Fast magnetization transfer saturation imaging of the brain using MP2RAGE T1 mapping.

PURPOSE: Magnetization transfer saturation (MTsat) mapping is commonly used to examine the macromolecular content of brain tissue. This study compared variable flip angle (VFA) T1 mapping against compressed-sensing MP2RAGE (csMP2RAGE) T1 mapping for accelerating MTsat imaging. METHODS: VFA, MP2RAGE, and csMP2RAGE were compared against inversion-recovery T1 in an aqueous phantom at 3 T. The same 1-mm VFA, MP2RAGE, and csMP2RAGE protocols were acquired in 4 healthy subjects to compare T1 and MTsat. Bloch-McConnell simulations were used to investigate differences between the phantom and in vivo T1 results. Ten healthy controls were imaged twice with the csMP2RAGE MTsat protocol to quantify repeatability. RESULTS: The MP2RAGE and csMP2RAGE protocols were 13.7% and 32.4% faster than the VFA protocol, respectively. At these scan times, all approaches provided strong repeatability and accurate T1 times (< 5% difference) in the phantom, but T1 accuracy was more impacted by T2 for VFA than for MP2RAGE. In vivo, VFA estimated longer T1 times than MP2RAGE and csMP2RAGE. Simulations suggest that the differences in the T1 measured using VFA, MP2RAGE, and inversion recovery could be explained by the magnetization-transfer effects. In the test-retest experiment, we found that the csMP2RAGE has a minimum detectable change of 2.3% for T1 mapping and 7.8% for MTsat imaging. CONCLUSIONS: We demonstrated that MP2RAGE can be used in place of VFA T1 mapping in an MTsat protocol. Furthermore, a shorter scan time and high repeatability can be achieved using the csMP2RAGE sequence.

An intraoperative accelerometry and real-time analysis tool for magnetic resonance-guided focused ultrasound thalamotomy.

Magnetic resonance-guided focused ultrasound (MRgFUS) is one of the newest surgical treatments for essential tremor (ET). During this procedure, a lesion is created within the thalamus to mitigate tremor. Targeting is done using a combination of stereotaxy, MR tractography, and sublesional heating, with tremor assessed during the procedure to gauge therapeutic effectiveness. Currently, tremor assessments are done qualitatively, but this approach requires the tremor change to be above a subjective threshold and provides no objective record of surgical tremor progression. Here, the authors present and demonstrate an MR-compatible accelerometer with custom MATLAB analysis code and graphical user interface to record, visualize, and quantify tremor in near real-time. Results can be exported and saved for future review. This method was used in 20 surgeries, with patients experiencing a 50.7% (95% CI -64.1% to -37.3%) improvement in the treated limb per the Clinical Rating Scale for Tremor. This method does not interrupt the surgery and is quantitative. As research on optimizing MRgFUS treatment for ET continues-for example, the refinement of targeting during sublesional sonications-such quantifying and recording of tremor changes will provide rapid and objective feedback.

The effect of transcranial ultrasound pulse repetition frequency on sustained inhibition in the human primary motor cortex: A double-blind, sham-controlled study.

BACKGROUND: Non-invasive brain stimulation techniques such as transcranial magnetic stimulation and transcranial direct current stimulation hold promise for inducing brain plasticity. However, their limited precision may hamper certain applications. In contrast, Transcranial Ultrasound Stimulation (TUS), known for its precision and deep brain targeting capabilities, requires further investigation to establish its efficacy in producing enduring effects for treating neurological and psychiatric disorders. OBJECTIVE: To investigate the enduring effects of different pulse repetition frequencies (PRF) of TUS on motor corticospinal excitability. METHODS: T1-, T2-weighted, and zero echo time magnetic resonance imaging scans were acquired from 21 neurologically healthy participants for neuronavigation, skull reconstruction, and the performance of transcranial ultrasound and thermal modelling. The effects of three different TUS PRFs (10, 100, and 1000 Hz) with a constant duty cycle of 10 % on corticospinal excitability in the primary motor cortex were assessed using TMS-induced motor evoked potentials (MEPs). Each PRF and sham condition was evaluated on separate days, with measurements taken 5-, 30-, and 60-min post-TUS. RESULTS: A significant decrease in MEP amplitude was observed with a PRF of 10 Hz (p = 0.007), which persisted for at least 30 min, and with a PRF of 100 Hz (p = 0.001), lasting over 60 min. However, no significant changes were found for the PRF of 1000 Hz and the sham conditions. CONCLUSION: This study highlights the significance of PRF selection in TUS and underscores its potential as a non-invasive approach to reduce corticospinal excitability, offering valuable insights for future clinical applications.

Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks.

Quantitative susceptibility mapping (QSM) is a post-processing technique for deriving tissue magnetic susceptibility distribution from MRI phase measurements. Deep learning (DL) algorithms hold great potential for solving the ill-posed QSM reconstruction problem. However, a significant challenge facing current DL-QSM approaches is their limited adaptability to magnetic dipole field orientation variations during training and testing. In this work, we propose a novel Orientation-Adaptive Latent Feature Editing (OA-LFE) module to learn the encoding of acquisition orientation vectors and seamlessly integrate them into the latent features of deep networks. Importantly, it can be directly Plug-and-Play (PnP) into various existing DL-QSM architectures, enabling reconstructions of QSM from arbitrary magnetic dipole orientations. Its effectiveness is demonstrated by combining the OA-LFE module into our previously proposed phase-to-susceptibility single-step instant QSM (iQSM) network, which was initially tailored for pure-axial acquisitions. The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a simulated-supervised manner on a specially-designed simulation brain dataset. Comprehensive experiments are conducted on simulated and in vivo human brain datasets, encompassing subjects ranging from healthy individuals to those with pathological conditions. These experiments involve various MRI platforms (3T and 7T) and aim to compare our proposed iQSM+ against several established QSM reconstruction frameworks, including the original iQSM. The iQSM+ yields QSM images with significantly improved accuracies and mitigates artifacts, surpassing other state-of-the-art DL-QSM algorithms. The PnP OA-LFE module's versatility was further demonstrated by its successful application to xQSM, a distinct DL-QSM network for dipole inversion. In conclusion, this work introduces a new DL paradigm, allowing researchers to develop innovative QSM methods without requiring a complete overhaul of their existing architectures.

Feasibility study to assess lesion repair in relapsing-remitting multiple sclerosis: A randomized controlled pilot clinical trial of domperidone add-on treatment.

BACKGROUND: Identification of therapies to promote repair in multiple sclerosis is challenged by the lack of an accepted trial model and associated outcome measures. The goal of this study was to determine the feasibility of a new trial model that enrolls disease modifying therapy (DMT)-treated relapsing-remitting multiple sclerosis (RRMS) participants who have enhancing lesions on clinically indicated brain MRI, and to explore estimates of lesion repair using MRI. METHODS: This was a single site randomized controlled clinical trial. Recruitment took place between November 2015 and January 2019, with final follow-up in February 2019. DMT-treated RRMS participants aged 18-60 years with at least one gadolinium-enhancing lesion on clinically indicated brain MRI were included. Participants were randomized 2:1 to oral domperidone add-on 10-mg three times daily for 16 weeks or no add-on treatment (control). The primary outcomes were feasibility of the model pre-defined as recruitment of 24 participants within 36 months with a 79 % completion rate, and MRI outcomes of lesion repair measured at 16 and 32 weeks using texture analysis, magnetization transfer imaging (MTI), and diffusion tensor imaging (DTI). The impact of domperidone on serum prolactin at 6 and 16 weeks was also evaluated. RESULTS: Of 237 RRMS participants screened, 17 (14 women) were randomized: 12 to domperidone add-on and 5 to control. All completed the study. Median (range) age was 38.9 (26.7-55.9) years; EDSS was 1.5 (1.0-3.5); and disease duration was 12.9 (2.9-23.3) years. Both groups showed improvement in MRI texture and diffusion fractional anisotropy (FA) at 32 weeks, and the domperidone group demonstrated additional recovery at 16 weeks in both texture and FA. There was no significant group difference in any MRI outcome. Of the 12 domperidone participants, 7 had ≥4x higher serum prolactin than normal. There were no serious adverse events. CONCLUSION: The recruitment target was not met and therefore the trial model was not feasible despite a full completion rate. The imaging techniques performed well, especially MRI texture analysis, suggesting the sample size being sufficient for estimating lesion repair. The main challenge of this trial model may be recruiting gadolinium-enhancing lesions in DMT-treated RRMS participants. Prolactin is safe and may hold promise as a remyelination therapy. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02493049.

The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts.

