4,180 results match your criteria: "Athinoula A. Martinos Center for Biomedical Imaging[Affiliation]"

Although evaluation of disorders of consciousness (DoC) following brain injury has traditionally relied on bedside behavioral examination, advances in neurotechnology have elucidated novel approaches to detecting and predicting recovery of consciousness. Professional society guidelines now recommend that clinicians integrate these neurotechnologies into clinical practice as part of multimodal evaluations for some patients with DoC but have not crafted concrete protocols for this translation. Little is known about the experiences and ethical perspectives held by key stakeholder groups around the clinical implementation of advanced neurotechnologies to detect and predict recovery of consciousness.

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The Effect of Pexidartinib on Neuropathic Pain via Influences on Microglia and Neuroinflammation in Mice.

Anesth Analg

October 2024

Genetics and Aging Research Unit, Department of Neurology, McCance Center for Brain Health, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts.

Background: Chronic pain is a debilitating medical condition that lacks effective treatments. Increasing evidence suggests that microglia and neuroinflammation underlie pain pathophysiology, which therefore supports a potential strategy for developing pain therapeutics. Here, our study is testing the hypothesis that the promise of pain amelioration can be achieved using the small-molecule pexidartinib (PLX-3397), a previously food and drug administration (FDA)-approved cancer medicine and a colony-stimulating factor-1 receptor (CSF-1R) inhibitor that display microglia-depleting properties.

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Clinical Implementation of fMRI and EEG to Detect Cognitive Motor Dissociation: Lessons Learned in an Acute Care Hospital.

Neurol Clin Pract

February 2025

Center for Neurotechnology and Neurorecovery (YGB, MF, HJF, WRS, AM, PKL, DF, LRH, SSC, MJY, BLE), Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA; Department of Physical Medicine and Rehabilitation (YGB), Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA; Geisel School of Medicine at Dartmouth Medical School College (WRS), Hanover, NH; Athinoula A. Martinos Center for Biomedical Imaging (JEK, BLE), Massachusetts General Hospital, Charlestown, MA; Department of Radiology (JEK, JHH, PWS, OR), Massachusetts General Hospital and Harvard Medical School, Boston, MA; Department of Neurology (DF), Hospital of the University of Pennsylvania, Philadelphia, PA; and Departments of Neurology (JC) and Medicine (ER), Massachusetts General Hospital and Harvard Medical School, Boston, MA.

Article Synopsis
  • Cognitive motor dissociation (CMD) involves patients who can follow commands in brain scans like fMRI, despite showing no behavioral signs of language function, highlighting the importance of accurate diagnosis in severe brain injuries.
  • Recent findings outline a structured approach for assessing CMD at clinical institutions, underlining the need for ethical considerations, standardized protocols, and effective communication of results.
  • The proposed method for CMD assessment aims to be adaptable, allowing for updates and improvements as more evidence becomes available in the field.
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Revealing membrane integrity and cell size from diffusion kurtosis time dependence.

Magn Reson Med

March 2025

Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.

Purpose: The nonmonotonic dependence of diffusion kurtosis on diffusion time has been observed in biological tissues, yet its relation to membrane integrity and cellular geometry remains to be clarified. Here we establish and explain the characteristic asymmetric shape of the kurtosis peak. We also derive the relation between the peak time , when kurtosis reaches its maximum, and tissue parameters.

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Comparing Commercial and Open-Source Large Language Models for Labeling Chest Radiograph Reports.

Radiology

October 2024

From the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 Thirteenth St, Charlestown, MA 02129 (F.J.D., T.R.B., M.C.C., A.E.K., C.P.B.); Department of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Berlin, Germany (F.J.D., L.D., F.A.M., F.B., L.J.); Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Mass (L.J.); Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany (L.C.A.); Mass General Brigham Data Science Office, Boston, Mass (J.S., T.S., C.P.B.); Microsoft Health and Life Sciences (HLS), Redmond, Wash (J.M.); Klinikum rechts der Isar, Technical University of Munich, Munich, Germany (K.K.B.); Department of Radiology and Nuclear Medicine, German Heart Center Munich, Munich, Germany (K.K.B.); and Department of Cardiovascular Radiology and Nuclear Medicine, Technical University of Munich, School of Medicine and Health, German Heart Center, TUM University Hospital, Munich, Germany (K.K.B.).

Article Synopsis
  • Advances in large language models (LLMs) have led to numerous commercial and open-source models, but there has been no real-world comparison of OpenAI's GPT-4 against these models for extracting information from radiology reports.
  • The study aimed to compare GPT-4 with several leading open-source LLMs in extracting relevant findings from chest radiograph reports using datasets from the ImaGenome and Massachusetts General Hospital.
  • Results showed that GPT-4 slightly outperformed the best open-source model, Llama 2-70B, in terms of accuracy scores, with both showing strong performance in extracting findings from the reports.
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Latent change-on-change between amyloid accumulation and cognitive decline.

