Diffusion Tensor Imaging Research Articles

Diffusion-tensor magnetic resonance imaging as a non-invasive assessment of extracellular matrix remodeling in lumbar paravertebral muscles of rats with sarcopenia

BackgroundExtracellular matrix (ECM) remodeling in skeletal muscle is a significant factor in the development of sarcopenia. This study aims to evaluate changes in ECM remodeling in the lumbar paravertebral muscles of sarcopenic rats using diffusion-tensor magnetic resonance imaging (DT-MRI) and compare them with histology.MethodsTwenty 6-month-old female Sprague Dawley rats were randomly divided into the dexamethasone (DEX) group and the control (CON) group. Both groups underwent 3.0T MRI scanning, including Mensa, T2WI, and DT-MRI sequences. The changes in muscle fibers and extracellular matrix (ECM) of the erector spinal muscle were observed using hematoxylineosin and sirius red staining. The expressions of collagen I, III, and fibronectin in the erector spinae were detected by western blot. Pearson correlation analysis was employed to assess the correlation between MRI quantitative parameters and corresponding histopathology markers.ResultsThe cross-sectional area and fractional anisotropy values of the erector spinae in the DEX group rats were significantly lower than those in the CON group (p < 0.05). Hematoxylin eosin staining revealed muscle fiber atrophy and disordered arrangement in the DEX group, while sirius red staining showed a significant increase in collagen volume fraction in the DEX group. The western blot results indicate a significant increase in the expression of collagen I, collagen III, and fibronectin in the DEX group (p < 0.001 for all). Correlation coefficients between fractional anisotropy values and collagen volume fraction, collagen I, collagen III, and fibronectin were − 0.71, -0.94, -0.85, and − 0.88, respectively (p < 0.05 for all).ConclusionsThe fractional anisotropy value is strongly correlated with the pathological collagen volume fraction, collagen I, collagen III, and fibronectin. This indicates that DT-MRI can non-invasively evaluate the changes in extracellular matrix remodeling in the erector spinal muscle of sarcopenia. It provides a potential imaging biomarker for the diagnosis of sarcopenia.

Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study.

Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain injury (TBI), especially for those patients with chronic post-TBI symptoms such as headaches, dizziness, fatigue, etc. The evaluation of structural and functional connectivity using DTI has become a promising method for identifying subtle alterations in brain connectivity associated with TBI that are otherwise not visible with conventional imaging. This study assessed whether TBI patients with (n = 17) or without (n = 16) chronic symptoms (TBIcs/TBIncs) exhibit any changes in structural connectivity (SC) and mean fractional anisotropy (mFA) of intra- and inter-hemispheric connections when compared to a control group (CG) (n = 13). Reductions in SC and mFA were observed for TBIcs compared to CG, but not for TBIncs. More connections were found to have mFA reductions than SC reductions. On the whole, SC is dominated by ipsilateral connections for all the groups after the comparison of contralateral and ipsilateral connections. More contra-ipsi reductions of mFA were found for TBIcs than TBIncs compared to CG. These findings suggest that TBI patients with chronic symptoms not only demonstrate decreased global and regional mFA but also reduced structural network connectivity.

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

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

Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).

Purpose To develop a deep learning algorithm to predict 2-year neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy using MRI and basic clinical data. Materials and Methods In this study, MRI data of term neonates with encephalopathy in the High-dose Erythropoietin for Asphyxia and Encephalopathy (HEAL) trial (ClinicalTrials.gov: NCT02811263), who were enrolled from 17 institutions between January 25, 2017, and October 9, 2019, were retrospectively analyzed. The harmonized MRI protocol included T1-weighted, T2-weighted, and diffusion tensor imaging. Deep learning classifiers were trained to predict the primary outcome of the HEAL trial (death or any neurodevelopmental impairment at 2 years) using multisequence MRI and basic clinical variables, including sex and gestational age at birth. Model performance was evaluated on test sets comprising 10% of cases from 15 institutions (in-distribution test set, n = 41) and 10% of cases from two institutions (out-of-distribution test set, n = 41). Model performance in predicting additional secondary outcomes, including death alone, was also assessed. Results For the 414 neonates (mean gestational age, 39 weeks ± 1.4 [SD]; 232 male, 182 female), in the study cohort, 198 (48%) died or had any neurodevelopmental impairment at 2 years. The deep learning model achieved an area under the receiver operating characteristic curve (AUC) of 0.74 (95% CI: 0.60, 0.86) and 63% accuracy in the in-distribution test set and an AUC of 0.77 (95% CI: 0.63, 0.90) and 78% accuracy in the out-of-distribution test set. Performance was similar or better for predicting secondary outcomes. Conclusion Deep learning analysis of neonatal brain MRI yielded high performance for predicting 2-year neurodevelopmental outcomes. Keywords: Convolutional Neural Network (CNN), Prognosis, Pediatrics, Brain, Brain Stem Clinical trial registration no. NCT02811263 Supplemental material is available for this article. © RSNA, 2024 See also commentary by Rafful and Reis Teixeira in this issue.