A central goal in neuroscience is the development of a comprehensive mapping between structural and functional brain features, which facilitates mechanistic interpretation of brain function. However, the interpretability of structure-function brain models remains limited by a lack of biological detail. Here, we characterize human structural brain networks weighted by multiple white matter microstructural features including total intra-axonal cross-sectional area and myelin content. We report edge-weight-dependent spatial distributions, variance, small-worldness, rich club, hubs, as well as relationships with function, edge length, and myelin. Contrasting networks weighted by the total intra-axonal cross-sectional area and myelin content of white matter tracts, we find opposite relationships with functional connectivity, an edge-length-independent inverse relationship with each other, and the lack of a canonical rich club in myelin-weighted networks. When controlling for edge length, networks weighted by either fractional anisotropy, radial diffusivity, or neurite density show no relationship with whole-brain functional connectivity. We conclude that the co-utilization of structural networks weighted by total intra-axonal cross-sectional area and myelin content could improve our understanding of the mechanisms mediating the structure-function brain relationship.

Persistence of neuropsychiatric symptoms and dementia prognostication: A comparison of three operational case definitions of mild behavioral impairment.

INTRODUCTION: We compared three operational case definitions of mild behavioral impairment (MBI) in the context of MBI prevalence estimates and dementia risk modeling. METHODS: Participants were dementia-free older adults (n = 13701) from the National Alzheimer's Coordinating Center. Operational case definitions of MBI were generated based on neuropsychiatric symptoms at one (OV), two-consecutive (TCV), or more than two-thirds (TTV) of dementia-free study visits. Definitions were compared in prevalence and in Cox regressions using MBI to predict incident dementia. RESULTS: OV MBI was the most prevalent (54.4%), followed by TCV (32.3%) and TTV (26.7%) MBI. However, OV MBI had the lowest rate of incident dementia (hazard ratio [HR] = 2.54, 95% confidence interval [CI]: 2.33-2.78) and generated poorer model metrics than TCV MBI (HR = 4.06, 95% CI: 3.74-4.40) and TTV MBI (HR = 5.77, 95% CI: 5.32-6.26). DISCUSSION: Case ascertainment with longer timeframe MBI operational case definitions may more accurately define groups at risk of dementia in datasets lacking tools designed to detect MBI.Highlights: Mild behavioral impairment (MBI) can identify older adults at risk of dementia.Neuropsychiatric symptom (NPS) assessment tools can be proxy measures for MBI.Hazard for dementia was highest for MBI defined by NPS presence at more than two-thirds of visits.

Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data.

OBJECTIVE: This work investigates if deep learning (DL) models can classify originating site locations directly from magnetic resonance imaging (MRI) scans with and without correction for intensity differences. MATERIAL AND METHODS: A large database of 1880 T1-weighted MRI scans collected across 41 sites originally for Parkinson's disease (PD) classification was used to classify sites in this study. Forty-six percent of the datasets are from PD patients, while 54% are from healthy participants. After preprocessing the T1-weighted scans, 2 additional data types were generated: intensity-harmonized T1-weighted scans and log-Jacobian deformation maps resulting from nonlinear atlas registration. Corresponding DL models were trained to classify sites for each data type. Additionally, logistic regression models were used to investigate the contribution of biological (age, sex, disease status) and non-biological (scanner type) variables to the models' decision. RESULTS: A comparison of the 3 different types of data revealed that DL models trained using T1-weighted and intensity-harmonized T1-weighted scans can classify sites with an accuracy of 85%, while the model using log-Jacobian deformation maps achieved a site classification accuracy of 54%. Disease status and scanner type were found to be significant confounders. DISCUSSION: Our results demonstrate that MRI scans encode relevant site-specific information that models could use as shortcuts that cannot be removed using simple intensity harmonization methods. CONCLUSION: The ability of DL models to exploit site-specific biases as shortcuts raises concerns about their reliability, generalization, and deployability in clinical settings.

Distinct characteristics and severity of brain magnetic resonance imaging lesions in women and men with multiple sclerosis assessed using verified texture analysis measures.

