Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains.
Ontology highlight
ABSTRACT:
SUBMITTER: Kelm ND
PROVIDER: S-EPMC4651761 | biostudies-literature | 2016 Jan
REPOSITORIES: biostudies-literature
Publications
Evaluation of diffusion kurtosis imaging in ex vivo hypomyelinated mouse brains.
Kelm Nathaniel D ND West Kathryn L KL Carson Robert P RP Gochberg Daniel F DF Ess Kevin C KC Does Mark D MD
NeuroImage 20150921 Pt A
Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and DKI-derived white matter tract integrity metrics (WMTI) were experimentally evaluated ex vivo through comparisons to histological measurements and established magnetic resonance imaging (MRI) measures of myelin in two knockout mouse models with varying degrees of hypomyelination. DKI metrics of mean and radial kurtosis were found to be better indicators of myelin content than conventional DTI metrics. The biophysical WMTI mode ...[more]
Similar Datasets
Project description:This study aimed to assess the relationship between mean kurtosis (MK) and mean diffusivity (MD) values from whole-brain diffusion kurtosis imaging (DKI) parametric maps in preoperative magnetic resonance (MR) images from 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups. Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 1 August 2013 and 30 October 2017. The area on scatter plots with a specific combination of MK and MD values, not occurring in the healthy brain, was labeled, and the corresponding voxels were visualized on the fluid-attenuated inversion recovery (FLAIR) images. Reversely, the labeled voxels were compared to those of the manually segmented tumor volume, and the Dice similarity coefficient was used to investigate their spatial overlap. A specific combination of MK and MD values in whole-brain DKI maps, visualized on a two-dimensional scatter plot, exclusively occurs in glioma tissue including the perifocal infiltrative zone and is absent in tissue of the normal brain or from other intracranial compartments. A unique diffusion signature with a specific combination of MK and MD values from whole-brain DKI can identify diffuse glioma without any previous segmentation. This feature might influence artificial intelligence algorithms for automatic tumor segmentation and provide new aspects of tumor heterogeneity.
| S-EPMC8199055 | biostudies-literature
Project description:PURPOSE:Diffusional kurtosis imaging (DKI) measures the deviation of the displacement probability from a normal distribution, complementing the data commonly acquired by diffusion MRI. It is important to elucidate the sources of kurtosis contrast, particularly in biological tissues where microscopic kurtosis (intrinsic kurtosis) and diffusional heterogeneity may co-exist. METHODS:We have developed a technique for microscopic kurtosis MRI, dubbed microscopic diffusional kurtosis imaging (µDKI), using a symmetrized double diffusion encoding (s-DDE) EPI sequence. We compared this newly developed µDKI to conventional DKI methods in both a triple compartment phantom and in vivo. RESULTS:Our results showed that whereas conventional DKI and µDKI provided similar measurements in a compartment of monosphere beads, kurtosis measured by µDKI was significantly less than that measured by conventional DKI in a compartment of mixed Gaussian pools. For in vivo brain imaging, µDKI showed small yet significantly lower kurtosis measurement in regions of the cortex, CSF, and internal capsule compared to the conventional DKI approach. CONCLUSIONS:Our study showed that µDKI is less susceptible than conventional DKI to sub-voxel diffusional heterogeneity. Our study also provided important preliminary demonstration of our technique in vivo, warranting future studies to investigate its diagnostic use in examining neurological disorders.
| S-EPMC6258297 | biostudies-literature
Project description:Peripheral nerve injuries result in severe loss of sensory and motor functions in the afflicted limb. There is a lack of standardised models to non-invasively study degeneration, regeneration, and normalisation of neuronal microstructure in peripheral nerves. This study aimed to develop a non-invasive evaluation of peripheral nerve injuries, using diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and tractography on a rat model of sciatic nerve injury. 10 female Sprague Dawley rats were exposed to sciatic nerve neurotmesis and studied using a 9.4?T magnet, by performing DTI and DKI of the sciatic nerve before and 4 weeks after injury. The distal nerve stump showed a decrease in fractional anisotropy (FA), mean kurtosis (MK), axonal water fraction (AWF), and radial and axonal kurtosis (RK, AK) after injury. The proximal stump showed a significant decrease in axial diffusivity (AD) and increase of MK and AK as compared with the uninjured nerve. Both mean diffusivity (MD) and radial diffusivity (RD) increased in the distal stump after injury. Tractography visualised the sciatic nerve and the site of injury, as well as local variations of the diffusion parameters following injury. In summary, the described method detects changes both proximal and distal to the nerve injury.
