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The heterogeneity of posttraumatic stress disorder (PTSD) is an obstacle to both understanding and therapy, and this has prompted a search for internally homogeneous neuroradiological subgroups within the broad clinical diagnosis. We set out to do this using the individual differential structural covariance network (IDSCN). We constructed cortical thickness‐based IDSCN using T1‐weighted images of 89 individuals with PTSD (mean age 42.8 years, 60 female) and 89 demographically matched trauma‐exposed non‐PTSD (TENP) controls (mean age 43.1 years, 63 female). The IDSCN metric quantifies how the structural covariance edges in a patient differ from those in the controls. We examined the structural diversity of PTSD and variation among subtypes using a hierarchical clustering analysis. PTSD patients exhibited notable diversity in distinct structural covariance edges but mainly affecting three networks: default mode, ventral attention, and sensorimotor. These changes predicted individual PTSD symptom severity. We identified two neuroanatomical subtypes: the one with higher PTSD symptom severity showed lower structural covariance edges in the frontal cortex and between frontal, parietal, and occipital cortex—regions that are functionally implicated in selective attention, response selection, and learning tasks. Thus, deviations in structural covariance in large‐scale networks are common in PTSD but fall into two subtypes. This work sheds light on the neurobiological mechanisms underlying the clinical heterogeneity and may aid in personalized diagnosis and therapeutic interventions. [ABSTRACT FROM AUTHOR]

Background and Aims: Exercise is recommended for the management of metabolic dysfunction‐associated steatotic liver disease (MASLD), yet effects on liver histology remain unknown, especially without significant weight loss. We aimed to examine changes in surrogate measures of liver histological response with exercise training. Methods: We conducted a post hoc pooled analysis of three randomised controlled trials (duration: 12–20 weeks) comparing aerobic exercise interventions with controls. The primary outcome measure was a ≥30% relative reduction in (MRI‐measured) liver fat, as a surrogate measure of liver histological response (the threshold necessary for fibrosis improvement). Secondary outcome measures were changes in other biomarkers of liver fibrosis, anthropometry, body composition and aerobic fitness. Results: Eighty‐eight adults (exercise: 54, control: 34; male: 67%) were included with mean (SD) age 51 (11) years and body mass index 33.3 (5.2) kg/m2. Following the intervention, exercise had ~5‐fold (OR [95%CI]: 4.86 [1.72, 13.8], p =.002) greater odds of ≥30% relative reduction in MRI‐measured liver fat compared with control. This paralleled the improvements in anthropometry (waist and hip circumference reduction), body composition (body fat, visceral and subcutaneous adipose tissue) and aerobic fitness (V̇O2peak, ventilatory threshold and exercise capacity). Importantly, these effects were independent of clinically significant body weight loss (<3% body weight). Conclusion: Exercise training led to clinically meaningful improvements in surrogate serum‐ and imaging‐based measures of liver histological change, without clinically meaningful body weight reduction. These data reinforce the weight‐neutral benefit of exercise training and suggest that aerobic training may improve liver fibrosis in patients with MASLD. [ABSTRACT FROM AUTHOR]

It has been shown using proton magnetic resonance spectroscopy (1H MRS) that, in a group of females, whole‐body insulin resistance was more closely related to accumulation of saturated intramyocellular lipid (IMCL) than to IMCL concentration alone. This has not been investigated in males. We investigated whether age‐ and body mass index‐matched healthy males differ from the previously reported females in IMCL composition (measured as CH2:CH3) and IMCL concentration (measured as CH3), and in their associations with insulin resistance. We ask whether saturated IMCL accumulation is more strongly associated with insulin resistance than other ectopic and adipose tissue lipid pools and remains a significant predictor when these other pools are taken into account. In this group of males, who had similar overall insulin sensitivity to the females, IMCL was similar between sexes. The males demonstrated similar and even stronger associations of IMCL with insulin resistance, supporting the idea that a marker reflecting the accumulation of saturated IMCL is more strongly associated with whole‐body insulin resistance than IMCL concentration alone. However, this marker ceased to be a significant predictor of whole‐body insulin resistance after consideration of other lipid pools, which implies that this measure carries no more information in practice than the other predictors we found, such as intrahepatic lipid and visceral adipose tissue. As the marker of saturated IMCL accumulation appears to be related to these two predictors and has a much smaller dynamic range, this finding does not rule out a role for it in the pathogenesis of insulin resistance. [ABSTRACT FROM AUTHOR]

Aims: Although static abnormalities of functional brain networks have been observed in patients with social anxiety disorder (SAD), the brain connectome dynamics at the macroscale network level remain obscure. We therefore used a multivariate data‐driven method to search for dynamic functional network connectivity (dFNC) alterations in SAD. Methods: We conducted spatial independent component analysis, and used a sliding‐window approach with a k‐means clustering algorithm, to characterize the recurring states of brain resting‐state networks; then state transition metrics and FNC strength in the different states were compared between SAD patients and healthy controls (HC), and the relationship to SAD clinical characteristics was explored. Results: Four distinct recurring states were identified. Compared with HC, SAD patients demonstrated higher fractional windows and mean dwelling time in the highest‐frequency State 3, representing "widely weaker" FNC, but lower in States 2 and 4, representing "locally stronger" and "widely stronger" FNC, respectively. In State 1, representing "widely moderate" FNC, SAD patients showed decreased FNC mainly between the default mode network and the attention and perceptual networks. Some aberrant dFNC signatures correlated with illness duration. Conclusion: These aberrant patterns of brain functional synchronization dynamics among large‐scale resting‐state networks may provide new insights into the neuro‐functional underpinnings of SAD. [ABSTRACT FROM AUTHOR]