Different patterns of structural network impairments in two amyotrophic lateral sclerosis subtypes driven by 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging.

The structural network damages in amyotrophic lateral sclerosis patients are evident but contradictory due to the high heterogeneity of the disease. We hypothesized that patterns of structural network impairments would be different in amyotrophic lateral sclerosis subtypes by a data-driven method using 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid imaging. The data of positron emission tomography, structural MRI and diffusion tensor imaging in fifty patients with amyotrophic lateral sclerosis and 23 healthy controls were collected by a 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance hybrid. Two amyotrophic lateral sclerosis subtypes were identified as the optimal cluster based on grey matter volume and standardized uptake value ratio. Network metrics at the global, local and connection levels were compared to explore the impaired patterns of structural networks in the identified subtypes. Compared with healthy controls, the two amyotrophic lateral sclerosis subtypes displayed a pattern of a locally impaired structural network centralized in the sensorimotor network and a pattern of an extensively impaired structural network in the whole brain. When comparing the two amyotrophic lateral sclerosis subgroups by a support vector machine classifier based on the decreases in nodal efficiency of structural network, the individualized network scores were obtained in every amyotrophic lateral sclerosis patient and demonstrated a positive correlation with disease severity. We clustered two amyotrophic lateral sclerosis subtypes by a data-driven method, which encompassed different patterns of structural network impairments. Our results imply that amyotrophic lateral sclerosis may possess the intrinsic damaged pattern of white matter network and thus provide a latent direction for stratification in clinical research.

Dual white matter pathology in fetal holoprosencephaly featuring concurrent malformative and destructive features: A case series.

Holoprosencephaly (HPE) is a classic brain malformation involving defective forebrain induction and patterning. Cases of HPE bearing white matter abnormalities have not been well documented, with only rare cases exhibiting hypoxic-ischemic damage. However, neuroradiologic studies of HPE using diffusion tensor imaging have suggested the presence of white matter architectural disarray. Described in this case series are the clinicopathologic features of 8 fetuses with HPE who underwent autopsy at BC Children's Hospital. All 8 cases exhibited subacute to chronic, periventricular leukomalacia (PVL)-like white matter pathology, with 7 of 8 cases also demonstrating aberrant white matter tracts, one of which manifested as a discreet bundle crossing the midline within the ventral aspects of the fused deep gray nuclei. In 6 of these 7 cases, the PVL-like pathology resided within this aberrant white matter tract. Original workup, alongside an additional HPE-focused next-generation sequencing panel identified a likely etiologic cause for the HPE in 4 cases, with an additional 2 cases exhibiting a variant of unknown significance in genes previously suggested to be involved in HPE. Despite our in-depth clinicopathologic and molecular review, no unifying etiology was definitively identified among our series of fetal HPE bearing this unusual pattern of white matter pathology.

Decreased DTI-ALPS index in delirium: a preliminary MRI study.