Background and goal: In vivo characterization of brain lesion types in multiple sclerosis (MS) has been an ongoing challenge. Based on verified texture analysis measures from clinical magnetic resonance imaging (MRI), this study aimed to develop a method to identify two extremes of brain MS lesions that were approximately severely demyelinated (sDEM) and highly remyelinated (hREM), and compare them in terms of common clinical variables. Method: Texture analysis used an optimized gray-level co-occurrence matrix (GLCM) method based on FLAIR MRI from 200 relapsing-remitting MS participants. Two top-performing metrics were calculated: texture contrast and dissimilarity. Lesion identification applied a percentile approach according to texture values calculated: ≤ 25 percentile for hREM and ≥75 percentile for sDEM. Results: The sDEM had a greater total normalized volume yet smaller average size, and worse MRI texture than hREM. In lesion distribution mapping, the two lesion types appeared to overlap largely in location and were present the most in the corpus callosum and periventricular regions. Further, in sDEM, the normalized volume was greater and in hREM, the average size was smaller in men than women. There were no other significant results in clinical variable-associated analyses. Conclusion: Percentile statistics of competitive MRI texture measures may be a promising method for probing select types of brain MS lesion pathology. Associated findings can provide another useful dimension for improved measurement and monitoring of disease activity in MS. The different characteristics of sDEM and hREM between men and women likely adds new information to the literature, deserving further confirmation.

Biaxial ultrasound driving technique for small animal blood-brain barrier opening.

Biaxial driving can more efficiently convert electrical power to forward acoustic power in piezoelectric materials, and the interaction between the orthogonal electric fields can produce a combination of extensional and shear deformations as a function of the phase difference between them to allow dynamic steering of the beam with a single-element. In this study, we demonstrate for the first time the application of a single-element biaxially driven ring transducerin vivofor blood-brain barrier opening in mice, and compare it to that achieved with a conventional single-element highly focused (F# = 0.7) spherical transducer operating at a similar frequency. Transcranial focused ultrasound (0.45 MPa, 10 ms pulse length, 1 Hz repetition frequency, 30 s duration) was applied bilaterally to mice with a 40µl/kg bolus of DefinityTMmicrobubbles, employing either a single-element biaxial ring (1.482 MHz, 10 mm inner diameter, 13.75 mm outer diameter) or spherical (1.5 MHz, 35 mm diameter, F# = 0.7; RK50, FUS Instruments) transducer on each side. Follow-up MRI scans (T1 pre- and post- 0.2 mmol/kg Gd injection, T2) were acquired to assess blood-brain barrier opening volume and potential damage. Compared to blood-brain barrier opening achieved with a conventional single-element spherical focused transducer, the opening volume achieved with a single-element biaxial ring transducer was 35% smaller (p= 0.002) with a device of a ring diameter of 40% the aperture size. Axial refocusing was further demonstrated with the single-element biaxial ring transducer, yielding a 1.63 mm deeper, five-fold larger opening volume (p= 0.048) relative to its small-focus mode. The biaxial ring transducer achieved a more localized opening compared to the spherical focused transducer under the same parameters, and further enabled dynamic axial refocusing with a single-element transducer with a smaller fabrication footprint.

Optimization of acquisition parameters for cortical inhomogeneous magnetization transfer (ihMT) imaging using a rapid gradient echo readout.

PURPOSE: Imaging biomarkers with increased myelin specificity are needed to better understand the complex progression of neurological disorders. Inhomogeneous magnetization transfer (ihMT) imaging is an emergent technique that has a high degree of specificity for myelin content but suffers from low signal to-noise ratio (SNR). This study used simulations to determine optimal sequence parameters for ihMT imaging for use in high-resolution cortical mapping. METHODS: MT-weighted cortical image intensity and ihMT SNR were simulated using modified Bloch equations for a range of sequence parameters. The acquisition time was limited to 4.5 min/volume. A custom MT-weighted RAGE sequence with center-out k-space encoding was used to enhance SNR at 3 T. Pulsed MT imaging was studied over a range of saturation parameters, and the impact of the turbo factor on the effective ihMT resolution was investigated. 1 mm isotropic ihMTsat maps were generated in 25 healthy adults. RESULTS: Greater SNR was observed for larger number of bursts consisting of 6-8 saturation pulses each, combined with a high readout turbo factor. However, that protocol suffered from a point spread function that was more than twice the nominal resolution. For high-resolution cortical imaging, we selected a protocol with a higher effective resolution at the cost of a lower SNR. We present the first group-average ihMTsat whole-brain map at 1 mm isotropic resolution. CONCLUSION: This study presents the impact of saturation and excitation parameters on ihMTsat SNR and resolution. We demonstrate the feasibility of high-resolution cortical myelin imaging using ihMTsat in less than 20 min.