We aimed to determine the extent of multiorgan fat accumulation and fibroinflammation in individuals living with type 2 diabetes. We deeply phenotyped individuals with type 2 diabetes (134 from secondary care, 69 from primary care) with multiorgan, quantitative, multiparametric MRI and compared with 134 matched control individuals without diabetes and 92 control individuals with normal weight. We examined the impact of diabetes duration, obesity status, and glycemic control. Ninety-three of the individuals with type 2 diabetes were reevaluated at 7 months (median). Multiorgan abnormalities were more common in individuals with type 2 diabetes (94%) than in age- and BMI-matched healthy individuals or healthy individuals with normal weight. We demonstrated a high burden of combined steatosis and fibroinflammation within the liver, pancreas, and kidneys (41%, 17%, and 10%) associated with visceral adiposity (73%) and poor vascular health (82%). Obesity was most closely associated with advanced liver disease, renal and visceral steatosis, and multiorgan abnormalities, while poor glycemic control was associated with pancreatic fibroinflammation. Pharmacological therapies with proven cardiorenal protection improved liver and vascular health unlike conventional glucose-lowering treatments, while weight loss or improved glycemic control reduced multiorgan adiposity (P ≤ 0.01). Quantitative imaging in people with type 2 diabetes highlights widespread organ abnormalities and may provide useful risk and treatment stratification. Article Highlights: Type 2 diabetes is a multisystem disease, but multiorgan imaging studies are lacking. The objective was to quantify organ abnormalities (steatosis and fibroinflammation) in type 2 diabetes using multiparametric MRI (mpMRI). In 126 of 134 individuals with type 2 diabetes, multiorgan abnormalities (steatosis and fibroinflammation) were detected with mpMRI, which persisted despite glucose-lowering therapy over 7 months. The therapeutic impact of new diabetes therapies on preventing or reversing end-organ damage can be measured by mpMRI. [ABSTRACT FROM AUTHOR]

Aim: This study assessed the impact of dapagliflozin on food intake, eating behaviour, energy expenditure, magnetic resonance imaging (MRI)‐determined brain response to food cues and body composition in patients with type 2 diabetes mellitus (T2D). Materials and Methods: Patients were given dapagliflozin 10 mg once daily in a randomized, double‐blind, placebo‐controlled trial with short‐term (1 week) and long‐term (12 weeks) cross‐over periods. The primary outcome was the difference in test meal food intake between long‐term dapagliflozin and placebo treatment. Secondary outcomes included short‐term differences in test meal food intake, short‐ and long‐term differences in appetite and eating rate, energy expenditure and functional MRI brain activity in relation to food images. We determined differences in glycated haemoglobin, weight, liver fat (by 1H magnetic resonance spectroscopy) and subcutaneous/visceral adipose tissue volumes (by MRI). Results: In total, 52 patients (43% were women) were randomized; with the analysis of 49 patients: median age 58 years, weight 99.1 kg, body mass index 35 kg/m2, glycated haemoglobin 49 mmol/mol. Dapagliflozin reduced glycated haemoglobin by 9.7 mmol/mol [95% confidence interval (CI) 3.91‐16.27, p =.004], and body weight (−2.84 vs. −0.87 kg) versus placebo. There was no short‐ or long‐term difference in test meal food intake between dapagliflozin and placebo [mean difference 5.7 g (95% CI −127.9 to 139.3, p =.933); 15.8 g (95% CI −147.7 to 116.1, p =.813), respectively] nor in the rate of eating, energy expenditure, appetite, or brain responses to food cues. Liver fat (median reduction −4.7 vs. 1.95%), but not subcutaneous/visceral adipose tissue, decreased significantly with 12 weeks of dapagliflozin. Conclusions: The reduction in body weight and liver fat with dapagliflozin was not associated with compensatory adaptations in food intake or energy expenditure. [ABSTRACT FROM AUTHOR]

Recent graph-theoretical studies of Parkinson's disease (PD) have examined alterations in the global properties of the brain structural connectome; however, reported alterations are not consistent. The present study aimed to identify the most robust global metric alterations in PD via a meta-analysis. A comprehensive literature search was conducted for all available diffusion MRI structural connectome studies that compared global graph metrics between PD patients and healthy controls (HC). Hedges' g effect sizes were calculated for each study and then pooled using a random-effects model in Comprehensive Meta-Analysis software, and the effects of potential moderator variables were tested. A total of 22 studies met the inclusion criteria for review. Of these, 16 studies reporting 10 global graph metrics (916 PD patients; 560 HC) were included in the meta-analysis. In the structural connectome of PD patients compared with HC, we found a significant decrease in clustering coefficient (g = -0.357, P = 0.005) and global efficiency (g = -0.359, P < 0.001), and a significant increase in characteristic path length (g = 0.250, P = 0.006). Dopaminergic medication, sex and age of patients were potential moderators of global brain network changes in PD. These findings provide evidence of decreased global segregation and integration of the structural connectome in PD, indicating a shift from a balanced small-world network to 'weaker small-worldization', which may provide useful markers of the pathophysiological mechanisms underlying PD. [ABSTRACT FROM AUTHOR]

