scholarly journals [Re] Optimization of a free water elimination two-compartment model for diffusion tensor imaging

2017 ◽  
Author(s):  
Rafael Neto Henriques ◽  
Ariel Rokem ◽  
Eleftherios Garyfallidis ◽  
Samuel St-Jean ◽  
Eric Thomas Peterson ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Free Water ◽  
Compartment Model ◽  
B Values ◽  
Brain White Matter ◽  
Diffusion Weighted ◽  
Two Compartment Model ◽  
Water Elimination

Typical diffusion-weighted imaging (DWI) is susceptible to partial volume effects: different types of tissue that reside in the same voxel are inextricably mixed. For instance, in regions near the cerebral ventricles or parenchyma, fractional anisotropy (FA) from diffusion tensor imaging (DTI) may be underestimated, due to partial volumes of cerebral spinal fluid (CSF). Free-water can be suppressed by adding parameters to diffusion MRI models. For example, the DTI model can be extended to separately take into account the contributions of tissue and CSF, by representing the tissue compartment with an anisotropic diffusion tensor and the CSF compartment as an isotropic free water diffusion coefficient. Recently, two procedures were proposed to fit this two-compartment model to diffusion-weighted data acquired for at least two different non-zero diffusion MRI b-values. In this work, the first open-source reference implementation of these procedures is provided. In addition to presenting some methodological improvements that increase model fitting robustness, the free water DTI procedures are re-evaluated using Monte-Carlo multicompartmental simulations. Analogous to previous studies, our results show that the free water elimination DTI model is able to remove confounding effects of fast diffusion for typical FA values of brain white matter. In addition, this study confirms that for a fixed scanning time the fwDTI fitting procedures have better performance when data is acquired for diffusion gradient direction evenly distributed along two b-values of 500 and 1500 s/mm2.

scholarly journals Optimization of a free water elimination two-compartment model for diffusion tensor imaging

NeuroImage ◽  
2014 ◽  
Vol 103 ◽  
pp. 323-333 ◽  
Author(s):  
Andrew R. Hoy ◽  
Cheng Guan Koay ◽  
Steven R. Kecskemeti ◽  
Andrew L. Alexander
Keyword(s):  
Diffusion Tensor Imaging ◽  
Diffusion Tensor ◽  
Free Water ◽  
Compartment Model ◽  
Two Compartment Model ◽  
Water Elimination

scholarly journals Microstructural white matter alterations in preclinical Alzheimer’s disease detected using free water elimination diffusion tensor imaging

PLoS ONE ◽  
2017 ◽  
Vol 12 (3) ◽  
pp. e0173982 ◽  
Author(s):  
Andrew R. Hoy ◽  
Martina Ly ◽  
Cynthia M. Carlsson ◽  
Ozioma C. Okonkwo ◽  
Henrik Zetterberg ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Free Water ◽  
Preclinical Alzheimer’S Disease ◽  
Water Elimination

scholarly journals Freewater EstimatoR using iNtErpolated iniTialization (FERNET): Toward Accurate Estimation of Free Water in Peritumoral Region Using Single-Shell Diffusion MRI Data

2019 ◽  
Author(s):  
Abdol Aziz Ould Ismail ◽  
Drew Parker ◽  
Moises Hernandez-Fernandez ◽  
Ronald Wolf ◽  
Steven Brem ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Diffusion Mri ◽  
Diffusion Tensor ◽  
Free Water ◽  
Simulated Data ◽  
Compartment Model ◽  
Accurate Estimation ◽  
Imaging Data ◽  
Tissue Microstructure ◽  
Single Shell

