Publications by authors named "Michael Zeineh"

54 Publications

Optimizing the frame duration for data-driven rigid motion estimation in brain PET imaging.

Med Phys 2021 Apr 20. Epub 2021 Apr 20.

Department of Radiology, University of Wisconsin, Madison, WI, USA.

Purpose: Data-driven rigid motion estimation for PET brain imaging is usually performed using data frames sampled at low temporal resolution to reduce the overall computation time and to provide adequate signal-to-noise ratio in the frames. In recent work it has been demonstrated that list-mode reconstructions of ultrashort frames are sufficient for motion estimation and can be performed very quickly. In this work we take the approach of using image-based registration of reconstructions of very short frames for data-driven motion estimation, and optimize a number of reconstruction and registration parameters (frame duration, MLEM iterations, image pixel size, post-smoothing filter, reference image creation, and registration metric) to ensure accurate registrations while maximizing temporal resolution and minimizing total computation time.

Methods: Data from F-fluorodeoxyglucose (FDG) and F-florbetaben (FBB) tracer studies with varying count rates are analyzed, for PET/MR and PET/CT scanners. For framed reconstructions using various parameter combinations interframe motion is simulated and image-based registrations are performed to estimate that motion.

Results: For FDG and FBB tracers using 4 × 10 true and scattered coincidence events per frame ensures that 95% of the registrations will be accurate to within 1 mm of the ground truth. This corresponds to a frame duration of 0.5-1 sec for typical clinical PET activity levels. Using four MLEM iterations with no subsets, a transaxial pixel size of 4 mm, a post-smoothing filter with 4-6 mm full width at half maximum, and averaging two or more frames to create the reference image provides an optimal set of parameters to produce accurate registrations while keeping the reconstruction and processing time low.

Conclusions: It is shown that very short frames (≤1 sec) can be used to provide accurate and quick data-driven rigid motion estimates for use in an event-by-event motion corrected reconstruction.
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http://dx.doi.org/10.1002/mp.14889DOI Listing
April 2021

Rapid Estimation of Entire Brain Strain Using Deep Learning Models.

IEEE Trans Biomed Eng 2021 Apr 14;PP. Epub 2021 Apr 14.

Objective: Many recent studies have suggested that brain deformation resulting from a head impact is linked to the corresponding clinical outcome, such as mild traumatic brain injury (mTBI). Even though several finite element (FE) head models have been developed and validated to calculate brain deformation based on impact kinematics, the clinical application of these FE head models is limited due to the time-consuming nature of FE simulations. This work aims to accelerate the process of brain deformation calculation and thus improve the potential for clinical applications.

Methods: We propose a deep learning head model with a five-layer deep neural network and feature engineering, and trained and tested the model on 2511 total head impacts from a combination of head model simulations and on-field college football and mixed martial arts impacts.

Results: The proposed deep learning head model can calculate the maximum principal strain (Green Lagrange) for every element in the entire brain in less than 0.001s with an average root mean squared error of 0.022, and with a standard deviation of 0.001 over twenty repeats with random data partition and model initialization.

Conclusion: Trained and tested using the dataset of 2511 head impacts, this model can be applied to various sports in the calculation of brain strain with accuracy, and its applicability can even further be extended by incorporating data from other types of head impacts.

Significance: In addition to the potential clinical application in real-time brain deformation monitoring, this model will help researchers estimate the brain strain from a large number of head impacts more efficiently than using FE models.
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http://dx.doi.org/10.1109/TBME.2021.3073380DOI Listing
April 2021

A new open-access platform for measuring and sharing mTBI data.

Sci Rep 2021 Apr 5;11(1):7501. Epub 2021 Apr 5.

Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.

Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.
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http://dx.doi.org/10.1038/s41598-021-87085-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8021549PMC
April 2021

Neuroimaging, Urinary, and Plasma Biomarkers of Treatment Response in Huntington's Disease: Preclinical Evidence with the p75 Ligand LM11A-31.

Neurotherapeutics 2021 Mar 30. Epub 2021 Mar 30.

Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, 94305, USA.

Huntington's disease (HD) is caused by an expansion of the CAG repeat in the huntingtin gene leading to preferential neurodegeneration of the striatum. Disease-modifying treatments are not yet available to HD patients and their development would be facilitated by translatable pharmacodynamic biomarkers. Multi-modal magnetic resonance imaging (MRI) and plasma cytokines have been suggested as disease onset/progression biomarkers, but their ability to detect treatment efficacy is understudied. This study used the R6/2 mouse model of HD to assess if structural neuroimaging and biofluid assays can detect treatment response using as a prototype the small molecule p75 ligand LM11A-31, shown previously to reduce HD phenotypes in these mice. LM11A-31 alleviated volume reductions in multiple brain regions, including striatum, of vehicle-treated R6/2 mice relative to wild-types (WTs), as assessed with in vivo MRI. LM11A-31 also normalized changes in diffusion tensor imaging (DTI) metrics and diminished increases in certain plasma cytokine levels, including tumor necrosis factor-alpha and interleukin-6, in R6/2 mice. Finally, R6/2-vehicle mice had increased urinary levels of the p75 extracellular domain (ecd), a cleavage product released with pro-apoptotic ligand binding that detects the progression of other neurodegenerative diseases; LM11A-31 reduced this increase. These results are the first to show that urinary p75-ecd levels are elevated in an HD mouse model and can be used to detect therapeutic effects. These data also indicate that multi-modal MRI and plasma cytokine levels may be effective pharmacodynamic biomarkers and that using combinations of these markers would be a viable and powerful option for clinical trials.
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http://dx.doi.org/10.1007/s13311-021-01023-8DOI Listing
March 2021

Exploring valence states of abnormal mineral deposits in biological tissues using correlative microscopy and spectroscopy techniques: A case study on ferritin and iron deposits from Alzheimer's disease patients.

Ultramicroscopy 2021 Mar 16:113254. Epub 2021 Mar 16.

