Diffusion Tensor Imaging Scans Research Articles

The added value of diffusion tensor imaging with systematic bias correction for the assessment of liver morphology and physiology.

Diffusion-weighted images of the human liver are prone to artifacts from bulk motions, poor SNR, non-uniformity of magnetic field gradients, and non-optimal choice of diffusion weightings. These factors markedly affect diffusion tensor imaging (DTI) metrics such as mean diffusivity (MD) and fractional anisotropy (FA). This work presents a simple preprocessing pipeline for enhanced magnetic field gradient non-uniformity calibration and analysis of the systematic bias removal attained in each correction step. Liver DTI scans were conducted in two isotropic phantoms and one healthy volunteer. Diffusion tensor was calculated for the original data and after denoising, B1 correction, rigid body registration, and magnetic field gradient non-uniformity correction applying the B-matrix spatial distribution (BSD) method and then, compared with the standard approach (sDTI). MD and FA were determined in three segments of the right lobe from DTI using four different combinations of b-values from the set 0, 400, and 800 s/mm2. Results showed that the proposed preprocessing and BSD methods have a significant impact on MD and FA values in off- and iso-centered isotropic phantoms. The applied corrections applied to the human liver resulted in a 11% change in MD and a - 64% change in FA. By manipulating the b-values used in the diffusion tensor calculation, DTI metrics that reflect only morphology or additional information about liver tissue physiology can be obtained. Accurate quantification of the human liver by diffusion requires appropriate preprocessing and carefully chosen b-value. Noise, B1 inhomogeneity, mis-registration, and non-uniform magnetic field gradients significantly change distributions of DTI metrics in isotropic phantoms and the human liver. Basic preprocessing and the B-matrix spatial distribution (BSD) method perform differently for off-center and isocenter locations. In the human liver, they removed systematic bias of FA and MD by up to -63% and 11%, respectively. Visible variability of FA and MD among b-value sets indicates the possibility of DTI sensitization to different liver compartments.

Multi-modality radiomics of conventional T1 weighted and diffusion tensor imaging for differentiating Parkinson’s disease motor subtypes in early-stages

This study aimed to develop and validate a multi-modality radiomics approach using T1-weighted and diffusion tensor imaging (DTI) to differentiate Parkinson's disease (PD) motor subtypes, specifically tremor-dominant (TD) and postural instability gait difficulty (PIGD), in early disease stages. We analyzed T1-weighted and DTI scans from 140 early-stage PD patients (70 TD, 70 PIGD) and 70 healthy controls from the Parkinson's Progression Markers Initiative database. Radiomics features were extracted from 16 brain regions of interest. After harmonization and feature selection, four machine learning classifiers were trained and evaluated for both three-class (HC vs TD vs PIGD) and binary (TD vs PIGD) classification tasks. The light gradient boosting machine (LGBM) classifier demonstrated the best overall performance. For the three-class classification, LGBM achieved an accuracy of 85% and an area under the receiver operating characteristic curve (AUC) of 0.94 using combined T1 and DTI features. In the binary classification task, LGBM reached an accuracy of 95% and AUC of 0.95. Key discriminative features were identified in the Thalamus, Amygdala, Hippocampus, and Substantia Nigra for the three-group classification, and in the Pallidum, Amygdala, Hippocampus, and Accumbens for binary classification. The combined T1 + DTI approach consistently outperformed single-modality classifications, with DTI alone showing particularly low performance (AUC 0.55–0.62) in binary classification. The high accuracy and AUC values suggest that this approach could significantly improve early diagnosis and subtyping of PD. These findings have important implications for clinical management, potentially enabling more personalized treatment strategies based on early, accurate subtype identification.

Diffusion tensor imaging shows increased physis organization after growth hormone initiation in hypophosphatasia.

Hypophosphatasia is a rare heritable disorder of bone mineralization, with a spectrum of severity based on age of initial presentation. We describe the case of a 14-year-old boy with gene-confirmed inherited hypophosphatasia and growth hormone deficiency, who presented with short stature, unremarkable radiographs, and only minor physeal and metaphyseal changes on magnetic resonance (MR) imaging. Diffusion tensor imaging (DTI) before growth hormone initiation revealed abundant, non-parallel tracts in the physes and metaphyses with loss of the typical columnar organization. After 8months of growth hormone treatment, DTI scans revealed realigned, nearly parallel, longer physeal tracts; duplication of tract volume; and decreased and more typical fractional anisotropy values. DTI can thus visualize physeal tract changes over time, could be a more sensitive diagnostic technique in milder physeal abnormality cases, and may be a potential marker of growth hormone treatment response.

