Intracellular Volume Fraction Research Articles

Predictive Value of the Diffusion Magnetic Resonance Imaging Technique for the Postoperative Outcome of Cervical Spondylotic Myelopathy.

Diffusion magnetic resonsance imaging (dMRI) can potentially predict the postoperative outcome of cervical spondylotic myelopathy (CSM). To explore preoperative dMRI parameters to predict the postoperative outcome of CSM through multifactor correlation analysis. Prospective. Post-surgery CSM patients; 102 total, 73 male (52.42 ± 10.60 years old) and 29 female (52.0 ± 11.45 years old). 3.0 T/Turbo spin echo T1/T2-weighted, T2*-weighted multiecho gradient echo and dMRI. Spinal cord function was evaluated using modified Japanese Orthopedic Association (mJOA) scoring at different time points: preoperative and 3, 6, and 12 months postoperative. Single-factor correlation and t test analyses were conducted based on fractional anisotropy (FA), mean diffusivity, intracellular volume fraction, isotropic volume fraction, orientation division index, increased signal intensity, compression ratio, age, sex, symptom duration and operation method, and multicollinearity was calculated. The linear quantile mixed model (LQMM) and the linear mixed-effects regression model (LMER) were used for multifactor correlation analysis using the combinations of the above variables. Distance correlation, Pearson's correlation, multiscale graph correlation and t tests were used for the single-factor correlation analyses. The variance inflation factor (VIF) was used to calculate multicollinearity. LQMM and LMER were used for multifactor correlation analyses. P < 0.05 was considered statistically significant. The single-factor correlation between all variables and the postoperative mJOA score was weak (all r < 0.3). The linear relationship was stronger than the nonlinear relationship, and there was no significant multicollinearity (VIF = 1.10-1.94). FA values in the LQMM and LMER models had a significant positive correlation with the mJOA score (r = 5.27-6.04), which was stronger than the other variables. The FA value based on dMRI significantly positively correlated with CSM patient postoperative outcomes, helping to predict the surgical outcome and formulate a treatment plan before surgery. 1 TECHNICAL EFFICACY: Stage 2.

The role of MR diffusion kurtosis and neurite orientation dispersion and density imaging in evaluating gliomas.

Conventional MRI sequences in neuro-oncology are insufficient for glioma grading. However, newly developed diffusion-weighted imaging techniques have been shown to have a great potential for glioma grading. This study examined the diagnostic performance of diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), and their combinations in glioma grading. Multishell diffusion tensor images were obtained with 3T MRI in 38 glioma patients (22 high-grade glioma [HGG], 16 low-grade glioma [LGG]). DTI (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], radial diffusivity [RD]), DKI (Axial kurtosis [AK], mean kurtosis [MK], radial kurtosis [RK]), and NODDI (intracellular volume fraction [ICVF], orientation distribution index, isotropic water fraction [ISO]) images were obtained after preprocessing. The average value of these parameters was calculated in the solid components of the tumors. The receiver operating characteristic curve analyses were performed to investigate the diagnostic performance and the curves were compared with the Delong test. FA shows an increase in HGG, while MD, RD, and AD exhibit a decrease. AK, MK, and RK were higher in HGG than LGG. ICVF increased in HGG, while ISO decreased. AK demonstrated the best diagnostic performance among all parameters, and kurtosis outperformed NODDI but not DTI. Combining these parameters did not yield a statistically significant improvement in diagnostic performance. DTI, DKI, and NODDI approaches can differentiate between HGG and LGG; however, kurtosis parameters perform better and adding NODDI parameters does not improve diagnostic performance. Using multishell b-value has not led to an increase in diagnostic performance.

High-resolution diffusion-weighted imaging at 7 Tesla: Single-shot readout trajectories and their impact on signal-to-noise ratio, spatial resolution and accuracy

