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Tomography (Ann Arbor, Mich.) Jan 2022Cognitive training-induced neuroplastic brain changes have been reported. This prospective study evaluated whether microscopic fractional anisotropy (μFA) derived from... (Randomized Controlled Trial)
Randomized Controlled Trial
Cognitive training-induced neuroplastic brain changes have been reported. This prospective study evaluated whether microscopic fractional anisotropy (μFA) derived from double diffusion encoding (DDE) MRI could detect brain changes following a 4 week cognitive training. Twenty-nine healthy volunteers were recruited and randomly assigned into the training ( = 21) and control ( = 8) groups. Both groups underwent brain MRI including DDE MRI and 3D-T1-weighted imaging twice at an interval of 4-6 weeks, during which the former underwent the training. The training consisted of hour-long dual N-back and attention network tasks conducted five days per week. Training and time-related changes of DDE MRI indices (μFA, fractional anisotropy (FA), and mean diffusivity (MD)) and the gray and white matter volume were evaluated using mixed-design analysis of variance. In addition, any significant imaging indices were tested for correlation with cognitive training-induced task performance changes, using partial correlation analyses. μFA in the left middle frontal gyrus decreased upon the training (53 voxels, uncorrected < 0.001), which correlated moderately with response time changes in the orienting component of attention (r = -0.521, uncorrected = 0.032). No significant training and time-related changes were observed for other imaging indices. Thus, μFA can become a sensitive index to detect cognitive training-induced neuroplastic changes.
Topics: Anisotropy; Brain; Cognition; Humans; Prospective Studies; White Matter
PubMed: 35076639
DOI: 10.3390/tomography8010004 -
The British Journal of Radiology Mar 2023To investigate the value of DTI in differentiation of renal allograft rejection from well-functioning stable allograft, using fractional anisotropy (FA) and apparent...
OBJECTIVES
To investigate the value of DTI in differentiation of renal allograft rejection from well-functioning stable allograft, using fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values.
METHODS
In this prospective study, 22 transplant recipients with well-functioning stable allograft (group A) and 20 patients with renal allograft rejection (group + C) were recruited over a period of 19 months from January 2018 to July 2019. DTI-MRI was performed in all the patients, and FA and ADC values were measured in cortical and medullary regions of the transplanted kidney. On biopsy, graft rejection was classified as acute (group B) ( = 7) and chronic graft rejection (group C) ( = 13) based on the BANNF scoring system. Statistical analysis was performed using STATA v.14.0.
RESULTS
Statistically significant difference between group A and group + C was noted for cortical ( < 0.001), and medullary ( = 0.003) FA values, and cortical ( = 0.020), and medullary ( = 0.046) ADC values. Cortical( < 0.001) and Medullary( = 0.020) FA values showed statistically significant difference between group A and group C, and cortical FA value( = 0.012) also showed statistically significant difference between group B and group C. AUC (to differentiate between renal allograft rejection and well-functioning stable allograft) for cortical, and medullary FA values and cortical and medullary ADC values were 0.853( < 0.001), 0.757( = 0.004), 0.709( = 0.021) and 0.736( = 0.009), respectively.
CONCLUSION AND ADVANCES IN KNOWLEDGE
DTI is a promising functional MRI technique for the non-invasive assessment of renal allograft function. Diffusion parameters, such as FA and ADC values, can be useful in the differentiation of renal allograft rejection from well-functioning stable allograft.
Topics: Humans; Diffusion Tensor Imaging; Kidney Transplantation; Prospective Studies; Kidney; Diffusion Magnetic Resonance Imaging; Anisotropy; Allografts
PubMed: 36607279
DOI: 10.1259/bjr.20220722 -
Human Brain Mapping Dec 2021Population averaged diffusion atlases can be utilized to characterize complex microstructural changes with less bias than data from individual subjects. In this study, a...
Population averaged diffusion atlases can be utilized to characterize complex microstructural changes with less bias than data from individual subjects. In this study, a fetal diffusion tensor imaging (DTI) atlas was used to investigate tract-based changes in anisotropy and diffusivity in vivo from 23 to 38 weeks of gestational age (GA). Healthy pregnant volunteers with typically developing fetuses were imaged at 3 T. Acquisition included structural images processed with a super-resolution algorithm and DTI images processed with a motion-tracked slice-to-volume registration algorithm. The DTI from individual subjects were used to generate 16 templates, each specific to a week of GA; this was accomplished by means of a tensor-to-tensor diffeomorphic deformable registration method integrated with kernel regression in age. Deterministic tractography was performed to outline the forceps major, forceps minor, bilateral corticospinal tracts (CST), bilateral inferior fronto-occipital fasciculus (IFOF), bilateral inferior longitudinal fasciculus (ILF), and bilateral uncinate fasciculus (UF). The mean fractional anisotropy (FA) and mean diffusivity (MD) was recorded for all tracts. For a subset of tracts (forceps major, CST, and IFOF) we manually divided the tractograms into anatomy conforming segments to evaluate within-tract changes. We found tract-specific, nonlinear, age related changes in FA and MD. Early in gestation, these trends appear to be dominated by cytoarchitectonic changes in the transient white matter fetal zones while later in gestation, trends conforming to the progression of myelination were observed. We also observed significant (local) heterogeneity in within-tract developmental trajectories for the CST, IFOF, and forceps major.
