High Resolution Diffusion MRI Research Articles

High-resolution diffusion MRI of the cortico-cortical connections between lower visual areas reveals divergence of connections and enhanced connectivity of the central visual field representation

High-resolution diffusion MRI of the cortico-cortical connections between lower visual areas reveals divergence of connections and enhanced connectivity of the central visual field representation

Translation of monosynaptic circuits underlying amygdala fMRI neurofeedback training.

fMRI neurofeedback using autobiographical memory recall to upregulate the amygdala is associated with resting-state functional connectivity (rsFC) changes between the amygdala and the salience and default mode networks (SN and DMN, respectively). We hypothesize the existence of anatomical circuits underlying these rsFC changes. Using a cross-species brain parcellation, we identified in non-human primates locations homologous to the regions of interest (ROIs) from studies showing pre-to-post-neurofeedback changes in rsFC with the left amygdala. We injected bidirectional tracers in the basolateral, lateral, and central amygdala nuclei of adult macaques and used bright- and dark-field microscopy to identify cells and axon terminals in each ROI (SN: anterior cingulate, ventrolateral, and insular cortices; DMN: temporal pole, middle frontal gyrus, angular gyrus, precuneus, posterior cingulate cortex, parahippocampal gyrus, hippocampus, and thalamus). We also performed additional injections in specific ROIs to validate the results following amygdala injections and delineate potential disynaptic pathways. Finally, we used high-resolution diffusion MRI data from four post-mortem macaque brains and one in vivo human brain to translate our findings to the neuroimaging domain. Different amygdala nuclei had significant monosynaptic connections with all the SN and DMN ipsilateral ROIs. Amygdala connections with the DMN contralateral ROIs are disynaptic through the hippocampus and parahippocampal gyrus. Diffusion MRI in both species benefitted from using the ground-truth tracer data to validate its findings, as we identified false-negative ipsilateral and false-positive contralateral connectivity results. This study provides the foundation for future causal investigations of amygdala neurofeedback modulation of the SN and DMN through these anatomic connections.

White matter microstructure alterations of the posterior limb of internal capsule in first-episode drug naive schizophrenia patients

ObjectivesPrevious studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores. MethodsThirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated. ResultsThe Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR_P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST_P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (fSTR_P) and NDI deviation in STR_P and CST_P compared to PLIC region (fPLIC) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of fPLIC reaching 0.872. ConclusionThe study’s findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

RADT-50. EVIDENCE-BASED MULTIVARIATE NORMAL TISSUE COMPLICATION PROBABILITY (NTCP) STUDY OF DOMAIN-SPECIFIC COGNITIVE DECLINE AFTER PARTIAL BRAIN RADIATION (RT)

Abstract Beyond the hippocampus, there are no evidence-based dose constraints for eloquent brain structures which subserve cognitive domains. We performed a multivariate NTCP analysis of post-RT neurocognitive decline, examining dosimetric predictors of eloquent brain regions in a prospective longitudinal clinical trial. 83 patients with primary brain tumors receiving fractionated RT completed comprehensive neurocognitive evaluation and high-resolution volumetric and diffusion MRI at baseline and 6 months post-RT. Image processing using robust, validated automated segmentation parcellated individual white matter (WM) tracts, cortical regions, and hippocampi. Well-validated neurocognitive tests evaluating multiple cognitive domains were assessed with negative reliable change indices adjusted for practice effects between timepoints scored as decline. Univariate logistic regression and multivariate model building were performed examining dose to eloquent structures and clinical variables. Univariate analysis showed mean dose to the bilateral caudal anterior cingulate cortex and WM were correlated with decline in executive function. Attention/processing speed decline was correlated with mean/max dose to the posterior corpus callosum (CC), volume getting &amp;gt;20 Gy in the combined CC, as well as anti-epileptic use and chemotherapy. On multivariate analysis for attention automated bootstrapped logistic regression performance at nested cross-validation by AUC was 0.59 (0.54-0.65); LASSO model performance by AUC was 0.60 (0.54-0.66) with mean dose to combined CC being the most frequent variable in both. The top three most important variables in Random Forest by mean decrease in Gini coefficient were max dose to posterior and combined CC and mean dose to anterior CC. Model performance by AUC was 0.70 (0.64-0.75). Here we present the first, to our knowledge, NTCP model for decline in attention/processing speed, along with dosimetric predictors of executive function decline. We found that after partial brain RT, dose to several ROIs significantly correlated with post-RT impairment. These data can guide future cognitive-sparing strategies for brain RT.

