Predicting motor improvement after stroke with clinical assessment and diffusion tensor imaging.
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ABSTRACT:
SUBMITTER: Buch ER
PROVIDER: S-EPMC4873682 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
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Predicting motor improvement after stroke with clinical assessment and diffusion tensor imaging.
Buch Ethan R ER Rizk Sviatlana S Nicolo Pierre P Cohen Leonardo G LG Schnider Armin A Guggisberg Adrian G AG
Neurology 20160429 20
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Project description:Electrophysiological and neuroimaging studies suggest that the integrity of ipsilesional and inter-hemispheric motor circuits is important for motor recovery after stroke. However, the extent to which each of these tracts contributes to the variance in outcome remains unclear. We examined whether diffusion tensor imaging (DTI)-derived measures of corticospinal and transcallosal tracts predict motor improvement in an experimental neurorehabilitation trial. 15 chronic stroke patients received bihemispheric transcranial direct current stimulation and simultaneous physical/occupational therapy for five consecutive days. Motor impairment was assessed prior to and after the intervention. At baseline, the patients underwent DTI; probabilistic fiber tracking was used to reconstruct the pyramidal tract (PT), alternate descending motor fibers (aMF), and transcallosal fibers connecting primary motor cortices (M1-M1). Ipsilesional corticospinal tracts (PT, aMF) and M1-M1 showed significantly decreased fractional anisotropy (FA) and increased directional diffusivities when compared to age-matched healthy controls. Partial correlations revealed that greater gains in motor function were related to higher FA values and lower directional diffusivities of transcallosal and ipsilesional corticospinal tracts. M1-M1 diffusivity had the greatest predictive value. An additional slice-by-slice analysis of FA values along the corticospinal tracts demonstrated that the more the ipsilesional FA profiles of patients resembled those of healthy controls, the greater their functional improvement. In conclusion, our study shows that DTI-derived measures can be used to predict functional potential for subsequent motor recovery in chronic stroke patients. Diffusivity parameters of individual tracts and tract combinations may help in assessing a patient's individual recovery potential and in determining optimal neurorehabilitative interventions.
| S-EPMC3175010 | biostudies-literature
Project description:Stroke is a leading cause of disability worldwide. Motor impairments occur in most of the patients with stroke in the acute phase and contribute substantially to disability. Diffusion tensor imaging (DTI) biomarkers such as fractional anisotropy (FA) measured at an early phase after stroke have emerged as potential predictors of motor recovery. In this narrative review, we: (1) review key concepts of diffusion MRI (dMRI); (2) present an overview of state-of-art methodological aspects of data collection, analysis and reporting; and (3) critically review challenges of DTI in stroke as well as results of studies that investigated the correlation between DTI metrics within the corticospinal tract and motor outcomes at different stages after stroke. We reviewed studies published between January, 2008 and December, 2018, that reported correlations between DTI metrics collected within the first 24 h (hyperacute), 2-7 days (acute), and >7-90 days (early subacute) after stroke. Nineteen studies were included. Our review shows that there is no consensus about gold standards for DTI data collection or processing. We found great methodological differences across studies that evaluated DTI metrics within the corticospinal tract. Despite heterogeneity in stroke lesions and analysis approaches, the majority of studies reported significant correlations between DTI biomarkers and motor impairments. It remains to be determined whether DTI results could enhance the predictive value of motor disability models based on clinical and neurophysiological variables.