Delirium is linked to brain abnormalities, yet the role of the glymphatic system is not well understood. This study aims to examine alterations in brain physiology in delirium by using diffusion-tensor imaging (DTI) to assess water diffusion along the perivascular space (ALPS) and to explore its correlation with clinical symptoms. We examined 15 patients with delirium and 15 healthy controls, measuring water diffusion metrics along the x-, y-, and z-axes in both projection and association fibers to determine the DTI-ALPS index. We used a general linear model, adjusted for age and sex, to compare the DTI-ALPS index between groups. We also investigated the relationship between the DTI-ALPS index and clinical symptoms using partial correlations. Patients with delirium exhibited significantly lower DTI-ALPS indices compared to healthy controls (1.25 ± 0.15 vs. 1.38 ± 0.10, t = 2.903, p = 0.007; 1.27 ± 0.16 vs. 1.39 ± 0.08, 1.22 ± 0.16 vs. 1.37 ± 0.14, t = 2.617, p = 0.014; t = 2.719, p = 0.011; respectively). However, there was no significant correlation between the DTI-ALPS index and clinical symptoms. Our findings indicate a decreased DTI-ALPS index in patients with delirium, suggesting potential alterations in brain physiology that may contribute to the pathophysiology of delirium. This study provides new insights into the mechanisms underlying delirium.

Association of Extent of Transverse Sinus Stenosis With Cerebral Glymphatic Clearance in Patients With Idiopathic Intracranial Hypertension.

Idiopathic intracranial hypertension (IIH) is a neurologic disorder characterized by symptoms of elevated intracranial pressure in the absence of a clear cause. There is a developing theory that IIH may, in part, be related to abnormal cerebral glymphatic clearance. In addition, transverse sinus stenosis (TSS) is a common finding in IIH of unclear pathophysiologic significance. Similarly, whether or not TSS is associated with glymphatic outflow in IIH is unknown. The aim of this investigation was to explore the possible association between glymphatic outflow and extent of TSS in patients with IIH. The study cohort consisted of patients with IIH and healthy controls who were retrospectively identified from our tertiary care institution located in upstate New York from 2016 to 2023. Patients with IIH were included if they had brain MRIs completed with sufficient sequences for analysis. Brain MRIs were computationally analyzed using diffusion tensor imaging analysis along the perivascular space technique to quantify the glymphatic function in patients with IIH. Glymphatic clearance, the primary outcome, was then correlated with the degree of TSS on MR venography using 2 different scoring systems, the 'Farb score' and 'Carvalho score.' Overall, 81 patients with IIH (70 [86%] female, mean age 29.8 years [SD: 8.2 years], mean BMI 41 [SD: 8.4]) and 10 normal controls were identified with sufficient imaging. Based on the Carvalho TSS score, IIH patients without TSS had significantly lower glymphatic clearance than healthy controls (mean ALPS index: 1.196 [SD: 0.05] vs 1.238 [SD: 0.04], respectively; p = 0.018). Furthermore, IIH patients with TSS had significantly lower glymphatic outflow than healthy controls (1.129 [SD: 0.07] vs 1.238 [SD: 0.04], respectively; p < 0.0001) and IIH patients without TSS (1.129 [SD: 0.07] vs 1.196 [SD: 0.05], respectively; p < 0.0001). In addition, there was a significant association between increasing extent of TSS and declining glymphatic clearance (p < 0.0001, R = 0.62). Finally, IIH patients with severe TSS had significantly lower glymphatic flow than IIH patients with mild stenosis (1.121 [SD: 0.07] vs 1.178 [SD: 0.05], respectively; p < 0.0001). These findings were similarly recapitulated using the Farb TSS scoring system. These preliminary findings suggest that the extent of TSS is associated with the degree of glymphatic clearance in IIH, providing novel insights into IIH pathophysiology. Further research is required to clarify the possible causal relationship between TSS and impaired glymphatic clearance in IIH.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BackgroundNew daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.MethodsThis study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson’s correlation analysis between the NODDI indicators and clinical characteristics.ResultsCompared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.ConclusionsOur research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

Microstructural properties in subacute aphasia: concurrent and prospective relationships underpinning recovery.

