OBJECTIVE:To examine the value of MRI outcomes as endpoints for preventive and early-stage trials of two polyglutamine spinocerebellar ataxias (SCAs). METHODS:A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene-negative controls) was scanned at 3T up to 6 times (median follow-up 3 years) in the READISCA study. Structural, microstructural, and neurochemical outcomes were assessed for sensitivity to change. Associations between change in MR and clinical and patient-reported outcomes were evaluated. Sample sizes were estimated for preventive trials (at preataxic stage) and early-stage trials using the most sensitive outcomes. RESULTS:Infratentorial volumes, middle cerebellar peduncle (MCP) diffusivities and select neurochemical outcomes were more sensitive to change than SARA in both SCAs with moderate-to-high effect sizes (Cohen's d ≥ 0.5). The pons volume was the most sensitive outcome at both preataxic (d = 1.09) and ataxic (d = 1.48) stages. The most sensitive MR measures overlapped between genotypes, except that SCA1 showed faster progression in the cerebellum and SCA3 in the pons. Changes in MCP diffusivities and pontine neurochemical measures were associated with changes in SARA and FARS-ADL (|r| = 0.28-0.47). INTERPRETATION:The estimated sample sizes to detect a 50% reduction in progression with 80% power using the pons volume as primary outcome measure indicate the feasibility of preventive trials (n = 73 per arm in a 1-year trial) in common SCAs and predict a 6-fold reduction in required sample sizes relative to SARA in early interventional trials. These findings support the use of MRI endpoints in early-stage SCA trials.

OBJECTIVE:Neurochemical levels measured by brain MR spectroscopy (MRS) have been proposed as endpoints for clinical trials in early-stage spinocerebellar ataxia (SCA) trials. We tested their trial-readiness by quantifying neurochemicals in three affected brain regions in early-stage cohorts of SCA2 and SCA3, examining their reproducibility in both patients and controls in a multisite/multivendor setting, and determining if the same neurochemical outcomes can be used as endpoints for different SCA genotypes. METHODS:Seventy-two participants (18 SCA2, mean Scale for the Assessment and Rating of Ataxia (SARA) = 9 +/- 5; 25 SCA3, mean SARA = 10 +/- 6; 29 controls) underwent 3 T scans at four sites using scanners from two vendors and a harmonized MRS protocol. Scans were performed twice with a maximum 2-week interval. We measured neurochemical concentrations in the cerebellum, pons, and putamen, and assessed their within- and between-site reproducibility and associations with clinician- and patient-reported outcomes. RESULTS:Test-retest coefficients of variance were comparable across sites and vendors, but concentration estimates had to be adjusted for sites to account for small vendor-based biases. Total N-acetylaspartate (tNAA) and glutamate were lower, and myo-inositol (mI) and total creatine (tCr) were higher in the cerebellum and pons in both SCAs vs. controls. Pontine tNAA and mI, and cerebellar tNAA, mI, and glutamate levels were significantly different between SCA2 and SCA3, with strong effect sizes (|Cohen's d| = 1.1-2.1). The tNAA/tCr ratio had the strongest associations with clinical outcomes (|r| ≥ 0.5), with stronger associations in the cerebellum for SCA2 and in the pons for SCA3. INTERPRETATION:These data support the use of tNAA and its ratios in a genotype-specific manner in early-stage SCA2 and SCA3 trials in the multisite/multivendor setting.

INTRODUCTION:Although many white matter tracts underlying language functions have been identified, even in aggregate they do not provide a sufficiently detailed and expansive picture to enable us to fully understand the computational processes that might underly language production and comprehension. We employed diffusion tensor tractography (DTT) with a tensor distribution model to more extensively explore the white matter tracts supporting core language functions. Our study was guided by hypotheses stemming largely from the aphasia literature. METHODS:We employed high angular resolution diffusion imaging (HARDI) with a dual region of interest tractography approach. Our diffusion tensor distribution model uses a mixture of Wishart distributions to estimate the water molecule displacement probability functions on a voxel-by-voxel basis and to model crossing/branching fibers using a multicompartmental approach. RESULTS:We replicated the results of previously published studies of tracts underlying language function. Our study also yielded a number of novel findings: 1) extensive connectivity between Broca's region and the entirety of the middle and superior frontal gyri; 2) extensive interconnectivity between the four subcomponents of Broca's region, pars orbitalis, pars triangularis, pars opercularis, and the inferior precentral gyrus; 3) connectivity between the mid-superior temporal gyrus and the transverse gyrus; 4) connectivity between the mid-superior temporal gyrus, the transverse gyrus, and the planum temporale and the inferior and middle temporal gyri; and 5) connectivity between mid- and anterior superior temporal gyrus and all components of Broca's region. DISCUSSION:These results, which replicate the results of prior DTT studies, also considerably extend them and thereby provide a fuller picture of the structural basis of language function and the basis for a novel model of the neural network architecture of language function. This new model is entirely consistent with discoveries from the aphasia literature and with parallel distributed processing conceptualizations of language function.