Diffusion MRI (dMRI) is a valuable imaging technique to study the connectivity and microstructure of the brain in vivo. However, the resolution of dMRI is limited by the low signal-to-noise ratio (SNR) of this technique. Various multi-shot acquisition strategies have been developed to achieve sub-millimeter resolution, but they require long scan times which can be restricting for patient scans. Alternatively, the SNR of single-shot acquisitions can be increased by using a spiral readout trajectory to minimize the sequence echo time. Imaging at ultra-high fields (UHF) could further increase the SNR of single-shot dMRI; however, the shorter T2* of brain tissue and the greater field non-uniformities at UHFs will degrade image quality, causing image blurring, distortions, and signal loss.In this study, we investigated the trade-off between the SNR and resolution of different k-space trajectories, including echo planar imaging (EPI), partial Fourier EPI, and spiral trajectories, over a range of dMRI resolutions at 7T. The effective resolution, spatial specificity and sharpening effect were measured from the point spread function (PSF) of the simulated diffusion sequences for a nominal resolution range of 0.6–1.8 mm. In-vivo partial brain scans at a nominal resolution of 1.5 mm isotropic were acquired using the three readout trajectories to validate the simulation results. Field probes were used to measure dynamic magnetic fields offline up to the 3rd order of spherical harmonics. Image reconstruction was performed using static ΔB0 field maps and the measured trajectories to correct image distortions and artifacts, leaving T2* effects as the primary source of blurring. The effective resolution was examined in fractional anisotropy (FA) maps calculated from a multi-shell dataset with b-values of 300, 1000, and 2000 s/mm2 in 5, 16, and 48 directions, respectively. In-vivo scans at nominal resolutions of 1, 1.2, and 1.5 mm were acquired and the SNR of the different trajectories calculated using the multiple replica method to investigate the SNR. Finally, in-vivo whole brain scans with an effective resolution of 1.5 mm isotropic were acquired to explore the SNR and efficiency of different trajectories at a matching effective resolution. FA and intra-cellular volume fraction (ICVF) maps calculated using neurite orientation dispersion and density imaging (NODDI) were used for the comparison. The simulations and in vivo imaging results showed that for matching nominal resolutions, EPI trajectories had the highest specificity and effective resolution with maximum image sharpening effect. However, spirals have a significantly higher SNR, in particular at higher resolutions and even when the effective image resolutions are matched. Overall, this work shows that the higher SNR of single-shot spiral trajectories at 7T allows us to achieve higher effective resolutions compared to EPI and PF-EPI to map the microstructure and connectivity of small brain structures.

Characterization of FTLD spectrum through advanced diffusion-weighted MRI metrics: a connectome approach (P11-6.003)

<h3>Objective:</h3> To investigate structural alterations in brain network of patients within the frontotemporal lobar degeneration (FTLD) spectrum using connectome analysis with advanced diffusion-weighted MRI metrics. <h3>Background:</h3> MRI connectomics is a promising tool to describe network-based degeneration in neurodegenerative diseases. Neurite orientation dispersion and density imaging (NODDI) has shown to provide novel insights on structural connectivity alterations. <h3>Design/Methods:</h3> Thirty-four behavioral-variant frontotemporal dementia (bvFTD), 11 semantic variant primary progressive aphasia (svPPA), 11 nonfluent (nfvPPA) patients and 48 healthy controls underwent multi-shell diffusion MRI. Fractional anisotropy (FA) maps were computed. Intra-cellular Volume Fraction (ICVF) maps were also estimated using NODDI, providing a direct quantification of neurite integrity. Graph analysis and connectomics assessed global and local structural topological network properties and regional structural connectivity. <h3>Results:</h3> Overall, widespread structural changes were observed in bvFTD patients relative to healthy controls and svPPA patients in terms of FA-derived network properties. nfvPPA patients also showed altered FA topological properties at global level compared to healthy controls. Sum of node weights (SN) in the sensorimotor lobe revealed that nfvPPA patients showed an altered connection strength compared to svPPA. Moreover, nfvPPA patients showed a significant decreased FA in the left hemispheric fronto-temporal-insular regions relative to controls. Considering ICVF, more severe alterations compared to FA maps allowed to find differences also between svPPA and nfvPPA patients. ICVF graph analysis measures also showed that svPPA had a lower degree centrality and SN in the temporal lobe compared to controls. <h3>Conclusions:</h3> These findings suggest that conventional diffusion-tensor measures might be sensitive enough to highlight vulnerable connections in the FTLD spectrum. However, ICVF demonstrated to be a more specific biomarker to differentiate FTLD syndromes. Specifically, the benefits emerged in the differentiation between svPPA patients and other groups. <b>Disclosure:</b> Federica Agosta has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Philips. Federica Agosta has received personal compensation in the range of $500-$4,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Elsevier INC. Silvia Basaia has nothing to disclose. Dr. Facente has nothing to disclose. Ms. Cividini has nothing to disclose. Dr. Spinelli has nothing to disclose. The institution of Elisa Canu has received research support from Italian Ministry of Health . Dr. Castelnovo has nothing to disclose. Giuseppe Magnani has nothing to disclose. Dr. Caso has nothing to disclose. Paola Caroppo has nothing to disclose. Sara Prioni has nothing to disclose. Miss Villa has nothing to disclose. Lucio Tremolizzo has nothing to disclose. Dr. Appollonio has nothing to disclose. Dr. Silani has nothing to disclose. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving on a Speakers Bureau for Bayer, Biogen Idec, Merck-Serono, Novartis, Roche, Sanofi Genzyme, Takeda, and Teva Pharmaceutical Industries. Dr. Filippi has received personal compensation in the range of $5,000-$9,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for Springer Nature. The institution of Dr. Filippi has received research support from Biogen Idec, Merck-Serono, Novartis, Roche, Teva Pharmaceutical Industries, Italian Ministry of Health, Fondazione Italiana Sclerosi Multipla, and ARiSLA (Fondazione Italiana di Ricerca per la SLA).