Few investigations examined the relationship between microstructural white matter integrity and subacute post-stroke linguistic performance or the relationship between microstructural integrity and the recovery of language function. We examined two key questions: (1) How does subacute language performance, measured in single words and discourse, relate to the microstructural integrity of key white matter regions of interest in the language network? and (2) Does the integrity of these regions before treatment predict the improvement or resolution of linguistic symptoms immediately and chronically following treatment? 58 participants within the first three months of stroke were enrolled in a randomized, single-center, double-blind, sham-controlled, study of anodal transcranial direct current stimulation combined with a computer-delivered speech and language naming therapy for subacute aphasia and were asked to complete magnetic resonance imaging at enrollment. Microstructural integrity was evaluated using diffusion tensor imaging processed with atlas-based segmentation. Regression and correlation analyses were conducted. A subset of 22 participants received diffusion tensor imaging. Picture naming accuracy significantly correlated with lower mean diffusivity (higher microstructural integrity) in the left posterior inferior temporal gyrus. Recovery of naming performance was predicted by days since stroke and baseline microstructural integrity of the left posterior middle temporal gyrus, arcuate fasciculus, and superior longitudinal fasciculus. Recovery of discourse efficiency was significantly predicted by the same model. This study demonstrates an association between picture naming and discourse and microstructural integrity of the key regions in the language network for patients with subacute post-stroke aphasia. Baseline microstructural integrity significantly predicts language recovery.

Rate of abnormalities in quantitative MR neuroimaging of persons with chronic traumatic brain injury

BackgroundMild traumatic brain injury (mTBI) can result in lasting brain damage that is often too subtle to detect by qualitative visual inspection on conventional MR imaging. Although a number of FDA-cleared MR neuroimaging tools have demonstrated changes associated with mTBI, they are still under-utilized in clinical practice.MethodsWe investigated a group of 65 individuals with predominantly mTBI (60 mTBI, 48 due to motor-vehicle collision, mean age 47 ± 13 years, 27 men and 38 women) with MR neuroimaging performed in a median of 37 months post-injury. We evaluated abnormalities in brain volumetry including analysis of left-right asymmetry by quantitative volumetric analysis, cerebral perfusion by pseudo-continuous arterial spin labeling (PCASL), white matter microstructure by diffusion tensor imaging (DTI), and neurometabolites via magnetic resonance spectroscopy (MRS).ResultsAll participants demonstrated atrophy in at least one lobar structure or increased lateral ventricular volume. The globus pallidi and cerebellar grey matter were most likely to demonstrate atrophy and asymmetry. Perfusion imaging revealed significant reductions of cerebral blood flow in both occipital and right frontoparietal regions. Diffusion abnormalities were relatively less common though a subset analysis of participants with higher resolution DTI demonstrated additional abnormalities. All participants showed abnormal levels on at least one brain metabolite, most commonly in choline and N-acetylaspartate.ConclusionWe demonstrate the presence of coup-contrecoup perfusion injury patterns, widespread atrophy, regional brain volume asymmetry, and metabolic aberrations as sensitive markers of chronic mTBI sequelae. Our findings expand the historic focus on quantitative imaging of mTBI with DTI by highlighting the complementary importance of volumetry, arterial spin labeling perfusion and magnetic resonance spectroscopy neurometabolite analyses in the evaluation of chronic mTBI.

β-Alanine supplementation improves fractional anisotropy scores in the hippocampus and amygdala in 60–80-year-old men and women

Recently, β-alanine (BA) supplementation was shown to improve cognitive function in older adults with decreased cognitive function. Mechanisms supporting these improvements have not been well defined. This study examined the effects of 10-weeks of BA supplementation on changes in circulating brain inflammatory markers, brain derived neurotrophic factor (BDNF), and brain morphology. Twenty participants were initially randomized into BA (2.4 g·d−1) or placebo (PL) groups. At each testing session, participants provided a resting blood sample and completed the Montreal cognitive assessment (MoCA) test and magnetic resonance imaging, which included diffusion tensor imaging to assess brain tissue integrity. Only participants that scored at or below normal for the MoCA assessment were analyzed (6 BA and 4 PL). The Mann-Whitney U test was used to examine Δ (POST–PRE) differences between the groups. No differences in Δ scores were noted in any blood marker (BDNF, CRP, TNF-α and GFAP). Changes in fractional anisotropy scores were significantly greater for BA than PL in the right hippocampus (p = 0.033) and the left amygdala (p = 0.05). No other differences were noted. The results provide a potential mechanism of how BA supplementation may improve cognitive function as reflected by improved tissue integrity within the hippocampus and amygdala.

