Detection Of White Matter Changes Research Articles

Early Detection of White Matter Changes with Cognitive Decline in Parkinson's Patients

Objective: The aim of this study was to detect changes in white matter in patients with Parkinson's disease applied by diffusion tensor imaging to predict cognitive impairment.
 Methods: Montreal cognitive assessment was applied to 50 Parkinson's disease patients to confirm cognitive decline (M: F = 41:9; age: 62.72±9.07 years) and to 20 Parkinson's disease patients with no cognitive impairment as a control (M: F =13:7; age 58.95±11.22). All patients underwent disease severity testing by using Modified Hoehn and Yahr Scale, Unified Parkinson disease rating scale and Diffusion tensor imaging (DTI) for the corpus callosum and cingulum including their involved parts to define affected tracts.
 Results: In PD with cognitive impairment subjects, the cognitive affection correlated with abnormal DTI parameters of the corpus callosum and cingulum. There were FA or MD differences in both the corpus callosum and cingulum pathways. These findings were independent of age, sex and total white matter volume.
 Conclusion: Patients with Parkinson's disease associated with cognition decline are detected by tractography changes of the corpus callosum and cingulum.

Clinical application of Half Fourier Acquisition Single Shot Turbo Spin Echo (HASTE) imaging accelerated by simultaneous multi-slice acquisition

PurposeAs a single-shot sequence with a long train of refocusing pulses, Half-Fourier Acquisition Single-Shot Turbo-Spin-Echo (HASTE) suffers from high power deposition limiting use at high resolutions and high field strengths, particularly if combined with acceleration techniques such as simultaneous multi-slice (SMS) imaging. Using a combination of multiband (MB)-excitation and PINS-refocusing pulses will effectively accelerate the acquisition time while staying within the SAR limitations. In particular, uncooperative and young patients will profit from the speed of the MB-PINS HASTE sequence, as clinical diagnosis can be possible without sedation.Materials and MethodsMB-excitation and PINS-refocusing pulses were incorporated into a HASTE-sequence with blipped CAIPIRINHA and TRAPS including an internal FLASH reference scan for online reconstruction. Whole brain MB-PINS HASTE data were acquired on a Siemens 3T-Prisma system from 10 individuals and compared to a clinical HASTE protocol.ResultsThe proposed MB-PINS HASTE protocol accelerates the acquisition by about a factor 2 compared to the clinical HASTE. The diagnostic image quality proved to be comparable for both sequences for the evaluation of the overall aspect of the brain, the detection of white matter changes and areas of tissue loss, and for the evaluation of the CSF spaces although artifacts were more frequently encountered with MB-PINS HASTE.ConclusionsMB-PINS HASTE enables acquisition of slice accelerated highly T2-weighted images and provides good diagnostic image quality while reducing acquisition time.

Supervoxel-based statistical analysis of diffusion tensor imaging in schizotypal personality disorder

To study white matter changes in schizotypal personality disorder (SPD), we developed a new statistical analysis method based on supervoxels for diffusion tensor imaging. Twenty patients with SPD and eighteen healthy controls were recruited from a pool of 3000 first-year university undergraduates, and underwent MRI using a 3T scanner. Diffusion tensors were first normalized into ICBM-152 space followed by a supervoxel segmentation based on graph clustering to segment white matter tensors into diffusion homogeneous supervoxels. Fractional anisotropy (FA) values in supervoxels were compared between SPD and healthy controls using permutation test. Suprathreshold cluster size test was used to correct multiple comparison. At last, fibers with significant differences were extracted from supervoxel clusters with significance level P < 0.05. Results showed that FA values in genu of corpus callosum were significantly reduced (P = 0.012) in patients with SPD (FA = 0.565) compared with healthy controls (FA = 0.593). In summary, this study proposed a novel supervoxel segmentation method for diffusion tensor imaging using graph-based clustering, and extended permutation test and suprathreshold cluster size test to supervoxels for detection of white matter changes.

Dynamic changes in diffusion measures improve sensitivity in identifying patients with mild traumatic brain injury.

The goal of this study was to investigate patterns of axonal injury in the first week after mild traumatic brain injury (mTBI). We performed a prospective cohort study of 20 patients presenting to the emergency department with mTBI, using 3.0T diffusion tensor MRI immediately after injury and again at 1 week post-injury. Corresponding data were acquired from 16 controls over a similar time interval. Fractional anisotropy (FA) and other diffusion measures were calculated from 11 a priori selected axon tracts at each time-point, and the change across time in each region was quantified for each subject. Clinical outcomes were determined by standardized neurocognitive assessment. We found that mTBI subjects were significantly more likely to have changes in FA in those 11 regions of interest across the one week time period, compared to control subjects whose FA measurements were stable across time. Longitudinal imaging was more sensitive to these subtle changes in white matter integrity than cross-sectional assessments at either of two time points, alone. Analyzing the sources of variance in our control population, we show that this increased sensitivity is likely due to the smaller within-subject variability obtained by longitudinal analysis with each subject as their own control. This is in contrast to the larger between-subject variability obtained by cross-sectional analysis of each individual subject to normalized data from a control group. We also demonstrated that inclusion of all a priori ROIs in an analytic model as opposed to measuring individual ROIs improves detection of white matter changes by overcoming issues of injury heterogeneity. Finally, we employed genetic programming (a bio-inspired computational method for model estimation) to demonstrate that longitudinal changes in FA have utility in predicting the symptomatology of patients with mTBI. We conclude concussive brain injury caused acute, measurable changes in the FA of white matter tracts consistent with evolving axonal injury and/or edema, which may contribute to post-concussive symptoms.

Embedded multicore computing and applications

Embedded multicore computing and applications

Statistical Instability of TBSS Analysis Based on DTI Fitting Algorithm.