Purpose To develop a dentate nucleus (DN) segmentation tool using deep learning applied to brain MRI-based quantitative susceptibility mapping (QSM) images. Materials and Methods Brain QSM images from healthy controls and individuals with cerebellar ataxia or multiple sclerosis were collected from nine different datasets (2016-2023) worldwide for this retrospective study (ClinicalTrials.gov identifier: NCT04349514). Manual delineation of the DN was performed by experienced raters. Automated segmentation performance was evaluated against manual reference segmentations following training with several deep learning architectures. A two-step approach was used, consisting of a localization model followed by DN segmentation. Performance metrics included intraclass correlation coefficient (ICC), Dice score, and Pearson correlation coefficient. Results The training and testing datasets comprised 328 individuals (age range, 11-64 years; 171 female individuals), including 141 healthy individuals and 187 with cerebellar ataxia or multiple sclerosis. The manual tracing protocol produced reference standards with high intrarater (average ICC, 0.91) and interrater reliability (average ICC, 0.78). Initial deep learning architecture exploration indicated that the nnU-Net framework performed best. The two-step localization plus segmentation pipeline achieved a Dice score of 0.90 ± 0.03 (SD) and 0.89 ± 0.04 for left and right DN segmentation, respectively. In external testing, the proposed algorithm outperformed the current leading automated tool (mean Dice scores for left and right DN, 0.86 ± 0.04 vs 0.57 ± 0.22 [P < .001]; 0.84 ± 0.07 vs 0.58 ± 0.24 [P < .001]). The model demonstrated generalizability across datasets unseen during the training step, with automated segmentations showing high correlation with manual annotations (left DN: r = 0.74 [P < .001]; right DN: r = 0.48 [P = .03]). Conclusion The proposed model accurately and efficiently segmented the DN from brain QSM images. The model is publicly available (https://github.com/art2mri/DentateSeg). Keywords: MR Imaging, Brain/Brain Stem, Segmentation, Convolutional Neural Network, Supervised Learning, Computer Applications-3D, Volume Analysis, Image Postprocessing ClinicalTrials.gov registration no. NCT04349514 Supplemental material is available for this article. © RSNA, 2025.

OBJECTIVE:We aimed to quantify differences in the brain and spinal cord between Friedreich ataxia and controls, stratified by age and disease stage, including for the first time in young children. METHODS:TRACK-FA is the largest prospective, longitudinal, multi-modal neuroimaging study in Friedreich ataxia to date. We assessed individuals with Friedreich ataxia and controls, 5 to 42 years, at 7 sites across 4 continents. The 17 imaging primary outcome measures (POMs) were selected from metrics that showed a significant longitudinal change in previous small-scale studies. These included brain and spinal cord morphometry (structural magnetic resonance imaging [MRI]) and microstructure (diffusion MRI); brain iron levels (quantitative susceptibility mapping); and spinal cord biochemistry (magnetic resonance spectroscopy). This study is registered with ClinicalTrials.gov (NCT04349514). RESULTS:Between February 2021 and August 2023, we assessed 169 individuals with Friedreich ataxia and 95 controls. Compared to controls, individuals with Friedreich ataxia had lower volume of dentate nucleus and superior cerebellar peduncles; smaller cross-sectional area of spinal cord; lower fractional anisotropy and higher diffusivity in spinal cord and superior cerebellar peduncles; and lower total N-acetyl-aspartate/myo-inositol ratio in spinal cord. Morphometric differences in spinal cord and superior cerebellar peduncles increased dramatically with age during childhood, with rapid development in controls, but not in Friedreich ataxia. Many imaging POMs showed significant associations with clinical severity. INTERPRETATION:Our findings provide strong imaging evidence of impaired development of spinal cord and superior cerebellar peduncles during childhood in Friedreich ataxia and open the way for the use of neuroimaging biomarkers in clinical trials. ANN NEUROL 2025;98:386-397.