Department of Materials Science and Engineering, Stanford University, 496 Lomita Mall, Stanford, CA 94305, USA. Electronic address:

Abnormal accumulation of inorganic trace elements in a human brain, such as iron, zinc and aluminum, oftentimes manifested as deposits and accompanied by a chemical valence change, is pathologically relevant to various neurodegenerative diseases. In particular, Fe has been hypothesized to produce free radicals that induce oxidative damage and eventually cause Alzheimer's disease (AD). However, traditional biomedical techniques, e.g. histology staining, are limited in studying the chemical composition and valence states of these inorganic deposits. We apply commonly used physical (phys-) science methods such as X-ray energy dispersive spectroscopy (EDS), focused-ion beam (FIB) and electron energy loss spectroscopy (EELS) in transmission electron microscopy in conjunction with magnetic resonance imaging (MRI), histology and optical microscopy (OM) to study the valence states of iron deposits in AD patients. Ferrous ions are found in all deposits in brain tissues from three AD patients, constituting 0.22-0.50 of the whole iron content in each specimen. Such phys-techniques are rarely used in medical science and have great potential to provide unique insight into biomedical problems.
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http://dx.doi.org/10.1016/j.ultramic.2021.113254DOI Listing
March 2021

Correlative Microscopy to Localize and Characterize Iron Deposition in Alzheimer's Disease.

J Alzheimers Dis Rep 2020 Dec 21;4(1):525-536. Epub 2020 Dec 21.

Department of Radiology, Stanford University, Stanford, CA, USA.

Background: Recent evidence suggests that the accumulation of iron, specifically ferrous Fe, may play a role in the development and progression of neurodegeneration in Alzheimer's disease (AD) through the production of oxidative stress.

Objective: To localize and characterize iron deposition and oxidation state in AD, we analyzed human hippocampal autopsy samples from four subjects with advanced AD that have been previously characterized with correlative MRI-histology.

Methods: We perform scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), and electron energy loss spectroscopy (EELS) in the higher resolution transmission electron microscope on the surface and cross-sections of specific iron-rich regions of interest.

Results: Specific previously analyzed regions were visualized using SEM and confirmed to be iron-rich deposits using EDS. Subsequent analysis using focused ion beam cross-sectioning and SEM characterized the iron deposition throughout the 3-D volumes, confirming the presence of iron throughout the deposits, and in two out of four specimens demonstrating colocalization with zinc. Analysis of traditional histology slides showed the analyzed deposits overlapped both with amyloid and tau deposition. Following higher resolution analysis of a single iron deposit using scanning transmission electron microscope (STEM), we demonstrated the potential of monochromated STEM-EELS to discern the relative oxidation state of iron within a deposit.

Conclusion: These findings suggest that iron is present in the AD hippocampus and can be visualized and characterized using combined MRI and EM techniques. An altered relative oxidation state may suggest a direct link between iron and oxidative stress in AD. These methods thus could potentially measure an altered relative oxidation state that could suggest a direct link between iron and oxidative stress in AD. Furthermore, we have demonstrated the ability to analyze metal deposition alongside commonly used histological markers of AD pathology, paving the way for future insights into the molecular interactions between Aβ, tau, iron, and other putative metals, such as zinc.
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http://dx.doi.org/10.3233/ADR-200234DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7835989PMC
December 2020

White Matter Tract-Oriented Deformation Is Dependent on Real-Time Axonal Fiber Orientation.

J Neurotrauma 2021 Feb 23. Epub 2021 Feb 23.

Department of Radiology, Stanford University, Stanford, California, USA.

Traumatic axonal injury (TAI) is a critical public health issue with its pathogenesis remaining largely elusive. Finite element (FE) head models are promising tools to bridge the gap between mechanical insult, localized brain response, and resultant injury. In particular, the FE-derived deformation along the direction of white matter (WM) tracts (i.e., tract-oriented strain) has been shown to be an appropriate predictor for TAI. The evolution of fiber orientation in time during the impact and its potential influence on the tract-oriented strain remains unknown, however. To address this question, the present study leveraged an embedded element approach to track real-time fiber orientation during impacts. A new scheme to calculate the tract-oriented strain was proposed by projecting the strain tensors from pre-computed simulations along the temporal fiber direction instead of its static counterpart directly obtained from diffuse tensor imaging. The results revealed that incorporating the real-time fiber orientation not only altered the direction but also amplified the magnitude of the tract-oriented strain, resulting in a generally more extended distribution and a larger volume ratio of WM exposed to high deformation along fiber tracts. These effects were exacerbated with the impact severities characterized by the acceleration magnitudes. Results of this study provide insights into how best to incorporate fiber orientation in head injury models and derive the WM tract-oriented deformation from computational simulations, which is important for furthering our understanding of the underlying mechanisms of TAI.
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http://dx.doi.org/10.1089/neu.2020.7412DOI Listing
February 2021

True ultra-low-dose amyloid PET/MRI enhanced with deep learning for clinical interpretation.

Eur J Nucl Med Mol Imaging 2021 Jan 8. Epub 2021 Jan 8.

Department of Radiology, Stanford University, 1201 Welch Road, Stanford, CA, 94305, USA.

Purpose: While sampled or short-frame realizations have shown the potential power of deep learning to reduce radiation dose for PET images, evidence in true injected ultra-low-dose cases is lacking. Therefore, we evaluated deep learning enhancement using a significantly reduced injected radiotracer protocol for amyloid PET/MRI.

Methods: Eighteen participants underwent two separate F-florbetaben PET/MRI studies in which an ultra-low-dose (6.64 ± 3.57 MBq, 2.2 ± 1.3% of standard) or a standard-dose (300 ± 14 MBq) was injected. The PET counts from the standard-dose list-mode data were also undersampled to approximate an ultra-low-dose session. A pre-trained convolutional neural network was fine-tuned using MR images and either the injected or sampled ultra-low-dose PET as inputs. Image quality of the enhanced images was evaluated using three metrics (peak signal-to-noise ratio, structural similarity, and root mean square error), as well as the coefficient of variation (CV) for regional standard uptake value ratios (SUVRs). Mean cerebral uptake was correlated across image types to assess the validity of the sampled realizations. To judge clinical performance, four trained readers scored image quality on a five-point scale (using 15% non-inferiority limits for proportion of studies rated 3 or better) and classified cases into amyloid-positive and negative studies.