Background: Although aberrant brain regional responses are reported in social anxiety disorder (SAD), little is known about resting-state functional connectivity at the macroscale network level. This study aims to identify functional network abnormalities using a multivariate data-driven method in a relatively large and homogenous sample of SAD patients, and assess their potential diagnostic value. Methods: Forty-six SAD patients and 52 demographically-matched healthy controls (HC) were recruited to undergo clinical evaluation and resting-state functional MRI scanning. We used group independent component analysis to characterize the functional architecture of brain resting-state networks (RSNs) and investigate between-group differences in intra-/inter-network functional network connectivity (FNC). Furtherly, we explored the associations of FNC abnormalities with clinical characteristics, and assessed their ability to discriminate SAD from HC using support vector machine analyses. Results: SAD patients showed widespread intra-network FNC abnormalities in the default mode network, the subcortical network and the perceptual system (i.e. sensorimotor, auditory and visual networks), and large-scale inter-network FNC abnormalities among those high-order and primary RSNs. Some aberrant FNC signatures were correlated to disease severity and duration, suggesting pathophysiological relevance. Furthermore, intrinsic FNC anomalies allowed individual classification of SAD v. HC with significant accuracy, indicating potential diagnostic efficacy. Conclusions: SAD patients show distinct patterns of functional synchronization abnormalities both within and across large-scale RSNs, reflecting or causing a network imbalance of bottom-up response and top-down regulation in cognitive, emotional and sensory domains. Therefore, this could offer insights into the neurofunctional substrates of SAD. [ABSTRACT FROM AUTHOR]

The article in the Journal of Magnetic Resonance Imaging discusses the potential of multiparametric quantitative muscle MRI (qMRI) in diagnosing Duchenne muscular dystrophy (DMD) in its early stages. The study compared 140 boys with DMD to healthy controls and found that T2 and fat fraction (FF) were effective in discriminating patients from controls. The authors suggest that qMRI could be useful in tracking disease progression or treatment effectiveness in DMD patients. [Extracted from the article]

Children and adolescents are more susceptible than adults to developing posttraumatic stress disorder (PTSD). Pediatric PTSD is characterized by functional alterations in brain fear circuitry, but little is known about the underlying microstructural changes; previous work has mainly focused on the corpus callosum. This study is aimed at investigating brain-wide microstructural abnormalities in pediatric PTSD, their relationship to age and sex, and their potential diagnostic value. The microstructure of major white matter tracts was assessed from diffusion tensor images acquired from 24 treatment-naive non-comorbid PTSD patients <18 years and 24 trauma-exposed non-PTSD controls (TENP) matched for age, sex, and years of education. Statistical analyses included pointwise comparisons, correlations with symptom severity, and diagnosis-by-age/sex interactions; support vector machine analyses were conducted to determine whether microstructure distinguishes PTSD from TENP. Compared with TENP, pediatric PTSD patients showed higher fractional anisotropy and lower radial diffusivity in right superior longitudinal fasciculus and lower axial diffusivity in right uncinate fasciculus. These white matter microstructural abnormalities were highly correlated with PTSD symptom severity. No significant diagnosis by age or sex interaction was observed. The pointwise axial diffusivity measurements presented the best PTSD vs. TENP classification performance. In summary, pediatric PTSD patients showed clinically relevant microstructural abnormalities in uncinate and superior longitudinal fasciculus, which extend understanding of pediatric PTSD neurobiology beyond the corpus callosum and have diagnostic potential in distinguishing stressed individuals with and without PTSD. [ABSTRACT FROM AUTHOR]

This article discusses the usefulness of phosphorus magnetic resonance spectroscopy (31P MRS) in studying skeletal muscle metabolism. The article highlights the limitations of 31P MRS, such as low signal-to-noise ratio and the need for separate exercise acquisitions for each volume of interest. The authors propose a new approach using CEST MRI to quantify postexercise phosphocreatine (PCr) recovery in calf muscle. The study found slower PCr recovery in individuals with type 2 diabetes compared to controls, indicating a functional impairment of mitochondrial ATP synthesis. The article concludes by emphasizing the feasibility of this method for studying muscle mitochondrial function in a clinical setting. [Extracted from the article]

Background: Multiple lesions are uncommon in brain gliomas, and their pathophysiology is poorly understood. Invasive growth along white matter tracts is an important clinicopathological characteristic of gliomas, and a major factor in a poor therapeutic outcome. Here, we used probabilistic fiber tracking and cluster analysis to investigate the inter-focal connectivity relationships of multiple gliomas, in order to seek inferential evidence of common origin. Methods: MRI scans of 46 patients with multiple gliomas were retrospectively analyzed. Before surgery, all patients underwent multimodal functional MR imaging, including diffusion tensor imaging, enhanced 3D T1-weighted imaging, diffusion-weighted imaging, 1H MR spectroscopy, and dynamic susceptibility contrast perfusion-weighted imaging. Probabilistic fiber tracking was used to quantify white matter connectivity between neoplastic foci. Hierarchical cluster analysis was performed to identify patterns of white matter connection. Results: Cluster analysis reveals two patterns of connectivity, one with smaller, and one with greater, connectivity (2675 ± 1098 versus 30432 ± 22707, p < 0.0001). The two subgroups show significant differences in relative cerebral blood volume (2.31 ± 0.95 versus 1.73 ± 0.48, p = 0.002) and lipid/creatine ratio (0.32 ± 0.22 versus 0.060 ± 0.051, p = 0.006). Conclusion: Two distinct patterns of white matter connection exist in multiple gliomas. Those with lower connectivity tend to have independent origins, and can be termed true multicentric glioma, whereas those with greater connectivity tend to share common origin, and spread along white matter tracts. True multicentric gliomas have higher vascularity and more intratumoral necrosis. These findings may help to develop personalized therapeutic strategies for multiple gliomas. [ABSTRACT FROM AUTHOR]

