Publications by authors named "Michael Zeineh"

Brain deformation caused by a head impact leads to traumatic brain injury (TBI). The maximum principal strain (MPS) was used to measure the extent of brain deformation and predict injury, and the recent evidence has indicated that incorporating the maximum principal strain rate (MPSR) and the product of MPS and MPSR, denoted as MPS × SR, enhances the accuracy of TBI prediction. However, ambiguities have arisen about the calculation of MPSR.

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Article Synopsis
  • Olfactory dysfunction may signal early stages of Alzheimer's disease (AD), prompting research into the piriform cortex using tau PET-MR imaging.
  • A study of 94 older adults revealed increased tau uptake in the piriform cortex correlating with disease severity, particularly in those with Alzheimer’s compared to amyloid-negative controls.
  • The results indicate heightened tau levels in AD and mild cognitive impairment, connecting greater piriform uptake with poorer memory performance, while no significant changes were observed in cognitively unimpaired Parkinson's disease.
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Introduction: Amyloid positron emission tomography (PET) acquisition timing impacts quantification.

Methods: In florbetaben (FBB) PET scans of 245 adults with and without cognitive impairment, we investigated the impact of post-injection acquisition time on Centiloids (CLs) across five reference regions. CL equations for FBB were derived using standard methods, using FBB data collected between 90 and 110 min with paired Pittsburgh compound B data.

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Objective: Wearable devices are developed to measure head impact kinematics but are intrinsically noisy because of the imperfect interface with human bodies. This study aimed to improve the head impact kinematics measurements obtained from instrumented mouthguards using deep learning to enhance traumatic brain injury (TBI) risk monitoring.

Methods: We developed one-dimensional convolutional neural network (1D-CNN) models to denoise mouthguard kinematics measurements for tri-axial linear acceleration and tri-axial angular velocity from 163 laboratory dummy head impacts.

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Detailed knowledge of the brain's nerve fiber network is crucial for understanding its function in health and disease. However, mapping fibers with high resolution remains prohibitive in most histological sections because state-of-the-art techniques are incompatible with their preparation. Here, we present a micron-resolution light-scattering-based technique that reveals intricate fiber networks independent of sample preparation for extended fields of view.

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Background: Dynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features.

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Objective: The machine-learning head model (MLHM) to accelerate the calculation of brain strain and strain rate, which are the predictors for traumatic brain injury (TBI), but the model accuracy was found to decrease sharply when the training/test datasets were from different head impacts types (i.e., car crash, college football), which limits the applicability of MLHMs to different types of head impacts and sports.

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Cerebral blood flow (CBF) may be estimated from early-frame PET imaging of lipophilic tracers, such as amyloid agents, enabling measurement of this important biomarker in participants with dementia and memory decline. Although previous methods could map relative CBF, quantitative measurement in absolute units (mL/100 g/min) remained challenging and has not been evaluated against the gold standard method of [O]water PET. The purpose of this study was to develop and validate a minimally invasive quantitative CBF imaging method combining early [F]florbetaben (eFBB) with phase-contrast MRI using simultaneous PET/MRI.

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Background: At the center of the cortical cholinergic network, the nucleus basalis of Meynert (NBM) is crucial for the cognitive domains most vulnerable in PD. Preclinical evidence has demonstrated the positive impact of NBM deep brain stimulation (DBS) on cognition but early human trials have had mixed results. It is possible that DBS of the lateral NBM efferent white matter fiber bundle may be more effective at improving cognitive-motor function.

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Background And Objectives: Repeated impacts in high-contact sports such as American football can affect the brain's microstructure, which can be studied using diffusion MRI. Most imaging studies are cross-sectional, do not include low-contact players as controls, or lack advanced tract-specific microstructural metrics. We aimed to investigate longitudinal changes in high-contact collegiate athletes compared with low-contact controls using advanced diffusion MRI and automated fiber quantification.

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Machine learning head models (MLHMs) are developed to estimate brain deformation for early detection of traumatic brain injury (TBI). However, the overfitting to simulated impacts and the lack of generalizability caused by distributional shift of different head impact datasets hinders the broad clinical applications of current MLHMs. We propose brain deformation estimators that integrates unsupervised domain adaptation with a deep neural network to predict whole-brain maximum principal strain (MPS) and MPS rate (MPSR).

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Objective: Repetitive head trauma is common in high-contact sports. Cerebral blood flow (CBF) can measure changes in brain perfusion that could indicate injury. Longitudinal studies with a control group are necessary to account for interindividual and developmental effects.