Results: The deep learning-enhanced PET images showed marked improvement on all quality metrics compared with the low-dose images as well as having generally similar regional CVs as the standard-dose. All enhanced images were non-inferior to their standard-dose counterparts. Accuracy for amyloid status was high (97.2% and 91.7% for images enhanced from injected and sampled ultra-low-dose data, respectively) which was similar to intra-reader reproducibility of standard-dose images (98.6%).

Conclusion: Deep learning methods can synthesize diagnostic-quality PET images from ultra-low injected dose simultaneous PET/MRI data, demonstrating the general validity of sampled realizations and the potential to reduce dose significantly for amyloid imaging.
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http://dx.doi.org/10.1007/s00259-020-05151-9DOI Listing
January 2021

High-resolution Structural Magnetic Resonance Imaging and Quantitative Susceptibility Mapping.

Magn Reson Imaging Clin N Am 2021 Feb;29(1):13-39

Department of Radiology, Stanford University, Lucas Center for Imaging, Room P271, 1201 Welch Road, Stanford, CA 94305-5488, USA. Electronic address:

High-resolution 7-T imaging and quantitative susceptibility mapping produce greater anatomic detail compared with conventional strengths because of improvements in signal/noise ratio and contrast. The exquisite anatomic details of deep structures, including delineation of microscopic architecture using advanced techniques such as quantitative susceptibility mapping, allows improved detection of abnormal findings thought to be imperceptible on clinical strengths. This article reviews caveats and techniques for translating sequences commonly used on 1.5 or 3 T to high-resolution 7-T imaging. It discusses for several broad disease categories how high-resolution 7-T imaging can advance the understanding of various diseases, improve diagnosis, and guide management.
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http://dx.doi.org/10.1016/j.mric.2020.09.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7886008PMC
February 2021

Validation and Comparison of Instrumented Mouthguards for Measuring Head Kinematics and Assessing Brain Deformation in Football Impacts.

Ann Biomed Eng 2020 Nov 28;48(11):2580-2598. Epub 2020 Sep 28.

Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.

Because of the rigid coupling between the upper dentition and the skull, instrumented mouthguards have been shown to be a viable way of measuring head impact kinematics for assisting in understanding the underlying biomechanics of concussions. This has led various companies and institutions to further develop instrumented mouthguards. However, their use as a research tool for understanding concussive impacts makes quantification of their accuracy critical, especially given the conflicting results from various recent studies. Here we present a study that uses a pneumatic impactor to deliver impacts characteristic to football to a Hybrid III headform, in order to validate and compare five of the most commonly used instrumented mouthguards. We found that all tested mouthguards gave accurate measurements for the peak angular acceleration, the peak angular velocity, brain injury criteria values (mean average errors < 13, 8, 13%, respectively), and the mouthguards with long enough sampling time windows are suitable for a convolutional neural network-based brain model to calculate the brain strain (mean average errors < 9%). Finally, we found that the accuracy of the measurement varies with the impact locations yet is not sensitive to the impact velocity for the most part.
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http://dx.doi.org/10.1007/s10439-020-02629-3DOI Listing
November 2020

COVID-19-induced anosmia associated with olfactory bulb atrophy.

Neuroradiology 2021 Jan 15;63(1):147-148. Epub 2020 Sep 15.

Division of Neuroradiology, Department of Radiology, Stanford University, 300 Pasteur Drive, Room S047, Stanford, CA, 94305-5105, USA.

As the global COVID-19 pandemic evolves, our knowledge of the respiratory and non-respiratory symptoms continues to grow. One such symptom, anosmia, may be a neurologic marker of coronavirus infection and the initial presentation of infected patients. Because this symptom is not routinely investigated by imaging, there is conflicting literature on neuroimaging abnormalities related to COVID-19-related anosmia. We present a novel case of COVID-19 anosmia with definitive olfactory bulb atrophy compared with pre-COVID imaging. The patient had prior MR imaging related to a history of prolactinoma that provided baseline volumes of her olfactory bulbs. After a positive diagnosis of COVID-19 and approximately 2 months duration of anosmia, an MRI was performed that showed clear interval olfactory bulb atrophy. This diagnostic finding is of prognostic importance and indicates that the olfactory entry point to the brain should be further investigated to improve our understanding of COVID infectious pathophysiology.
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http://dx.doi.org/10.1007/s00234-020-02554-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7490479PMC
January 2021

The ENIGMA sports injury working group:- an international collaboration to further our understanding of sport-related brain injury.

Brain Imaging Behav 2021 Apr;15(2):576-584

H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA.

Sport-related brain injury is very common, and the potential long-term effects include a wide range of neurological and psychiatric symptoms, and potentially neurodegeneration. Around the globe, researchers are conducting neuroimaging studies on primarily homogenous samples of athletes. However, neuroimaging studies are expensive and time consuming, and thus current findings from studies of sport-related brain injury are often limited by small sample sizes. Further, current studies apply a variety of neuroimaging techniques and analysis tools which limit comparability among studies. The ENIGMA Sports Injury working group aims to provide a platform for data sharing and collaborative data analysis thereby leveraging existing data and expertise. By harmonizing data from a large number of studies from around the globe, we will work towards reproducibility of previously published findings and towards addressing important research questions with regard to diagnosis, prognosis, and efficacy of treatment for sport-related brain injury. Moreover, the ENIGMA Sports Injury working group is committed to providing recommendations for future prospective data acquisition to enhance data quality and scientific rigor.
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http://dx.doi.org/10.1007/s11682-020-00370-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855299PMC
April 2021

Simultaneous FDG-PET/MRI detects hippocampal subfield metabolic differences in AD/MCI.

Sci Rep 2020 07 21;10(1):12064. Epub 2020 Jul 21.

Department of Radiology, Stanford University, Stanford, USA.