Evidence-Based Multivariate Normal Tissue Complication Probability (NTCP) Study of Domain-Specific Cognitive Decline after Partial Brain RT

Beyond the hippocampus, there are no evidence-based dose constraints for eloquent brain structures which subserve memory and attention/processing speed. We performed a multivariate normal tissue complication probability analysis of post-RT neurocognitive decline, examining dosimetric predictors of eloquent brain regions. Data were analyzed from a prospective longitudinal clinical trial. Patients (n = 78) with primary brain tumors receiving fractionated RT complete a comprehensive neurocognitive evaluation and high-resolution volumetric and diffusion MRI at baseline and 6 months post-RT. Image processing using robust, validated automated segmentation parcellated individual WM tracts, cortical regions, and hippocampi. Well-validated neurocognitive tests including Delis-Kaplan Executive Function System and Wechsler Adult Intelligence Scale-IV coding (attention/processing), Boston Naming Test (language) and Hopkins Verbal Learning Test and Brief Visuospatial Memory Test (verbal/visuospatial memory) were assessed. Reliable change indices adjusted for practice effects (RCI-PE) were calculated for each patient between baseline and 6 months; a negative RCI-PE was scored as decline. Univariate logistic regression was performed with mean and max dose to structures of interest as well as clinical variables. Multivariate model building was performed using automated bootstrapped logistic regression, LASSO and random forest modeling. On univariate analysis mean and max dose to multiple regions of the corpus callosum (CC) were correlated with attention/processing speed decline; most significantly in WAIS coding, including Dmax to the anterior CC (p = 0.011) and central CC (p = 0.010), and Dmax and Dmean to the mid anterior CC (p = 0.006 and 0.010). Mean dose to the left fornix was associated with decline in memory (p = 0.023, cutoff 12.9 Gy), as were increasing age and both concurrent and adjuvant chemotherapy. On multivariate analysis for attention, automated bootstrapped logistic regression showed the most frequently selected variable was mean dose to the mid anterior CC. Performance at nested cross-validation by AUC was 0.80 (0.75-0.84); LASSO model performance by AUC was 0.76 (0.72-0.81) with Dmean to the mid anterior CC being the most frequent variable. The top five most important variables in the Random Forest as ranked by mean decrease in Gini coefficient were mean dose to mid anterior CC, all white matter, combined CC and max dose to CC and posterior CC. Model performance by AUC was 0.66 (0.60-0.71). Here, we present the first, to our knowledge, NTCP model for decline in attention/processing speed, along with dosimetric predictors of memory decline beyond the hippocampus. We found that after partial brain RT, dose to several ROIs significantly correlated with post-RT impairment. These data can guide future cognitive-sparing strategies for brain RT.

Feasibility of Cognitive-Sparing Stereotactic Radiosurgery for Brain Metastases: Initial Report of Phase II COG-SRS Trial