Association between sleep stages and brain microstructure in preterm infants: Insights from DTI analysis

Study objectivesThe aim of this study was to investigate the relationship between sleep stages and neural microstructure – measured using diffusion tensor imaging – of the posterior limb of the internal capsule and corticospinal tract in preterm infants. MethodsA retrospective cohort of 50 preterm infants born between 24 + 4 and 29 + 3 weeks gestational age was included in the study. Sleep stages were continuously measured for 5–7 consecutive days between 29 + 0 and 31 + 6 weeks postmenstrual age using an in-house-developed, and recently published, automated sleep staging algorithm based on routinely measured heart rate and respiratory rate. Additionally, a diffusion tensor imaging scan was conducted at term equivalent age as part of standard care. Region of interest analysis of the posterior limb of the internal capsule was performed, and tractography was used to analyze the corticospinal tract. The association between sleep and white matter microstructure of the posterior limb of the internal capsule and corticospinal tract was examined using a multiple linear regression model, adjusted for potential confounders. ResultsThe results of the analyses revealed an interaction effect between sleep stage and days of invasive ventilation on the fractional anisotropy of the left and right posterior limb of the internal capsule (β = 0.04, FDR-adjusted p = 0.001 and β = 0.04, FDR-adjusted p = 0.02, respectively). Furthermore, an interaction effect between sleep stage and days of invasive ventilation was observed for the radial diffusivity of the mean of the left and right PLIC (β = −4.1e-05, FDR-adjusted p = 0.04). ConclusionsPrevious research has shown that, in very preterm infants, invasive ventilation has a negative effect on white matter tract maturation throughout the brain. A positive association between active sleep and white matter microstructure of the posterior limb of the internal capsule, may indicate a protective role of sleep in this vulnerable population.

Association between the functional connectivity of ventral tegmental area-prefrontal network and pure apathy in Parkinson's disease: a cross-sectional study.

Apathy, characterized by diminished goal-directed behaviors, frequently occurs in patients with Parkinson's disease (PD). The dopamine-releasing neurons of the ventral tegmental area (VTA) have been closely related to this behavioral disruption and project widely to the corticolimbic areas, yet their functional and structural connectivity in regard to other brain regions remain unknown in patients with PD and pure apathy (PD-PA). This study thus aimed to characterize the alterations of functional connectivity (FC) of the VTA and white matter structural connectivity in PD-PA. In this study, 29 patients with PD-PA, 37 with PD but not pure apathy (PD-NPA), and 28 matched healthy controls (HCs) underwent T1-weighted, resting state functional magnetic resonance imaging, and diffusion tensor imaging scans. Patients of this cross-sectional retrospective study were consecutively recruited from The First Affiliated Hospital of Nanjing Medical University between April 2017 and October 2021. Meanwhile, HCs were consecutively recruited from the local community and the Health Examination Center of our hospital. An analysis of covariance and a general linear model were respectively conducted to investigate the functional and structural connectivity among three groups. The tract-based spatial statistics (TBSS) approach was used to investigate the white matter structural connectivity. Patients with PD-PA showed reduced FC of the VTA with the left medial superior frontal gyrus (SFGmed) when compared to the patients with PD-NPA [t=-3.67; voxel-level P<0.001; cluster-level family-wise error-corrected P (PFWE)<0.05]. Relative to the HCs, patients with PD-PA demonstrated reduced FC of the VTA with the left SFGmed (t=-4.98; voxel-level P<0.001; cluster-level PFWE<0.05), right orbital superior frontal gyrus (SFGorb) (t=-5.08; voxel-level P<0.001; cluster-level PFWE<0.05), and right middle frontal gyrus (MFG) (t=-5.08; voxel-level P<0.001; cluster-level PFWE<0.05). Moreover, the reductions in VTA FC with the left SFGmed were associated with severe apathy symptoms in patients with PD-PA (r=-0.600; P=0.003). However, a TBSS approach did not reveal any significant differences in fiber tracts between the three groups. This study identified reduced FC within the mesocortical network (VTA-SFGmed) of patients with PD-PA. These findings may provide valuable information for administering neuromodulation therapies in the alleviation of apathy symptoms in those with PD.