Background: Clinical trials for upcoming disease-modifying therapies of spinocerebellar ataxias (SCA), a group of rare movement disorders, lack endpoints sensitive to early disease progression, when therapeutics will be most effective. In addition, regulatory agencies emphasize the importance of biological outcomes. Objectives: READISCA, a transatlantic clinical trial readiness consortium, investigated whether advanced multimodal magnetic resonance imaging (MRI) detects pathology progression over 6 months in preataxic and early ataxic carriers of SCA mutations. Methods: A total of 44 participants (10 SCA1, 25 SCA3, and 9 controls) prospectively underwent 3-T MR scanning at baseline and a median [interquartile range] follow-up of 6.2 [5.9-6.7] months; 44% of SCA participants were preataxic. Blinded analyses of annual changes in structural, diffusion MRI, MR spectroscopy, and the Scale for Assessment and Rating of Ataxia (SARA) were compared between groups using nonparametric testing. Sample sizes were estimated for 6-month interventional trials with 50% to 100% treatment effect size, leveraging existing large cohort data (186 SCA1, 272 SCA3) for the SARA estimate. Results: Rate of change in microstructural integrity (decrease in fractional anisotropy, increase in diffusivities) in the middle cerebellar peduncle, corona radiata, and superior longitudinal fasciculus significantly differed in SCAs from controls (P < 0.005), with high effect sizes (Cohen's d = 1-2) and moderate-to-high responsiveness (|standardized response mean| = 0.6-0.9) in SCAs. SARA scores did not change, and their rate of change did not differ between groups. Conclusions: Diffusion MRI is sensitive to disease progression at very early-stage SCA1 and SCA3 and may provide a >5-fold reduction in sample sizes relative to SARA as endpoint for 6-month-long trials. (c) 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Spinocerebellar ataxias are rare inherited neurodegenerative diseases that cause degeneration in the cerebellum and brainstem. The multi-site READISCA clinical trial readiness study aims to validate MR biomarkers at early stages of SCA1 and SCA3. SCA gene carriers (including individuals at pre-ataxic and ataxic stage) and matched controls (total N=107) were scanned at 3T to obtain structural and diffusion MRI and MR spectroscopy. Medulla, pons, and cerebellar peduncles were the earliest sites of involvement in both SCAs. Neurochemical and microstructural abnormalities were detected with very high sensitivity (AUC>0.9 in ROC analyses) prior to ataxia onset.

A custom segmentation workflow was applied to ex vivo high-field MR images of rat brains acquired following in vivo intraventricular contrast agent infusion to generate maps of the perivascular spaces (PVS). The resulting perivascular network segmentations enabled analysis of perivascular connections to the ventricles, parenchymal solute clearance, and dispersive solute transport within PVS. Numerous perivascular connections between the brain surface and the ventricles suggest the ventricles integrate into a PVS-mediated clearance system and raise the possibility of cerebrospinal fluid (CSF) return from the subarachnoid space to the ventricles via PVS. Assuming rapid solute exchange between the PVS and CSF spaces primarily by advection, the extensive perivascular network decreased the mean clearance distance from parenchyma to the nearest CSF compartment resulting in an over 21-fold reduction in the estimated diffusive clearance time scale, irrespective of solute diffusivity. This corresponds to an estimated diffusive clearance time scale under 10 min for amyloid-beta which suggests that the widespread distribution of PVS may render diffusion an effective parenchymal clearance mechanism. Additional analysis of oscillatory solute dispersion within PVS indicates that advection rather than dispersion is likely the primary transport mechanism for dissolved compounds greater than 66 kDa in the long (> 2 mm) perivascular segments identified here, although dispersion may be significant for smaller compounds in shorter perivascular segments.