Radiotherapy at high doses leads to white matter (WM) and hippocampal injury which can cause cognitive decline. We designed the first, to our knowledge, evidence-based cognitive sparing brain SRS trial for patients with limited brain metastases. In this report we analyze feasibility of cognitive-sparing SRS, utilizing dose constraints for eloquent WM tracts and bilateral hippocampi. This is a single-institution phase II NCI-funded clinical trial (NCT04343157) of cognitive-sparing brain SRS; eloquent regions of interest (ROI) and associated cognitive domains are outlined in Table 1. Patients underwent high-resolution quantitative diffusion and volumetric MRI at baseline and post-SRS follow-up. Comprehensive neurocognitive assessment was performed at baseline and 3 months post-SRS by a neuropsychologist evaluating different neurocognitive domains (Table 1). Clinical processing/workflow was largely automated with robust, validated segmentation tools of eloquent WM tracts and the hippocampi. Single fraction dose constraints to WM tracts were 12 Gy Dmax and 8.4 Gy to hippocampi with 3 and 5 fraction equivalent doses, based on our prior NTCP studies. Patient accrual, follow up imaging and neurocognitive testing is still active. To date, n = 59 patients and 114 lesions have been treated with cognitive-sparing Linac-based SRS on trial. Median age is 63 years. Lung cancer was the most common primary (35.6%), along with breast cancer (23.7%) and melanoma (15.3%). Patients had 1-4 brain metastases; median prescription dose was 24 Gy/1, 27 Gy/3, or 30 Gy/5 depending on target volume. Most patients were treated < 7 business days from MRI. Cognitive endpoints have been collected on 89.5% of patients. Cognitive sparing constraints were met in 79.3% of plans while maintaining standard clinical SRS plan indices and coverage benchmarks. 38.9% of the plans that failed to meet the Dmax constraint kept D0.03cc under constraints. Plans going over constraints had tumors overlying or within 1 mm of eloquent ROIs. Local control for treated lesions at 6 months was 97.9% and 95.7% at 12 months. Distant intracranial control was 68.1% at 6 and 12 months. Median OS was 18 months. Cognitive-sparing SRS treatment planning was successfully implemented for the majority of treated lesions with excellent local control. Mitigation of damage to eloquent structures has potential to further reduce cognitive decline after SRS. Full neurocognitive outcomes will be reported after accrual and testing are complete.

LMAP-20 EVIDENCE-BASED MULTIVARIATE NORMAL TISSUE COMPLICATION PROBABILITY (NTCP) STUDY OF DOMAIN-SPECIFIC COGNITIVE DECLINE AFTER PARTIAL BRAIN RT

Abstract Beyond the hippocampus, there are no evidence-based dose constraints for eloquent structures which subserve memory and attention/processing speed. We performed a multivariate normal tissue complication probability analysis of post-RT neurocognitive decline, examining dosimetric predictors of eloquent brain regions in a prospective longitudinal clinical trial. 78 patients with primary brain tumors receiving fractionated RT completed a comprehensive neurocognitive evaluation and high-resolution volumetric and diffusion MRI at baseline and 6 months post-RT. Image processing using validated automated segmentation parcellated individual white matter (WM) tracts, cortical regions, and hippocampi. Neurocognitive test performance was scored using reliable change indices adjusted for practice effects: negative scores indicate decline. Univariate logistic regression and multivariate model building were performed. On univariate analysis mean and max dose to multiple regions of the corpus callosum (CC) correlated with attention/processing speed decline including Dmax to anterior CC (p=0.011) and central CC (p=0.010), and Dmax/Dmean to mid-anterior CC (p=0.006 and 0.010). Dmean to left fornix was associated with memory decline (p=0.023), as were increasing age and chemotherapy. On multivariate analysis for attention, automated bootstrapped logistic regression showed the most frequently selected variable was Dmean to mid-anterior CC. Performance at nested cross-validation by AUC was 0.80 (0.75-0.84); LASSO model performance by AUC was 0.76 (0.72-0.81) with Dmean to the mid-anterior CC being the most frequent variable. The top five most important variables in Random Forest were Dmean to mid-anterior CC, all WM, combined CC and Dmax to CC and posterior CC. Model performance by AUC was 0.66 (0.60-0.71). We present the first, to our knowledge, multivariate NTCP model for decline in attention/processing speed, and dosimetric predictors of memory decline beyond the hippocampus. Dose to several eloquent ROIs significantly correlated with post-RT impairment. These data can guide future cognitive-sparing strategies for brain RT.