Harmonization of Longitudinal Diffusion Tensor Imaging Data of the Pediatric Cervical and Thoracic Spinal Cord at 3T Using Longitudinal ComBat.

Diffusion tensor imaging (DTI) of the spinal cord has been extensively used to identify biomarkers for spinal cord pathology. Previously, the longitudinal ComBat (longComBat) technique was examined to reduce scanner effects in multi-site, multi-scanner spinal cord DTI data. This study aimed to assess its effectiveness on longitudinal scans using a single-scanner pediatric dataset, including healthy and spinal cord injury (SCI) subjects. Two identical datasets were collected from 42 healthy and 27 SCI subjects with a 2-hour interval between scans on a 3T Siemens MRI scanner. Axial DTI images of the entire cervical and thoracic spinal cord were obtained, and various average diffusion tensor metrics (FA, MD, RD, & AD) were measured at each vertebral level. Pearson correlation and intraclass correlation coefficients were used to evaluate inter- and intra-subject agreement pre- and post-harmonization. Minimal improvement in agreement was observed with the mean square residual (MSR) model, while the restricted maximum likelihood estimator (REML) model showed reduced intra-subject agreement in all the tensor metrics. The significant variability between longitudinal DTI scans within a single scanner was likely due to physiological motion rather than scanner effects. Post-harmonization using the longComBat MSR model showed limited improvement in agreement.

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

Magnetic resonance diffusion tensor imaging (DTI) has recently been used to evaluate the developing cartilage of children, but the influencing factors have not been well studied. The objective of this study was to investigate the influence of the diffusion gradient strength (b value), diffusion gradient direction, age and sex on knee cartilage DTI in healthy children aged 6-12years. A total of 30 healthy child volunteers, with an average age of 8.9 ± 1.6 (mean ± standard deviation) years, were enrolled in this study. They were categorized into three groups according to their age range: 6-8years, 8-10years and 10-12years, ensuring equal sex distribution in each group (5 boys and 5 girls). These volunteers underwent routine left knee joint magnetic resonance imaging (MRI) and serial DTI scans. DTI parameters were altered as follows: when b value = 600s/mm2, diffusion gradient direction was set to 6, 15, 25, 35 and 45; and when diffusion gradient direction = 25, b value was set to 300, 600, 900 and 1200s/mm2. The values of fractional anisotropy (FA) and apparent diffusion coefficient (ADC) were separately acquired using image post-processing techniques. The correlation between various b values, diffusion gradient directions, age and sex on the one hand and FA and ADC values on the other, was investigated. (1) When diffusion gradient direction was fixed and the b value was varied, both FA and ADC exhibited a decreasing trend as the b value increased (P < 0.001). (2) When the b value was fixed and diffusion gradient direction was varied, the FA of knee cartilage showed a decreasing trend with increasing diffusion gradient direction (P < 0.001). (3) The FA value increased with age (P < 0.05). The b value, diffusion gradient direction value and age exert a significant impact on both FA and ADC values in MR DTI of knee cartilage in children aged 6-12years. In order to obtain a stable DTI, it is recommended to select a b value ≥ 600s/mm2 and a diffusion gradient direction ≥ 25 during scanning.

Diffusion Tensor Imaging Identifies Cervical Spondylosis, Myelitis, and Spinal Cord Tumors.

Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation. To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis, myelitis, and spinal tumors. This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal-Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements. FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA's superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in myelitis patients (r = -0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = -0.71, p = 0.0002). DTI indicators, especially FA, have the potential in distinguishing spondylosis, myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.