Background: Recent research shows that older adults electing to undergo total knee arthroplasty with general anesthesia have a pre- to postoperative acute increase in molecular free-water within their cerebral white matter. It is unknown if this change is similar for individuals who elect spinal anesthesia methods. Objective: To explore white matter microstructural changes in a pilot sample of older adults undergoing total knee arthroplasty and receiving general or spinal anesthesia. Methods: We assessed acute perioperative changes in brain white matter free-water in a limited number of older adults electing total knee arthroplasty under spinal anesthesia (n = 5) and matched groups of older adults who received general anesthesia (n = 5) or had no surgery (n = 5). Patterns of free-water changes were also compared in the larger group of older adults electing total knee arthroplasty under general anesthesia (n = 61) and older adults with chronic knee pain who received no surgical intervention (n = 65). Results: Our pilot results suggest older adults receiving general anesthesia had pre- to post-surgery free-water increases extensively throughout their white matter whereas those receiving spinal anesthesia appeared to have less consistent free-water increases. Conclusions: Our pilot results possibly suggest different patterns of perioperative brain white matter free-water changes based on anesthetic approach. We recommend future, larger studies to further examine the effects of anesthetic approach on perioperative brain free-water. The results of our study have potential implications for acute and chronic cognitive changes, perioperative complications, neurodegenerative processes including Alzheimer’s disease, and understanding neuroinflammation.

Objective: Individuals with Parkinson's disease (PD) have varying trajectories of cognitive decline. One reason for this heterogeneity may be "cognitive reserve": where higher education/IQ/current mental engagement compensates for increasing brain burden (Stern et al., 2020). With few exceptions, most studies examining cognitive reserve in PD fail to include brain metrics. This study's goal was to examine whether cognitive reserve moderated the relationship between neuroimaging indices of brain burden (diffusion free water fraction and T2-weighted white matter changes) and two commonly impaired domains in PD: executive function and memory. We hypothesized cognitive reserve would mitigate the relationship between higher brain burden and worse cognitive performance. Participants and Methods: Participants included 108 individuals with PD without dementia (age mean=67.9±6.3, education mean=16.6±2.5) who were prospectively recruited for two NIH-funded projects at the University of Florida. All received neuropsychological measures of executive function (Trails B, Stroop, Letter Fluency) and memory (delayed recall: Hopkin's Verbal Learning Test-Revised, WMS-III Logical Memory). Domain specific z-score composites were created using data from age/education matched non-PD peer controls (N=62). For the Cognitive Reserve (CR) proxy, a z-score composite included years of education, WASI-II Vocabulary, and Wechsler Test of Adult Reading. At the time of testing, participants completed multiple MRI scans (T1-weighted, diffusion, Fluid Attenuated Inversion Recovery) from which the following were extracted: 1) whole-brain free water within the white matter (a measure of microstructural integrity and neuroinflammation), 2) white matter hyperintensities/white matter total volume (WMH/WMV), and bilaterally-averaged edge weights of white matter connectivity between 3) dorsolateral prefrontal cortex and caudate and 4) entorhinal cortex and hippocampi. Separate linear regressions for each brain metric used executive function and memory composites as dependent variables; predictors were age, CR proxy, respective brain metric, and a residual centered interaction term (brain metric*CR proxy). Identical models were run in dichotomized short and long disease duration groups (median split=6 years). Results: In all models, a lower CR proxy significantly predicted worse executive function (WMH/WMV: beta=0.49, free water: beta=0.54, frontal edge weight: beta=0.49, p's<0.001) and memory (WMH/WMV: beta=0.42, free water: beta=0.35, temporal edge weight: beta=0.39, p's <0.01). For neuroimaging metrics, higher free water significantly predicted worse executive function (beta=-0.39, p=0.002) but not memory. No other brain metrics were significant predictors of either domain. Accounting for PD duration, higher free water predicted worse executive function for those with both short (beta=-0.49, p=0.04) and long disease duration (beta=-0.48, p=0.02). Specifically in those with long disease duration, higher free water (beta=-0.57 p=0.02) and lower edge weights between entorhinal cortex and hippocampi (beta=0.30, p=0.03) predicted worse memory. Overall, no models contained significant interactions between the CR proxy and any brain metric. Conclusions: Results replicate previous work showing that a cognitive reserve proxy relates to cognition. However, cognitive reserve did not moderate brain burden's relationship to cognition. Across the sample, greater neuroinflammation was associated with worse executive function. For those with longer disease duration, higher neuroinflammation and lower medial temporal white matter connectivity related to worse memory. Future work should examine other brain burden metrics to determine whether/how cognitive reserve influences the cognitive trajectory of PD.