LMAP-17 FEASIBILITY OF COGNITIVE-SPARING STEREOTACTIC RADIOSURGERY FOR BRAIN METASTASES: INITIAL REPORT OF PHASE II COG-SRS TRIAL

Abstract Radiotherapy at high doses leads to white matter (WM) and hippocampal injury which can cause cognitive decline. We designed the first, to our knowledge, evidence-based cognitive-sparing brain SRS trial for patients with limited brain metastases. In this report we analyze feasibility of cognitive-sparing SRS, utilizing dose constraints for eloquent WM tracts and bilateral hippocampi. Patients underwent high-resolution quantitative diffusion and volumetric MRI at baseline and post-SRS follow-up. Comprehensive neurocognitive assessment was performed at baseline and 3 months post-SRS evaluating multiple neurocognitive domains. Clinical workflow was largely automated with robust, validated segmentation of eloquent WM tracts and the hippocampi. Single fraction max dose constraints to WM tracts and hippocampi were 12 Gy and 8.4 Gy, respectively, with 3 and 5 fraction equivalent doses based on our prior NTCP studies. Patient accrual, follow-up imaging and neurocognitive testing is still active. To date, 59 patients and 114 lesions have been treated with cognitive-sparing linac-based SRS on trial. Median age is 63 years. Patients had 1-4 brain metastases; median prescription dose was 24Gy/1, 27Gy/3, or 30Gy/5 depending on target volume. Most patients were treated &amp;lt;7 business days from MRI. Cognitive endpoints have been collected on 89.5% of patients. Cognitive-sparing constraints were met in 79.3% of plans while maintaining standard clinical SRS plan indices and coverage benchmarks. Plans going over constraints had tumors overlying or within 1 mm of eloquent ROIs. Local control for treated lesions at 6 months was 97.9% and 95.7% at 12 months. Distant intracranial control was 68.1% at 6 and 12 months. Median OS was 18 months. Cognitive-sparing SRS treatment planning was successfully implemented for the majority of treated lesions with excellent local control. Mitigation of damage to eloquent structures has potential to further reduce cognitive decline after SRS. Full neurocognitive outcomes will be reported after accrual and testing are complete.

Sampling strategies and integrated reconstruction for reducing distortion and boundary slice aliasing in high-resolution 3D diffusion MRI.

To develop a new method for high-fidelity, high-resolution 3D multi-slab diffusion MRI with minimal distortion and boundary slice aliasing. Our method modifies 3D multi-slab imaging to integrate blip-reversed acquisitions for distortion correction and oversampling in the slice direction (kz ) for reducing boundary slice aliasing. Our aim is to achieve robust acceleration to keep the scan time the same as conventional 3D multi-slab acquisitions, in which data are acquired with a single direction of blip traversal and without kz -oversampling. We employ a two-stage reconstruction. In the first stage, the blip-up/down images are respectively reconstructed and analyzed to produce a field map for each diffusion direction. In the second stage, the blip-reversed data and the field map are incorporated into a joint reconstruction to produce images that are corrected for distortion and boundary slice aliasing. We conducted experiments at 7T in six healthy subjects. Stage 1 reconstruction produces images from highly under-sampled data (R = 7.2) with sufficient quality to provide accurate field map estimation. Stage 2 joint reconstruction substantially reduces distortion artifacts with comparable quality to fully-sampled blip-reversed results (2.4× scan time). Whole-brain in-vivo results acquired at 1.22 mm and 1.05 mm isotropic resolutions demonstrate improved anatomical fidelity compared to conventional 3D multi-slab imaging. Data demonstrate good reliability and reproducibility of the proposed method over multiple subjects. The proposed acquisition and reconstruction framework provide major reductions in distortion and boundary slice aliasing for 3D multi-slab diffusion MRI without increasing the scan time, which can potentially produce high-quality, high-resolution diffusion MRI.

Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex

Intrinsic coupling modes (ICMs) can be observed in ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted micro-ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are significantly related to SC, except for phase ICMs when using measures removing zero-lag coupling. The correlation between SC and ICMs increases with increasing frequency which is accompanied by reduced delays. Computational models produced results that were highly dependent on the specific parameter settings. The most consistent predictions were derived from measures solely based on SC. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are both related, albeit to different degrees, to the underlying structural connectivity in the cerebral cortex.