| S-EPMC6530391 | biostudies-literature
Project description:Motor impairment after stroke is related to the integrity of the corticospinal tract (CST). However, considerable variability in motor impairment remains unexplained. To increase the accuracy in evaluating long-term motor function after ischemic stroke, we tested the hypothesis that combining diffusion tensor imaging (DTI) and gray matter (GM) volumetry can better characterize long-term motor deficit than either method alone in patients with chronic stroke. We recruited 31 patients whose Medical Research Council strength grade was ≤ 3/5 in the extensor muscles of the affected upper extremity in the acute phase. We used the Upper Extremity Fugl-Meyer (UE-FM) assessment to evaluate motor impairment, and as the primary outcome variable. We computed the fractional anisotropy ratio of the entire CST (CSTratio) and the volume of interest ratio (VOIratio), between ipsilesional and contralesional hemispheres, to explain long-term motor impairment. The results showed that CSTratio, VOIratio of motor-related brain regions, and VOIratio in the temporal lobe were correlated with UE-FM. A multiple regression model including CSTratio and VOIratio of the caudate nucleus explained 40.7% of the variability in UE-FM. The adjusted R2 of the regression model with CSTratio as an independent variable was 29.4%, and that of using VOIratio of the caudate nucleus as an independent variable was 23.1%. These results suggest that combining DTI and GM volumetry may achieve better explanation of long-term motor deficit in stroke patients, than using either measure individually. This finding may provide guidance in determining optimal neurorehabilitative interventions.
| S-EPMC4428789 | biostudies-literature
Project description:BackgroundTo investigate the efficacy of acupuncture in improving motor dysfunction after ischemic stroke (IS) and to investigate the effect of acupuncture on corticospinal tract (CST) remodeling using diffusion tensor imaging.MethodsPublished literature on the effect of acupuncture on CST remodeling after IS using diffusion tensor imaging in the form of randomized controlled trials (RCTs) were systematically retrieved and screened from Cochrane Library, Web of Science, PubMed, Embase, CNKI, CBM, VIP, and Wanfang databases from inception to December 2022. The methodological quality of the included studies was critically and independently evaluated by 2 reviewers using the Cochrane Risk of Bias Assessment Tool for RCTs. The correlated data were extracted using the pre-designed form, and all analyses were performed using Reviewer Manager version 5.4.ResultsEleven eligible RCTs involving 459 patients were eventually included. The combined evidence results showed that the acupuncture group significantly improved patients' National Institute of Health stroke scale, Fugl-Meyer Assessment Scale, and Barthel index compared with conventional medical treatment. The acupuncture group significantly promoted remodeling of the CST, as reflected by an increase in fractional anisotropy (FA) throughout the CST [MD = 0.04, 95% CI (0.02, 0.07), P = .001], and in addition, subgroup analysis showed that the acupuncture group significantly improved FA in the infarct area compared with conventional medical treatment at around 4 weeks [MD = 0.04, 95% CI (0.02, 0.06), P = .0002] and FA of the affected cerebral peduncle [MD = 0.03, 95% CI (0.00, 0.07), P = .02]. Also, compared with conventional medical treatment, the acupuncture group significantly increased average diffusion coefficient of the affected cerebral peduncle [MD = -0.21, 95% CI (-0.28, -0.13), P < .00001].ConclusionThe results of the meta-analysis suggest that acupuncture therapy can improve the clinical manifestations of motor dysfunction in patients after IS and advance a possibly beneficial effect on CST remodeling. However, due to the number and quality of eligible studies, these findings need to be further validated in more standardized, rigorous, high-quality clinical trials.
| S-EPMC10419801 | biostudies-literature
Project description:This study investigated factors associated with aphasia severity at both 2 weeks and 3 months after stroke using demographic and clinical variables, brain diffusion tensor imaging (DTI) parameters, and lesion volume measurements. Patients with left hemisphere stroke were assessed at 2 weeks (n = 68) and at 3 months (n = 20) after stroke. Demographic, clinical, and neuroimaging data were collected; language functions were assessed using the Western Aphasia Battery. For neuroimaging, DTI parameters, including the laterality index (LI) of fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity, mean diffusivity and fibre density (FD) of the arcuate fasciculus (AF), and lesion volume, were measured. Lesion volume, cortical involvement, and the National Institutes of Health Stroke Scale score significantly predicted aphasia severity at 2 weeks after stroke, whereas the aphasia quotient and presence of depression during the early subacute stage were significant predictors at 3 months after stroke. According to Pearson correlation, LI-AD and LI-FD were significantly correlated with the aphasia quotient 2 weeks after ischaemic stroke, and the LI-FA was significantly correlated with the aphasia quotient 2 weeks after haemorrhagic stroke, suggesting that the extent and mechanism of AF injuries differ between ischaemic and haemorrhagic strokes. These differences may contribute to aphasia severity.
