN and NoREN individuals differ regarding microstructural properties in attention-related white matter (WM) regions, and whether such differences are related to noradrenergic processing. In this diffusion tensor imaging (DTI) analysis we investigated the relation between microstructural properties of attention-related WM tracts and ABA renewal propensity, under conditions of noradrenergic stimulation by means of the noradrenergic reuptake inhibitor atomoxetine, compared to placebo. Fractional anisotropy (FA) was higher in participants with noradrenergic stimulation (ATO) compared to placebo (PLAC), the effect was predominantly left-lateralized and based on the comparison of ATO REN and PLAC REN participants. In REN participants of both treatment groups, FA in several WM tracts showed a positive correlation with the ABA renewal level, suggesting higher renewal levels were associated with higher microstructural integrity. These findings point towards a relation between microstructural properties of attention-related WM tracts and the propensity for renewal that is not specifically dependent on noradrenergic processing.

The angular gyrus serves as an interface between the non-lexical reading network and the semantic system: evidence from dynamic causal modeling.

Understanding encoded language, such as written words, requires multiple cognitive processes that act in a parallel and interactive fashion. These processes and their interactions, however, are not fully understood. Various conceptual and methodical approaches including computational modeling and neuroimaging have been applied to better understand the neural underpinnings of these complex processes in the human brain. In this study, we tested different predictions of cortical interactions that derived from computational models for reading using dynamic causal modeling. Morse code was used as a model for non-lexical decoding followed by a lexical-decision during a functional magnetic resonance examination. Our results suggest that individual letters are first converted into phonemes within the left supramarginal gyrus, followed by a phoneme assembly to reconstruct word phonology, involving the left inferior frontal cortex. To allow the identification and comprehension of known words, the inferior frontal cortex then interacts with the semantic system via the left angular gyrus. As such, the left angular gyrus is likely to host phonological and semantic representations and serves as a bidirectional interface between the networks involved in language perception and word comprehension.