An anatomical and connectivity atlas of the marmoset cerebellum

The cerebellum is essential for motor control and cognitive functioning, engaging in bidirectional communication with the cerebral cortex. The common marmoset, a small non-human primate, offers unique advantages for studying cerebello-cerebral circuits. However, the marmoset cerebellum is not well described in published resources. In this study, we present a comprehensive atlas of the marmoset cerebellum comprising (1) fine-detailed anatomical atlases and surface-analysis tools of the cerebellar cortex based on ultra-high-resolution exvivo MRI, (2) functional connectivity and gradient patterns of the cerebellar cortex revealed by awake resting-state fMRI, and (3) structural-connectivity mapping of cerebellar nuclei using high-resolution diffusion MRI tractography. The atlas elucidates the anatomical details of the marmoset cerebellum, reveals distinct gradient patterns of intra-cerebellar and cerebello-cerebral functional connectivity, and maps the topological relationship of cerebellar nuclei in cerebello-cerebral circuits. As version 5 of the Marmoset Brain Mapping project, this atlas is publicly available at https://marmosetbrainmapping.org/MBMv5.html.

Three-dimensional diffusion MRI using simultaneous multislab with blipped-CAIPI in a 4D k-space framework.

To develop an efficient simultaneous multislab imaging method with blipped-controlled aliasing in parallel imaging (blipped-SMSlab) in a 4D k-space framework, and to demonstrate its efficacy in high-resolution diffusion MRI (dMRI). First, the SMSlab 4D k-space signal expression is formulated, and the phase interferences from intraslab and interslab encodings on the same physical z-axis are analyzed. Then, the blipped-SMSlab dMRI sequence is designed, with blipped-controlled aliasing in parallel imaging (blipped-CAIPI) gradients for interslab encoding, and a 2D multiband accelerated navigator for inter-kz-shot phase correction. Third, strategies are developed to remove the phase interferences, by RF phase modulation and/or phase correction during reconstruction, thus decoupling intraslab and interslab encodings that are otherwise entangled. In vivo experiments are performed to validate the blipped-SMSlab method and preliminarily evaluate its performance in high-resolution dMRI compared with traditional 2D imaging. In the 4D k-space framework, interslab and intraslab phase interferences of blipped-SMSlab are successfully removed using the proposed strategies. Compared with non-CAIPI sampling, the blipped-SMSlab acquisition reduces the g-factor and g-factor-related SNR penalty by about 12%. In addition, in vivo experiments show the SNR advantage of blipped-SMSlab dMRI over traditional 2D dMRI for 1.3-mm and 1.0-mm isotropic resolution imaging with matched acquisition time. Removing interslab and intraslab phase interferences enables SMSlab dMRI with blipped-CAIPI in a 4D k-space framework. The proposed blipped-SMSlab dMRI is demonstrated to be more SNR-efficient than 2D dMRI and thus capable of high-quality, high-resolution fiber orientation detection.

A synchronized multimodal neuroimaging dataset for studying brain language processing

We present a synchronized multimodal neuroimaging dataset for studying brain language processing (SMN4Lang) that contains functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) data on the same 12 healthy volunteers while the volunteers listened to 6 hours of naturalistic stories, as well as high-resolution structural (T1, T2), diffusion MRI and resting-state fMRI data for each participant. We also provide rich linguistic annotations for the stimuli, including word frequencies, syntactic tree structures, time-aligned characters and words, and various types of word and character embeddings. Quality assessment indicators verify that this is a high-quality neuroimaging dataset. Such synchronized data is separately collected by the same group of participants first listening to story materials in fMRI and then in MEG which are well suited to studying the dynamic processing of language comprehension, such as the time and location of different linguistic features encoded in the brain. In addition, this dataset, comprising a large vocabulary from stories with various topics, can serve as a brain benchmark to evaluate and improve computational language models.

Multi-band multi-shot diffusion MRI reconstruction with joint usage of structured low-rank constraints and explicit phase mapping.