Cerebellar gray matter and white matter damage among older adults with prediabetes

AimsTo investigate alterations in cerebrum and cerebellum in prediabetes. Cerebellar injury in diabetes is traceable, but it has not been systematically studied, and whether cerebellar injury occurs and the degree of damage in prediabetes are not known. MethodsThe current study investigated cerebral and cerebellar gray matter volume, white matter volume, white matter microstructure and white matter hyperintensity on T1-weighted, T2-weighted fluid-attenuated inversion recovery and diffusion tensor imaging scans in 78 individuals with normal glucose metabolism, 92 with prediabetes, and 108 with type 2 diabetes. ResultsParticipants with prediabetes showed significant gray matter and white matter atrophy, microstructural damage in the cerebellar and cerebral regions. Additionally, widespread structural alterations were observed in the diabetic stage. The function of the damaged brain area was further decoded in Neurosynth, and the damaged cerebellar area with prediabetic lesions was closely related to motor function, while the area affected by diabetes was related to complex cognitive function in addition to motor function. ConclusionsCerebellar injury had already appeared in the prediabetic stage, and cerebellar injury was aggravated in the diabetic stage; therefore, the cerebellum is a key area that is damaged early in the development of diabetes.

Resting-state brain plasticity is associated with the severity in cervical spondylotic myelopathy

ObjectiveTo investigate the brain mechanism of non-correspondence between imaging presentations and clinical symptoms in cervical spondylotic myelopathy (CSM) patients and to test the utility of brain imaging biomarkers for predicting prognosis of CSM.MethodsForty patients with CSM (22 mild-moderate CSM, 18 severe CSM) and 25 healthy controls (HCs) were recruited for rs-fMRI and cervical spinal cord diffusion tensor imaging (DTI) scans. DTI at the spinal cord (level C2/3) with fractional anisotropy (FA) and degree centrality (DC) were recorded. Then one-way analysis of covariance (ANCOVA) was conducted to detect the group differences in the DC and FA values across the three groups. Pearson correlation analysis was then separately performed between JOA with FA and DC.ResultsAmong them, degree centrality value of left middle temporal gyrus exhibited a progressive increase in CSM groups compared with HCs, the DC value in severe CSM group was higher compared with mild-moderate CSM group. (P < 0.05), and the DC values of the right superior temporal gyrus and precuneus showed a decrease after increase. Among them, DC values in the area of precuneus in severe CSM group were significantly lower than those in mild-moderate CSM and HCs. (P < 0.05). The fractional anisotropy (FA) values of the level C2/3 showed a progressive decrease in different clinical stages, that severe CSM group was the lowest, significantly lower than those in mild-moderate CSM and HCs (P < 0.05). There was negative correlation between DC value of left middle temporal gyrus and JOA scores (P < 0.001), and the FA values of dorsal column in the level C2/3 positively correlated with the JOA scores (P < 0.001).ConclusionStructural and functional changes have taken place in the cervical spinal cord and brain of CSM patients. The Brain reorganization plays an important role in maintaining the symptoms and signs of CSM, aberrant DC values in the left middle temporal gyrus may be the possible mechanism of inconsistency between imaging findings and clinical symptoms. Degree centrality is a potentially useful prognostic functional biomarker in cervical spondylotic myelopathy.

P.109 Machine learning based approach to improving the prediction of neurological deterioration in mild Degenerative Cervical Myelopathy

Background: Degenerative cervical myelopathy (DCM) is the most common form of atraumatic spinal cord injury globally, yet clinical guidelines remain unclear on surgical recommendations for patients with mild forms of DCM. This is in part due to limitations in current MR imaging interpretation and complex mechanisms of neurological deterioration. Supervised machine learning (ML) models can help to identify clinical and imaging indicators of deterioration within mild DCM patients. Methods: 127 MRI scans (T2w, Diffusion Tensor Imaging, and Magnetization transfer scans) accompanied by a series of clinical tests underwent a semi-automated analysis to derive quantitative metrics. Random forest classifier, Support Vector Machine, and Logistic Regression models were trained and tested to predict 6-month neurological deterioration within patients. Results: The ML models performed, on average, better than previous studies with a balanced accuracy ranging between 70-75%. “Advanced” imaging metrics such as diffusion tensor imaging and magnetization transfer scans played an important role in improving model accuracy but only when used near the maximally compressed disc level, suggesting that limited yet targetted imaging metrics support ML model performance. Conclusions: The inclusion of specific, targeted imaging and clinical metrics support ML model performance in predicting neurological deterioration within mild DCM patients.

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure.

Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

Structural Changes in Brain White Matter Tracts Associated With Overactive Bladder Revealed by Diffusion Tensor Magnetic Resonance Imaging: Findings From a Symptoms of Lower Urinary Tract Dysfunction Research Network Cross-Sectional Case-Control Study.