Background: Orthodontic pain is orofacial pain caused by tooth movement. Anxiety is a strong predictor of the severity of such pain, but little is known about the underlying neuropsychological mechanisms of such effects. The purpose of this study was to investigate the effect of orthodontic pain on brain functional networks and to define the mediating role of anxiety in orthodontic pain and brain function. Methods: Graph theory-based network analyses were applied to brain functional magnetic resonance imaging data from 48 healthy participants exposed to 24 h orthodontic pain stimuli and 49 healthy controls without any stimulation. Results: In the experimental orthodontic pain stimulation, brain functional networks retained a small-world organization. At the regional level, the nodal centrality of ipsilateral brain nodes to the pain stimulus was enhanced; in contrast the nodal centrality of contralateral brain areas was decreased, especially the right mid-cingulate cortex, which is involved in pain intensity coding. Furthermore, anxiety mediated the relationship between nodal efficiency of mid-cingulate cortex and pain severity. Conclusion: The results illuminate the neural mechanisms of orthodontic pain by revealing unbalanced hemispherical brain function related to the unilateral pain stimulation, and reveal clinically exploitable evidence that anxiety mediates the relationship between nodal function of right mid-cingulate cortex and orthodontic pain. [ABSTRACT FROM AUTHOR]

Purpose: Lactate is a key metabolite in skeletal muscle and whole‐body physiology. Its MR visibility in muscle is affected by overlapping lipid signals and fiber orientation. Double‐quantum filtered (DQF) 1H MRS selectively detects lactate at 1.3 ppm, but at ultra‐high field the efficiency of slice‐selective 3D‐localization with conventional RF pulses is limited by bandwidth. This novel 3D‐localized 1H DQF MRS sequence uses adiabatic refocusing pulses to unambiguously detect lactate in skeletal muscle at 7 T. Methods: Lactate double‐quantum coherences were 3D‐localized using slice‐selective Shinnar–Le Roux optimized excitation and adiabatic refocusing pulses (similar to semi‐LASER). DQF MR spectra were acquired at 7 T from lactate phantoms, meat specimens with injected lactate (exploring multiple TEs and fiber orientations), and human gastrocnemius in vivo during and after exercise (without cuff ischemia). Results: Lactate was readily detected, achieving the full potential of 50% signal with a DQF, in solution. The effects of fiber orientation and TE on the lactate doublet (peak splitting, amplitude, and phase) were in good agreement with theory and literature. Exercise‐induced lactate accumulation was detected with 30 s time resolution. Conclusion: This novel 3D‐localized 1H DQF MRS sequence can dynamically detect glycolytically generated lactate in muscle during exercise and recovery at 7 T. [ABSTRACT FROM AUTHOR]

Aims: In populations of black African ancestry (BA), a paradox exists whereby lower visceral adipose tissue is found despite their high risk for type 2 diabetes (T2D). This systematic review investigates ethnic differences in other ectopic fat depots (intrahepatic lipid: IHL; intramyocellular lipid: IMCL and intrapancreatic lipid; IPL) to help contextualise their potential contribution to T2D risk. Methods: A systematic literature search was performed in December 2020 to identify studies reporting at least one ectopic fat comparison between BA and one/more other ethnicity. For IHL, a meta-analysis was carried out with studies considered comparable based on the method of measurement. Results: Twenty-eight studies were included (IHL: n = 20; IMCL: n = 8; IPL: n = 4). Meta-analysis of 11 studies investigating IHL revealed that it was lower in BA populations vs pooled ethnic comparators (MD −1.35%, 95% CI −1.55 to −1.16, I2 = 85%, P < 0.00001), white European ancestry (MD −0.94%, 95% CI −1.17 to -0.70, I2 = 79%, P < 0.00001), Hispanic ancestry (MD −2.06%, 95% CI −2.49 to −1.63, I2 = 81%, P < 0.00001) and South Asian ancestry comparators (MD −1.92%, 95% CI −3.26 to −0.57, I2 = 78%, P = 0.005). However, heterogeneity was high in all analyses. Most studies found no significant differences in IMCL between BA and WE. Few studies investigated IPL, however, indicated that IPL is lower in BA compared to WE and HIS. Conclusion: The discordance between ectopic fat and greater risk for T2D in BA populations raises questions around its contribution to T2D pathophysiology in BA. [ABSTRACT FROM AUTHOR]

Background: Neuroimaging studies in posttraumatic stress disorder (PTSD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these are localized to specific regions of fiber tracts, and what diagnostic value they might have. This study set out to explore the spatial profile of WM abnormalities along defined fiber tracts in PTSD. Methods: Diffusion tensor images were obtained from 77 treatment‐naive noncomorbid patients with PTSD and 76 demographically matched trauma‐exposed non‐PTSD (TENP) controls. Using automated fiber quantification, tract profiles of fractional anisotropy, axial diffusivity, mean diffusivity, and radial diffusivity were calculated to evaluate WM microstructural organization. Results were analyzed by pointwise comparisons, by correlation with symptom severity, and for diagnosis‐by‐sex interactions. Support vector machine analyses assessed the ability of tract profiles to discriminate PTSD from TENP. Results: Compared to TENP, PTSD showed lower fractional anisotropy accompanied by higher radial diffusivity and mean diffusivity in the left uncinate fasciculus, and lower fractional anisotropy accompanied by higher radial diffusivity in the right anterior thalamic radiation. Tract profile alterations were correlated with symptom severity, suggesting a pathophysiological relevance. There were no significant differences in diagnosis‐by‐sex interaction. Tract profiles allowed individual classification of PTSD versus TENP with significant accuracy, of potential diagnostic utility. Conclusions: These findings add to the knowledge of the neuropathological basis of PTSD. WM alterations based on a tract‐profile quantification approach are a potential biomarker for PTSD. [ABSTRACT FROM AUTHOR]