IntroductionDrug development for neurodegenerative diseases such as Friedreich's ataxia (FRDA) is limited by a lack of validated, sensitive biomarkers of pharmacodynamic response in affected tissue and disease progression. Studies employing neuroimaging measures to track FRDA have thus far been limited by their small sample sizes and limited follow up. TRACK-FA, a longitudinal, multi-site, and multi-modal neuroimaging natural history study, aims to address these shortcomings by enabling better understanding of underlying pathology and identifying sensitive, clinical trial ready, neuroimaging biomarkers for FRDA.Methods200 individuals with FRDA and 104 control participants will be recruited across seven international study sites. Inclusion criteria for participants with genetically confirmed FRDA involves, age of disease onset ≤ 25 years, Friedreich's Ataxia Rating Scale (FARS) functional staging score of ≤ 5, and a total modified FARS (mFARS) score of ≤ 65 upon enrolment. The control cohort is matched to the FRDA cohort for age, sex, handedness, and years of education. Participants will be evaluated at three study visits over two years. Each visit comprises of a harmonized multimodal Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) scan of the brain and spinal cord; clinical, cognitive, mood and speech assessments and collection of a blood sample. Primary outcome measures, informed by previous neuroimaging studies, include measures of: spinal cord and brain morphometry, spinal cord and brain microstructure (measured using diffusion MRI), brain iron accumulation (using Quantitative Susceptibility Mapping) and spinal cord biochemistry (using MRS). Secondary and exploratory outcome measures include clinical, cognitive assessments and blood biomarkers.DiscussionPrioritising immediate areas of need, TRACK-FA aims to deliver a set of sensitive, clinical trial-ready neuroimaging biomarkers to accelerate drug discovery efforts and better understand disease trajectory. Once validated, these potential pharmacodynamic biomarkers can be used to measure the efficacy of new therapeutics in forestalling disease progression.Clinical trial registrationClinicalTrails.gov Identifier: NCT04349514.

Objective This study was undertaken to identify magnetic resonance (MR) metrics that are most sensitive to early changes in the brain in spinocerebellar ataxia type 1 (SCA1) and type 3 (SCA3) using an advanced multimodal MR imaging (MRI) protocol in the multisite trial setting. Methods SCA1 or SCA3 mutation carriers and controls (n = 107) underwent MR scanning in the US‐European READISCA study to obtain structural, diffusion MRI, and MR spectroscopy data using an advanced protocol at 3T. Morphometric, microstructural, and neurochemical metrics were analyzed blinded to diagnosis and compared between preataxic SCA (n = 11 SCA1, n = 28 SCA3), ataxic SCA (n = 14 SCA1, n = 37 SCA3), and control (n = 17) groups using nonparametric testing accounting for multiple comparisons. MR metrics that were most sensitive to preataxic abnormalities were identified using receiver operating characteristic (ROC) analyses. Results Atrophy and microstructural damage in the brainstem and cerebellar peduncles and neurochemical abnormalities in the pons were prominent in both preataxic groups, when patients did not differ from controls clinically. MR metrics were strongly associated with ataxia symptoms, activities of daily living, and estimated ataxia duration. A neurochemical measure was the most sensitive metric to preataxic changes in SCA1 (ROC area under the curve [AUC] = 0.95), and a microstructural metric was the most sensitive metric to preataxic changes in SCA3 (AUC = 0.92). Interpretation Changes in cerebellar afferent and efferent pathways underlie the earliest symptoms of both SCAs. MR metrics collected with a harmonized advanced protocol in the multisite trial setting allow detection of disease effects in individuals before ataxia onset with potential clinical trial utility for subject stratification. ANN NEUROL 2023;93:686–701