Our objective was to investigate structural changes in brain white matter tracts using diffusion tensor imaging (DTI) in patients with overactive bladder (OAB). Treatment-seeking OAB patients and matched controls enrolled in the cross-sectional case-control LURN (Symptoms of Lower Urinary Tract Dysfunction Research Network) Neuroimaging Study received a brain DTI scan. Microstructural integrity of brain white matter was assessed using fractional anisotropy (FA) and mean diffusivity. OAB and urgency urinary incontinence (UUI) symptoms were assessed using the OAB Questionnaire Short-Form and International Consultation on Incontinence Questionnaire-Urinary Incontinence. The Lower Urinary Tract Symptoms Tool UUI questions and responses were correlated with FA values. Among 221 participants with evaluable DTI data, 146 had OAB (66 urinary urgency-only without UUI, 80 with UUI); 75 were controls. Compared with controls, participants with OAB showed decreased FA and increased mean diffusivity, representing greater microstructural abnormalities of brain white matter tracts among OAB participants. These abnormalities occurred in the corpus callosum, bilateral anterior thalamic radiation and superior longitudinal fasciculus tracts, and bilateral insula and parahippocampal region. Among participants with OAB, higher OAB Questionnaire Short-Form scores were associated with decreased FA in the left inferior fronto-occipital fasciculus, P < .0001. DTI differences between OAB and controls were driven by the urinary urgency-only (OAB-dry) but not the UUI (OAB-wet) subgroup. Abnormalities in microstructural integrity in specific brain white matter tracts were more frequent in OAB patients. More severe OAB symptoms were correlated with greater degree of microstructural abnormalities in brain white matter tracts in patients with OAB. ClinicalTrials.gov: NCT02485808.

White Matter Microstructure of the Genu of the Corpus Callosum Measured Using Neurite Orientation Dispersion and Density Imaging (NODDI) Is Associated with Cardiorespiratory Fitness in Older Adults

Changes in white matter microstructure of the genu of the corpus callosum are predictive of cognitive decline in patients with mild cognitive impairment. Cardiorespiratory fitness (CRF) is positively associated with brain health; however, the relationship between cardiorespiratory fitness and white matter microstructure of the genu of the corpus callosum is unknown. Further, a novel diffusion method for assessing white matter microstructure, neurite orientation dispersion and density imaging (NODDI), can detect specific microstructural features that are not observed with conventional diffusion tensor imaging (DTI). Young (n=27, age=25±5, m=12, f=15) and older (n=23, age=64±5, m=12, f=11) adults free of underlying disease participated in this study. CRF was assessed using an incremental maximal exercise test on a cycle ergometer. On a separate visit, white matter microstructure of the genu of the corpus callosum was measured using both DTI and NODDI MRI scans. In young adults, there were no associations between CRF and white matter microstructure of the genu of the corpus callosum measured using either DTI or NODDI (p&gt;0.05). In older adults, there were no associations between CRF and white matter microstructure of the genu of the corpus callosum measured with DTI. However, in older adults, there was a positive association between CRF and orientation dispersion index of the genu of the corpus callosum measured with NODDI (r=0.47, p=0.02). In conclusion, using conventional DTI, no associations between CRF and white matter microstructure of the genu of the corpus callosum were observed. However, using NODDI, which can detect specific microstructural features, our results suggest that older adults with higher CRF demonstrated enhanced white matter microstructure, specifically orientation dispersion index, of the genu of the corpus callosum. Conventional DTI may underestimate the impact of CRF on age-related changes in white matter microstructure. National Institutes of Health - HL118154 (JNB), HL007936 (KBM). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Three-dimensional architecture and moment arms of human rotator cuff muscles invivo: Interindividual, intermuscular, and intramuscular variations.