Background: Children exposed to natural disasters are vulnerable to developing posttraumatic stress disorder (PTSD). Previous studies using resting-state functional neuroimaging have revealed alterations in graph-based brain topological network metrics in pediatric PTSD patients relative to healthy controls (HC). Here we aimed to apply deep learning (DL) models to neuroimaging markers of classification which may be of assistance in diagnosis of pediatric PTSD. Methods: We studied 33 pediatric PTSD and 53 matched HC. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole-brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was used to examine the topological properties of the functional connectome. A DL algorithm then used this measure to classify pediatric PTSD vs HC. Results: Graphic topological measures using DL provide a potentially clinically useful classifier for differentiating pediatric PTSD and HC (overall accuracy 71.2%). Frontoparietal areas (central executive network), cingulate cortex, and amygdala contributed the most to the DL model's performance. Conclusions: Graphic topological measures based on fMRI data could contribute to imaging models of clinical utility in distinguishing pediatric PTSD from HC. DL model may be a useful tool in the identification of brain mechanisms PTSD participants. [ABSTRACT FROM AUTHOR]

Patients with Parkinson's disease with mild cognitive impairment (PD‐M) progress to dementia more frequently than those with normal cognition (PD‐N), but the underlying neurobiology remains unclear. This study aimed to define the specific morphological brain network alterations in PD‐M, and explore their potential diagnostic value. Twenty‐four PD‐M patients, 17 PD‐N patients, and 29 healthy controls (HC) underwent a structural MRI scan. Similarity between interregional gray matter volume distributions was used to construct individual morphological brain networks. These were analyzed using graph theory and network‐based statistics (NBS), and their relationship to neuropsychological tests was assessed. Support vector machine (SVM) was used to perform individual classification. Globally, compared with HC, PD‐M showed increased local efficiency (p =.001) in their morphological networks, while PD‐N showed decreased normalized path length (p =.008). Locally, similar nodal deficits were found in the rectus and lingual gyrus, and cerebellum of both PD groups relative to HC; additionally in PD‐M nodal deficits involved several frontal and parietal regions, correlated with cognitive scores. NBS found that similar connections were involved in the default mode and cerebellar networks of both PD groups (to a greater extent in PD‐M), while PD‐M, but not PD‐N, showed altered connections involving the frontoparietal network. Using connections identified by NBS, SVM allowed discrimination with high accuracy between PD‐N and HC (90%), PD‐M and HC (85%), and between the two PD groups (65%). These results suggest that default mode and cerebellar disruption characterizes PD, more so in PD‐M, whereas frontoparietal disruption has diagnostic potential. [ABSTRACT FROM AUTHOR]

Objective: There is increasing evidence that amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease impacting large-scale brain networks. However, it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression. This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate. Methods: Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire diffusion-weighted magnetic resonance images and construct white matter (WM) networks using tractography methods. The global and regional network properties were compared between ALS and healthy subjects. The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms. Results: Compared with the healthy participants, the patients with ALS showed significantly decreased clustering coefficient Cp (P = 0.0034, t = 2.98), normalized clustering coefficient γ (P = 0.039, t = 2.08), and small‐worldness σ (P = 0.038, t = 2.10) at the global network level. The patients also showed decreased regional centralities in motor and non-motor systems including the frontal, temporal and subcortical regions. Using the single-subject structural connection matrix, our classification model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%. Conclusion: Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems, extending the classical pathophysiological understanding of ALS as a motor disorder. The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice. [ABSTRACT FROM AUTHOR]

Purpose: To use structural magnetic resonance imaging and graph theory approaches to investigate the topological organization of the brain morphological network based on gray matter in essential tremor, and its potential relation to disease severity. Methods: In this prospective study conducted from November 2018 to November 2019, 36 participants with essential tremor and 37 matched healthy controls underwent magnetic resonance imaging. Brain networks based on the morphological similarity of gray matter across regions were analyzed using graph theory. Nonparametric permutation testing was used to assess group differences in topological metrics. Support vector machine was applied to the gray matter morphological matrices to classify participants with essential tremor vs. healthy controls. Results: Compared with healthy controls, participants with essential tremor showed increased global efficiency (p < 0.01) and decreased path length (p < 0.01); abnormal nodal properties in frontal, parietal, and cerebellar lobes; and disconnectivity in cerebello-thalamo-cortical network. The abnormal brain nodal centralities (left superior cerebellum gyrus; right caudate nucleus) correlated with clinical measures, both motor (Fahn–Tolosa–Marìn tremor rating, p = 0.017, r = − 0.41) and nonmotor (Hamilton depression scale, p = 0.040, r = − 0.36; Hamilton anxiety scale, p = 0.008, r = − 0.436). Gray matter morphological matrices classified individuals with high accuracy of 80.0%. Conclusion: Participants with essential tremor showed randomization in global properties and dysconnectivity in the cerebello-thalamo-cortical network. Participants with essential tremor could be distinguished from healthy controls by gray matter morphological matrices. [ABSTRACT FROM AUTHOR]