Alzheimers Dement

December 2024

Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Article Synopsis
  • The study investigates the relationship between changes in β-amyloid (Aβ) levels and cognitive decline over time, highlighting that Aβ accumulation is linked to subsequent cognitive deterioration in older adults.
  • Researchers utilized sophisticated statistical models on data from a long-term study of 352 cognitively normal older participants, revealing that short-term changes in Aβ are more impactful on cognition than traditional measurements of Aβ burden and tau levels.
  • Contrary to previous findings, the study found no significant link between tau levels in the medial temporal lobe and cognitive performance, suggesting that understanding cognitive decline requires looking at dynamic changes rather than static measures.
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Thematic analysis of cardiac arrest survivors' and their caregivers' psychosocial intervention needs.

Gen Hosp Psychiatry

October 2024

Center for Health Outcomes and Interdisciplinary Research, Department of Psychiatry, Massachusetts General Hospital, 1 Bowdoin Sq, Suite 100, Boston, MA, 02114, United States; Department of Psychiatry, Harvard Medical School, 1 Bowdoin Sq, Suite 100, Boston, MA, 02114, United States.

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The Development and Evaluation of a Novel Highly Selective PET Radiotracer for Targeting BET BD1.

Pharmaceuticals (Basel)

September 2024

Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.

Small molecules that interfere with the interaction between acetylated protein tails and the tandem bromodomains of BET (bromodomain and extra-terminal) family proteins are pivotal in modulating immune/inflammatory and neoplastic diseases. This study aimed to develop a novel PET imaging tracer, [C]GSK023, that targets the N-terminal bromodomain (BD1) of BET family proteins with high selectivity and potency, thereby enriching the chemical probe toolbox for epigenetic imaging. [C]GSK023, a radio-chemical probe, was designed and synthesized to specifically target the BET BD1.

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The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative.

Brain Commun

October 2024

Radiology, Pathology and Laboratory Medicine, Physics and Astronomy, International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, Canada, BC V6T 1Z4.

The use of ultra-high-field 7-Tesla (7T) MRI in multiple sclerosis (MS) research has grown significantly over the past two decades. With recent regulatory approvals of 7T scanners for clinical use in 2017 and 2020, the use of this technology for routine care is poised to continue to increase in the coming years. In this context, the North American Imaging in MS Cooperative (NAIMS) convened a workshop in February 2023 to review the previous and current use of 7T technology for MS research and potential future research and clinical applications.

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Better Together: Integrating Multivariate with Univariate Methods, and MEG with EEG to Study Language Comprehension.

Lang Cogn Neurosci

June 2023

Department of Psychiatry and the Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA.

We used MEG and EEG to examine the effects of Plausibility ( vs. ) and Animacy ( vs. ) on activity to incoming words during language comprehension.

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Article Synopsis
  • C-PBR28 PET imaging and paramagnetic rim lesions (PRL) are both potential markers for assessing chronic inflammation in multiple sclerosis (MS), but there's no agreed-upon best option between them.
  • In a study with 30 MS patients, less than half of the non-PRL white matter lesions were found to be active according to C-PBR28 PET imaging, and both marker types showed similar levels of microstructural integrity but were distinct in their correlation with disability measures.
  • C-PBR28 PET proved to be more effective in identifying active lesions compared to PRL assessments, with the volume of whole active lesions being the strongest predictor of neurological impairment as measured by the Expanded Disability Status Scale.
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Reorganization of integration and segregation networks in brain-based visual impairment.

Neuroimage Clin

November 2024

Harvard Medical School, Boston, MA, USA; Department of Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USA; Laboratory for Visual Neuroplasticity, Massachusetts Eye and Ear, Boston, MA, USA. Electronic address:

Article Synopsis
  • Growing evidence shows that the brain's connectivity changes based on development and environment, but the effects of early neurological injury on visual impairment (CVI) are not fully understood.
  • This study used advanced imaging techniques to compare brain connectivity in individuals with CVI to neurotypical controls, revealing reduced grey matter volume in key visual processing areas and significant changes in how different brain regions connect.
  • Participants with CVI had increased integration of visual information with sensory and multimodal areas, along with decreased connectivity to areas linked to emotional processing and default activities, providing insights into how early brain injury impacts visual function and overall brain organization.
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Purpose: To develop a single-shot SNR-efficient distortion-free multi-echo imaging technique for dynamic imaging applications.