| S-EPMC6110718 | biostudies-literature
Project description:Ex vivo diffusion imaging can be used to study healthy and pathological tissue microstructure in the rodent brain with high resolution, providing a link between in vivo MRI and ex vivo microscopy techniques. Major challenges for the successful acquisition of ex vivo diffusion imaging data however are changes in the relaxivity and diffusivity of brain tissue following perfusion fixation. In this study we address this question by examining the combined effects of tissue preparation factors that influence signal-to-noise ratio (SNR) and consequently image quality, including fixative concentration, contrast agent concentration and tissue rehydration time. We present an optimization strategy combining these factors to manipulate the T1 and T2 of fixed tissue and maximize SNR efficiency. We apply this strategy in the rat brain, for a diffusion-weighted spin echo protocol with TE = 27 ms on a 9.4 T scanner with a 39 mm volume coil and 660 mT/m 114 mm gradient insert. We used a reduced fixative concentration of 2% paraformaldehyde (PFA), rehydration time more than 20 days, 15 mM Gd-DTPA in perfusate and TR 250 ms. This resulted in a doubling of SNR and an increase in SNR per unit time of 135% in cortical grey matter and 88% in white matter compared with 4% PFA and no contrast agent. This improved SNR efficiency enabled the acquisition of excellent-quality high-resolution (78 μ m isotropic voxel size) diffusion data with b = 4000 s/mm 2 , 30 diffusion directions and a field of view of 40×13×18 mm3 in less than 4 days. It was also possible to achieve comparable data quality for a standard resolution (150 μ m) diffusion dataset in 214 h. In conclusion, the tissue optimization strategy presented here may be used to improve SNR, increase spatial resolution and/or allow faster acquisitions in preclinical ex vivo diffusion MRI experiments.
| S-EPMC10078604 | biostudies-literature
Project description:PurposeThe general utility of diffusion kurtosis imaging (DKI) is challenged by its poor robustness to imaging artifacts and thermal noise that often lead to implausible kurtosis values.Theory and methodsA robust scalar kurtosis index can be estimated from powder-averaged diffusion-weighted data. We introduce a novel DKI estimator that uses this scalar kurtosis index as a proxy for the mean kurtosis to regularize the fit.ResultsThe regularized DKI estimator improves the robustness and reproducibility of the kurtosis metrics and results in parameter maps with enhanced quality and contrast.ConclusionOur novel DKI estimator promotes the wider use of DKI in clinical research and potentially diagnostics by improving the reproducibility and precision of DKI fitting and, as such, enabling enhanced visual, quantitative, and statistical analyses of DKI parameters.
| S-EPMC8199974 | biostudies-literature
Project description:Prior postmortem studies have shown gray matter (GM) microstructural abnormalities in schizophrenia. However, few studies to date have examined GM microstructural integrity in schizophrenia in vivo. Here, we employed diffusion kurtosis imaging (DKI) to test for differences in GM microstructure in eighteen schizophrenia (SZ) patients versus nineteen healthy controls (HC). GM microstructure was characterized in each participant using DKI-derived metrics of mean kurtosis (MK) and mean diffusivity (MD). Individual T1-weighted images were used to create subject-specific cortically-labelled regions of interest (ROIs) of the four cortical lobes and sixty-eight cortical GM regions delineated by the Desikan-Killiany atlas, and to derive the associated cortical thickness and area measures. The derived ROIs were also registered to the diffusion space of each subject and used to generate region-specific mean MK and MD values. We additionally administered the Wisconsin Card Sorting Test (WCST), Stroop test, and Trail Making Test part B (Trails-B) to test the relationship between GM metrics and executive function in SZ. We found significantly increased MK and MD in SZ compared to HC participants in the temporal lobe, sub-lobar temporal cortical regions (fusiform, inferior temporal, middle temporal and temporal pole), and posterior cingulate cortex after correcting for multiple comparisons. Correlational analyses revealed significant associations of MK and MD with executive function scores derived from the WCST, Stroop, and Trails-B tests, along with an inverse relationship between MK and MD and cortical thickness and area. A hierarchical multiple linear regression analysis showed that up to 85% of the inter-subject variability in cognitive function in schizophrenia measured by the WCST could be explained by MK in combination with either GM thickness or area. MK and MD appear to be sensitive to GM microstructural pathology in schizophrenia and may provide useful biomarkers of abnormal cortical microstructure in this disorder.
| S-EPMC7556324 | biostudies-literature
Project description:Simple summaryGlioblastoma (GBM) is the most common and aggressive primary brain tumor. Diffusion kurtosis imaging (DKI) has characterized non-Gaussian diffusion behaviors in brain normal tissue and gliomas, but there are very limited efforts in investigating treatment responses of kurtosis in GBM. This study aimed to investigate whether any parameter derived from the DKI is a significant predictor of overall survival (OS). We found that the large mean, 80 and 90 percentile kurtosis values in the contrast enhanced gross tumor volume (Gd-GTV) on post-Gd T1-weighted images pre-RT were significantly associated with reduced OS. In the multivariate Cox model, the mean kurtosis Gd-GTV pre-RT after considering effects of age, extent of surgery, and methylation were significant predictors of OS. In addition, the 80 and 90 percentile kurtosis values in Gd-GTV post RT were significantly associated with progression free survival (PFS). The DKI model demonstrates the potential to predict outcomes in the patients with GBM.PurposeNon-Gaussian diffusion behaviors in gliomas have been characterized by diffusion kurtosis imaging (DKI). But there are very limited efforts in investigating the kurtosis in glioblastoma (GBM) and its prognostic and predictive values. This study aimed to investigate whether any of the diffusion kurtosis parameters derived from DKI is a significant predictor of overall survival.Methods and materialsThirty-three patients with GBM had pre-radiation therapy (RT) and mid-RT diffusion weighted (DW) images. Kurtosis and diffusion coefficient (DC) values in the contrast enhanced gross tumor volume (Gd-GTV) on post-Gd T1 weighted images pre-RT and mid-RT were calculated. Univariate and multivariate Cox models were used to evaluate the DKI parameters and clinical factors for prediction of OS and PFS.ResultsThe large mean kurtosis values in the Gd-GTV pre-RT were significantly associated with reduced OS (p = 0.02), but the values at mid-RT were not (p > 0.8). In the multivariate Cox model, the mean kurtosis in the Gd-GTV pre-RT (p = 0.009) was still a significant predictor of OS after adjusting effects of age, O6-Methylguanine-DNA Methyl transferase (MGMT) methylation and extent of resection. In Gd-GTV post-RT, 80 and 90 percentile kurtosis values were significant predictors (p ≤ 0.05) for progression free survival (PFS).ConclusionThe DKI model demonstrates the potential to predict OS and PFS in the patients with GBM. Further development and histopathological validation of the DKI model will warrant its role in clinical management of GBM.