Correspondence between BOLD fMRI task response and cerebrovascular reactivity across the cerebral cortex.

BOLD sensitivity to baseline perfusion and blood volume is a well-acknowledged fMRI confound. Vascular correction techniques based on cerebrovascular reactivity (CVR) might reduce variance due to baseline cerebral blood volume, however this is predicated on an invariant linear relationship between CVR and BOLD signal magnitude. Cognitive paradigms have relatively low signal, high variance and involve spatially heterogenous cortical regions; it is therefore unclear whether the BOLD response magnitude to complex paradigms can be predicted by CVR. The feasibility of predicting BOLD signal magnitude from CVR was explored in the present work across two experiments using different CVR approaches. The first utilized a large database containing breath-hold BOLD responses and 3 different cognitive tasks. The second experiment, in an independent sample, calculated CVR using the delivery of a fixed concentration of carbon dioxide and a different cognitive task. An atlas-based regression approach was implemented for both experiments to evaluate the shared variance between task-invoked BOLD responses and CVR across the cerebral cortex. Both experiments found significant relationships between CVR and task-based BOLD magnitude, with activation in the right cuneus (R 2 = 0.64) and paracentral gyrus (R 2 = 0.71), and the left pars opercularis (R 2 = 0.67), superior frontal gyrus (R 2 = 0.62) and inferior parietal cortex (R 2 = 0.63) strongly predicted by CVR. The parietal regions bilaterally were highly consistent, with linear regressions significant in these regions for all four tasks. Group analyses showed that CVR correction increased BOLD sensitivity. Overall, this work suggests that BOLD signal response magnitudes to cognitive tasks are predicted by CVR across different regions of the cerebral cortex, providing support for the use of correction based on baseline vascular physiology.

Subcortical volumes in cerebral amyloid angiopathy compared with Alzheimer's disease and controls.

Background: Previous reports have suggested that patients with cerebral amyloid angiopathy (CAA) may harbor smaller white matter, basal ganglia, and cerebellar volumes compared to age-matched healthy controls (HC) or patients with Alzheimer's disease (AD). We investigated whether CAA is associated with subcortical atrophy. Methods: The study was based on the multi-site Functional Assessment of Vascular Reactivity cohort and included 78 probable CAA (diagnosed according to the Boston criteria v2.0), 33 AD, and 70 HC. Cerebral and cerebellar volumes were extracted from brain 3D T1-weighted MRI using FreeSurfer (v6.0). Subcortical volumes, including total white matter, thalamus, basal ganglia, and cerebellum were reported as proportion (%) of estimated total intracranial volume. White matter integrity was quantified by the peak width of skeletonized mean diffusivity. Results: Participants in the CAA group were older (74.0 ± 7.0, female 44%) than the AD (69.7 ± 7.5, female 42%) and HC (68.8 ± 7.8, female 69%) groups. CAA participants had the highest white matter hyperintensity volume and worse white matter integrity of the three groups. After adjusting for age, sex, and study site, CAA participants had smaller putamen volumes (mean differences, -0.024% of intracranial volume; 95% confidence intervals, -0.041% to -0.006%; p = 0.005) than the HCs but not AD participants (-0.003%; -0.024 to 0.018%; p = 0.94). Other subcortical volumes including subcortical white matter, thalamus, caudate, globus pallidus, cerebellar cortex or cerebellar white matter were comparable between all three groups. Conclusion: In contrast to prior studies, we did not find substantial atrophy of subcortical volumes in CAA compared to AD or HCs, except for the putamen. Differences between studies may reflect heterogeneity in CAA presenting syndromes or severity.

A biologically informed polygenic score of neuronal plasticity moderates the association between cognitive aptitudes and cortical thickness in adolescents.