The impact of diffusion tensor imaging tractography settings on muscle fascicle architecture and diffusion parameter estimates: Tract length, completion, and curvature are most sensitive to tractography settings.

Diffusion-tensor (DT)-MRI tractography provides information about properties relevant to muscle health and function, including estimates of architectural properties such as fascicle length, pennation angle, and curvature and diffusion properties such as mean diffusivity (MD) and fractional anisotropy (FA). Tractography settings, including integration algorithms, thresholds for early tract termination, and tract smoothing approaches, impact the accuracy of the muscle property estimates. However, muscle DT-MRI tractography is performed using a variety of these settings, complicating comparisons between different studies. The effects of different tractography settings on muscle architecture estimates have not been fully explored, and optimized settings for muscle tractography have not yet been determined. We examined the influence of integration algorithm and termination check settings combined with a range of step sizes, termination criteria, and smoothing polynomial orders on tract characteristics, completion/reason for termination, and goodness of fit between fiber tracts and smoothing polynomials using 3-T DT-MR images of the lower leg muscles of seven healthy adults. We found that tract length and completion were highly sensitive to strict FA and intersegment angle thresholds (25%-69% reduction in complete fiber tracts from lowest to highest minimum FA threshold and 11%-36% reduction from highest to lowest intersegment angle threshold). Higher order polynomials (third and fourth order vs. second order) better fit the muscle fiber trajectories, but curvature estimates were highly sensitive to smoothing polynomial order (3.9-6.6 m-1 increase for second- vs. fourth-order fitting polynomials). Step size impacted curvature estimates, albeit to a lesser degree. Integration algorithm had little impact, and mean pennation angle, and tract-based FA and MD, were relatively insensitive to all parameters. The results demonstrate which muscle diffusion measures and architectural estimates are most sensitive to varying tractography settings and support the need for consistent reporting of tractography details to aid interpretation and comparison of results between studies.

Abnormal white matter integrity of anterior-inferior hypothalamus in mild cognitive impairment patients with depression symptoms

BackgroundThe hypothalamus is a key brain structure involved in the pathogenesis of depression, and its abnormal activity is considered an important pathological mechanism for the formation of depression. The presence of abnormalities in the white matter integrity of hypothalamic subregions in mild cognitive impairment with depressive symptoms (D-MCI) remains unknown. MethodsIn this study, we used diffusion tensor imaging (DTI) to explore the white matter integrity of hypothalamic subregions in D-MCI. On a 3 T magnetic resonance imaging scanner, we collected DTI data from 63 subjects. The subjects included 20 healthy controls (HC), 23 MCI patients without depression (nD-MCI), and 20 patients with D-MCI. The differences in DTI metrics of hypothalamic subregions of the three groups were compared using analysis of variance and post hoc t-tests. We looked at the relationship between clinical variables and DTI metrics in hypothalamus subregions using Pearson correlation analysis. ResultsCompared with nD-MCI and HC groups, D-MCI group showed increased fractional anisotropy (FA) in anterior-inferior hypothalamus. There was a weak negative correlation between FA values in the anterior-inferior hypothalamus and depression scores in D-MCI patients. ConclusionsOur findings suggest that depressive symptoms in MCI patients are associated with abnormal white matter integrity in the anterior-inferior hypothalamus.

Advancements in ultrasonography and MRI for enhanced diagnosis of Parkinson's disease: An updated review

Parkinson's disease (PD) is a progressive neurological illness characterized by symptoms such as bradykinesia (slowness of movement), tremor, rigidity, and postural instability. Diagnosing parkinsonian syndromes (PS) can be challenging, even for specialized neurology centers, due to the high rate of diagnostic errors. This review article highlights the challenges in diagnosing PS and the importance of accurately differentiating it from PD. It discusses the utility of various magnetic resonance imaging (MRI) techniques and transcranial ultrasound (TUS) in improving diagnostic accuracy. The focus is on both conventional and cutting-edge MRI procedures, including T2*/T2-weighted MRI, susceptibility-weighted imaging (SWI), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), magnetic resonance spectroscopy (MRS), and ultra-high-resolution MRI. These advanced techniques have shown promising potential in aiding diagnosis and identifying early signs of PD. The review emphasizes the clinical relevance of these imaging modalities in discriminating PD from other parkinsonian disorders and detecting early-stage disease before the onset of clinical symptoms.