| S-EPMC8316991 | biostudies-literature
Project description:We assessed the test-retest reliability of high spatial resolution diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI). Diffusion MRI was acquired using a Siemens 3 Tesla Prisma scanner with 80 mT/m gradients and a 32-channel head coil from each of 3 concussive traumatic brain injury (cTBI) patients and 4 controls twice 0 to 24 days apart. Coefficients of variation (CoV) for DTI parameters were calculated in each DTI Studio parcellated white matter tract at 1.25 mm and 1.75 mm isotropic voxel resolution, as well as DKI parameters at 1.75 mm isotropic. Overall, fractional anisotropy had the best reliability, with mean CoV at 5% for 1.25 mm and 3.5% for 1.75 mm isotropic voxels. Mean CoV for the other DTI metrics were <7.0% for both 1.25 and 1.75 mm isotropic voxels. The mean CoV was ≤4.5% across the DKI metrics. In the commonly injured orbitofrontal and temporal pole regions CoV was <3.5% for all parameters. Thus, with appropriate processing, high spatial resolution advanced diffusion MRI has good to excellent test-retest reproducibility in both human cTBI patients and controls. However, further technical improvements will be needed to reliably discern the most subtle diffusion abnormalities, especially at high spatial resolution.
| S-EPMC5593980 | biostudies-literature
Project description:The purpose of this explorative study was to investigate whether diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) parameter changes are reliable measures of white matter integrity changes in Alzheimer's disease (AD) patients using a whole brain voxel-based analysis (VBA). Therefore, age- and gender-matched patients with mild cognitive impairment (MCI) due to AD (n = 18), dementia due to AD (n = 19), and age-matched cognitively healthy controls (n = 14) were prospectively included. The magnetic resonance imaging protocol included routine structural brain imaging and DKI. Datasets were transformed to a population-specific atlas space. Groups were compared using VBA. Differences in diffusion and mean kurtosis measures between MCI and AD patients and controls were shown, and were mainly found in the splenium of the corpus callosum and the corona radiata. Hence, DTI and DKI parameter changes are suggestive of white matter changes in AD.
| S-EPMC4927852 | biostudies-literature
Project description:ObjectivePhenylketonuria (PKU) is an autosomal recessive disorder whereby deficiencies in phenylalanine metabolism cause progressive neurological dysfunction. Managing PKU is challenging, with disease monitoring focussed on short-term phenylalanine control rather than measures of neuronal damage. Conventional imaging lacks sensitivity, however diffusion kurtosis imaging (DKI), a new MRI method may reveal subclinical white matter structural changes in PKU.MethodsThis cohort study involved adults with PKU recruited during routine clinical care. MRI, neurocognitive assessment and historical phenylalanine (Phe) levels were collected. A hypothesis-generating case study comparing diet-compliant and non-compliant siblings confirmed that DKI metrics are sensitive to dietary adherence and prompted a candidate metric (Krad/KFA ratio). We then tested this metric in a Replication cohort (PKU = 20; controls = 43).ResultsBoth siblings scored outside the range of controls for all DKI-based metrics, with severe changes in the periventricular white matter and a gradient of severity toward the cortex. Krad/KFA provided clear separation by diagnosis in the Replication cohort (p < 0.001 in periventricular, deep and pericortical compartments). The ratio also correlated negatively with attention (r = -0.51 & -0.50, p < 0.05) and positively with 3-year mean Phe (r = 0.45 & 0.58, p < 0.01).ConclusionDKI reveals regionally-specific, progressive abnormalities of brain diffusion characteristics in PKU, even in the absence of conspicuous clinical signs or abnormalities on conventional MRI. A DKI-based marker derived from these scores (Krad/KFA ratio) was sensitive to cognitive impairment and PKU control over the medium term and may provide a meaningful subclinical biomarker of end-organ damage.
| S-EPMC7814191 | biostudies-literature