Methods: Echo planar time-resolved imaging (EPTI) was first introduced as a multi-shot technique for distortion-free multi-echo imaging. This work aims to develop single-shot EPTI (ss-EPTI) to achieve improved robustness to motion/physiological noise, increased temporal resolution, and higher SNR efficiency.

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Study Objectives: Disrupted nighttime sleep (DNS) is common in pediatric Narcolepsy type 1, yet its cognitive impact is unknown. As N2 sleep spindles are necessary for sleep-dependent memory consolidation, we hypothesized that Narcolepsy Type 1 impairs memory consolidation via N2 sleep fragmentation and N2 sleep spindle alterations.

Methods: We trained 28 pediatric Narcolepsy Type 1 participants and 27 healthy controls (HC) on a spatial declarative memory task before a nocturnal in-lab polysomnogram and then gave them a cued recall test upon awakening in the morning.

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Article Synopsis
  • Combining MRI and EEG offers a comprehensive way to study brain function, but existing EEG nets limit the quality of simultaneous imaging due to radiofrequency interference.
  • The study tested the Inknet2, a new high-resistance EEG net using conductive ink, which showed potential to minimize artifacts and maintain image quality across various MRI sequences.
  • Results indicated that Inknet2 produced fewer artifacts than traditional nets and achieved comparable image quality to scans without any net, making it a promising tool for high-quality brain imaging.
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Alpha (8-12 Hz) frequency band oscillations are among the most informative features in electroencephalographic (EEG) assessment of patients with disorders of consciousness (DoC). Because interareal alpha synchrony is thought to facilitate long-range communication in healthy brains, coherence measures of resting-state alpha oscillations may provide insights into a patient's capacity for higher-order cognition beyond channel-wise estimates of alpha power. In multi-channel EEG, global coherence methods may be used to augment standard spectral analysis methods by both estimating the strength and identifying the structure of coherent oscillatory networks.

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Motion artifacts are a pervasive problem in MRI, leading to misdiagnosis or mischaracterization in population-level imaging studies. Current retrospective rigid intra-slice motion correction techniques jointly optimize estimates of the image and the motion parameters. In this paper, we use a deep network to reduce the joint image-motion parameter search to a search over rigid motion parameters alone.

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The brainstem is a fundamental component of the central nervous system, yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex.

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Article Synopsis
  • Research aims to identify how tau PET imaging correlates with clinical decline in atypical Alzheimer's disease (AD) to improve patient care.
  • Despite known tau accumulation in atypical AD, its predictive value for clinical decline is still uncertain.
  • Findings show tau levels in the default mode network are strong predictors of decline, outperforming other clinical and imaging factors in patients with atypical AD.
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Introduction: Cortical thinning is well-documented in individuals with amyotrophic lateral sclerosis (ALS), yet its association with speech deterioration remains understudied. This study characterizes anatomical changes in the brain within the context of speech impairment patterns in individuals with ALS, providing insight into the disease's multiregional spread and biology.

Methods: To evaluate patterns of cortical thickness in speakers with ALS with and without functional speech changes compared to healthy controls (HCs) using whole-brain and region of interest (ROI) analyses.

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Article Synopsis
  • By age 40, over 90% of adults with Down syndrome develop Alzheimer’s disease, with many progressing to dementia, despite having few typical vascular risk factors.
  • This study analyzed how small vessel cerebrovascular disease impacts Alzheimer's disease progression and neurodegeneration in adults with Down syndrome, using MRI and plasma biomarker data from 185 participants.
  • Results indicated a complex relationship where white matter hyperintensity (WMH) levels influenced phosphorylated tau, linked by glial fibrillary acidic protein, suggesting that cerebrovascular health affects Alzheimer’s pathology in this population.
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Prediction of stroke severity: systematic evaluation of lesion representations.

Ann Clin Transl Neurol

December 2024

Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Article Synopsis
  • The study aimed to identify which imaging features can best predict poststroke deficits by analyzing data from three different patient groups who experienced acute strokes.
  • It was found that models trained on small datasets performed well within their own dataset but failed to generalize to new patient data; however, using larger and multicenter datasets significantly improved predictive performance.
  • Including structural and functional disconnection in the models yielded better predictions of stroke severity compared to relying solely on lesion volume or location.
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Physics-guided self-supervised learning: Demonstration for generalized RF pulse design.

Magn Reson Med

February 2025

Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.

Purpose: To introduce a new method for generalized RF pulse design using physics-guided self-supervised learning (GPS), which uses the Bloch equations as the guiding physics model.

Theory And Methods: The GPS framework consists of a neural network module and a physics module, where the physics module is a Bloch simulator for MRI applications. For RF pulse design, the neural network module maps an input target profile to an RF pulse, which is subsequently loaded into the physics module.

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