Efficacy of personalized rTMS to enhance upper limb function in subacute stroke patients: a protocol for a multi-center, randomized controlled study.

Repetitive transcranial magnetic stimulation (rTMS) is widely used therapy to enhance motor deficit in stroke patients. To date, rTMS protocols used in stroke patients are relatively unified. However, as the pathophysiology of stroke is diverse and individual functional deficits are distinctive, more precise application of rTMS is warranted. Therefore, the objective of this study was to determine the effects of personalized protocols of rTMS therapy based on the functional reserve of each stroke patient in subacute phase. This study will recruit 120 patients with stroke in subacute phase suffering from the upper extremity motor impairment, from five different hospitals in Korea. The participants will be allocated into three different study conditions based on the functional reserve of each participant, measured by the results of TMS-induced motor evoked potentials (MEPs), and brain MRI with diffusion tensor imaging (DTI) evaluations. The participants of the intervention-group in the three study conditions will receive different protocols of rTMS intervention, a total of 10 sessions for 2 weeks: high-frequency rTMS on ipsilesional primary motor cortex (M1), high-frequency rTMS on ipsilesional ventral premotor cortex, and high-frequency rTMS on contralesional M1. The participants of the control-group in all three study conditions will receive the same rTMS protocol: low-frequency rTMS on contralesional M1. For outcome measures, the following assessments will be performed at baseline (T0), during-intervention (T1), post-intervention (T2), and follow-up (T3) periods: Fugl-Meyer Assessment (FMA), Box-and-block test, Action Research Arm Test, Jebsen-Taylor hand function test, hand grip strength, Functional Ambulatory Category, fractional anisotropy measured by the DTI, and brain network connectivity obtained from MRI. The primary outcome will be the difference of upper limb function, as measured by FMA from T0 to T2. The secondary outcomes will be the differences of other assessments. This study will determine the effects of applying different protocols of rTMS therapy based on the functional reserve of each patient. In addition, this methodology may prove to be more efficient than conventional rTMS protocols. Therefore, effective personalized application of rTMS to stroke patients can be achieved based on their severity, predicted mechanism of motor recovery, or functional reserves. https://clinicaltrials.gov/, identifier NCT06270238.

Magnetic resonance imaging in canine idiopathic epilepsy: a mini-review.

Magnetic resonance imaging (MRI) in an integral part of the diagnostic workup in canines with idiopathic epilepsy (IE). While highly sensitive and specific in identifying structural lesions, conventional MRI is unable to detect changes at the microscopic level. Utilizing more advanced neuroimaging techniques may provide further information on changes at the neuronal level in the brain of canines with IE, thus providing crucial information on the pathogenesis of canine epilepsy. Additionally, earlier detection of these changes may aid clinicians in the development of improved and targeted therapies. Advances in MRI techniques are being developed which can assess metabolic, cellular, architectural, and functional alterations; as well alterations in neuronal tissue mechanical properties, some of which are currently being applied in research on canine IE. This mini-review focuses on novel MRI techniques being utilized to better understand canine epilepsy, which include magnetic resonance spectroscopy, diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, voxel based morphometry, and functional MRI; as well as techniques applied in human medicine and their potential use in veterinary species.

Brain white matter microstructural alterations in Behcet's syndrome correlate with cognitive impairment and disease severity: A diffusion tensor imaging study

