An Adaptive 3D U-Net for White Matter, Gray Matter and Cerebrospinal Fluid Segmentation from 3D-Brain MRI

2021 ◽  
Author(s):  
Bao The Pham ◽  
ANH TUAN TRAN ◽  
ANH TUAN(A) TRAN ◽  
NHI LAM THUY LE ◽  
Jin Young Kim
Keyword(s):  
Cerebrospinal Fluid ◽  
White Matter ◽  
Gray Matter ◽  
Brain Mri

scholarly journals Long-term cerebral white and gray matter changes after preeclampsia

Neurology ◽  
2017 ◽  
Vol 88 (13) ◽  
pp. 1256-1264 ◽  
Author(s):  
Timo Siepmann ◽  
Henry Boardman ◽  
Amy Bilderbeck ◽  
Ludovica Griffanti ◽  
Yvonne Kenworthy ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
White Matter ◽  
Temporal Lobe ◽  
Gray Matter ◽  
Diffusion Tensor ◽  
Brain Mri ◽  
Risk Profile ◽  
Lesion Volume ◽  
Cardiovascular Risk Profile ◽  
Microstructural Integrity

Objective:To determine whether changes in cerebral structure are present after preeclampsia that may explain increased cerebrovascular risk in these women.Methods:We conducted a case control study in women between 5 and 15 years after either a preeclamptic or normotensive pregnancy. Brain MRI was performed. Analysis of white matter structure was undertaken using voxel-based segmentation of fluid-attenuation inversion recovery sequences to assess white matter lesion volume and diffusion tensor imaging to measure microstructural integrity. Voxel-based analysis of gray matter volumes was performed with adjustment for skull size.Results:Thirty-four previously preeclamptic women (aged 42.8 ± 5.1 years) and 49 controls were included. Previously preeclamptic women had reduced cortical gray matter volume (523.2 ± 30.1 vs 544.4 ± 44.7 mL, p < 0.05) and, although both groups displayed white matter lesions, changes were more extensive in previously preeclamptic women. They displayed increased temporal lobe white matter disease (lesion volume: 23.2 ± 24.9 vs 10.9 ± 15.0 μL, p < 0.05) and altered microstructural integrity (radial diffusivity: 538 ± 19 vs 526 ± 18 × 10−6 mm2/s, p < 0.01), which also extended to occipital and parietal lobes. The degree of temporal lobe white matter change in previously preeclamptic women was independent of their current cardiovascular risk profile (p < 0.05) and increased with time from index pregnancy (p < 0.05).Conclusion:A history of preeclampsia is associated with temporal lobe white matter changes and reduced cortical volume in young women, which is out of proportion to their classic cardiovascular risk profile. The severity of changes is proportional to time since pregnancy, which would be consistent with continued accumulation of damage after pregnancy.

scholarly journals The 12-Word Philadelphia Verbal Learning Test Performances in Older Adults: Brain MRI and Cerebrospinal Fluid Correlates and Regression-Based Normative Data

2018 ◽  
Vol 8 (3) ◽  
pp. 476-491 ◽  
Author(s):  
Katherine A. Gifford ◽  
Dandan Liu ◽  
Jacquelyn E. Neal ◽  
Michelle A. Babicz ◽  
Jennifer L. Thompson ◽  
...  
Keyword(s):  
Older Adults ◽  
Cerebrospinal Fluid ◽  
White Matter ◽  
Normative Data ◽  
Verbal Learning ◽  
Brain Mri ◽  
Axonal Injury ◽  
Cognitive Change ◽  
Csf Biomarkers ◽  
Learning Test

Background/Aims: This study evaluated neuroimaging and biological correlates, psychometric properties, and regression-based normative data of the 12-word Philadelphia Verbal Learning Test (PVLT), a list-learning test. Methods: Vanderbilt Memory and Aging Project participants free of clinical dementia and stroke (n = 230, aged 73 ± 7 years) completed a neuropsychological protocol and brain MRI. A subset (n = 111) underwent lumbar puncture for analysis of Alzheimer’s disease (AD) and axonal integrity cerebrospinal fluid (CSF) biomarkers. Regression models related PVLT indices to MRI and CSF biomarkers adjusting for age, sex, race/ethnicity, education, APOE-ε4 carrier status, cognitive status, and intracranial volume (MRI models). Secondary analyses were restricted to participants with normal cognition (NC; n = 127), from which regression-based normative data were generated. Results: Lower PVLT performances were associated with smaller medial temporal lobe volumes (p < 0.05) and higher CSF tau concentrations (p < 0.04). Among NC, PVLT indices were associated with white matter hyperintensities on MRI and an axonal injury biomarker (CSF neurofilament light; p < 0.03). Conclusion: The PVLT appears sensitive to markers of neurodegeneration, including temporal regions affected by AD. Conversely, in cognitively normal older adults, PVLT performance seems to relate to white matter disease and axonal injury, perhaps reflecting non-AD pathways to cognitive change. Enhanced normative data enrich the clinical utility of this tool.