ABSTRACTCharacterization of healthy versus pathological tissue is a key concern when modeling tissue microstructure in the peritumoral area, confounded by the presence of free water (e.g., edema). Most methods that model tissue microstructure are either based on advanced acquisition schemes not readily available in the clinic, or are not designed to address the challenge of edema. This underscores the need for a robust free water elimination (FWE) method that estimates free water in pathological tissue but can be used with clinically prevalent single-shell diffusion tensor imaging data. FWE in single-shell data requires the fitting of a bi-compartment model, which is an ill-posed problem. Its solution requires optimization, which relies on an initialization step. We propose a novel initialization approach for FWE, FERNET, which improves the estimation of free water in edematous and infiltrated peritumoral regions, using single-shell diffusion MRI data. The method has been extensively investigated on simulated data and healthy and brain tumor datasets, demonstrating its applicability on clinically acquired data. Additionally, it has been applied to data from brain tumor patients to demonstrate the improvement in tractography in the peritumoral region.

scholarly journals Diffusion tensor imaging on 3-T MRI breast: diagnostic performance in comparison to diffusion-weighted imaging

2021 ◽  
Vol 52 (1) ◽  
Author(s):  
Dalia Abdelhady ◽  
Amany Abdelbary ◽  
Ahmed H. Afifi ◽  
Alaa-eldin Abdelhamid ◽  
Hebatallah H. M. Hassan
Keyword(s):  
Breast Cancer ◽  
Diffusion Tensor Imaging ◽  
Sensitivity And Specificity ◽  
Diffusion Weighted Imaging ◽  
Diffusion Tensor ◽  
Breast Mri ◽  
Breast Lesions ◽  
Dce Mri ◽  
Additional Tool ◽  
Diffusion Weighted

Abstract Background Breast cancer is the most prevalent cancer among females. Dynamic contrast-enhanced MRI (DCE-MRI) breast is highly sensitive (90%) in the detection of breast cancer. Despite its high sensitivity in detecting breast cancer, its specificity (72%) is moderate. Owing to 3-T breast MRI which has the advantage of a higher signal to noise ratio and shorter scanning time rather than the 1.5-T MRI, the adding of new techniques as diffusion tensor imaging (DTI) to breast MRI became more feasible. Diffusion-weighted imaging (DWI) which tracks the diffusion of the tissue water molecule as well as providing data about the integrity of the cell membrane has been used as a valuable additional tool of DCE-MRI to increase its specificity. Based on DWI, more details about the microstructure could be detected using diffusion tensor imaging. The DTI applies diffusion in many directions so apparent diffusion coefficient (ADC) will vary according to the measured direction raising its sensitivity to microstructure elements and cellular density. This study aimed to investigate the diagnostic accuracy of DTI in the assessment of breast lesions in comparison to DWI. Results By analyzing the data of the 50 cases (31 malignant cases and 19 benign cases), the sensitivity and specificity of DWI in differentiation between benign and malignant lesions were about 90% and 63% respectively with PPV 90% and NPV 62%, while the DTI showed lower sensitivity and specificity about 81% and 51.7%, respectively, with PPV 78.9% and NPV 54.8% (P-value ≤ 0.05). Conclusion While the DWI is still the most established diffusion parameter, DTI may be helpful in the further characterization of tumor microstructure and differentiation between benign and malignant breast lesions.

White Matter Alteration Following SWAT Explosive Breaching Training and the Moderating Effect of a Neck Collar Device: A DTI and NODDI Study

2021 ◽  
Author(s):  
Weihong Yuan ◽  
Jonathan Dudley ◽  
Alexis B Slutsky-Ganesh ◽  
James Leach ◽  
Pete Scheifele ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Diffusion Tensor ◽  
Moderating Effect ◽  
Significant Group ◽  
Blast Exposure ◽  
Diffusion Weighted ◽  
Weighted Data ◽  
The Right ◽  
The Impact