The human rotator cuff consists of four muscles, each with a complex, multipennate architecture. Despite the functional and clinical importance, the architecture of the human rotator cuff has yet to be clearly described in humans invivo. The purpose of this study was to investigate the intramuscular, intermuscular, and interindividual variations in architecture and moment arms of the human rotator cuff. Muscle volumes, fascicle lengths, physiological cross-sectional areas (PCSAs), pennation angles, and moment arms of all four rotator cuff muscles were measured from mDixon and diffusion tensor imaging (DTI) scans of the right shoulders of 20 young adults. In accordance with the most detailed dissections available to date, we found substantial intramuscular variation in fascicle length (coefficients of variation (CVs) ranged from 26% to 40%) and pennation angles (CVs ranged from 56% to 62%) in all rotator cuff muscles. We also found substantial intermuscular and interindividual variations in muscle volumes, but relatively consistent mean fascicle lengths, pennation angles, and moment arms (CVs for all ≤17%). Moreover, when expressed as a proportion of total rotator cuff muscle volume, the volumes of individual rotator cuff muscles were highly consistent between individuals and sexes (CVs ≤16%), suggesting that rotator cuff muscle volumes scale uniformly, at least in a younger population without musculoskeletal problems. Together, these data indicate limited interindividual and intermuscular variability in architecture, which may simplify scaling routines for musculoskeletal models. However, the substantial intramuscular variation in architecture questions the validity of previously reported mean architectural parameters to adequately describe rotator cuff function.

Multi-level prediction of substance use: Interaction of white matter integrity, resting-state connectivity and inhibitory control measured repeatedly in every-day life.

Substance use disorders are characterized by inhibition deficits related to disrupted connectivity in white matter pathways, leading via interaction to difficulties in resisting substance use. By combining neuroimaging with smartphone-based ecological momentary assessment (EMA), we questioned how biomarkers moderate inhibition deficits to predict use. Thus, we aimed to assess white matter integrity interaction with everyday inhibition deficits and related resting-state network connectivity to identify multi-dimensional predictors of substance use. Thirty-eight patients treated for alcohol, cannabis or tobacco use disorder completed 1 week of EMA to report substance use five times and complete Stroop inhibition testing twice daily. Before EMA tracking, participants underwent resting state functional MRIand diffusion tensor imaging (DTI) scanning. Regression analyses were conducted between mean Stroop performances and whole-brain fractional anisotropy (FA) in white matter. Moderation testing was conducted between mean FA within significant clusters as moderator and the link between momentary Stroop performance and use as outcome. Predictions between FA and resting-state connectivity strength in known inhibition-related networks were assessed using mixed modelling. Higher FA values in the anterior corpus callosum and bilateral anterior corona radiata predicted higher mean Stroop performance during the EMA week and stronger functional connectivity in occipital-frontal-cerebellar regions. Integrity in these regions moderated the link between inhibitory control and substance use, whereby stronger inhibition was predictive of the lowest probability of use for the highest FA values. In conclusion, compromised white matter structural integrity in anterior brain systems appears to underlie impairment in inhibitory control functional networks and compromised ability to refrain from substance use.

Toward diffusion tensor imaging as a biomarker in neurodegenerative diseases: technical considerations to optimize recordings and data processing.

Neuroimaging biomarkers have shown high potential to map the disease processes in the application to neurodegenerative diseases (NDD), e.g., diffusion tensor imaging (DTI). For DTI, the implementation of a standardized scanning and analysis cascade in clinical trials has potential to be further optimized. Over the last few years, various approaches to improve DTI applications to NDD have been developed. The core issue of this review was to address considerations and limitations of DTI in NDD: we discuss suggestions for improvements of DTI applications to NDD. Based on this technical approach, a set of recommendations was proposed for a standardized DTI scan protocol and an analysis cascade of DTI data pre-and postprocessing and statistical analysis. In summary, considering advantages and limitations of the DTI in NDD we suggest improvements for a standardized framework for a DTI-based protocol to be applied to future imaging studies in NDD, towards the goal to proceed to establish DTI as a biomarker in clinical trials in neurodegeneration.

The white matter characteristic of the genu of corpus callosum coupled with pain intensity and negative emotion scores in patients with trigeminal neuralgia: a multivariate analysis.

Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder that not only causes intense pain but also affects the psychological health of patients. Since TN pain intensity and negative emotion may be grounded in our own pain experiences, they exhibit huge inter-individual differences. This study investigates the effect of inter-individual differences in pain intensity and negative emotion on brain structure in patients with TN and the possible pathophysiology mechanism underlying this disease. T1 weighted magnetic resonance imaging and diffusion tensor imaging scans were obtained in 46 patients with TN and 35 healthy controls. All patients with TN underwent pain-related and emotion-related questionnaires. Voxel-based morphometry and regional white matter diffusion property analysis were used to investigate whole brain grey and white matter quantitatively. Innovatively employing partial least squares correlation analysis to explore the relationship among pain intensity, negative emotion and brain microstructure in patients with TN. Significant difference in white matter integrity were identified in patients with TN compared to the healthy controls group; The most correlation brain region in the partial least squares correlation analysis was the genus of the corpus callosum, which was negatively associated with both pain intensity and negative emotion. The genu of corpus callosum plays an important role in the cognition of pain perception, the generation and conduction of negative emotions in patients with TN. These findings may deepen our understanding of the pathophysiology of TN.