Dystonia is Associated with Macro and Microstructural Abnormalities of the Cerebellum: Analysis of Volumetric and Diffusion-Weighted MRI Data in the UK Biobank (P11-11.004)

<h3>Objective:</h3> To determine whether subjects with dystonia in the UK Biobank exhibit MRI-based cerebellar pathology. <h3>Background:</h3> Dystonia is a movement disorder characterized by sustained or intermittent muscle contractions causing abnormal movements and/or postures. Although classically considered a basal-ganglia disorder, neuroimaging studies of dystonia have revealed physiologic, structural, and functional changes in both the (1) pallido-thalamic and (2) cerebello-thalamic networks. Diffusion-weighted-MRI (DWI) analyses of both networks in dystonia have revealed differences in non-specific Diffusion-Tensor metrics such as Fractional Anisotropy. However newer DWI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), assess more specific and biologically relevant white-matter properties. <h3>Design/Methods:</h3> Using the UK Biobank, 23 subjects with isolated dystonia and diffusion-MRI data were identified, along with 69 control subjects without neurologic (ICD10 G-coded) diagnoses, matched (1:3) on age, sex, imaging site, and medical comorbidities relevant to white-matter integrity (hypertension, hyperlipidemia, and diabetes). Two DTI metrics (mean diffusivity and fractional anisotropy) and three NODDI metrics (intracellular volume fraction, isotropic volume fraction, and orientation dispersion) were extracted from each of four tracts (inferior, middle, and superior cerebellar peduncles, and superior thalamic radiations). Volumetric data consisted of cerebellar (15 regions), basal ganglia (3 regions), and whole-brain grey and white-matter volumes. <h3>Results:</h3> After correcting for multiple-comparisons (40 volumetric and 35 diffusion-related) using the Benjamini-Hochberg procedure (FDR = 0.05), intracellular-volume-fraction (ICVF) of the middle- and superior-cerebellar peduncles was significantly lower in subjects with dystonia, suggesting reduced axon density; volumetric analysis showed significantly reduced volumes of the motor cerebellum (lobules VI and VIII). There were no differences in basal ganglia, cortical, or whole-brain volumes. <h3>Conclusions:</h3> These findings support the hypothesis that abnormalities of cerebellar networks contribute to the pathogenesis of dystonia. <b>Disclosure:</b> Dr. Mason has nothing to disclose. Miss Haddad has nothing to disclose. The institution of Neda Jahanshad has received research support from Biogen Inc.

Unraveling the heterogeneous pathological substrates of relapse-onset multiple sclerosis: a multiparametric voxel-wise 3T MRI study.

In multiple sclerosis (MS), pathological processes affecting brain gray (GM) and white matter (WM) are heterogeneous. To apply a multimodal MRI approach to investigate the regional distribution of the different pathological processes occurring in the brain WM and GM of relapse-onset MS patients. Fifty-seven MS patients (forty-two relapsing remitting [RR], fifteen secondary progressive [SP]) and forty-seven age- and sex-matched healthy controls (HC) underwent a multimodal 3T MRI acquisition. Between-group voxel-wise differences of brain WM and GM volumes, magnetization transfer ratio (MTR), T1-weighted(w)/T2w ratio, intracellular volume fraction (ICV_f), and quantitative susceptibility mapping (QSM) maps were investigated. Compared to HC, RRMS showed significant WM, deep GM and cortical atrophy, significantly lower MTR and T1w/T2w ratio of periventricular and infratentorial WM, deep GM and several cortical areas, lower ICV_f in supratentorial and cerebellar WM and in some cortical areas, and lower QSM values in bilateral periventricular WM (p < 0.001). Compared to RRMS, SPMS patients showed significant deep GM and widespread cortical atrophy, significantly lower MTR of periventricular WM, deep GM and cerebellum, lower T1w/T2w ratio of fronto-temporal WM regions, lower ICV_f of some fronto-tempo-occipital WM and cortical areas. They also had increased QSM and T1w/T2w ratio in the pallidum, bilaterally (p < 0.001). A periventricular pattern of demyelination and widespread GM and WM neuro-axonal loss are detectable in RRMS and are more severe in SPMS. Higher T1w/T2w ratio and QSM in the pallidum, possibly reflecting iron accumulation and neurodegeneration, may represent a relevant MRI marker to differentiate SPMS from RRMS.