To develop a joint reconstruction method for multi-band multi-shot diffusion MRI. Multi-band multi-shot EPI acquisition is an effective approach for high-resolution diffusion MRI, but requires specific algorithms to correct the inter-shot phase variations. The phase correction can be done by first estimating the explicit phase map and then feeding it into the k-space signal formulation model. Alternatively, the phase information can be used indirectly as structured low-rank constraints in k-space. The 2 methods differ in reconstruction accuracy and efficiency. We aim to combine the 2 different approaches for improved image quality and reconstruction efficiency simultaneously, termed "joint usage of structured low-rank constraints and explicit phase mapping" (JULEP). The proposed JULEP reconstruction is tested on both single-band and multi-band, multi-shot diffusion data, with different resolutions and b values. The results of JULEP are compared with conventional methods with explicit phase mapping (i.e., multiplexed sensitivity-encoding [MUSE]) and structured low-rank constraints (i.e., MUSSELS), and another joint reconstruction method (i.e., network estimated artifacts for tempered reconstruction [NEATR]). JULEP improves the quality of the navigator and subsequently facilitates the reconstruction of final diffusion images. Compared with all 3 other methods (MUSE, MUSSELS, and NEATR), JULEP mitigates residual structural bias and improves temporal SNRs in the final diffusion image, particularly at high multi-band factors. Compared with MUSSELS, JULEP also improves computational efficiency. The proposed JULEP method significantly improves the image quality and reconstruction efficiency of multi-band multi-shot diffusion MRI, which can promote a broader application of high-resolution diffusion MRI.

Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain.

BackgroundThe subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients.ObjectiveThis study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1).MethodsWe used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles.ResultsWe successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta.ConclusionMulti-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.

Resolution and b value dependent structural connectome in ex vivo mouse brain

Diffusion magnetic resonance imaging has been widely used in both clinical and preclinical studies to characterize tissue microstructure and structural connectivity. The diffusion MRI protocol for the Human Connectome Project (HCP) has been developed and optimized to obtain high-quality, high-resolution diffusion MRI (dMRI) datasets. However, such efforts have not been fully explored in preclinical studies, especially for rodents. In this study, high quality dMRI datasets of mouse brains were acquired at 9.4T system from two vendors. In particular, we acquired a high-spatial resolution dMRI dataset (25 μm isotropic with 126 diffusion encoding directions), which we believe to be the highest spatial resolution yet obtained; and a high-angular resolution dMRI dataset (50 μm isotropic with 384 diffusion encoding directions), which we believe to be the highest angular resolution compared to the dMRI datasets at the microscopic resolution. We systematically investigated the effects of three important parameters that affect the final outcome of the connectome: b value (1000s/mm2 to 8000 s/mm2), angular resolution (10 to 126), and spatial resolution (25 µm to 200 µm). The stability of tractography and connectome increase with the angular resolution, where more than 50 angles is necessary to achieve consistent results. The connectome and quantitative parameters derived from graph theory exhibit a linear relationship to the b value (R2 > 0.99); a single-shell acquisition with b value of 3000 s/mm2 shows comparable results to the multi-shell high angular resolution dataset. The dice coefficient decreases and both false positive rate and false negative rate gradually increase with coarser spatial resolution. Our study provides guidelines and foundations for exploration of tradeoffs among acquisition parameters for the structural connectome in ex vivo mouse brain.

Improving Imaging of the Brainstem and Cerebellum in Autistic Children: Transformation-Based High-Resolution Diffusion MRI (TiDi-Fused) in the Human Brainstem.