Although many studies of the adolescent brain identified positive associations between cognitive abilities and cortical thickness, little is known about mechanisms underlying such brain-behavior relationships. With experience-induced plasticity playing an important role in shaping the cerebral cortex throughout life, it is likely that some of the inter-individual variations in cortical thickness could be explained by genetic variations in relevant molecular processes, as indexed by a polygenic score of neuronal plasticity (PGS-NP). Here, we studied associations between PGS-NP, cognitive abilities, and thickness of the cerebral cortex, estimated from magnetic resonance images, in the Saguenay Youth Study (SYS, 533 females, 496 males: age=15.0 ± 1.8 years of age; cross-sectional), and the IMAGEN Study (566 females, 556 males; between 14 and 19 years; longitudinal). Using Gene Ontology, we first identified 199 genes implicated in neuronal plasticity, which mapped to 155,600 single nucleotide polymorphisms (SNPs). Second, we estimated their effect sizes from an educational attainment meta-GWAS to build a PGS-NP. Third, we examined a possible moderating role of PGS-NP in the relationship between performance intelligence quotient (PIQ), and its subtests, and the thickness of 34 cortical regions. In SYS, we observed a significant interaction between PGS-NP and object assembly vis-à-vis thickness in male adolescents (p = 0.026). A median-split analysis showed that, in males with a 'high' PGS-NP, stronger associations between object assembly and thickness were found in regions with larger age-related changes in thickness (r = 0.55, p = 0.00075). Although the interaction between PIQ and PGS-NP was non-significant (p = 0.064), we performed a similar median-split analysis. Again, in the high PGS-NP males, positive associations between PIQ and thickness were observed in regions with larger age-related changes in thickness (r = 0.40, p = 0.018). In the IMAGEN cohort, we did not replicate the first set of results (interaction between PGS-NP and cognitive abilities via-a-vis cortical thickness) while we did observe the same relationship between the brain-behaviour relationship and (longitudinal) changes in cortical thickness (Matrix reasoning: r = 0.63, p = 6.5e-05). No statistically significant results were observed in female adolescents in either cohort. Overall, these cross-sectional and longitudinal results suggest that molecular mechanisms involved in neuronal plasticity may contribute to inter-individual variations of cortical thickness related to cognitive abilities during adolescence in a sex-specific manner.

Limb Preference Changes after Focused-Ultrasound Thalamotomy for Tremor.

BACKGROUND: Magnetic resonance-guided focused-ultrasound (MRgFUS) thalamotomy is an effective treatment for essential and other tremors. It targets the ventrointermedius (Vim) nucleus, which is the thalamic relay in a proprioceptive pathway, and contains kinesthetic cells. Although MRgFUS thalamotomy reduces some risks associated with more invasive surgeries, it still has side effects, such as balance and gait disturbances; these may be caused by the lesion impacting proprioception. OBJECTIVES: Our aim was to quantitatively measure the effects of MRgFUS on proprioception and limb use in essential tremor patients. We hypothesized that this thalamotomy alters proprioception, because the sensorimotor Vim thalamus is lesioned. METHODS: Proprioception was measured using the Kinarm exoskeleton robot in 18 patients. Data were collected pre-operatively, and then 1 day, 3 months, and 1 year after surgery. Patients completed four tasks, assessing motor coordination and postural control, goal-directed movement and bimanual planning, position sense, and kinesthesia. RESULTS: Immediately after surgery there were changes in posture speed (indicating tremor improvement), and in bimanual hand use, with the untreated limb being preferred. However, these measures returned to pre-operative baseline over time. There were no changes in parameters related to proprioception. None of these measures correlated with lesion size or lesion-overlap with the dentato-rubro-thalamic tract. CONCLUSIONS: This is the first quantitative assessment of proprioception and limb preference following MRgFUS thalamotomy. Our results suggest that focused-ultrasound lesioning of the Vim thalamus does not degrade proprioception but alters limb preference. This change may indicate a required "relearning" in the treated limb, because the effect is transient. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

The Unresolved Methodological Challenge of Detecting Neuroplastic Changes in Astronauts.

After completing a spaceflight, astronauts display a salient upward shift in the position of the brain within the skull, accompanied by a redistribution of cerebrospinal fluid. Magnetic resonance imaging studies have also reported local changes in brain volume following a spaceflight, which have been cautiously interpreted as a neuroplastic response to spaceflight. Here, we provide evidence that the grey matter volume changes seen in astronauts following spaceflight are contaminated by preprocessing errors exacerbated by the upwards shift of the brain within the skull. While it is expected that an astronaut's brain undergoes some neuroplastic adaptations during spaceflight, our findings suggest that the brain volume changes detected using standard processing pipelines for neuroimaging analyses could be contaminated by errors in identifying different tissue types (i.e., tissue segmentation). These errors may undermine the interpretation of such analyses as direct evidence of neuroplastic adaptation, and novel or alternate preprocessing or experimental paradigms are needed in order to resolve this important issue in space health research.