273 Dystonia is associated with macro and microstructural abnormalities of the cerebellum: A nested case-control study

OBJECTIVES/GOALS: Dystonia is a brain disorder which causes excessive muscle activation, manifesting as abnormal movements. Neuroimaging studies of dystonia have revealed changes in a network involving the cerebellum. We sought out to determine whether subjects with dystonia in the UK Biobank exhibit MRI-based cerebellar pathology. METHODS/STUDY POPULATION: This nested case-control study drew from the UK Biobank, a cohort of &gt;500,000 subjects in the United Kingdom, aged 40-69, enrolled 2006-2010. Eligible subjects must have undergone diffusion-weighted brain MRI. Dystonia cases were ascertained using ICD10 codes. We selected controls without neurologic diagnoses, matched (1:3) on age, sex, imaging site, and medical comorbidities. Mean diffusivity, fractional anisotropy, intracellular and isotropic volume fractions, and orientation dispersion were extracted from four white-matter tracts (inferior, middle, superior cerebellar peduncles; superior thalamic radiations) along with cerebellum, basal ganglia, and whole-brain grey and white-matter volumes. Means were compared using two-tailed t-tests and the Benjamini-Hochberg procedure (FDR = 0.05). RESULTS/ANTICIPATED RESULTS: 23 cases of dystonia and 69 control subjects were selected and ascertained. After correcting for multiple-comparisons (40 volumetric and 35 diffusion-related), intracellular-volume-fraction (ICVF) of the middle- and superior-cerebellar peduncles was significantly lower in subjects with dystonia, suggesting reduced axon density. Volumetric analysis showed significantly reduced volumes of the motor cerebellum (lobules VI and VIII). There were no differences in basal ganglia, cortical, or whole-brain volumes. DISCUSSION/SIGNIFICANCE: These findings support the hypothesis that abnormalities of cerebellar networks contribute to dystonia. In future we will use similar techniques to assess these tracts in subjects with dystonia who are undergoing Deep Brain Stimulation, with the goal of guiding stimulation targeting, and predicting therapeutic outcomes.

Efficient approximate signal reconstruction for correction of gradient nonlinearities in diffusion-weighted imaging

In diffusion weighted MRI (DW-MRI), hardware nonlinearities lead to spatial variations in the orientation and magnitude of diffusion weighting. While the correction of these spatial distortions has been well established for analyses of DW-MRI, the existing voxel-wise empirical correction for gradient nonlinearities requires reimplementation of existing models, as the resultant gradients vary by voxel. Herein, we propose a two-step signal approximation after voxel-wise correction of gradient nonlinearity effects in DW-MRI. The proposed technique (1) scales the diffusion signal and (2) resamples the gradient orientations. This results in uniform gradients across the corrected image and provides the key advantage of seamless integration into current diffusion workflows. We investigated the validity of our technique by fitting a multi-compartment neurite orientation dispersion and density imaging (NODDI) model to the empirical correction and proposed approximation in five subjects from the MASiVar pediatric dataset. We evaluated intra-cellular volume fraction (iVF), CSF volume fraction (cVF), and orientation dispersion index (ODI) from NODDI. The Cohen's d of iVF, cVF and ODI between the techniques was <0.2 indicating the proposed technique does not exhibit significant differences from the voxel-wise correction technique. Our two-step signal approximation is an efficient representation of the voxel-wise gradient table correction. Using this approximation, correction of gradient nonlinearities can be easily incorporated into existing diffusion preprocessing pipelines and is implemented in “PreQual: An automated pipeline for integrated preprocessing and quality assurance of diffusion weighted MRI images”.

Altered isotropic volume fraction in gray matter after sleep deprivation and its association with visuospatial memory: A neurite orientation dispersion and density imaging study.

Diffusion magnetic resonance imaging (dMRI) studies have revealed microstructural abnormalities in white matter resulting from sleep deprivation (SD). This study aimed to adopt neurite orientation dispersion and density imaging (NODDI) to investigate the effect of SD on gray matter (GM) microstructural properties and its association to visuospatial memory (VSM). Twenty-four healthy women underwent two sessions of dMRI scanning and visuospatial ability assessment by Complex Figure Test (CFT), once during rested wakefulness (RW) and once after 24 h of SD. We calculated NODDI metrics, including intracellular volume fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fraction (ISO). Differences in NODDI-related metrics between RW and SD were determined using a voxel-wise paired t-test. We identified an association between NODDI metrics and CFT results using Spearman's correlation coefficient. Sleep deprivation worsened subjects' performance in the delayed-CFT trial. We observed no significant difference in ICVF and ODI between RW and SD. After SD, subjects showed decreases in ISO, primarily in the prefrontal cortex and temporal lobe, while exhibiting ISO increases in the anterior and posterior cerebellar lobe and cerebellar vermis. Furthermore, ISO change in the left superior, middle and inferior frontal gyrus was significantly correlated with completion time change in delayed-CFT trial performance. Our results suggested that SD hardly affected the density and spatial organization of neurites in GM, but the extra-neurite water molecule diffusion process was affected (perhaps resulting from neuroinflammation), which contributed to VSM dysfunction.