INTRODUCTION:Free water fraction (FWF) is considered a metric of microstructural integrity and may be useful in predicting cognitive decline in idiopathic Parkinson's Disease (PD). We sought to determine if higher FWF within the dorsal portion of the caudate nucleus and basal nucleus of Meynert, two regions associated with cognitive decline in PD, predict change in cognition over a two-year span. Due to the existence of cognitive and neurophysiological subgroups within PD, we statistically categorized participants based on FWF in these regions.METHODS:At baseline, participants completed a research cognitive protocol followed by MRI structural and diffusion metrics. We used k-means cluster analysis with average FWF values from bilateral basal nucleus of Meynert and dorsal caudate to create data-driven FWF clusters for baseline. Two-year reliable change indices were calculated for metrics of language, visuospatial, memory, cognitive flexibility, and reasoning domains. Reliable change scores were compared between the clusters and non-PD peers.RESULTS:Baseline participants included 174 participants (112 PD, 62 non-PD). Cluster analysis yielded three clusters: low FWF in both regions of interest (ROIs), high FWF in both ROIs, and moderate FWF in both ROIs. Reliable change analyses were completed on 93 participants (67 PD, 26 non-PD). After controlling for age and education, the High FWF cluster declined more than non-PD peers in every domain except memory.CONCLUSION:Individuals with high FWF in regions associated with cognitive decline in PD show significant decline across several cognitive domains compared to non-PD peers. Future research should include FWF in additional cortical regions.

Background: Greater brain network integrity may associate with physically active lifestyles. Three resting state networks may provide unique insights into known physical activity-mediated brain health benefits: the default mode network (involved with self-monitoring), the salience network (involved in orienting oneself to salient external and internal stimuli), and the central executive network (responsible for higher level cognitive task). The current study explored relationships between system-wide neural network integrity measured by functional magnetic resonance imaging and objectively-measured physical activity. We hypothesize connectivity patterns as measured by fMRI networks will relate to actigraphy markers such that 1) there will be higher connectivity within the central executive network in more physically active individuals, and 2) there will be higher connectivity within the default mode network and salience network in those with higher levels of physical activity. Methods: Eighteen non-demented older adults with orthopedic pain (age 67.11 +/- 5.61, 50% female, education 15.94 +/- 2.51 years) completed brain magnetic resonance imaging, and wore an actigraphy device to objectively measure types of physical and sedentary engagement. Results: Results showed a negative relationship between central executive network connectivity and sedentary time (13 =-0.108, p = .039), and a positive relationship with both moderate-to-vigorous physical activity (13 = 0.629, p = .029) and total activity time (13 = 0.645, p = .039). Results also showed positive relationships for the default mode network (13 = 0.588, p = .033) and the salience network (13 = 0.608, p = .037) with mean cadence (i.e. steps per minute). Conclusions: Our work adds to the existing literature on specific types of activity measurement (i.e. sedentary time, cadence and moderate-to-vigorous physical activity) which will be useful for interventions aimed at improving the integrity of underlying neural networks.

Background: Some individuals with Parkinson’s disease (PD) experience working memory and inhibitory difficulties, others learning and memory difficulties, while some only minimal to no cognitive deficits for many years. Objective: To statistically derive PD executive and memory phenotypes, and compare PD phenotypes on disease and demographic variables, vascular risk factors, and specific neuroimaging variables with known associations to executive and memory function relative to non-PD peers. Methods: Non-demented individuals with PD (n = 116) and non-PD peers (n = 62) were recruited to complete neuropsychology measures, blood draw, and structural magnetic resonance imaging. Tests representing the cognitive domains of interest (4 executive function, 3 memory) were included in a k-means cluster analysis comprised of the PD participants. Resulting clusters were compared demographic and disease-related variables, vascular risk markers, gray/white regions of interest, and white matter connectivity between known regions involved in executive and memory functions (dorsolateral prefrontal cortices to caudate nuclei; entorhinal cortices to hippocampi). Results: Clusters showed: 1) PD Executive, n = 25; 2) PD Memory, n = 35; 3) PD Cognitively Well; n = 56. Even after disease variable corrections, PD Executive had less subcortical gray matter, white matter, and fewer bilateral dorsolateral-prefrontal cortex to caudate nucleus connections; PD Memory showed bilaterally reduced entorhinal-hippocampal connections. PD Cognitively Well showed only reduced putamen volume and right entorhinal cortex to hippocampi connections relative to non-PD peers. Groups did not statistically differ on cortical integrity measures or cerebrovascular disease markers. Conclusion: PD cognitive phenotypes showed different structural gray and white matter patterns. We discuss data relative to phenotype demographics, cognitive patterns, and structural brain profiles.