Topics: Anisotropy; Atlases as Topic; Diffusion Tensor Imaging; Female; Fetus; Gestational Age; Humans; Male; Pregnancy; Prenatal Diagnosis; White Matter
PubMed: 34487404
DOI: 10.1002/hbm.25653 -
Journal of Magnetic Resonance Imaging :... Apr 2020Diffusion MRI (dMRI) is a growing imaging technique with the potential to provide biomarkers of tissue variation, such as cellular density, tissue anisotropy, and... (Review)
Review
Diffusion MRI (dMRI) is a growing imaging technique with the potential to provide biomarkers of tissue variation, such as cellular density, tissue anisotropy, and microvascular perfusion. However, the role of dMRI in characterizing different aspects of bone quality, especially in aging and osteoporosis, has not yet been fully established, particularly in clinical applications. The reason lies in the complications accompanied with implementation of dMRI in assessment of human bone structure, in terms of acquisition and quantification. Bone is a composite tissue comprising different elements, each contributing to the overall quality and functional competence of bone. As diffusion is a critical biophysical process in biological tissues, early changes of tissue microstructure and function can affect diffusive properties of the tissue. While there are multiple MRI methods to detect variations of individual properties of bone quality due to aging and osteoporosis, dMRI has potential to serve as a superior method for characterizing different aspects of bone quality within the same framework but with higher sensitivity to early alterations. This is mainly because several properties of the tissue including directionality and anisotropy of trabecular bone and cell density can be collected using only dMRI. In this review article, we first describe components of human bone that can be potentially detected by their diffusivity properties and contribute to variations in bone quality during aging and osteoporosis. Then we discuss considerations and challenges of dMRI in bone imaging, current status, and suggestions for development of dMRI in research studies and clinics to segregate different contributing components of bone quality in an integrated acquisition. Level of Evidence: 5 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:975-992.
Topics: Anisotropy; Diffusion Magnetic Resonance Imaging; Healthy Aging; Humans; Magnetic Resonance Imaging; Osteoporosis
PubMed: 31709670
DOI: 10.1002/jmri.26973 -
Biological Psychiatry Mar 2020Internalizing disorders such as anxiety and depression are common psychiatric disorders that frequently begin in youth and exhibit marked heterogeneity in treatment...
BACKGROUND
Internalizing disorders such as anxiety and depression are common psychiatric disorders that frequently begin in youth and exhibit marked heterogeneity in treatment response and clinical course. Given that symptom-based classification approaches do not align with underlying neurobiology, an alternative approach is to identify neurobiologically informed subtypes based on brain imaging data.
METHODS
We used a recently developed semisupervised machine learning method (HYDRA [heterogeneity through discriminative analysis]) to delineate patterns of neurobiological heterogeneity within youths with internalizing symptoms using structural data collected at 3T from a sample of 1141 youths.
RESULTS
Using volume and cortical thickness, cross-validation methods indicated 2 highly stable subtypes of internalizing youths (adjusted Rand index = 0.66; permutation-based false discovery rate p < .001). Subtype 1, defined by smaller brain volumes and reduced cortical thickness, was marked by impaired cognitive performance and higher levels of psychopathology than both subtype 2 and typically developing youths. Using resting-state functional magnetic resonance imaging and diffusion images not considered during clustering, we found that subtype 1 also showed reduced amplitudes of low-frequency fluctuations in frontolimbic regions at rest and reduced fractional anisotropy in several white matter tracts. In contrast, subtype 2 showed intact cognitive performance and greater volume, cortical thickness, and amplitudes during rest compared with subtype 1 and typically developing youths, despite still showing clinically significant levels of psychopathology.
CONCLUSIONS
We identified 2 subtypes of internalizing youths differentiated by abnormalities in brain structure, function, and white matter integrity, with one of the subtypes showing poorer functioning across multiple domains. Identification of biologically grounded internalizing subtypes may assist in targeting early interventions and assessing longitudinal prognosis.