The medial temporal lobe is one of the most well-studied brain regions affected by Alzheimer's disease (AD). Although the spread of neurofibrillary pathology in the hippocampus throughout the progression of AD has been thoroughly characterized and staged using histology and other imaging techniques, it has not been precisely quantified in vivo at the subfield level using simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI). Here, we investigate alterations in metabolism and volume using [F]fluoro-deoxyglucose (FDG) and simultaneous time-of-flight (TOF) PET/MRI with hippocampal subfield analysis of AD, mild cognitive impairment (MCI), and healthy subjects. We found significant structural and metabolic changes within the hippocampus that can be sensitively assessed at the subfield level in a small cohort. While no significant differences were found between groups for whole hippocampal SUVr values (p = 0.166), we found a clear delineation in SUVr between groups in the dentate gyrus (p = 0.009). Subfield analysis may be more sensitive for detecting pathological changes using PET-MRI in AD compared to global hippocampal assessment.
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http://dx.doi.org/10.1038/s41598-020-69065-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374580PMC
July 2020

Tau PET imaging with F-PI-2620 in aging and neurodegenerative diseases.

Eur J Nucl Med Mol Imaging 2020 Jun 23. Epub 2020 Jun 23.

Department of Radiology, Stanford Medical School, Stanford, CA, USA.

Purpose: In vivo measurement of the spatial distribution of neurofibrillary tangle pathology is critical for early diagnosis and disease monitoring of Alzheimer's disease (AD).

Methods: Forty-nine participants were scanned with F-PI-2620 PET to examine the distribution of this novel PET ligand throughout the course of AD: 36 older healthy controls (HC) (age range 61 to 86), 11 beta-amyloid+ (Aβ+) participants with cognitive impairment (CI; clinical diagnosis of either mild cognitive impairment or AD dementia, age range 57 to 86), and 2 participants with semantic variant primary progressive aphasia (svPPA, age 66 and 78). Group differences in brain regions relevant in AD (medial temporal lobe, posterior cingulate cortex, and lateral parietal cortex) were examined using standardized uptake value ratios (SUVRs) normalized to the inferior gray matter of the cerebellum.

Results: SUVRs in target regions were relatively stable 60 to 90 min post-injection, with the exception of very high binders who continued to show increases over time. Robust elevations in F-PI-2620 were observed between HC and Aβ+ CI across all AD regions. Within the HC group, older age was associated with subtle elevations in target regions. Mildly elevated focal uptake was observed in the anterior temporal pole in one svPPA patient.

Conclusion: Preliminary results suggest strong differences in the medial temporal lobe and cortical regions known to be impacted in AD using F-PI-2620 in patients along the AD trajectory. This work confirms that F-PI-2620 holds promise as a tool to visualize tau aggregations in AD.
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http://dx.doi.org/10.1007/s00259-020-04923-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7755737PMC
June 2020

Deep flow-net for EPI distortion estimation.

Neuroimage 2020 08 7;217:116886. Epub 2020 May 7.

Stanford University, Department of Radiology, Stanford, CA, USA; Stanford 3D and Quantitative Imaging Laboratory, Stanford, CA, USA.

Introduction: Geometric distortions along the phase encoding direction caused by off-resonant spins are a major issue in EPI based functional and diffusion imaging. The widely used blip up/down approach estimates the underlying distortion field from a pair of images with inverted phase encoding direction. Typically, iterative methods are used to find a solution to the ill-posed problem of finding the displacement field that maps up/down acquisitions onto each other. Here, we explore the use of a deep convolutional network to estimate the displacement map from a pair of input images.

Methods: We trained a deep convolutional U-net architecture that was previously used to estimate optic flow between moving images to learn to predict the distortion map from an input pair of distorted EPI acquisitions. During the training step, the network minimizes a loss function (similarity metric) that is calculated from corrected input image pairs. This approach does not require the explicit knowledge of the ground truth distortion map, which is difficult to get for real life data.

Results: We used data from a total of N ​= ​22 healthy subjects to train our network. A separate dataset of N ​= ​12 patients including some with abnormal findings and unseen acquisition modes, e.g. LR-encoding, coronal orientation) was reserved for testing and evaluation purposes. We compared our results to FSL's topup function with default parameters that served as the gold standard. We found that our approach results in a correction accuracy that is virtually identical to the optimum found by an iterative search, but with reduced computational time.

Conclusion: By using a deep convolutional network, we can reduce the processing time to a few seconds per volume, which is significantly faster than iterative approaches like FSL's topup which takes around 10min on the same machine (but using only 1 CPU). This facilitates the use of a blip up/down scheme for all diffusion-weighted acquisitions and potential real-time EPI distortion correction without sacrificing accuracy.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116886DOI Listing
August 2020

Longitudinal alteration of cortical thickness and volume in high-impact sports.

Neuroimage 2020 08 29;217:116864. Epub 2020 Apr 29.

Department of Radiology, Stanford University, Stanford, CA, 94035, USA. Electronic address:

Collegiate football athletes are subject to repeated head impacts. The purpose of this study was to determine whether this exposure can lead to changes in brain structure. This prospective cohort study was conducted with up to 4 years of follow-up on 63 football (high-impact) and 34 volleyball (control) male collegiate athletes with a total of 315 MRI scans (after exclusions: football n ​= ​50, volleyball n ​= ​24, total scans ​= ​273) using high-resolution structural imaging. Volumetric and cortical thickness estimates were derived using FreeSurfer 5.3's longitudinal pipeline. A linear mixed-effects model assessed the effect of group (football vs. volleyball), time from baseline MRI, and the interaction between group and time. We confirmed an expected developmental decrement in cortical thickness and volume in our cohort (p ​< ​.001). Superimposed on this, total cortical gray matter volume (p ​= ​.03) and cortical thickness within the left hemisphere (p ​= ​.04) showed a group by time interaction, indicating less age-related volume reduction and thinning in football compared to volleyball athletes. At the regional level, sport by time interactions on thickness and volume were identified in the left orbitofrontal (p ​= ​.001), superior temporal (p ​= ​.001), and postcentral regions (p ​< ​.001). Additional cortical thickness interactions were found in the left temporal pole (p ​= ​.003) and cuneus (p ​= ​.005). At the regional level, we also found main effects of sport in football athletes characterized by reduced volume in the right hippocampus (p ​= ​.003), right superior parietal cortical gray (p ​< ​.001) and white matter (p ​< ​.001), and increased volume of the left pallidum (p ​= ​.002). Within football, cortical thickness was higher with greater years of prior play (left hemisphere p ​= ​.013, right hemisphere p ​= ​.005), and any history of concussion was associated with less cortical thinning (left hemisphere p ​= ​.010, right hemisphere p ​= ​.011). Additionally, both position-associated concussion risk (p ​= ​.002) and SCAT scores (p ​= ​.023) were associated with less of the expected volume decrement of deep gray structures. This prospective longitudinal study comparing football and volleyball athletes shows divergent age-related trajectories of cortical thinning, possibly reflecting an impact-related alteration of normal cortical development. This warrants future research into the underlying mechanisms of impacts to the head on cortical maturation.
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http://dx.doi.org/10.1016/j.neuroimage.2020.116864DOI Listing
August 2020