Simultaneous estimation of the cellular water exchange rate, intracellular volume fraction, and longitudinal relaxation rate in cancer cells.

The purpose of the current study was to investigate the feasibility of simultaneously estimating the cellular water efflux rate ( ), intracellular longitudinal relaxation rate ( ), and intracellular volume fraction ( ) of a cell suspension using multiple samples with different gadolinium concentrations. Numerical simulation studies were conducted to assess the uncertainty in the estimation of , , and from saturation recovery data using single (SC) or multiple concentrations (MC) of gadolinium-based contrast agent (GBCA). In vitro experiments with 4 T1 murine breast cancer and SCCVII squamous cell cancer models were conducted at 11 T to compare parameter estimation using the SC protocol with that using the MC protocol. The cell lines were challenged with a Na+ /K+ -ATPase inhibitor, digoxin, to assess the treatment response in terms of , , and . Data analysis was conducted using the two-compartment exchange model for parameter estimation. The simulation study data demonstrate that the MC method, compared with the SC method, reduces the uncertainty of the estimated by decreasing the interquartile ranges from 27.3% ± 3.7% to 18.8% ± 5.1% and the median differences from ground truth from 15.0% ± 6.3% to 7.2% ± 4.2%, while estimating and simultaneously. In the cell studies, the MC method demonstrated reduced uncertainty in overall parameter estimation compared with the SC approach. MC method-measured parameter changes in cells treated with digoxin increased by 11.7% (p = 0.218) and by 5.9% (p = 0.234) for 4 T1 cells, respectively, and decreased by 28.8% (p = 0.226) and by 1.6% (p = 0.751) for SCCVII cells, respectively. did not change noticeably by the treatment. The results of this study substantiate the feasibility of using saturation recovery data of multiple samples with different GBCA concentrations for simultaneous measurement of the cellular water efflux rate, intracellular volume fraction, and intracellular longitudinal relaxation rate in cancer cells.

Neurite orientation dispersion and density imaging and diffusion tensor imaging to facilitate distinction between infiltrating tumors and edemas in glioblastoma

BackgroundGlioblastomas are highly infiltrative tumors, and differentiating between non-enhancing tumors (NETs) and vasogenic edema (Edemas) occurring in the non-enhancing T2-weighted hyperintense area is challenging. Here, we differentiated between NETs and Edemas in glioblastomas using neurite orientation dispersion and density imaging (NODDI) and diffusion tensor imaging (DTI). Materials and methodsData were collected retrospectively from 21 patients with primary glioblastomas, three with metastasis, and two with meningioma as controls. MRI data included T2 weighted images and contrast enhanced T1 weighted images, NODDI, and DTI. Three neurosurgeons manually assigned volumes of interest (VOIs) to the NETs and Edemas. The DTI and NODDI-derived parameters calculated for each VOI were fractional anisotropy (FA), apparent diffusion coefficient (ADC), intracellular volume fraction (ICVF), isotropic volume fraction (ISOVF), and orientation dispersion index. ResultsSixteen and 14 VOIs were placed on NETs and Edemas, respectively. The ICVF, ISOVF, FA, and ADC values of NETs and Edemas differed significantly (p < 0.01). Receiver operating characteristic curve analysis revealed that using all parameters allowed for improved differentiation of NETs from Edemas (area under the curve = 0.918) from the use of NODDI parameters (0.910) or DTI parameters (0.899). Multiple logistic regression was performed with all parameters, and a predictive formula to differentiate between NETs and Edemas could be created and applied to the edematous regions of the negative control-group images; the tumor prediction degree was well below 0.5, confirming differentiation as edema. ConclusionsUsing NODDI and DTI may prove useful in differentiating NETs from Edemas in the non-contrast T2 hyperintensity region of glioblastomas.

Grading meningiomas with diffusion metrics: a comparison between diffusion kurtosis, mean apparent propagator, neurite orientation dispersion and density, and diffusion tensor imaging.