Reproducibility of cerebellar involvement as quantified by consensus structural MRI biomarkers in advanced essential tremor.

Essential tremor (ET) is the most prevalent movement disorder with poorly understood etiology. Some neuroimaging studies report cerebellar involvement whereas others do not. This discrepancy may stem from underpowered studies, differences in statistical modeling or variation in magnetic resonance imaging (MRI) acquisition and processing. To resolve this, we investigated the cerebellar structural differences using a local advanced ET dataset augmented by matched controls from PPMI and ADNI. We tested the hypothesis of cerebellar involvement using three neuroimaging biomarkers: VBM, gray/white matter volumetry and lobular volumetry. Furthermore, we assessed the impacts of statistical models and segmentation pipelines on results. Results indicate that the detected cerebellar structural changes vary with methodology. Significant reduction of right cerebellar gray matter and increase of the left cerebellar white matter were the only two biomarkers consistently identified by multiple methods. Results also show substantial volumetric overestimation from SUIT-based segmentation-partially explaining previous literature discrepancies. This study suggests that current estimation of cerebellar involvement in ET may be overemphasized in MRI studies and highlights the importance of methods sensitivity analysis on results interpretation. ET datasets with large sample size and replication studies are required to improve our understanding of regional specificity of cerebellum involvement in ET. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 21 March 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.19697776 .

Direct machine learning reconstruction of respiratory variation waveforms from resting state fMRI data in a pediatric population.

In many functional magnetic resonance imaging (fMRI) studies, respiratory signals are unavailable or do not have acceptable quality due to issues with subject compliance, equipment failure or signal error. In large databases, such as the Human Connectome Projects, over half of the respiratory recordings may be unusable. As a result, the direct removal of low frequency respiratory variations from the blood oxygen level-dependent (BOLD) signal time series is not possible. This study proposes a deep learning-based method for reconstruction of respiratory variation (RV) waveforms directly from BOLD fMRI data in pediatric participants (aged 5 to 21 years old), and does not require any respiratory measurement device. To do this, the Lifespan Human Connectome Project in Development (HCP-D) dataset, which includes respiratory measurements, was used to both train a convolutional neural network (CNN) and evaluate its performance. Results show that a CNN can capture informative features from the BOLD signal time course and reconstruct accurate RV timeseries, especially when the subject has a prominent respiratory event. This work advances the use of direct estimation of physiological parameters from fMRI, which will eventually lead to reduced complexity and decrease the burden on participants because they may not be required to wear a respiratory bellows.

Detecting monocyte trafficking in an animal model of glioblastoma using R2* and quantitative susceptibility mapping.

BACKGROUND: The role of tumor-associated macrophages (TAMs) in glioblastoma (GBM) disease progression has received increasing attention. Recent advances have shown that TAMs can be re-programmed to exert a pro-inflammatory, anti-tumor effect to control GBMs. However, imaging methods capable of differentiating tumor progression from immunotherapy treatment effects have been lacking, making timely assessment of treatment response difficult. We showed that tracking monocytes using iron oxide nanoparticle (USPIO) with MRI can be a sensitive imaging method to detect therapy response directed at the innate immune system. METHODS: We implanted syngeneic mouse glioma stem cells into C57/BL6 mice and treated the animals with either niacin (a stimulator of innate immunity) or vehicle. Animals were imaged using an anatomical MRI sequence, R2* mapping, and quantitative susceptibility mapping (QSM) before and after USPIO injection. RESULTS: Compared to vehicles, niacin-treated animals showed significantly higher susceptibility and R2*, representing USPIO and monocyte infiltration into the tumor. We observed a significant reduction in tumor size in the niacin-treated group 7 days later. We validated our MRI results with flow cytometry and immunofluoresence, which showed that niacin decreased pro-inflammatory Ly6C high monocytes in the blood but increased CD16/32 pro-inflammatory macrophages within the tumor, consistent with migration of these pro-inflammatory innate immune cells from the blood to the tumor. CONCLUSION: MRI with USPIO injection can detect therapeutic responses of innate immune stimulating agents before changes in tumor size have occurred, providing a potential complementary imaging technique to monitor cancer immunotherapies. MANUSCRIPT HIGHLIGHT: We show that iron oxide nanoparticles (USPIOs) can be used to label innate immune cells and detect the trafficking of pro-inflammatory monocytes into the glioblastoma. This preceded changes in tumor size, making it a more sensitive imaging technique.