scholarly journals Regional Gray Matter, White Matter, and Cerebrospinal Fluid Distributions in Schizophrenic Patients, Their Siblings, and Controls

1998 ◽  
Vol 55 (12) ◽  
pp. 1084 ◽  
Author(s):  
Tyrone D. Cannon ◽  
Theo G. M. van Erp ◽  
Matti Huttunen ◽  
Jouko Lönnqvist ◽  
Oili Salonen ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
White Matter ◽  
Gray Matter ◽  
Schizophrenic Patients

scholarly journals Circulating cortisol and cognitive and structural brain measures

Neurology ◽  
2018 ◽  
Vol 91 (21) ◽  
pp. e1961-e1970 ◽  
Author(s):  
Justin B. Echouffo-Tcheugui ◽  
Sarah C. Conner ◽  
Jayandra J. Himali ◽  
Pauline Maillard ◽  
Charles S. DeCarli ◽  
...  
Keyword(s):  
White Matter ◽  
Visual Perception ◽  
Gray Matter ◽  
Brain Volume ◽  
Brain Mri ◽  
Serum Cortisol ◽  
Community Dwelling ◽  
White Matter Hyperintensity ◽  
Middle Aged ◽  
Middle Aged Adults

ObjectiveTo assess the association of early morning serum cortisol with cognitive performance and brain structural integrity in community-dwelling young and middle-aged adults without dementia.MethodsWe evaluated dementia-free Framingham Heart Study (generation 3) participants (mean age 48.5 years, 46.8% men) who underwent cognitive testing for memory, abstract reasoning, visual perception, attention, and executive function (n = 2,231) and brain MRI (n = 2018) to assess total white matter, lobar gray matter, and white matter hyperintensity volumes and fractional anisotropy (FA) measures. We used linear and logistic regression to assess the relations of cortisol (categorized in tertiles, with the middle tertile as referent) to measures of cognition, MRI volumes, presence of covert brain infarcts and cerebral microbleeds, and voxel-based microstructural white matter integrity and gray matter density, adjusting for age, sex, APOE, and vascular risk factors.ResultsHigher cortisol (highest tertile vs middle tertile) was associated with worse memory and visual perception, as well as lower total cerebral brain and occipital and frontal lobar gray matter volumes. Higher cortisol was associated with multiple areas of microstructural changes (decreased regional FA), especially in the splenium of corpus callosum and the posterior corona radiata. The association of cortisol with total cerebral brain volume varied by sex (p for interaction = 0.048); higher cortisol was inversely associated with cerebral brain volume in women (p = 0.001) but not in men (p = 0.717). There was no effect modification by the APOE4 genotype of the relations of cortisol and cognition or imaging traits.ConclusionHigher serum cortisol was associated with lower brain volumes and impaired memory in asymptomatic younger to middle-aged adults, with the association being evident particularly in women.

scholarly journals The Impact of Common Epidemiological Factors on Gray and White Matter Volumes in Magnetic Resonance Imaging–Is Prevention of Brain Degeneration Possible?

2021 ◽  
Vol 12 ◽  
Author(s):  
Jagoda Jacków-Nowicka ◽  
Przemysław Podgórski ◽  
Joanna Bladowska ◽  
Dorota Szcześniak ◽  
Joanna Rymaszewska ◽  
...  
Keyword(s):  
Risk Factors ◽  
White Matter ◽  
Gray Matter ◽  
Brain Mri ◽  
Intracranial Volume ◽  
Before And After ◽  
Urban Rural ◽  
Gray Matter Loss ◽  
Age Range ◽  
The Impact