To compare the histogram features of multiple diffusion metrics in predicting the grade and cellular proliferation of meningiomas. Diffusion spectrum imaging was performed in 122 meningiomas (30 males, 13-84years), which were divided into 31 high-grade meningiomas (HGMs, grades 2 and 3) and 91 low-grade meningiomas (LGMs, grade 1). The histogram features of multiple diffusion metrics obtained from diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), mean apparent propagator (MAP), and neurite orientation dispersion and density imaging (NODDI) in the solid tumours were analysed. All values between the two groups were compared with the Man-Whitney U test. Logistic regression analysis was applied to predict meningioma grade. The correlation between diffusion metrics and Ki-67 index was analysed. The DKI_AK (axial kurtosis) maximum, DKI_AK range, MAP_RTPP (return-to-plane probability) maximum, MAP_RTPP range, NODDI_ICVF (intracellular volume fraction) range, and NODDI_ICVF maximum values were lower (p < 0.0001), whilst the DTI_MD (mean diffusivity) minimum values were higher in LGMs than those in HGMs (p < 0.001). Amongst the DTI, DKI, MAP, NODDI, and combined diffusion models, no significant differences were found in areas under the receiver operating characteristic curves (AUCs) for grading meningiomas (AUCs, 0.75, 0.75, 0.80, 0.79, and 0.86, respectively; all corrected p > 0.05, Bonferroni correction). Significant but weak positive correlations were found between the Ki-67 index and DKI, MAP, and NODDI metrics (r = 0.26-0.34, all p < 0.05). Whole tumour histogram analyses of the multiple diffusion metrics from four diffusion models are promising methods in grading meningiomas. The DTI model has similar diagnostic performance compared with advanced diffusion models. • Whole tumour histogram analyses of multiple diffusion models are feasible for grading meningiomas. • The DKI, MAP, and NODDI metrics are weakly associated with the Ki-67 proliferation status. • DTI has similar diagnostic performance compared with DKI, MAP, and NODDI in grading meningiomas.

Effects of television viewing on brain structures and risk of dementia in the elderly: Longitudinal analyses.

TV viewing in the elderly and in children is associated with subsequent greater decline of various cognitive functions including verbal working memory, but results of its association with subsequent risk of dementia were divided. In this longitudinal cohort study of UK Biobank, we investigated the associations of TV viewing length with subsequent risk of dementia and longitudinal changes of brain structural measures after corrections of a wide range of potential confounders. Our results showed longer TV viewing was associated with increased risk of subsequent onset of dementia, as well as subsequent greater decline in intracellular volume fraction (ICVF) in the extensive areas of right lateral temporal cortex and the right medial temporal cortex, in the area around the left middle and inferior temporal cortex as well as the left fusiform gyrus, and the area adjacent to the left inferior frontal gyrus, and left insula. These results may suggest prolonged TV viewing was associated with decline in density of neurites (axon, dendrites) in areas particularly implicated in language, communication, and memory, which are altered in dementia.

Blood pressure-related white matter microstructural disintegrity and associated cognitive function impairment in asymptomatic adults

Background and objectivesWe aimed to investigate the white matter (WM) microstructural/cytostructural disintegrity patterns related to higher systolic blood pressure (SBP), and whether they mediate SBP effects on cognitive performance in...

Associations of Life's Simple 7 with cerebral white matter hyperintensities and microstructural integrity: UK Biobank cohort study.

The American Heart Association Life's Simple 7 (LS7) metric was used to define optimal cardiovascular and brain health, but the associations with macrostructural hyperintensities and microstructural white matter damage are unclear. The objective was to determine the association of LS7 ideal cardiovascular health factors with macrostructural and microstructural integrity. A total of 37,140 participants with available LS7 and imaging data from UK Biobank were included in this study. Linear associations were implemented to examine the associations of LS7 score and subscores with white matter hyperintensity load (WMH) (WMH volume normalized by total white matter volume and logit-transformed) and diffusion imaging indices (fractional anisotropy [FA], mean diffusivity, orientation dispersion index [OD], intracellular volume fraction, isotropic volume fraction [ISOVF]). In individuals (mean age 54.76 years; 19,697 females, 52.4%), higher LS7 score and subscores were strongly associated with lower WMH and microstructural white matter injury, including OD, ISOVF, FA. Both interaction analyses and stratified analyses of LS7 score and subscores with age and sex showed a strong association with microstructural damage markers, with remarkable age and sex differences. The association of OD was pronounced in females and populations younger than 50 years and FA, mean diffusivity and ISOVF were pronounced in males and populations older than 50 years. These findings suggest that healthier LS7 profiles are associated with better profiles of both macrostructural and microstructural markers of brain health, and indicate that ideal cardiovascular health is associated with improved brain health.