Substantia Nigra Volume Dissociates Bradykinesia and Rigidity from Tremor in Parkinson's Disease: A 7 Tesla Imaging Study.

J Parkinsons Dis 2020 ;10(2):591-604

Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.

Background: In postmortem analysis of late stage Parkinson's disease (PD) neuronal loss in the substantial nigra (SN) correlates with the antemortem severity of bradykinesia and rigidity, but not tremor.

Objective: To investigate the relationship between midbrain nuclei volume as an in vivo biomarker for surviving neurons in mild-to-moderate patients using 7.0 Tesla MRI.

Methods: We performed ultra-high resolution quantitative susceptibility mapping (QSM) on the midbrain in 32 PD participants with less than 10 years duration and 8 healthy controls. Following blinded manual segmentation, the individual volumes of the SN, subthalamic nucleus, and red nucleus were measured. We then determined the associations between the midbrain nuclei and clinical metrics (age, disease duration, MDS-UPDRS motor score, and subscores for bradykinesia/rigidity, tremor, and postural instability/gait difficulty).

Results: We found that smaller SN correlated with longer disease duration (r = -0.49, p = 0.004), more severe MDS-UPDRS motor score (r = -0.42, p = 0.016), and more severe bradykinesia-rigidity subscore (r = -0.47, p = 0.007), but not tremor or postural instability/gait difficulty subscores. In a hemi-body analysis, bradykinesia-rigidity severity only correlated with SN contralateral to the less-affected hemi-body, and not contralateral to the more-affected hemi-body, possibly reflecting the greatest change in dopamine neuron loss early in disease. Multivariate generalized estimating equation model confirmed that bradykinesia-rigidity severity, age, and disease duration, but not tremor severity, predicted SN volume.

Conclusions: In mild-to-moderate PD, SN volume relates to motor manifestations in a motor domain-specific and laterality-dependent manner. Non-invasive in vivo 7.0 Tesla QSM may serve as a biomarker in longitudinal studies of SN atrophy and in studies of people at risk for developing PD.
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http://dx.doi.org/10.3233/JPD-191890DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7242837PMC
January 2020

A within-coil optical prospective motion-correction system for brain imaging at 7T.

Magn Reson Med 2020 09 20;84(3):1661-1671. Epub 2020 Feb 20.

Department of Radiology, Stanford University, Stanford, California.

Purpose: Motion artifact limits the clinical translation of high-field MR. We present an optical prospective motion correction system for 7 Tesla MRI using a custom-built, within-coil camera to track an optical marker mounted on a subject.

Methods: The camera was constructed to fit between the transmit-receive coils with direct line of sight to a forehead-mounted marker, improving upon prior mouthpiece work at 7 Tesla MRI. We validated the system by acquiring a 3D-IR-FSPGR on a phantom with deliberate motion applied. The same 3D-IR-FSPGR and a 2D gradient echo were then acquired on 7 volunteers, with/without deliberate motion and with/without motion correction. Three neuroradiologists blindly assessed image quality. In 1 subject, an ultrahigh-resolution 2D gradient echo with 4 averages was acquired with motion correction. Four single-average acquisitions were then acquired serially, with the subject allowed to move between acquisitions. A fifth single-average 2D gradient echo was acquired following subject removal and reentry.

Results: In both the phantom and human subjects, deliberate and involuntary motion were well corrected. Despite marked levels of motion, high-quality images were produced without spurious artifacts. The quantitative ratings confirmed significant improvements in image quality in the absence and presence of deliberate motion across both acquisitions (P < .001). The system enabled ultrahigh-resolution visualization of the hippocampus during a long scan and robust alignment of serially acquired scans with interspersed movement.

Conclusion: We demonstrate the use of a within-coil camera to perform optical prospective motion correction and ultrahigh-resolution imaging at 7 Tesla MRI. The setup does not require a mouthpiece, which could improve accessibility of motion correction during 7 Tesla MRI exams.
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http://dx.doi.org/10.1002/mrm.28211DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7263977PMC
September 2020

Electrophysiological dynamics of antagonistic brain networks reflect attentional fluctuations.

Nat Commun 2020 01 16;11(1):325. Epub 2020 Jan 16.

Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA, 94304, USA.

Neuroimaging evidence suggests that the default mode network (DMN) exhibits antagonistic activity with dorsal attention (DAN) and salience (SN) networks. Here we use human intracranial electroencephalography to investigate the behavioral relevance of fine-grained dynamics within and between these networks. The three networks show dissociable profiles of task-evoked electrophysiological activity, best captured in the high-frequency broadband (HFB; 70-170 Hz) range. On the order of hundreds of milliseconds, HFB responses peak fastest in the DAN, at intermediate speed in the SN, and slowest in the DMN. Lapses of attention (behavioral errors) are marked by distinguishable patterns of both pre- and post-stimulus HFB activity within each network. Moreover, the magnitude of temporally lagged, negative HFB coupling between the DAN and DMN (but not SN and DMN) is associated with greater sustained attention performance and is reduced during wakeful rest. These findings underscore the behavioral relevance of temporally delayed coordination between antagonistic brain networks.
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http://dx.doi.org/10.1038/s41467-019-14166-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6965628PMC
January 2020

Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI.