Neuroimaging studies using a variety of techniques have demonstrated abnormal patterns of spontaneous brain activity in patients with essential tremor (ET). However, the findings are variable and inconsistent, hindering understanding of underlying neuropathology. We conducted a meta‐analysis of whole‐brain resting‐state functional neuroimaging studies in ET compared to healthy controls (HC), using anisotropic effect‐size seed‐based d mapping, to identify the most consistent brain activity alterations and their relation to clinical features. After systematic literature search, we included 13 studies reporting 14 comparisons, describing 286 ET patients and 254 HC. Subgroup analyses were conducted considering medication status, head tremor status, and methodological factors. Brain activity in ET is altered not only in the cerebellum and cerebral motor cortex, but also in nonmotor cortical regions including prefrontal cortex and insula. Most of the results remained unchanged in subgroup analyses of patients with head tremor, medication‐naive patients, studies with statistical threshold correction, and the large subgroup of studies using functional magnetic resonance imaging. These findings not only show consistent and robust abnormalities in specific brain regions but also provide new information on the biology of patient heterogeneity, and thus help to elucidate the pathophysiology of ET. [ABSTRACT FROM AUTHOR]

Background: The EMPOWER trial aimed to assess the effects of a 9-week exercise prehabilitation programme on physical fitness compared with a usual care control group. Secondary aims were to investigate the effect of (1) the exercise prehabilitation programme on psychological health; and (2) neoadjuvant chemoradiotherapy (NCRT) on physical fitness and psychological health. Methods: Between October 2013 and December 2016, adults with locally advanced rectal cancer undergoing standardised NCRT and surgery were recruited to a multi-centre trial. Patients underwent cardiopulmonary exercise testing (CPET) and completed HRQoL questionnaires (EORTC-QLQ-C30 and EQ-5D-5L) pre-NCRT and post-NCRT (week 0/baseline). At week 0, patients were randomised to exercise prehabilitation or usual care (no intervention). CPET and HRQoL questionnaires were assessed at week 0, 3, 6 and 9, whilst semi-structured interviews were assessed at week 0 and week 9. Changes in oxygen uptake at anaerobic threshold (VO2 at AT (ml kg−1 min−1)) between groups were compared using linear mixed modelling. Results: Thirty-eight patients were recruited, mean age 64 (10.4) years. Of the 38 patients, 33 were randomised: 16 to usual care and 17 to exercise prehabilitation (26 males and 7 females). Exercise prehabilitation significantly improved VO2 at AT at week 9 compared to the usual care. The change from baseline to week 9, when adjusted for baseline, between the randomised groups was + 2.9 ml kg −1 min −1; (95% CI 0.8 to 5.1), p = 0.011. Conclusion: A 9-week exercise prehabilitation programme significantly improved fitness following NCRT. These findings have informed the WesFit trial (NCT03509428) which is investigating the effects of community-based multimodal prehabilitation before cancer surgery. Trial registration: ClinicalTrials.gov NCT01914068. Registered 1 August 2013. [ABSTRACT FROM AUTHOR]

While previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis. [ABSTRACT FROM AUTHOR]

The translation of MRS to clinical practice has been impeded by the lack of technical standardization. There are multiple methods of acquisition, post‐processing, and analysis whose details greatly impact the interpretation of the results. These details are often not fully reported, making it difficult to assess MRS studies on a standardized basis. This hampers the reviewing of manuscripts, limits the reproducibility of study results, and complicates meta‐analysis of the literature. In this paper a consensus group of MRS experts provides minimum guidelines for the reporting of MRS methods and results, including the standardized description of MRS hardware, data acquisition, analysis, and quality assessment. This consensus statement describes each of these requirements in detail and includes a checklist to assist authors and journal reviewers and to provide a practical way for journal editors to ensure that MRS studies are reported in full. [ABSTRACT FROM AUTHOR]

Skeletal muscle phosphorus‐31 31P MRS is the oldest MRS methodology to be applied to in vivo metabolic research. The technical requirements of 31P MRS in skeletal muscle depend on the research question, and to assess those questions requires understanding both the relevant muscle physiology, and how 31P MRS methods can probe it. Here we consider basic signal‐acquisition parameters related to radio frequency excitation, TR, TE, spectral resolution, shim and localisation. We make specific recommendations for studies of resting and exercising muscle, including magnetisation transfer, and for data processing. We summarise the metabolic information that can be quantitatively assessed with 31P MRS, either measured directly or derived by calculations that depend on particular metabolic models, and we give advice on potential problems of interpretation. We give expected values and tolerable ranges for some measured quantities, and minimum requirements for reporting acquisition parameters and experimental results in publications. Reliable examination depends on a reproducible setup, standardised preconditioning of the subject, and careful control of potential difficulties, and we summarise some important considerations and potential confounders. Our recommendations include the quantification and standardisation of contraction intensity, and how best to account for heterogeneous muscle recruitment. We highlight some pitfalls in the assessment of mitochondrial function by analysis of phosphocreatine (PCr) recovery kinetics. Finally, we outline how complementary techniques (near‐infrared spectroscopy, arterial spin labelling, BOLD and various other MRI and 1H MRS measurements) can help in the physiological/metabolic interpretation of 31P MRS studies by providing information about blood flow and oxygen delivery/utilisation. Our recommendations will assist in achieving the fullest possible reliable picture of muscle physiology and pathophysiology. [ABSTRACT FROM AUTHOR]