Temporal trajectories of normal myelination and axonal development assessed by quantitative macromolecular and diffusion MRI: Ultrastructural and immunochemical validation in a rabbit model

IntroductionQuantitative and non-invasive measures of brain myelination and maturation during development are of great importance to both clinical and translational research communities. While the metrics derived from diffusion tensor imaging, are sensitive to developmental changes and some pathologies, they remain difficult to relate to the actual microstructure of the brain tissue. The advent of advanced model-based microstructural metrics requires histological validation. The purpose of the study was to validate novel, model-based MRI techniques, such as macromolecular proton fraction mapping (MPF) and neurite orientation and dispersion indexing (NODDI), against histologically derived indexes of myelination and microstructural maturation at various stages of development. MethodsNew Zealand White rabbit kits underwent serial in-vivo MRI examination at postnatal days 1, 5, 11, 18, and 25, and as adults. Multi-shell, diffusion-weighted experiments were processed to fit NODDI model to obtain estimates, intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Macromolecular proton fraction (MPF) maps were obtained from three source (MT-, PD-, and T1-weighted) images. After MRI sessions, a subset of animals was euthanized and regional samples of gray and white matter were taken for western blot analysis, to determine myelin basic protein (MBP), and electron microscopy, to estimate axonal, myelin fractions and g-ratio. ResultsMPF of white matter regions showed a period of fast growth between P5 and P11 in the internal capsule, with a later onset in the corpus callosum. This MPF trajectory was in agreement with levels of myelination in the corresponding brain region, as assessed by western blot and electron microscopy. In the cortex, the greatest increase of MPF occurred between P18 and P26. In contrast, myelin, according to MBP western blot, saw the largest hike between P5 and P11 in the sensorimotor cortex and between P11 and P18 in the frontal cortex, which then seemingly plateaued after P11 and P18 respectively.G-ratio by MRI markers decreased with age in the white matter. However, electron microscopy suggest a relatively stable g-ratio throughout development. ConclusionDevelopmental trajectories of MPF accurately reflected regional differences of myelination rate in different cortical regions and white matter tracts. MRI-derived estimation of g-ratio was inaccurate during early development, likely due to the overestimation of axonal volume fraction by NODDI due to the presence of a large proportion of unmyelinated axons.

Joint estimation of relaxation and diffusion tissue parameters for prostate cancer with relaxation-VERDICT MRI

This work presents a biophysical model of diffusion and relaxation MRI for prostate called relaxation vascular, extracellular and restricted diffusion for cytometry in tumours (rVERDICT). The model includes compartment-specific relaxation effects providing T1/T2 estimates and microstructural parameters unbiased by relaxation properties of the tissue. 44 men with suspected prostate cancer (PCa) underwent multiparametric MRI (mp-MRI) and VERDICT-MRI followed by targeted biopsy. We estimate joint diffusion and relaxation prostate tissue parameters with rVERDICT using deep neural networks for fast fitting. We tested the feasibility of rVERDICT estimates for Gleason grade discrimination and compared with classic VERDICT and the apparent diffusion coefficient (ADC) from mp-MRI. The rVERDICT intracellular volume fraction fic discriminated between Gleason 3 + 3 and 3 + 4 (p = 0.003) and Gleason 3 + 4 and ≥ 4 + 3 (p = 0.040), outperforming classic VERDICT and the ADC from mp-MRI. To evaluate the relaxation estimates we compare against independent multi-TE acquisitions, showing that the rVERDICT T2 values are not significantly different from those estimated with the independent multi-TE acquisition (p > 0.05). Also, rVERDICT parameters exhibited high repeatability when rescanning five patients (R2 = 0.79–0.98; CV = 1–7%; ICC = 92–98%). The rVERDICT model allows for accurate, fast and repeatable estimation of diffusion and relaxation properties of PCa sensitive enough to discriminate Gleason grades 3 + 3, 3 + 4 and ≥ 4 + 3.

Multimodal Imaging of Substantia Nigra in Parkinson's Disease with Levodopa-Induced Dyskinesia.