Diffusion-weighted magnetic resonance imaging (dMRI) of the brainstem is technically challenging, especially in young autistic children as nearby tissue-air interfaces and motion (voluntary and physiological) can lead to artifacts. This limits the availability of high-resolution images, which are desirable for improving the ability to study brainstem structures. Furthermore, inherently low signal-to-noise ratios, geometric distortions, and sensitivity to motion not related to molecular diffusion have resulted in limited techniques for high-resolution data acquisition compared to other modalities such as T1-weighted imaging. Here, we implement a method for achieving increased apparent spatial resolution in pediatric dMRI that hinges on accurate geometric distortion correction and on high fidelity within subject image registration between dMRI and magnetization prepared rapid acquisition gradient echo (MPnRAGE) images. We call this post-processing pipeline T1 weighted-diffusion fused, or “TiDi-Fused”. Data used in this work consists of dMRI data (2.4 mm resolution, corrected using FSL’s Topup) and T1-weighted (T1w) MPnRAGE anatomical data (1 mm resolution) acquired from 128 autistic and non-autistic children (ages 6–10 years old). Accurate correction of geometric distortion permitted for a further increase in apparent resolution of the dMRI scan via boundary-based registration to the MPnRAGE T1w. Estimation of fiber orientation distributions and further analyses were carried out in the T1w space. Data processed with the TiDi-Fused method were qualitatively and quantitatively compared to data processed with conventional dMRI processing methods. Results show the advantages of the TiDi-Fused pipeline including sharper brainstem gray-white matter tissue contrast, improved inter-subject spatial alignment for group analyses of dMRI based measures, accurate spatial alignment with histology-based imaging of the brainstem, reduced variability in brainstem-cerebellar white matter tracts, and more robust biologically plausible relationships between age and brainstem-cerebellar white matter tracts. Overall, this work identifies a promising pipeline for achieving high-resolution imaging of brainstem structures in pediatric and clinical populations who may not be able to endure long scan times. This pipeline may serve as a gateway for feasibly elucidating brainstem contributions to autism and other conditions.

Cholinergic and hippocampal systems facilitate cross-domain cognitive recovery after stroke.

Spontaneous recovery of motor and cognitive function occurs in many individuals after stroke. The mechanisms are incompletely understood, but may involve neurotransmitter systems that support neural plasticity, networks that are involved in learning and regions of the brain that are able to flexibly adapt to demand (such as the ‘multiple-demand system').Forty-two patients with first symptomatic ischaemic stroke were enrolled in a longitudinal cohort study of cognitive function after stroke. High-resolution volumetric, diffusion MRI and neuropsychological assessment were performed at a mean of 70 ± 18 days after stroke. Cognitive assessment was repeated 1 year after stroke, using parallel test versions to avoid learning effects, and change scores were computed for long-term episodic, short-term and working memory. Structural MRI features that predicted change in cognitive scores were identified by a two-stage analysis: a discovery phase used whole-brain approaches in a hypothesis-free unbiased way; and an independent focused phase, where measurements were derived from regions identified in the discovery phase, using targeted volumetric measurements or tractography. Evaluation of the cholinergic basal forebrain, based on a validated atlas-based approach, was included given prior evidence of a role in neural plasticity.The status of the fornix, cholinergic basal forebrain and a set of hippocampal subfields were found to predict improvement in long-term memory performance. In contrast to prior expectation, the same pattern was found for short-term and working memory, suggesting that these regions are part of a common infrastructure that supports recovery across cognitive domains. Associations between cholinergic basal forebrain volume and cognitive recovery were found primarily in subregions associated with the nucleus basalis of Meynert, suggesting that it is the cholinergic outflow to the neocortex that enables recovery. Support vector regression models derived from baseline measurements of fornix, cholinergic basal forebrain and hippocampal subfields were able to explain 62% of change in long-term episodic and 41% of change in working memory performance over the subsequent 9 months.The results suggest that the cholinergic system and extended hippocampal network play key roles in cognitive recovery after stroke. Evaluation of these systems early after stroke may inform personalized therapeutic strategies to enhance recovery.

Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors.

High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on a 3D kq-space under-sampling scheme to enable accelerated acquisitions. The inverse problem for the reconstruction of the fiber orientation distribution (FOD) is regularized by a structured sparsity prior promoting simultaneously voxel-wise sparsity and spatial smoothness of fiber orientation. Prior knowledge of the spatial distribution of white matter, gray matter, and cerebrospinal fluid is also leveraged. A minimization problem is formulated and solved via a stochastic forward–backward algorithm. Simulations and real data analysis suggest that accurate FOD mapping can be achieved from severe kq-space under-sampling regimes potentially enabling high spatio-angular resolution dMRI in the clinical setting.