Nat Commun 2019 12 3;10(1):5504. Epub 2019 Dec 3.

Department of Radiology, Stanford University, Stanford, CA, 94035, USA.

3D histology, slice-based connectivity atlases, and diffusion MRI are common techniques to map brain wiring. While there are many modality-specific tools to process these data, there is a lack of integration across modalities. We develop an automated resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling the analysis of histological features across multiple fiber tracts and networks, and their correlation with in-vivo biomarkers. We apply our pipeline in a murine stroke model, demonstrating not only strong correspondence between MRI abnormalities and CLARITY-tissue staining, but also uncovering acute cellular effects in areas connected to the ischemic core. We provide improved maps of connectivity by quantifying projection terminals from CLARITY viral injections, and integrate diffusion MRI with CLARITY viral tracing to compare connectivity maps across scales. Finally, we demonstrate tract-level histological changes of stroke through this multimodal integration. This resource can propel investigations of network alterations underlying neurological disorders.
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http://dx.doi.org/10.1038/s41467-019-13374-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6890789PMC
December 2019

Validation of the NeuroImaging Radiological Interpretation System for Acute Traumatic Brain Injury.

J Comput Assist Tomogr 2019 Sep/Oct;43(5):690-696

From the Department of Radiology, Neuroradiology Section, Stanford University, Stanford, CA.

Purpose: The aim of the study was to refine and validate the NeuroImaging Radiological Interpretation System (NIRIS), which was developed to predict management and clinical outcome based on noncontrast head computerized tomography findings in patients suspected of acute traumatic brain injury (TBI).

Methods: We assessed the performance of the NIRIS score in a prospective, single-center cohort of patients suspected of TBI (n = 648) and compared the performance of NIRIS with that of the Marshall and Rotterdam scoring systems. We also revised components of the NIRIS scoring system using decision tree methodologies implemented on pooled data from the retrospective and prospective studies (N = 1190).

Results: The NIRIS performed similarly to the Marshall and Rotterdam scoring systems in predicting mortality and markedly better in terms of predicting more granular elements of disposition and management of TBI patients, such as admission, follow-up imaging, intensive care unit stay, and neurosurgical procedures. The revised NIRIS classification correctly predicted disposition and outcome in 91.2% (331/363) after excluding patients with other major extracranial traumatic injuries or intracranial nontraumatic injuries.

Conclusions: The present study further demonstrates the predictive value of NIRIS in guiding standardized clinical management and decision-making regarding treatment options for TBI patients.
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http://dx.doi.org/10.1097/RCT.0000000000000913DOI Listing
October 2019

Rigid Motion Correction for Brain PET/MR Imaging using Optical Tracking.

IEEE Trans Radiat Plasma Med Sci 2019 Jul 31;3(4):498-503. Epub 2018 Oct 31.

PET/MR engineering, GE Healthcare, Waukesha, WI, USA.

A significant challenge during high-resolution PET brain imaging on PET/MR scanners is patient head motion. This challenge is particularly significant for clinical patient populations who struggle to remain motionless in the scanner for long periods of time. Head motion also affects the MR scan data. An optical motion tracking technique, which has already been demonstrated to perform MR motion correction during acquisition, is used with a list-mode PET reconstruction algorithm to correct the motion for each recorded event and produce a corrected reconstruction. The technique is demonstrated on real Alzheimer's disease patient data for the GE SIGNA PET/MR scanner.
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http://dx.doi.org/10.1109/TRPMS.2018.2878978DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686883PMC
July 2019

MR susceptibility contrast imaging using a 2D simultaneous multi-slice gradient-echo sequence at 7T.

PLoS One 2019 17;14(7):e0219705. Epub 2019 Jul 17.

Department of Radiology, Stanford University, Palo Alto, CA, United States of America.

Purpose: To develop a 7T simultaneous multi-slice (SMS) 2D gradient-echo sequence for susceptibility contrast imaging, and to compare its quality to 3D imaging.

Methods: A frequency modulated and phase cycled RF pulse was designed to simultaneously excite multiple slices in multi-echo 2D gradient-echo imaging. The imaging parameters were chosen to generate images with susceptibility contrast, including T2*-weighted magnitude/phase images, susceptibility-weighted images and quantitative susceptibility/R2* maps. To compare their image quality with 3D gradient-echo imaging, both 2D and 3D imaging were performed on 11 healthy volunteers and 4 patients with multiple sclerosis (MS). The signal to noise ratio (SNR) in gray and white matter and their contrast to noise ratio (CNR) was simulated for the 2D and 3D magnitude images using parameters from the imaging. The experimental SNRs and CNRs were measured in gray/white matter and deep gray matter structures on magnitude, phase, R2* and QSM images from volunteers and the visibility of MS lesions on these images from patients was visually rated. All SNRs and CNRs were compared between the 2D and 3D imaging using a paired t-test.

Results: Although the 3D magnitude images still had significantly higher SNRs (by 13.0~17.6%), the 2D magnitude and QSM images generated significantly higher gray/white matter or globus pallidus/putamen contrast (by 13.3~87.5%) and significantly higher MS lesion contrast (by 5.9~17.3%).

Conclusion: 2D SMS gradient-echo imaging can serve as an alternative to often used 3D imaging to obtain susceptibility-contrast-weighted images, with an advantage of providing better image contrast and MS lesion sensitivity.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219705PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636815PMC
March 2020

Hippocampal CA1 subfield predicts episodic memory impairment in Parkinson's disease.

Neuroimage Clin 2019 18;23:101824. Epub 2019 Apr 18.