Introduction: The aim of the study was to evaluate the impact of multiple risk factors (age, diabetes, hypertension, hyperlipidemia, BMI, smoking, alcohol) on the gray and white matter volumes as well as on the burden of white matter hyperintensities (WMH).Material and Methods: The study group consisted of 554 subjects (age range: 50–69 yrs, F/M: 367/187) recruited from the larger cohort of the Polish fraction of the Prospective Urban Rural Epidemiological (PURE) study. The participants answered questionnaires about their lifestyle, underwent physical and psychological examination (MoCA test), laboratory blood tests followed by brain MRI. Volumetric measurements of the total gray matter (GMvol), total white matter (WMvol) and WHM (WMHvol) normalized to the total intracranial volume were performed using the Computational Anatomy Toolbox 12 (CAT12) and Statistical Parametric Maps 12 (SPM12) based on 3D T1-weighted sequence. The influence of risk factors was assessed using multiple regression analysis before and after correction for multiple comparisons.Results: Older age was associated with lower GMvol and WMvol, and higher WMHvol (p &lt; 0.001). Smaller GMvol volume was associated with higher WMHvol (p &lt; 0.001). Higher WMHvol was associated with hypertension (p = 0.01) and less significantly with hyperlipidemia (only before correction p = 0.03). Diabetes, abnormal BMI, smoking and alcohol intake did not have any significant impact on GMvol, WMvol or WMHvol (p &gt; 0.05). MoCA score was not influenced by any of the factors.Conclusions: Gray matter loss is strongly associated with the accumulation of WMH which seems to be potentially preventable by maintaining normal blood pressure and cholesterol levels.

scholarly journals Multilevel Thresholding Method Based on Electromagnetism for Accurate Brain MRI Segmentation to Detect White Matter, Gray Matter, and CSF

2017 ◽  
Vol 2017 ◽  
pp. 1-17 ◽  
Author(s):  
G. Sandhya ◽  
Giri Babu Kande ◽  
T. Satya Savithri
Keyword(s):  
White Matter ◽  
Gray Matter ◽  
Brain Mri ◽  
Ground Truth ◽  
Gaussian Mixture ◽  
Multilevel Thresholding ◽  
Mri Segmentation ◽  
Thresholding Method ◽  
Skull Stripping ◽  
Mr Brain

This work explains an advanced and accurate brain MRI segmentation method. MR brain image segmentation is to know the anatomical structure, to identify the abnormalities, and to detect various tissues which help in treatment planning prior to radiation therapy. This proposed technique is a Multilevel Thresholding (MT) method based on the phenomenon of Electromagnetism and it segments the image into three tissues such as White Matter (WM), Gray Matter (GM), and CSF. The approach incorporates skull stripping and filtering using anisotropic diffusion filter in the preprocessing stage. This thresholding method uses the force of attraction-repulsion between the charged particles to increase the population. It is the combination of Electromagnetism-Like optimization algorithm with the Otsu and Kapur objective functions. The results obtained by using the proposed method are compared with the ground-truth images and have given best values for the measures sensitivity, specificity, and segmentation accuracy. The results using 10 MR brain images proved that the proposed method has accurately segmented the three brain tissues compared to the existing segmentation methods such as K-means, fuzzy C-means, OTSU MT, Particle Swarm Optimization (PSO), Bacterial Foraging Algorithm (BFA), Genetic Algorithm (GA), and Fuzzy Local Gaussian Mixture Model (FLGMM).

scholarly journals Development of a Stand-Alone Independent Graphical User Interface for Neurological Disease Prediction with Automated Extraction and Segmentation of Gray and White Matter in Brain MRI Images

2019 ◽  
Vol 2019 ◽  
pp. 1-21 ◽  
Author(s):  
Ayush Goyal ◽  
Sunayana Tirumalasetty ◽  
Gahangir Hossain ◽  
Rajab Challoo ◽  
Manish Arya ◽  
...  
Keyword(s):  
White Matter ◽  
Gray Matter ◽  
Neurological Disorders ◽  
Neurological Disease ◽  
Automatic Segmentation ◽  
Brain Mri ◽  
Image Data ◽  
Disease Prediction ◽  
Mri Segmentation ◽  
Segmentation Algorithms

This research presents an independent stand-alone graphical computational tool which functions as a neurological disease prediction framework for diagnosis of neurological disorders to assist neurologists or researchers in the field to perform automatic segmentation of gray and white matter regions in brain MRI images. The tool was built in collaboration with neurologists and neurosurgeons and many of the features are based on their feedback. This tool provides the user automatized functionality to perform automatic segmentation and extract the gray and white matter regions of patient brain image data using an algorithm called adapted fuzzy c-means (FCM) membership-based clustering with preprocessing using the elliptical Hough transform and postprocessing using connected region analysis. Dice coefficients for several patient brain MRI images were calculated to measure the similarity between the manual tracings by experts and automatic segmentations obtained in this research. The average Dice coefficients are 0.86 for gray matter, 0.88 for white matter, and 0.87 for total cortical matter. Dice coefficients of the proposed algorithm were also the highest when compared with previously published standard state-of-the-art brain MRI segmentation algorithms in terms of accuracy in segmenting the gray matter, white matter, and total cortical matter.

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