Diffusion MRI (dMRI) has been able to detect early structural changes related to neurological symptoms present in Huntington's disease (HD). However, there is still a knowledge gap to interpret the biological significance at early neuropathological stages. The purpose of this study is two-fold: (i) establish if the combination of Ultra-High Field Diffusion MRI (UHFD-MRI) techniques can add a more comprehensive analysis of the early microstructural changes observed in HD, and (ii) evaluate if early changes in dMRI microstructural parameters can be linked to cellular biomarkers of neuroinflammation. Ultra-high field magnet (16.7T), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) techniques were applied to fixed ex-vivo brains of a preclinical model of HD (R6/1 mice). Fractional anisotropy (FA) was decreased in deep and superficial grey matter (GM) as well as white matter (WM) brain regions with well-known early HD microstructure and connectivity pathology. NODDI parameters associated with the intracellular and extracellular compartment, such as intracellular ventricular fraction (ICVF), orientation dispersion index (ODI), and isotropic volume fractions (IsoVF) were altered in R6/1 mice GM. Further, histological studies in these areas showed that glia cell markers associated with neuroinflammation (GFAP & Iba1) were consistent with the dMRI findings. dMRI can be used to extract non-invasive information of neuropathological events present in the early stages of HD. The combination of multiple imaging techniques represents a better approach to understand the neuropathological process allowing the early diagnosis and neuromonitoring of patients affected by HD.

To determine whether deuterated water (HDO) generated from the metabolism of [2H7]glucose is a sensitive biomarker of cerebral glycolysis and oxidative flux.

Respiratory insufficiency is a leading cause of death due to drug overdose or neuromuscular disease. We hypothesized that a stimulation paradigm using temporal interference (TI) could restore breathing in such conditions. Following opioid overdose in rats, two high frequency (5000 Hz and 5001 Hz), low amplitude waveforms delivered via intramuscular wires in the neck immediately activated the diaphragm and restored ventilation in phase with waveform offset (1 Hz or 60 breaths/min). Following cervical spinal cord injury (SCI), TI stimulation via dorsally placed epidural electrodes uni- or bilaterally activated the diaphragm depending on current and electrode position. In silico modeling indicated that an interferential signal in the ventral spinal cord predicted the evoked response (left versus right diaphragm) and current-ratio-based steering. We conclude that TI stimulation can activate spinal motor neurons after SCI and prevent fatal apnea during drug overdose by restoring ventilation with minimally invasive electrodes.

Switching gradients generate eddy currents and mechanical vibrations of the gradient assembly causing errors in the gradient time integrals. This results in image distortions in k-space and inaccuracies in q-space imaging. The purpose of this work is to develop an MRI based unbiased measurement of the switched gradient impulse response function (sGIRF). A new gradient pattern, called the Tukey windowed Shifted Sine-Integral (Tw-SSI) pulse, is introduced to excite the gradient eigenmodes uniformly over a user-defined bandwidth. A 3D MRI-based method with Hadamard encoding was developed to map the spatiotemporal magnetic field generated after the excitation pulse to obtain the sGIRF for all the three gradient axes simultaneously. Compared to an energy-equivalent traditional trapezoidal pulse, the Tw-SSI pulse is able to excite the weak bandlimited cross-terms of the sGIRF by uniformly distributing the energy across eigenmodes. The developed field mapping method is sensitive enough to capture both the direct and cross-terms in the sGIRF. The various mechanical resonant modes of the gradient coils are also revealed, which were found to last longer than eddy currents in the shielded gradient coil studied. Tunable Tw-SSI pulse offers the flexibility to perform unbiased sGIRF measurements over a bandwidth of interest. Rapid MRI field mapping can be easily implemented in any MRI system. The method may be used to perform gradient pre-emphasis, to evaluate new gradient coil designs, and to characterize higher order shims.