Topics: Adolescent; Anisotropy; Anxiety Disorders; Brain; Humans; Magnetic Resonance Imaging; White Matter
PubMed: 31690494
DOI: 10.1016/j.biopsych.2019.09.005 -
Magnetic Resonance in Medicine May 2021The apparent propagator anisotropy (APA) is a new diffusion MRI metric that, while drawing on the benefits of the ensemble averaged propagator anisotropy (PA) compared...
PURPOSE
The apparent propagator anisotropy (APA) is a new diffusion MRI metric that, while drawing on the benefits of the ensemble averaged propagator anisotropy (PA) compared to the fractional anisotropy (FA), can be estimated from single-shell data.
THEORY AND METHODS
Computation of the full PA requires acquisition of large datasets with many diffusion directions and different b-values, and results in extremely long processing times. This has hindered adoption of the PA by the community, despite evidence that it provides meaningful information beyond the FA. Calculation of the complete propagator can be avoided under the hypothesis that a similar sensitivity/specificity may be achieved from apparent measurements at a given shell. Assuming that diffusion anisotropy (DiA) is nondependent on the b-value, a closed-form expression using information from one single shell (ie, b-value) is reported.
RESULTS
Publicly available databases with healthy and diseased subjects are used to compare the APA against other anisotropy measures. The structural information provided by the APA correlates with that provided by the PA for healthy subjects, while it also reveals statistically relevant differences in white matter regions for two pathologies, with a higher reliability than the FA. Additionally, APA has a computational complexity similar to the FA, with processing-times several orders of magnitude below the PA.
CONCLUSIONS
The APA can extract more relevant white matter information than the FA, without any additional demands on data acquisition. This makes APA an attractive option for adoption into existing diffusion MRI analysis pipelines.
Topics: Anisotropy; Brain; Diffusion Magnetic Resonance Imaging; Humans; Image Processing, Computer-Assisted; Reproducibility of Results; White Matter
PubMed: 33314330
DOI: 10.1002/mrm.28620 -
Human Brain Mapping May 2020Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called... (Review)
Review
Investigative studies of white matter (WM) brain structures using diffusion MRI (dMRI) tractography frequently require manual WM bundle segmentation, often called "virtual dissection." Human errors and personal decisions make these manual segmentations hard to reproduce, which have not yet been quantified by the dMRI community. It is our opinion that if the field of dMRI tractography wants to be taken seriously as a widespread clinical tool, it is imperative to harmonize WM bundle segmentations and develop protocols aimed to be used in clinical settings. The EADC-ADNI Harmonized Hippocampal Protocol achieved such standardization through a series of steps that must be reproduced for every WM bundle. This article is an observation of the problematic. A specific bundle segmentation protocol was used in order to provide a real-life example, but the contribution of this article is to discuss the need for reproducibility and standardized protocol, as for any measurement tool. This study required the participation of 11 experts and 13 nonexperts in neuroanatomy and "virtual dissection" across various laboratories and hospitals. Intra-rater agreement (Dice score) was approximately 0.77, while inter-rater was approximately 0.65. The protocol provided to participants was not necessarily optimal, but its design mimics, in essence, what will be required in future protocols. Reporting tractometry results such as average fractional anisotropy, volume or streamline count of a particular bundle without a sufficient reproducibility score could make the analysis and interpretations more difficult. Coordinated efforts by the diffusion MRI tractography community are needed to quantify and account for reproducibility of WM bundle extraction protocols in this era of open and collaborative science.
Topics: Anisotropy; Diffusion Magnetic Resonance Imaging; Diffusion Tensor Imaging; Dissection; Humans; Observer Variation; Reproducibility of Results; White Matter
PubMed: 31925871
DOI: 10.1002/hbm.24917 -
Magnetic Resonance in Medicine Nov 2019To directly compare diffusion metrics derived from multiband (MB) imaging sequences to those derived using a single-band acquisition. (Comparative Study)
Comparative Study
PURPOSE
To directly compare diffusion metrics derived from multiband (MB) imaging sequences to those derived using a single-band acquisition.
METHODS
In this work, diffusion metrics from DTI and mean apparent propagator MRI derived from a commercial MB sequence with an acceleration factor of 3 are compared with those derived from a conventional diffusion MRI sequence using a novel bootstrapping analysis scheme on oversampled diffusion MRI data. The average parameter values for fractional anisotropy and mean diffusivity derived from DTI, as well as propagator anisotropy and return to origin probability derived from mean apparent propagator MRI, are compared.