Department of Neurology and Neurological Sciences, Stanford University, 300 Pasteur Dr. Room H3144, MC 5235, Stanford, CA 94305, United States of America; Department of Neurosurgery, Stanford University, 300 Pasteur Dr. Room H3144, MC 5235, Stanford, CA 94305, United States of America. Electronic address:

Objective: Parkinson's disease (PD) episodic memory impairments are common; however, it is not known whether these impairments are due to hippocampal pathology. Hippocampal Lewy-bodies emerge by Braak stage 4, but are not uniformly distributed. For instance, hippocampal CA1 Lewy-body pathology has been specifically associated with pre-mortem episodic memory performance in demented patients. By contrast, the dentate gyrus (DG) is relatively free of Lewy-body pathology. In this study, we used ultra-high field 7-Tesla to measure hippocampal subfields in vivo and determine if these measures predict episodic memory impairment in PD during life.

Methods: We studied 29 participants with PD (age 65.5 ± 7.8 years; disease duration 4.5 ± 3.0 years) and 8 matched-healthy controls (age 67.9 ± 6.8 years), who completed comprehensive neuropsychological testing and MRI. With 7-Tesla MRI, we used validated segmentation techniques to estimate CA1 stratum pyramidale (CA1-SP) and stratum radiatum lacunosum moleculare (CA1-SRLM) thickness, dentate gyrus/CA3 (DG/CA3) area, and whole hippocampus area. We used linear regression, which included imaging and clinical measures (age, duration, education, gender, and CSF), to determine the best predictors of episodic memory impairment in PD.

Results: In our cohort, 62.1% of participants with PD had normal cognition, 27.6% had mild cognitive impairment, and 10.3% had dementia. Using 7-Tesla MRI, we found that smaller CA1-SP thickness was significantly associated with poorer immediate memory, delayed memory, and delayed cued memory; by contrast, whole hippocampus area, DG/CA3 area, and CA1-SRLM thickness did not significantly predict memory. Age-adjusted linear regression models revealed that CA1-SP predicted immediate memory (beta[standard error]10.895[4.215], p < .05), delayed memory (12.740[5.014], p < .05), and delayed cued memory (12.801[3.991], p < .05). In the fully-adjusted models, which included all five clinical measures as covariates, only CA1-SP remained a significant predictor of delayed cued memory (13.436[4.651], p < .05).

Conclusions: In PD, we found hippocampal CA1-SP subfield thickness estimated on 7-Tesla MRI scans was the best predictor of episodic memory impairment, even when controlling for confounding clinical measures. Our results imply that ultra-high field imaging could be a sensitive measure to identify changes in hippocampal subfields and thus probe the neuroanatomical underpinnings of episodic memory impairments in patients with PD.
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http://dx.doi.org/10.1016/j.nicl.2019.101824DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6500913PMC
April 2020

Longitudinal Changes in Hippocampal Subfield Volume Associated with Collegiate Football.

J Neurotrauma 2019 10 17;36(19):2762-2773. Epub 2019 Jun 17.

Department of Radiology, Stanford University, Stanford, California.

Collegiate football athletes are subject to repeated traumatic brain injuriesthat may cause brain injury. The hippocampus is composed of several distinct subfields with possible differential susceptibility to injury. The aim of this study is to determine whether there are longitudinal changes in hippocampal subfield volume in collegiate football. A prospective cohort study was conducted over a 5-year period tracking 63 football and 34 volleyball male collegiate athletes. Athletes underwent high-resolution structural magnetic resonance imaging, and automated segmentation provided hippocampal subfield volumes. At baseline, football ( = 59) athletes demonstrated a smaller subiculum volume than volleyball ( = 32) athletes (-67.77 mm;  = 0.012). A regression analysis performed within football athletes similarly demonstrated a smaller subiculum volume among those at increased concussion risk based on athlete position ( = 0.001). For the longitudinal analysis, a linear mixed-effects model assessed the interaction between sport and time, revealing a significant decrease in cornu ammonis area 1 (CA1) volume in football ( = 36) athletes without an in-study concussion compared to volleyball ( = 23) athletes (volume difference per year = -35.22 mm;  = 0.005). This decrease in CA1 volume over time was significant when football athletes were examined in isolation from volleyball athletes ( = 0.011). Thus, this prospective, longitudinal study showed a decrease in CA1 volume over time in football athletes, in addition to baseline differences that were identified in the downstream subiculum. Hippocampal changes may be important to study in high-contact sports.
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http://dx.doi.org/10.1089/neu.2018.6357DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872005PMC
October 2019

Stability of Blood Biomarkers of Traumatic Brain Injury.

J Neurotrauma 2019 08 7;36(16):2407-2416. Epub 2019 May 7.

1Department of Radiology, Stanford University, Stanford, California.

Blood biomarker tests were recently approved for clinical diagnosis of traumatic brain injury (TBI), yet there are still fundamental questions that need attention. One such question is the stability of putative biomarkers in blood over the course of several days after injury if the sample is unable to be processed into serum or plasma and stored at low temperatures. Blood may not be able to be stored at ultra-low temperatures in austere combat or sports environments. In this prospective study of 20 adult patients with positive head computed tomography imaging findings, the stability of three biomarkers (glial fibrillary acidic protein [GFAP], ubiquitin C-terminal hydrolase-L1 [UCH-L1], and S100 calcium binding protein B [S100B]) in whole blood and in serum stored at 4-5°C was evaluated over the course of 72 h after blood collection. The amount of time whole blood and serum were refrigerated had no significant effect on GFAP concentration in plasma obtained from whole blood and in serum ( = 0.6256 and  = 0.3687, respectively), UCH-L1 concentration in plasma obtained from whole blood and in serum ( = 0.0611 and  = 0.5189, respectively), and S100B concentration in serum ( = 0.4663). Concentration levels of GFAP, UCH-L1, and S100B in blood collected from patients with TBI were found to be stable at 4-5°C for at least 3 days after blood draw. This study suggests that the levels of the three diagnostic markers above are still valid for diagnostic TBI tests if the sample is stored in 4-5°C refrigerated conditions.
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http://dx.doi.org/10.1089/neu.2018.6053DOI Listing
August 2019

Lateral impacts correlate with falx cerebri displacement and corpus callosum trauma in sports-related concussions.

Biomech Model Mechanobiol 2019 Jun 12;18(3):631-649. Epub 2019 Mar 12.

Department of Mechanical Engineering, Stanford University, Stanford, CA, 94305, USA.