ABSTRACT Introduction Special Weapons and Tactics (SWAT) personnel who practice breaching with blast exposure are at risk for blast-related head trauma. We aimed to investigate the impact of low-level blast exposure on underlying white matter (WM) microstructure based on diffusion tensor imaging (DTI) and neurite orientation and density imaging (NODDI) in SWAT personnel before and after breacher training. Diffusion tensor imaging is an advanced MRI technique sensitive to underlying WM alterations. NODDI is a novel MRI technique emerged recently that acquires diffusion weighted data from multiple shells modeling for different compartments in the microstructural environment in the brain. We also aimed to evaluate the effect of a jugular vein compression collar device in mitigating the alteration of the diffusion properties in the WM as well as its role as a moderator on the association between the diffusion property changes and the blast exposure. Materials and Methods Twenty-one SWAT personnel (10 non-collar and 11 collar) completed the breacher training and underwent MRI at both baseline and after blast exposure. Diffusion weighted data were acquired with two shells (b = 1,000, 2,000 s/mm2) on 3T Phillips scanners. Diffusion tensor imaging metrices, including fractional anisotropy, mean, axial, and radial diffusivity, and NODDI metrics, including neurite density index (NDI), isotropic volume fraction (fiso), and orientation dispersion index, were calculated. Tract-based spatial statistics was used in the voxel-wise statistical analysis. Post hoc analyses were performed for the quantification of the pre- to post-blast exposure diffusion percentage change in the WM regions with significant group difference and for the assessment of the interaction of the relationship between blast exposure and diffusion alteration. Results The non-collar group exhibited significant pre- to post-blast increase in NDI (corrected P < .05) in the WM involving the right internal capsule, the right posterior corona radiation, the right posterior thalamic radiation, and the right sagittal stratum. A subset of these regions showed significantly greater alteration in NDI and fiso in the non-collar group when compared with those in the collar group (corrected P < .05). In addition, collar wearing exhibited a significant moderating effect for the alteration of fiso for its association with average peak pulse pressure. Conclusions Our data provided initial evidence of the impact of blast exposure on WM diffusion alteration based on both DTI and NODDI. The mitigating effect of WM diffusivity changes and the moderating effect of collar wearing suggest that the device may serve as a promising solution to protect WM against blast exposure.

scholarly journals White Matter Integrity Predicts Delay Discounting Behavior in 9- to 23-Year-Olds: A Diffusion Tensor Imaging Study

2009 ◽  
Vol 21 (7) ◽  
pp. 1406-1421 ◽  
Author(s):  
Elizabeth A. Olson ◽  
Paul F. Collins ◽  
Catalina J. Hooper ◽  
Ryan Muetzel ◽  
Kelvin O. Lim ◽  
...  
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Delay Discounting ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Imaging Study ◽  
Temporal Lobes ◽  
Brain White Matter ◽  
Independent Effects ◽  
Age Range

Healthy participants (n = 79), ages 9–23, completed a delay discounting task assessing the extent to which the value of a monetary reward declines as the delay to its receipt increases. Diffusion tensor imaging (DTI) was used to evaluate how individual differences in delay discounting relate to variation in fractional anisotropy (FA) and mean diffusivity (MD) within whole-brain white matter using voxel-based regressions. Given that rapid prefrontal lobe development is occurring during this age range and that functional imaging studies have implicated the prefrontal cortex in discounting behavior, we hypothesized that differences in FA and MD would be associated with alterations in the discounting rate. The analyses revealed a number of clusters where less impulsive performance on the delay discounting task was associated with higher FA and lower MD. The clusters were located primarily in bilateral frontal and temporal lobes and were localized within white matter tracts, including portions of the inferior and superior longitudinal fasciculi, anterior thalamic radiation, uncinate fasciculus, inferior fronto-occipital fasciculus, corticospinal tract, and splenium of the corpus callosum. FA increased and MD decreased with age in the majority of these regions. Some, but not all, of the discounting/DTI associations remained significant after controlling for age. Findings are discussed in terms of both developmental and age-independent effects of white matter organization on discounting behavior.

scholarly journals Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

2021 ◽  
Vol 22 (10) ◽  
pp. 5216
Author(s):  
Koji Kamagata ◽  
Christina Andica ◽  
Ayumi Kato ◽  
Yuya Saito ◽  
Wataru Uchida ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Neurodegenerative Diseases ◽  
Diffusion Magnetic Resonance Imaging ◽  
New Technologies ◽  
Diffusion Tensor ◽  
Free Water ◽  
Diffusion Kurtosis Imaging ◽  
Resonance Imaging

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

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