Voxel-based DTI analysis is an important approach in the comparison of subject groups by detecting and localizing gray and white matter changes in the brain. One of the principal problems for intersubject comparison is the absence of a "gold standard" processing pipeline. As a result, contradictory results may be obtained from identical data using different data processing pipelines, for example, in the data normalization or smoothing procedures. Tract-based spatial statistics (TBSS) shows potential to overcome this problem by automatic detection of white matter changes and decreasing variation in the performed analysis. However, skeleton projection approaches, such as TBSS, critically depend on the accuracy of the diffusion scalar metric estimations. In this work, we demonstrate that the agreement and reliability of TBSS results depend on the applied DTI data processing algorithm. Statistical tests have been performed using two in vivo measured datasets and compared with different implementations of the least squares algorithm. As a result, we recommend repeating TBSS analysis using different fitting algorithms, in particular, using on iteratively-assessed robust estimators, as accurate and more reliable approach in voxel-based analysis, particularly, for TBSS. Repeating TBSS analysis allows one to detect and localize suspicious regions in white matter which were estimated as the regions with significant difference. Finally, we did not find a favorite fitting algorithm (or class of them) which can be marked as more reliable for group comparison.

Automated Detection of White Matter Changes in Elderly People Using Fuzzy, Geostatistical, and Information Combining Models

Detection of white matter changes of the brain using magnetic resonance imaging (MRI) has increasingly been an active and challenging research area in computational neuroscience. There have rarely been any single image analysis methods that can effectively address the issue of automated quantification of neuroimages, which are subject to different interests of various medical hypotheses. This paper presents new image segmentation models for automated detection of white matter changes of the brain in an elderly population. The methods are based on the computational models of fuzzy clustering, possibilistic clustering, geostatistics, and knowledge combination. Experimental results on MRI data have shown that the proposed image analysis methodology can be applied as a very useful computerized tool for the validation of our particular medical question, where white matter changes of the brain are thought to be the most important social medical evidence.

A Severe Case of Dentatorubro-Pallidoluysian Atrophy (DRPLA) with Microcephaly, Very Early Onset of Seizures, and Cerebral White Matter Involvement

We report a severe case of Dentatorubro-pallidoluysian atrophy (DRPLA) presenting with microcephaly, developmental delay, severe epilepsy, and progressive mental deterioration with a very early onset of disease. The case is notable for the early detection of white matter changes by brain MRI. Neuroradiological findings from the case were compared to those of previously reported patients with disease onset before 10 years of age.

High b value q-space-analyzed diffusion MRI in vascular dementia: A preliminary study

High b value diffusion weighted magnetic resonance imaging (high- b DWI) was used to characterize white matter changes in the brain of patients with vascular dementia (VaD). Hyperintense white matter areas detected by T2-weighted magnetic resonance imaging (MRI) represent lesions, also termed leukoaraiosis that are very common in VaD as well as in other types of dementia. Therefore, the role of white matter changes in the cognitive and memory decline that occurs in VaD patients is still under debate. High- b DWI, analyzed using the q-space approach, is a more sensitive MRI method for detection of white matter changes. High- b DWI revealed massive white matter loss in VaD patients that surpassed the boundaries of T2 hyperintensities. This technique, therefore, might serve as a better indication for the extensive nerve fiber loss in the white matter that is caused by vascular disease.

Cardiovascular characteristics and cerebral CT findings in elderly subjects with psychomotor disadaptation syndrome.

In previous studies, we described a clinical picture typically observed in frail old people, called "Psychomotor Disadaptation Syndrome" (PDS), but we have never studied etiopathogenic data. The aim of this study was to complete the clinical picture, record cardiovascular risk factors and provide cerebral CT scan findings in patients with PDS. 73 patients with PDS were recruited in the Geriatric Medicine departments of the University Hospitals of Dijon (Burgundy, France) and Strasbourg (Alsace, France); this group included prospectively all hospitalized patients showing postural and gait abnormalities according to the following criteria: trend towards backward falling and gait pattern alteration characterized by hesitancy in initiation, small steps, and increase in the double support durations. General characteristics, neurological and cardiovascular information were collected for each patient. For the detection of white matter changes (WMC), we used a third-generation CT scanner (GE CT HSA) evaluating a section of 7 mm at each interval of 8 mm. Neurological examination showed that "reactional hypertonia" was observed in more than 90% of the patients, and that no patient showed normal reactive postural responses. Prior history of hypertension was noted in 49% of the patients, while a current antihypertensive treatment was taken by 13% of the patients. Orthostatic hypotension was observed in 44% of patients. Severe or moderate periventricular lucencies on CT scan were found in 67% of the patients, and severe ventricular enlargement in 50.5% of the patients. We advance that PDS might be associated with WMC, and that hypotension might be an important etiologic factor of WMC in causing reduction of the cerebral blood flow in subcortical areas.

Lower Body (Vascular) Parkinsonism

To the Editor. —I was very interested in the recent article in theArchivesby Masdeu et al 1 on the correlation between white matter hypodensity on computed tomography (CT) and impaired gait and balance in the elderly. The investigators excluded orthopedic, cognitive, sensory, and other neurologic reasons for the ambulatory problems and falls. While the fallers (66.7% of 20) were more likely to be demented than the controls (25.0% of 20), and the dementia could have contributed to the poor balance, I agree with their conclusion that the periventricular white matter disease, suggested by the abnormal CT scans, was primarily responsible for the abnormal gait and falls. Although CT may be less sensitive than magnetic resonance imaging (MRI) for detection of white matter changes, these MRI changes may be seen also in normal individuals. 2 As noted by the authors, while the possible correlation between CT-MRI white matter changes