Degeneration of the substantia nigra (SN) may contribute to levodopa-induced dyskinesia (LID) in Parkinson's disease (PD), but the exact characteristics of SN in LID remain unclear. To further understand the pathogenesis of patients with PD with LID (PD-LID), we explored the structural and functional characteristics of SN in PD-LID using multimodal magnetic resonance imaging (MRI). Twenty-nine patients with PD-LID, 37 patients with PD without LID (PD-nLID), and 28 healthy control subjects underwent T1-weighted MRI, quantitative susceptibility mapping, neuromelanin-sensitive MRI, multishell diffusion MRI, and resting-state functional MRI. Different measures characterizing the SN were obtained using a region of interest-based approach. Compared with patients with PD-nLID and healthy control subjects, the quantitative susceptibility mapping values of SN pars compacta (SNpc) were significantly higher (P= 0.049 and P= 0.00002), and the neuromelanin contrast-to-noise ratio values in SNpc were significantly lower (P= 0.012 and P= 0.000002) in PD-LID. The intracellular volume fraction of the posterior SN in PD-LID was significantly higher compared with PD-nLID (P= 0.037). Resting-state fMRI indicated that PD-LID in the medication off state showed higher functional connectivity between the SNpc and putamen compared with PD-nLID (P= 0.031), and the functional connectivity changes in PD-LID were positively correlated with Unified Dyskinesia Rating Scale total scores (R= 0.427, P=0.042). Our multimodal imaging findings highlight greater neurodegeneration in SN and the altered nigrostriatal connectivity in PD-LID. These characteristics provide a new perspective into the role of SN in the pathophysiological mechanisms underlying PD-LID. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Diffusion time dependency of extracellular diffusion.

To quantify the variations of the power-law dependences on diffusion time t or gradient frequency of extracellular water diffusion measured by diffusion MRI (dMRI). Model cellular systems containing only extracellular water were used to investigate the dependence of , the extracellular diffusion coefficient. Computer simulations used a randomly packed tissue model with realistic intracellular volume fractions and cell sizes. DMRI measurements were performed on samples consisting of liposomes containing heavy water(D2 O, deuterium oxide) dispersed in regular water (H2 O). was obtained over a broad range (∼1-1000 ms) and then fit power-law equations and . Both simulated and experimental results suggest that no single power-law adequately describes the behavior of over the range of diffusion times of most interest in practical dMRI. Previous theoretical predictions are accurate over only limited ranges; for example, is valid only for short times, whereas or is valid only for long times but cannot describe other ranges simultaneously. For the specific range of 5-70 ms used in typical human dMRI measurements, matches the data well empirically. The optimal power-law fit of extracellular diffusion varies with diffusion time. The dependency obtained at short or long limits cannot be applied to typical dMRI measurements in human cancer or liver. It is essential to determine the appropriate diffusion time range when modeling extracellular diffusion in dMRI-based quantitative microstructural imaging.

Abstract 131: Brain Mri Biomarkers Of Impaired Balance And Slow Walk Speed: Atherosclerosis Risk In Communities And UK Biobank Studies

Background and Objectives: Vascular brain injury (VBI) may contribute to imbalance and slow walk speed, but this is uncertain. We hypothesize that MRI biomarkers of VBI associate with impaired balance and slow walk speed. Methods: We performed separate, cross-sectional analyses in the Atherosclerosis Risk in Communities (ARIC) and UK Biobank (UKB) studies. Eligible participants had no prior clinical stroke and underwent a brain MRI and balance and walk speed ascertainment. MRI biomarkers of VBI analyzed were: ventricular volume, white matter hyperintensity volume (WMH), non-lacunar infarction, lacunar infarction, microhemorrhage in ARIC; ventricular volume, brain volume, WMH, fractional anisotropy (FA), mean diffusivity (MD), intra-cellular volume fraction, isotropic free water volume fraction in UKB. Quantitative biomarker levels were classified into tertiles, the unhealthiest tertile designated as the exposure. Our outcomes were poor balance and slow walk speed. We constructed multivariable logistic regression models to examine the associations between each MRI biomarker and the outcomes, adjusting for demographics and clinical history. Results: We included 1,626 ARIC participants (mean age 76.2 years; 23.4% impaired balance, 25.0% slow walk speed) and 40,098 UKB participants (mean age 55 years; 15.8% impaired balance, 2.8% slow walk speed). In ARIC, impaired balance was associated with 4 of 5 MRI measures of VBI in adjusted analysis (all p-values &lt;0.05). The strongest association was with WMH (OR 1.36; 95% C.I. 1.04-1.76). Slow walk speed in ARIC was significantly associated with 4 of 5 MRI measures; the strongest association was with silent lacunar infarcts (OR 2.17; 95% C.I. 1.61-2.93). In UKB, poor balance was associated with all MRI biomarkers except WMH. The strongest association was with FA (OR 1.16; 95% C.I. 1.08-1.24). Slow walking speed was associated with WMH, FA, and MD. The strongest association was with FA (OR 1.42; 95% C.I. 1.21-1.67). Conclusions: We demonstrate that MRI measures of VBI are independently associated with impaired balance and slow walk speed in two studies of community-dwelling adults with no history of clinical stroke. Consequences of VBI may extend beyond clinically apparent stroke to also include mobility.