Objective: This study examined the effects of a short-term reduction in physical activity, and subsequent resumption, on metabolic profiles, body composition and cardiovascular (endothelial) function. Design: Twenty-eight habitually active (≥10,000 steps/day) participants (18 female, 10 male; age 32 ± 11 years; BMI 24.3 ± 2.5 kg/m2) were assessed at baseline, following 14 days of step-reduction and 14 days after resuming habitual activity. Methods: Physical activity was monitored throughout (SenseWear Armband). Endothelial function (flow mediated dilation; FMD), cardiorespiratory fitness ( V. ⁢ O 2 peak) and body composition including liver fat (dual-energy x-ray absorptiometry and magnetic resonance spectroscopy) were determined at each assessment. Statistical analysis was performed using one-way within subject's ANOVA; data presented as mean (95% CI). Results: Participants decreased their step count from baseline by 10,111 steps/day (8949, 11,274; P < 0.001), increasing sedentary time by 103 min/day (29, 177; P < 0.001). Following 14 days of step-reduction, endothelial function was reduced by a 1.8% (0.4, 3.3; P = 0.01) decrease in FMD. Following resumption of habitual activity, FMD increased by 1.4%, comparable to the baseline level 0.4% (–1.8, 2.6; P = 1.00). Total body fat, waist circumference, liver fat, whole body insulin sensitivity and cardiorespiratory fitness were all adversely affected by 14 days step-reduction (P < 0.05) but returned to baseline levels following resumption of activity. Conclusion: This data shows for the first time that whilst a decline in endothelial function is observed following short-term physical inactivity, this is reversed on resumption of habitual activity. The findings highlight the need for public health interventions that focus on minimizing time spent in sedentary behavior. [ABSTRACT FROM AUTHOR]

Key points: The post‐exercise recovery of phosphocreatine, a measure of the oxidative capacity of muscles, as assessed by 31P MR spectroscopy, shows a striking increase from distal to proximal along the human tibialis anterior muscle.To investigate why this muscle exhibits a greater oxidative capacity proximally, we tested whether the spatial variation in phosphocreatine recovery rate is related to oxygen supply, muscle fibre type or type of exercise.We revealed that oxygen supply also increases from distal to proximal along the tibialis anterior, and that it strongly correlated with phosphocreatine recovery. Carnosine level, a surrogate measure for muscle fibre type was not different between proximal and distal, and type of exercise did not affect the gradient in phosphocreatine recovery rate.Taken together, the findings of this study suggest that the post‐exercise spatial gradients in oxygen supply and phosphocreatine recovery are driven by a higher intrinsic mitochondrial oxidative capacity proximally. Phosphorus magnetic resonance spectroscopy (31P MRS) of human tibialis anterior (TA) revealed a strong proximo‐distal gradient in the post‐exercise phosphocreatine (PCr) recovery rate constant (kPCr), a measure of muscle oxidative capacity. The aim of this study was to investigate whether this kPCr gradient is related to O2 supply, resting phosphorylation potential, muscle fibre type, or type of exercise. Fifteen male volunteers performed continuous isometric ankle dorsiflexion at 30% maximum force until exhaustion. At multiple locations along the TA, we measured the oxidative PCr resynthesis rate (VPCr = kPCr × PCr depletion) by 31P MRS, the oxyhaemoglobin recovery rate constant (kO2Hb) by near infrared spectroscopy, and muscle perfusion with MR intravoxel incoherent motion imaging. The kO2Hb, kPCr, VPCr and muscle perfusion depended on measurement location (P < 0.001, P < 0.001, P = 0.032 and P = 0.003, respectively), all being greater proximally. The kO2Hb and muscle perfusion correlated with kPCr (r = 0.956 and r = 0.852, respectively) and VPCr (r = 0.932 and r = 0.985, respectively), the latter reflecting metabolic O2 consumption. Resting phosphorylation potential (PCr/inorganic phosphate) was also higher proximally (P < 0.001). The surrogate for fibre type, carnosine content measured by 1H MRS, did not differ between distal and proximal TA (P = 0.884). Performing intermittent exercise to avoid exercise ischaemia, still led to larger kPCr proximally than distally (P = 0.013). In conclusion, the spatial kPCr gradient is strongly associated with the spatial variation in O2 supply. It cannot be explained by exercise‐induced ischaemia nor by fibre type. Our findings suggest it is driven by a higher proximal intrinsic mitochondrial oxidative capacity, apparently to support contractile performance of the TA. Key points: The post‐exercise recovery of phosphocreatine, a measure of the oxidative capacity of muscles, as assessed by 31P MR spectroscopy, shows a striking increase from distal to proximal along the human tibialis anterior muscle.To investigate why this muscle exhibits a greater oxidative capacity proximally, we tested whether the spatial variation in phosphocreatine recovery rate is related to oxygen supply, muscle fibre type or type of exercise.We revealed that oxygen supply also increases from distal to proximal along the tibialis anterior, and that it strongly correlated with phosphocreatine recovery. Carnosine level, a surrogate measure for muscle fibre type was not different between proximal and distal, and type of exercise did not affect the gradient in phosphocreatine recovery rate.Taken together, the findings of this study suggest that the post‐exercise spatial gradients in oxygen supply and phosphocreatine recovery are driven by a higher intrinsic mitochondrial oxidative capacity proximally. [ABSTRACT FROM AUTHOR]

The hippocampus, a key structure with distinct subfield functions, is strongly implicated in the pathophysiology of post-traumatic stress disorder (PTSD); however, few studies of hippocampus subfields in PTSD have focused on pediatric patients. We therefore investigated the hippocampal subfield volume using an automated segmentation method and explored the subfield-centered functional connectivity aberrations related to the anatomical changes, in a homogenous population of traumatized children with and without PTSD. To investigate the potential diagnostic value in individual patients, we used a machine learning approach to identify features with significant discriminative power for diagnosis of PTSD using random forest classifiers. Compared to controls, we found significant mean volume reductions of 8.4% and 9.7% in the right presubiculum and hippocampal tail in patients, respectively. These two subfields' volumes were the most significant contributors to group discrimination, with a mean classification accuracy of 69% and a specificity of 81%. These anatomical alterations, along with the altered functional connectivity between (pre)subiculum and inferior frontal gyrus, may underlie deficits in fear circuitry leading to dysfunction of fear extinction and episodic memory, causally important in post-traumatic symptoms such as hypervigilance and re-experience. For the first time, we suggest that hippocampal subfield volumes might be useful in discriminating traumatized children with and without PTSD. [ABSTRACT FROM AUTHOR]