Accelerated IVIM-corrected DTI in acute hamstring injury: towards a clinically feasible acquisition time

BackgroundIntravoxel incoherent motion (IVIM)-corrected diffusion tensor imaging (DTI) potentially enhances return-to-play (RTP) prediction after hamstring injuries. However, the long scan times hamper clinical implementation. We assessed accelerated IVIM-corrected DTI approaches in acute hamstring injuries and explore the sensitivity of the perfusion fraction (f) to acute muscle damage.MethodsAthletes with acute hamstring injury received DTI scans of both thighs < 7 days after injury and at RTP. For a subset, DTI scans were repeated with multiband (MB) acceleration. Data from standard and MB-accelerated scans were fitted with standard and accelerated IVIM-corrected DTI approach using high b-values only. Segmentations of the injury and contralateral healthy muscles were contoured. The fitting methods as well as the standard and MB-accelerated scan were compared using linear regression analysis. For sensitivity to injury, Δ(injured minus healthy) DTI parameters between the methods and the differences between injured and healthy muscles were compared (Wilcoxon signed-rank test).ResultsThe baseline dataset consisted of 109 athletes (16 with MB acceleration); 64 of them received an RTP scan (8 with MB acceleration). Linear regression of the standard and high-b DTI fitting showed excellent agreement. With both fitting methods, standard and MB-accelerated scans were comparable. Δ(injured minus healthy) was similar between standard and accelerated methods. For all methods, all IVIM-DTI parameters except f were significantly different between injured and healthy muscles.ConclusionsHigh-b DTI fitting with MB acceleration reduced the scan time from 11:08 to 3:40 min:s while maintaining sensitivity to hamstring injuries; f was not different between healthy and injured muscles.Relevance statementThe accelerated IVIM-corrected DTI protocol, using fewer b-values and MB acceleration, reduced the scan time to under 4 min without affecting the sensitivity of the quantitative outcome parameters to hamstring injuries. This allows for routine clinical monitoring of hamstring injuries, which could directly benefit injury treatment and monitoring.Key points• Combining high-b DTI-fitting and multiband-acceleration dramatically reduced by two thirds the scan time.• The accelerated IVIM-corrected DTI approaches maintained the sensitivity to hamstring injuries.• The IVIM-derived perfusion fraction was not sensitive to hamstring injuries.Graphical

Corpus callosum and cerebellum participate in semantic dysfunction of Parkinson's disease: a diffusion tensor imaging-based cross-sectional study.

Language dysfunction is common in Parkinson's disease (PD) patients, among which, the decline of semantic fluency is usually observed. This study aims to explore the relationship between white matter (WM) alterations and semantic fluency changes in PD patients. 127 PD patients from the Parkinson's Progression Markers Initiative cohort who received diffusion tensor imaging scanning, clinical assessment and semantic fluency test (SFT) were included. Tract-based special statistics, automated fiber quantification, graph-theoretical and network-based analyses were performed to analyze the correlation between WM structural changes, brain network features and semantic fluency in PD patients. Fractional anisotropy of corpus callosum, anterior thalamic radiation, inferior front-occipital fasciculus, and uncinate fasciculus, were positively correlated with SFT scores, while a negative correlation was identified between radial diffusion of the corpus callosum, inferior longitudinal fasciculus, and SFT scores. Automatic fiber quantification identified similar alterations with more details in these WM tracts. Brain network analysis positively correlated SFT scores with nodal efficiency of cerebellar lobule VIII, and nodal local efficiency of cerebellar lobule X. WM integrity and myelin integrity in the corpus callosum and several other language-related WM tracts may influence the semantic function in PD patients. Damage to the cerebellum lobule VIII and lobule X may also be involved in semantic dysfunction in PD patients.