ObjectivesTo evaluate the microstructural integrity of brain white matter tracts in patients with Neuro-Behcet's syndrome (NBS) and Behcet's syndrome (BS) without neurological manifestations using diffusion tensor imaging (DTI) and to investigate potential utility of DTI as a surrogate biomarker of neurocognitive functioning and disease severity. MethodsThis cross-sectional study comprised 34 NBS patients and 32 BS patients without neurological involvement, identified based on the International Study Group of the Behcet's disease (ISGBD) and the International Consensus Recommendation (ICR) criteria, as well as 33 healthy controls. Cognitive functions, including attention, memory, language, abstraction, executive control, visuospatial skills, and sensorimotor performance were assessed using standardized questionnaires. DTI data were analyzed using tract-based spatial statistics (TBSS) and automated probabilistic tractography to investigate inter-group differences. Subsequently, correlations between tensor-derived parameters of white matter tracts, neurocognitive test scores, and disease severity measures were examined. ResultsDTI revealed decreased fractional anisotropy and increased radial diffusivity, mean diffusivity, and axial diffusivity in both supratentorial and infratentorial white matter in NBS patients, indicating widespread loss of microstructural integrity. Moreover, this loss of integrity was also observed in BS patients without neurological manifestations, albeit to a lesser extent. In NBS patients, certain white matter tracts, including cingulum bundle, were associated with poor cognitive performance across multiple domains and disease severity. DiscussionDTI findings might potentially serve as a neuroimaging marker to predict the extent of neurocognitive impairment and disease severity associated with central nervous system involvement in BS.

Comparative Analysis of the Apparent Diffusion Coefficient and Diffusion Tensor Imaging in the Diagnosis of Prostate Cancer.

The aim of this work was to demonstrate capabilities of diffusion tensor imaging as a diagnostic tool for prostate cancer in comparison with the apparent diffusion coefficient. 364 patients with suspected prostate cancer underwent multiparametric magnetic resonance imaging including diffusion tensor imaging. The anatomical structure of the prostate obtained on T2-weighted imaging was compared with the apparent diffusion coefficient and diffusion tensor imaging maps. The rest of the gland (central and peripheral regions) were used as healthy areas. The apparent diffusion coefficient at diffusion-weighted imaging, fractional anisotropy and mean diffusivity at diffusion tensor imaging were evaluated in pathological zones. Cancer-suspicious areas of the prostate had high fractional anisotropy fractional anisotropy and low mean diffusivity compared to unaltered areas. Fractional anisotropy values were significantly elevated in central gland cancer, compared to normal tissue, and slightly elevated in peripheral zone cancer. Diffusion tensor imaging has the potential to identify prostate cancer with high accuracy and specificity. The combination of standard magnetic resonance imaging and diffusion tensor imaging can significantly improve the prognosis of the disease during active surveillance. The fractional anisotropy and mean diffusivity values can be useful in assessing the grade of malignancy and the radiolopathological correlation of the lesion.

The effect of elimination of gibbs ringing, noise and systematic errors on the DTI metrics and tractography in a rat brain

Diffusion tensor imaging (DTI) metrics and tractography can be biased due to low signal-to-noise ratio (SNR) and systematic errors resulting from image artifacts and imperfections in magnetic field gradients. The imperfections include non-uniformity and nonlinearity, effects caused by eddy currents, and the influence of background and imaging gradients. We investigated the impact of systematic errors on DTI metrics of an isotropic phantom and DTI metrics and tractography of a rat brain measured at high resolution. We tested denoising and Gibbs ringing removal methods combined with the B matrix spatial distribution (BSD) method for magnetic field gradient calibration. The results showed that the performance of the BSD method depends on whether Gibbs ringing is removed and the effectiveness of stochastic error removal. Region of interest (ROI)-based analysis of the DTI metrics showed that, depending on the size of the ROI and its location in space, correction methods can remove systematic bias to varying degrees. The preprocessing pipeline proposed and dedicated to this type of data together with the BSD method resulted in an even − 90% decrease in fractional anisotropy (FA) (globally and locally) in the isotropic phantom and − 45% in the rat brain. The largest global changes in the rat brain tractogram compared to the standard method without preprocessing (sDTI) were noticed after denoising. The direction of the first eigenvector obtained from DTI after denoising, Gibbs ringing removal and BSD differed by an average of 56 and 10 degrees in the ROI from sDTI and from sDTI after denoising and Gibbs ringing removal, respectively. The latter can be identified with the amount of improvement in tractography due to the elimination of systematic errors related to imperfect magnetic field gradients. Based on the results, the systematic bias for high resolution data mainly depended on SNR, but the influence of non-uniform gradients could also be seen. After denoising, the BSD method was able to further correct both the metrics and tractography of the diffusion tensor in the rat brain by taking into account the actual distribution of magnetic field gradients independent of the examined object and uniquely dependent on the scanner and sequence. This means that in vivo studies are also subject to this type of errors, which should be taken into account when processing such data.