Obsessive–compulsive disorder (OCD) is a disabling neuropsychiatric disorder whose neurobiological basis remains unclear. Magnetic resonance imaging (MRI) studies have reported functional and structural alterations of the anterior cingulate cortex (ACC) in OCD. In this study, we explored the functional activity of subregions of the ACC and effective connectivity (EC) between ACC subregions and the whole brain in OCD. We used a Granger causality analysis (GCA) to identify the direction of information flow and whether the impact of that flow was excitatory or inhibitory. We performed resting‐state functional MRI in 31 patients with OCD and 36 healthy controls and analyzed the amplitude of low‐frequency fluctuation (ALFF) and coefficient‐based GCA. The left pregenual ACC (pACC) in patients with OCD showed decreased ALFF relative to controls. There was significantly decreased excitatory output from the left pACC to both right dorsal superior frontal gyrus (dSFG) and left precuneus in patients compared with controls. Patients also had decreased inhibitory input to left pACC from left ventral SFG and left thalamus and caudate relative to controls. Results were similar in drug‐naive patients and those with prior but not current psychopharmacological treatment. In patients, path coefficients of GCA from left pACC to right dSFG showed significant negative correlations with obsession and anxiety ratings. Decreased spontaneous neural activity and altered EC of pACC with widely distributed cortical circuitry, and associations with clinical ratings highlight the importance of pACC functional alteration in OCD. [ABSTRACT FROM AUTHOR]

This study explores the topological properties of brain gray matter (GM) networks in patients with paroxysmal kinesigenic dyskinesia (PKD) and asks whether GM network features have potential diagnostic value. We used 3D T1‐weighted magnetic resonance imaging and graph theoretical approaches to investigate the topological organization of GM morphological networks in 87 PKD patients and 115 age‐ and sex‐matched healthy controls. We applied a support vector machine to GM morphological network matrices to classify PKD patients versus healthy controls. Compared with the HC group, the GM morphological networks of PKD patients showed significant abnormalities at the global level, including an increase in characteristic path length (Lp) and decreases in local efficiency (Eloc), clustering coefficient (Cp), normalized clustering coefficient (γ), and small‐worldness (σ). The decrease in Cp was significantly correlated with disease duration and age of onset. The GM morphological networks of PKD patients also showed significant changes in nodal topological characteristics, mainly in the basal ganglia‐thalamus circuitry, default‐mode network and central executive network. Finally, we used the GM morphological network matrices to classify individuals as PKD patients versus healthy controls, achieving 87.8% accuracy. Overall, this study demonstrated disruption of GM morphological networks in PKD, which might extend our understanding of the pathophysiology of PKD; further, GM morphological network matrices might have the potential to serve as network neuroimaging biomarkers for the diagnosis of PKD. [ABSTRACT FROM AUTHOR]

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size–signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses. [ABSTRACT FROM AUTHOR]

This study explored the topological characteristics of brain white matter structural networks in patients with Paroxysmal Kinesigenic Dyskinesia (PKD), and the potential influence of the brain network stability gene PRRT2 on the structural connectome in PKD. Thirty‐five PKD patients with PRRT2 mutations (PKD‐M), 43 PKD patients without PRRT2 mutations (PKD‐N), and 40 demographically‐matched healthy control (HC) subjects underwent diffusion tensor imaging. Graph theory and network‐based statistic (NBS) approaches were performed; the topological properties of the white matter structural connectome were compared across the groups, and their relationships with the clinical variables were assessed. Both disease groups PKD‐M and PKD‐N showed lower local efficiency (implying decreased segregation ability) compared to the HC group; PKD‐M had longer characteristic path length and lower global efficiency (implying decreased integration ability) compared to PKD‐N and HC, independently of the potential effects of medication. Both PKD‐M and PKD‐N had decreased nodal characteristics in the left thalamus and left inferior frontal gyrus, the alterations being more pronounced in PKD‐M patients, who also showed abnormalities in the left fusiform and bilateral middle temporal gyrus. In the connectivity characteristics assessed by NBS, the alterations were more pronounced in the PKD‐M group versus HC than in PKD‐N versus HC. As well as the white matter alterations in the basal ganglia‐thalamo‐cortical circuit related to PKD with or without PRRT2 mutations, findings in the PKD‐M group of weaker small‐worldness and more pronounced regional disturbance show the adverse effects of PRRT2 gene mutations on brain structural connectome. [ABSTRACT FROM AUTHOR]

Mesial temporal lobe epilepsy (mTLE), the most common type of focal epilepsy, is associated with functional and structural brain alterations. Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controls. However, either functional or structural neuroimaging data are mostly used separately as input, and the opportunity to combine both has not been exploited yet. We conducted a multimodal ML study based on functional and structural neuroimaging measures. We enrolled 37 patients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vector ML model to distinguish them by using each measure and the combinations of the measures. For each single measure, we obtained a mean accuracy of 74% and 69% for discriminating left mTLE and right mTLE from controls, respectively, and 64% when all patients were combined. We achieved an accuracy of 78% by integrating functional data and 79% by integrating structural data for left mTLE, and the highest accuracy of 84% was obtained when all functional and structural measures were combined. These findings suggest that combining multimodal measures within a single model is a promising direction for improving the classification of individual patients with mTLE. [ABSTRACT FROM AUTHOR]