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Disentangling human brain connectivity requires an accurate description of nerve fiber trajectories, unveiled via detailed mapping of axonal orientations. However, this is challenging because axons can cross one another on a micrometer scale. Diffusion magnetic resonance imaging (dMRI) can be used to infer axonal connectivity because it is sensitive to axonal alignment, but it has limited spatial resolution and specificity.

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Article Synopsis
  • Myelinated axons transmit signals in the brain through action potentials, but accurately mapping their crossing paths is challenging due to influence from unrelated brain structures.
  • Small-angle X-ray scattering (SAXS) can specifically detect myelinated axons by identifying distinct peaks in their scattering patterns, allowing for better resolution of fiber crossings.
  • The study demonstrates SAXS's effectiveness in various brain samples and positions it as a reliable tool for validating fiber orientations obtained from other imaging techniques like diffusion MRI and microscopy.
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  • The study investigated how different types of head impacts (like those from football, MMA, and car crashes) affect brain injury risk, focusing on their spectral characteristics.
  • Researchers analyzed over 3,000 head impacts using a machine-learning classifier that accurately identified impact types with a median accuracy of 96%.
  • The findings revealed that impact types have distinct spectral density profiles, which can help improve brain injury prediction models and enhance the understanding of impact dynamics in sports and safety systems.
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Protective headgear effects measured in the laboratory may not always translate to the field. In this study, we evaluated the impact attenuation capabilities of a commercially available padded helmet shell cover in the laboratory and on the field. In the laboratory, we evaluated the padded helmet shell cover's efficacy in attenuating impact magnitude across six impact locations and three impact velocities when equipped to three different helmet models.

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Emotional states influence bodily physiology, as exemplified in the top-down process by which anxiety causes faster beating of the heart. However, whether an increased heart rate might itself induce anxiety or fear responses is unclear. Physiological theories of emotion, proposed over a century ago, have considered that in general, there could be an important and even dominant flow of information from the body to the brain.

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In a previous study, we found that the relationship between brain strain and kinematic features cannot be described by a generalized linear model across different types of head impacts. In this study, we investigate if such a linear relationship exists when partitioning head impacts using a data-driven approach. We applied the K-means clustering method to partition 3161 impacts from various sources including simulation, college football, mixed martial arts, and car crashes.

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Alzheimer's disease (AD) is a debilitating brain disorder that afflicts millions worldwide with no effective treatment. Currently, AD progression has primarily been characterized by abnormal accumulations of β-amyloid within plaques and phosphorylated tau within neurofibrillary tangles, giving rise to neurodegeneration due to synaptic and neuronal loss. While β-amyloid and tau deposition are required for clinical diagnosis of AD, presence of such abnormalities does not tell the complete story, and the actual mechanisms behind neurodegeneration in AD progression are still not well understood.

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The medial temporal lobe (MTL) is a complex anatomic region encompassing the hippocampal formation, parahippocampal region, and amygdaloid complex. To enable the reader to understand the well-studied regional anatomic relationships and cytoarchitecture that form the basis of functional connectivity, the authors have created a detailed yet approachable anatomic reference for clinicians and scientists, with special attention to MR imaging. They have focused primarily on the hippocampal formation, discussing its gross structural features, anatomic relationships, and subfield anatomy and further discuss hippocampal terminology and development, hippocampal connectivity, normal anatomic variants, clinically relevant disease processes, and automated hippocampal segmentation software.

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Objective: We explore the possibility of using diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) to discern microstructural abnormalities in the hippocampus indicative of mesial temporal sclerosis (MTS) at the subfield level.

Methods: We analyzed data from 57 patients with refractory epilepsy who previously underwent 3.0-T magnetic resonance imaging (MRI) including DTI as a standard part of presurgical workup.

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Background: The resective surgery plus responsive neurostimulation (RNS) system is an effective treatment for patients with refractory focal epilepsy. Furthermore, the long-term intracranial electroencephalography data provided by the system can inform a future resection or ablation procedure. RNS patients may undergo 1.

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In recent years, transcranial magnetic resonance-guided focused ultrasound (tcMRgFUS) has been established as a potential treatment option for movement disorders, including essential tremor (ET). So far, however, little is known about the impact of tcMRgFUS on structural connectivity. The objective of this study was to detect microstructural changes in tremor- and motor-related white matter tracts in ET patients treated with tcMRgFUS thalamotomy.

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