Corpus callosum trauma has long been implicated in mild traumatic brain injury (mTBI), yet the mechanism by which forces penetrate this structure is unknown. We investigated the hypothesis that coronal and horizontal rotations produce motion of the falx cerebri that damages the corpus callosum. We analyzed previously published head kinematics of 115 sports impacts (2 diagnosed mTBI) measured with instrumented mouthguards and used finite element (FE) simulations to correlate falx displacement with corpus callosum deformation. Peak coronal accelerations were larger in impacts with mTBI (8592 rad/s avg.) than those without (1412 rad/s avg.). From FE simulations, coronal acceleration was strongly correlated with deep lateral motion of the falx center (r = 0.85), while horizontal acceleration was correlated with deep lateral motion of the falx periphery (r > 0.78). Larger lateral displacement at the falx center and periphery was correlated with higher tract-oriented strains in the corpus callosum body (r = 0.91) and genu/splenium (r > 0.72), respectively. The relationship between the corpus callosum and falx was unique: removing the falx from the FE model halved peak strains in the corpus callosum from 35% to 17%. Consistent with model results, we found indications of corpus callosum trauma in diffusion tensor imaging of the mTBI athletes. For a measured alteration of consciousness, depressed fractional anisotropy and increased mean diffusivity indicated possible damage to the mid-posterior corpus callosum. Our results suggest that the corpus callosum may be sensitive to coronal and horizontal rotations because they drive lateral motion of a relatively stiff membrane, the falx, in the direction of commissural fibers below.
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http://dx.doi.org/10.1007/s10237-018-01106-0DOI Listing
June 2019

RNA-Sequencing Analysis Revealed a Distinct Motor Cortex Transcriptome in Spontaneously Recovered Mice After Stroke.

Stroke 2018 09;49(9):2191-2199

From the Department of Neurosurgery (M.I., M.A., S.I., Z.C., E.H.W., S.L.L., D.L.S., M.Y.C., G.K.S.).

Background and Purpose- Many restorative therapies have been used to study brain repair after stroke. These therapeutic-induced changes have revealed important insights on brain repair and recovery mechanisms; however, the intrinsic changes that occur in spontaneously recovery after stroke is less clear. The goal of this study is to elucidate the intrinsic changes in spontaneous recovery after stroke, by directly investigating the transcriptome of primary motor cortex in mice that naturally recovered after stroke. Methods- Male C57BL/6J mice were subjected to transient middle cerebral artery occlusion. Functional recovery was evaluated using the horizontal rotating beam test. A novel in-depth lesion mapping analysis was used to evaluate infarct size and locations. Ipsilesional and contralesional primary motor cortices (iM1 and cM1) were processed for RNA-sequencing transcriptome analysis. Results- Cluster analysis of the stroke mice behavior performance revealed 2 distinct recovery groups: a spontaneously recovered and a nonrecovered group. Both groups showed similar lesion profile, despite their differential recovery outcome. RNA-sequencing transcriptome analysis revealed distinct biological pathways in the spontaneously recovered stroke mice, in both iM1 and cM1. Correlation analysis revealed that 38 genes in the iM1 were significantly correlated with improved recovery, whereas 74 genes were correlated in the cM1. In particular, ingenuity pathway analysis highlighted the involvement of cAMP signaling in the cM1, with selective reduction of Adora2a (adenosine receptor A2A), Drd2 (dopamine receptor D2), and Pde10a (phosphodiesterase 10A) expression in recovered mice. Interestingly, the expressions of these genes in cM1 were negatively correlated with behavioral recovery. Conclusions- Our RNA-sequencing data revealed a panel of recovery-related genes in the motor cortex of spontaneously recovered stroke mice and highlighted the involvement of contralesional cortex in spontaneous recovery, particularly Adora2a, Drd2, and Pde10a-mediated cAMP signaling pathway. Developing drugs targeting these candidates after stroke may provide beneficial recovery outcome.
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http://dx.doi.org/10.1161/STROKEAHA.118.021508DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6205731PMC
September 2018

Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor.

Neuroimage Clin 2018 9;19:572-580. Epub 2018 May 9.

Department of Radiology, Stanford University, Stanford, CA, United States.

Purpose: To evaluate the use of diffusion magnetic resonance imaging (MRI) tractography for neurosurgical guidance of transcranial MRI-guided focused ultrasound (tcMRgFUS) thalamotomy for essential tremor (ET).

Materials And Methods: Eight patients with medication-refractory ET were treated with tcMRgFUS targeting the ventral intermediate nucleus (Vim) of the thalamus contralateral to their dominant hand. Diffusion and structural MRI data and clinical evaluations were acquired pre-treatment and post-treatment. To identify the optimal target location, tractography was performed on pre-treatment diffusion MRI data between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus. The tractography-identified locations were compared to the lesion location delineated on 1 year post-treatment T-weighted MR image. Their overlap was correlated with the clinical outcomes measured by the percentage change of the Clinical Rating Scale for Tremor scores acquired pre-treatment, as well as 1 month, 3 months, 6 months and 1 year post-treatment.

Results: The probabilistic tractography was consistent from subject-to-subject and followed the expected anatomy of the thalamocortical radiation and the dentatothalamic tract. Higher overlap between the tractography-identified location and the tcMRgFUS treatment-induced lesion highly correlated with better treatment outcome (r = -0.929, -0.75, -0.643, p = 0.00675, 0.0663, 0.139 for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex, the entire ipsilateral motor cortex and the contralateral dentate nucleus, respectively, at 1 year post-treatment). The correlation for the tractography between the treated thalamus and the hand-knob region of the ipsilateral motor cortex is the highest for all time points (r = -0.719, -0.976, -0.707, -0.929, p = 0.0519, 0.000397, 0.0595, 0.00675 at 1 month, 3 months, 6 months and 1 year post-treatment, respectively).

Conclusion: Our data support the use of diffusion tractography as a complementary approach to current targeting methods for tcMRgFUS thalamotomy.
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http://dx.doi.org/10.1016/j.nicl.2018.05.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6029558PMC
January 2019