RESULTS
Fractional anisotropy and propagator anisotropy are very similar when computed from data collected with and without MB, but show minor differences at low and high values of fractional anisotropy/propagator anisotropy. Mean diffusivity values are generally lower in the MB-derived maps, and return to origin probability is generally higher. The coefficient of variation of each parameter is shown to be slightly higher on average from the maps derived from MB versus single band when the TR is short, and slightly lower when the TR of the MB and single-band experiments is equal.
CONCLUSION
These results demonstrate that the MB sequence tested in this work provides very similar results to a conventional diffusion MRI sequence. The MB sequence is affected minimally by the slight decrease in SNR associated with the parallel reconstruction and reduced TR, and there are relaxation effects associated with the reduced TR.
Topics: Anisotropy; Brain Mapping; Diffusion Magnetic Resonance Imaging; Healthy Volunteers; Humans; Image Enhancement; Image Processing, Computer-Assisted
PubMed: 31155758
DOI: 10.1002/mrm.27833 -
Magnetic Resonance in Medicine Dec 2022Quasi-diffusion MRI (QDI) is a novel quantitative technique based on the continuous time random walk model of diffusion dynamics. QDI provides estimates of the diffusion...
PURPOSE
Quasi-diffusion MRI (QDI) is a novel quantitative technique based on the continuous time random walk model of diffusion dynamics. QDI provides estimates of the diffusion coefficient, in mm s and a fractional exponent, , defining the non-Gaussianity of the diffusion signal decay. Here, the b-value selection for rapid clinical acquisition of QDI tensor imaging (QDTI) data is optimized.
METHODS
Clinically appropriate QDTI acquisitions were optimized in healthy volunteers with respect to a multi-b-value reference (MbR) dataset comprising 29 diffusion-sensitized images arrayed between and 5000 s mm . The effects of varying maximum b-value ( ), number of b-value shells, and the effects of Rician noise were investigated.
RESULTS
QDTI measures showed dependence, most significantly for in white matter, which monotonically decreased with higher leading to improved tissue contrast. Optimized 2 b-value shell acquisitions showed small systematic differences in QDTI measures relative to MbR values, with overestimation of and underestimation of in white matter, and overestimation of and anisotropies in gray and white matter. Additional shells improved the accuracy, precision, and reliability of QDTI estimates with 3 and 4 shells at s mm , and 4 b-value shells at s mm , providing minimal bias in and compared to the MbR.
CONCLUSION
A highly detailed optimization of non-Gaussian dMRI for in vivo brain imaging was performed. QDI provided robust parameterization of non-Gaussian diffusion signal decay in clinically feasible imaging times with high reliability, accuracy, and precision of QDTI measures.
Topics: Anisotropy; Brain; Diffusion Magnetic Resonance Imaging; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Reproducibility of Results; White Matter
PubMed: 36054778
DOI: 10.1002/mrm.29420 -
Journal of Biomechanical Engineering Nov 2022Due to lack of full vascularization, the meniscus relies on diffusion through the extracellular matrix to deliver small (e.g., nutrients) and large (e.g., proteins) to...
Due to lack of full vascularization, the meniscus relies on diffusion through the extracellular matrix to deliver small (e.g., nutrients) and large (e.g., proteins) to resident cells. Under normal physiological conditions, the meniscus undergoes up to 20% compressive strains. While previous studies characterized solute diffusivity in the uncompressed meniscus, to date, little is known about the diffusive transport under physiological strain levels. This information is crucial to fully understand the pathophysiology of the meniscus. The objective of this study was to investigate strain-dependent diffusive properties of the meniscus fibrocartilage. Tissue samples were harvested from the central portion of porcine medial menisci and tested via fluorescence recovery after photobleaching to measure diffusivity of fluorescein (332 Da) and 40 K Da dextran (D40K) under 0%, 10%, and 20% compressive strain. Specifically, average diffusion coefficient and anisotropic ratio, defined as the ratio of the diffusion coefficient in the direction of the tissue collagen fibers to that orthogonal, were determined. For all the experimental conditions investigated, fluorescein diffusivity was statistically faster than that of D40K. Also, for both molecules, diffusion coefficients significantly decreased, up to ∼45%, as the strain increased. In contrast, the anisotropic ratios of both molecules were similar and not affected by the strain applied to the tissue. This suggests that compressive strains used in this study did not alter the diffusive pathways in the meniscus. Our findings provide new knowledge on the transport properties of the meniscus fibrocartilage that can be leveraged to further understand tissue pathophysiology and approaches to tissue restoration.
Topics: Animals; Anisotropy; Diffusion; Fibrocartilage; Fluoresceins; Meniscus; Swine
PubMed: 35789377
DOI: 10.1115/1.4054931