| S-EPMC7393375 | biostudies-literature
Project description:Motor skills and the acquisition of brain plasticity are important topics in current research. The development of non-invasive white matter imaging technology, such as diffusion-tensor imaging and the introduction of graph theory make it possible to study the effects of learning skills on the connection patterns of brain networks. However, few studies have characterized the brain network topological features of motor skill learning, especially open skill. Given the need to interact with environmental changes in real time, we hypothesized that the brain network of high-level open-skilled athletes had higher transmission efficiency and stronger interaction in attention, visual and sensorimotor networks. We selected 21 high-level basketball players and 25 ordinary individuals as control subjects, collected their DTI data, built a network of brain structures, and used graph theory to analyze and compare the network properties of the two groups at global and regional levels. In addition, we conducted a correlation analysis on the training years of high-level athletes and brain network nodal parameters on the regional level to assess the relationship between brain network topological characteristics and skills learning. We found that on the global-level, the brain network of high-level basketball players had a shorter path length, small-worldness, and higher global efficiency. On the regional level, the brain nodes of the high-level athletes had nodal parameters that were significantly higher than those of control groups, and were mainly distributed in the visual network, the default mode network, and the attention network. The changes in brain node parameters were significantly related to the number of training years.
| S-EPMC6364877 | biostudies-literature
Project description:BackgroundMetachromatic leukodystrophy (MLD) is a lysosomal enzyme deficiency disorder leading to progressive demyelination and, consecutively, to cognitive and motor decline. Brain magnetic resonance imaging (MRI) can detect affected white matter as T2 hyperintense areas but cannot quantify the gradual microstructural process of demyelination more accurately. Our study aimed to investigate the value of routine MR diffusion tensor imaging in assessing disease progression.MethodsMR diffusion parameters (apparent diffusion coefficient [ADC] and fractional anisotropy [FA]) were in the frontal white matter, central region (CR), and posterior limb of the internal capsule in 111 MR datasets from a natural history study of 83 patients (age: 0.5-39.9 years; 35 late-infantile, 45 juvenile, 3 adult, with clinical diffusion sequences of different scanner manufacturers) as well as 120 controls. Results were correlated with clinical parameters reflecting motor and cognitive function.ResultsADC values increase and FA values decrease depending on disease stage/severity. They show region-specific correlations with clinical parameters of motor and cognitive symptoms, respectively. Higher ADC levels in CR at diagnosis predicted a disease course with more rapid motor deterioration in juvenile MLD patients. In highly organized tissues such as the corticospinal tract, in particular, diffusion MR parameters were highly sensitive to MLD-associated changes and did not correlate with the visual quantification of T2 hyperintensities.ConclusionOur results show that diffusion MRI can deliver valuable, robust, clinically meaningful, and easily obtainable/accessible/available parameters in the assessment of prognosis and progression of MLD. Therefore, it provides additional quantifiable information to established methods such as T2 hyperintensity.
| S-EPMC10332944 | biostudies-literature
Project description:Conventional diffusion MRI yields voxel-averaged parameters that suffer from ambiguities for heterogeneous anisotropic materials such as brain tissue. Using principles from solid-state NMR spectroscopy, we have previously introduced the shape of the diffusion encoding tensor as a separate acquisition dimension that disentangles isotropic and anisotropic contributions to the observed diffusivities, thereby allowing for unconstrained data inversion into diffusion tensor distributions with "size," "shape," and orientation dimensions. Here we combine our recent non-parametric data inversion algorithm and data acquisition protocol with an imaging pulse sequence to demonstrate spatial mapping of diffusion tensor distributions using a previously developed composite phantom with multiple isotropic and anisotropic components. We propose a compact format for visualizing two-dimensional arrays of the distributions, new scalar parameters quantifying intra-voxel heterogeneity, and a binning procedure giving maps of all relevant parameters for each of the components resolved in the multidimensional distribution space.
| S-EPMC6593682 | biostudies-literature
Project description:Background and objectivesClinical factors are not sufficient to fix a prognosis of recovery after stroke. Pyramidal tract or alternate motor fiber (aMF: reticulo-, rubrospinal pathways and transcallosal fibers) integrity and remodeling processes assessable by diffusion tensor MRI (DTI) and voxel-based morphometry (VBM) may be of interest. The primary objective was to study longitudinal cortical brain changes using VBM and longitudinal corticospinal tract changes using DTI during the first 4 months after lacunar cerebral infarction. The second objective was to determine which changes were correlated to clinical improvement.MethodsTwenty-one patients with deep brain ischemic infarct with pure motor deficit (NIHSS score ≥ 2) were recruited at Purpan Hospital and included. Motor deficit was measured [Nine peg hole test (NPHT), dynamometer (DYN), Hand-Tapping Test (HTT)], and a 3T MRI scan (VBM and DTI) was performed during the acute and subacute phases.ResultsWhite matter changes: corticospinal fractional anisotropy (FACST) was significantly reduced at follow-up (approximately 4 months) on the lesion side. FAr (FA ratio in affected/unaffected hemispheres) in the corona radiata was correlated to the motor performance at the NPHT, DYN, and HTT at follow-up. The presence of aMFs was not associated with the extent of recovery. Grey matter changes: VBM showed significant increased cortical thickness in the ipsilesional premotor cortex at follow-up. VBM changes in the anterior cingulum positively correlated with improvement in motor measures between baseline and follow-up.DiscussionTo our knowledge, this study is original because is a longitudinal study combining VBM and DTI during the first 4 months after stroke in a series of patients selected on pure motor deficit. Our data would suggest that good recovery relies on spared CST fibers, probably from the premotor cortex, rather than on the aMF in this group with mild motor deficit. The present study suggests that VBM and FACST could provide reliable biomarkers of post-stroke atrophy, reorganization, plasticity and recovery.ClinicaltrialsGov identifierNCT01862172, registered May 24, 2013.
| S-EPMC11447101 | biostudies-literature
Project description:Accumulating diffusion tensor imaging (DTI) evidence suggests that white matter abnormalities evaluated by local diffusion homogeneity (LDH) or fractional anisotropy (FA) occur in patients with blepharospasm (BSP), both of which are significantly correlated with disease severity. However, whether the individual severity of BSP can be identified using these DTI metrics remains unknown. We aimed to investigate whether a combination of machine learning techniques and LDH or FA can accurately identify the individual severity of BSP. Forty-one patients with BSP were assessed using the Jankovic Rating Scale and DTI. The patients were assigned to non-functionally and functionally limited groups according to their Jankovic Rating Scale scores. A machine learning scheme consisting of beam search and support vector machines was designed to identify non-functionally versus functionally limited outcomes, with the input features being LDH or FA in 68 white matter regions. The proposed machine learning scheme with LDH or FA yielded an overall accuracy of 88.67 versus 85.19% in identifying non-functionally limited versus functionally limited outcomes. The scheme also identified a sensitivity of 91.40 versus 85.87% in correctly identifying functionally limited outcomes, a specificity of 83.33 versus 83.67% in accurately identifying non-functionally limited outcomes, and an area under the curve of 93.7 versus 91.3%. These findings suggest that a combination of LDH or FA measurements and a sophisticated machine learning scheme can accurately and reliably identify the individual disease severity in patients with BSP.
| S-EPMC8155629 | biostudies-literature