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Brackenier Y, Cordero-Grande L, McElroy S, Tomi-Tricot R, Barbaroux H, Bridgen P, Malik SJ, Hajnal JV. Sequence-agnostic motion-correction leveraging efficiently calibrated Pilot Tone signals. Magn Reson Med 2024; 92:1881-1897. [PMID: 38860530 DOI: 10.1002/mrm.30161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/18/2024] [Accepted: 05/07/2024] [Indexed: 06/12/2024]
Abstract
PURPOSE This study leverages externally generated Pilot Tone (PT) signals to perform motion-corrected brain MRI for sequences with arbitrary k-space sampling and image contrast. THEORY AND METHODS PT signals are promising external motion sensors due to their cost-effectiveness, easy workflow, and consistent performance across contrasts and sampling patterns. However, they lack robust calibration pipelines. This work calibrates PT signal to rigid motion parameters acquired during short blocks (˜4 s) of motion calibration (MC) acquisitions, which are short enough to unobstructively fit between acquisitions. MC acquisitions leverage self-navigated trajectories that enable state-of-the-art motion estimation methods for efficient calibration. To capture the range of patient motion occurring throughout the examination, distributed motion calibration (DMC) uses data acquired from MC scans distributed across the entire examination. After calibration, PT is used to retrospectively motion-correct sequences with arbitrary k-space sampling and image contrast. Additionally, a data-driven calibration refinement is proposed to tailor calibration models to individual acquisitions. In vivo experiments involving 12 healthy volunteers tested the DMC protocol's ability to robustly correct subject motion. RESULTS The proposed calibration pipeline produces pose parameters consistent with reference values, even when distributing only six of these approximately 4-s MC blocks, resulting in a total acquisition time of 22 s. In vivo motion experiments reveal significant (p < 0.05 $$ p<0.05 $$ ) improved motion correction with increased signal to residual ratio for both MPRAGE and SPACE sequences with standard k-space acquisition, especially when motion is large. Additionally, results highlight the benefits of using a distributed calibration approach. CONCLUSIONS This study presents a framework for performing motion-corrected brain MRI in sequences with arbitrary k-space encoding and contrast, using externally generated PT signals. The DMC protocol is introduced, promoting observation of patient motion occurring throughout the examination and providing a calibration pipeline suitable for clinical deployment. The method's application is demonstrated in standard volumetric MPRAGE and SPACE sequences.
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Affiliation(s)
- Yannick Brackenier
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Lucilio Cordero-Grande
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BNN, ISCIII, Madrid, Spain
| | - Sarah McElroy
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Raphael Tomi-Tricot
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Hugo Barbaroux
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Philippa Bridgen
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Shaihan J Malik
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Joseph V Hajnal
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
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2
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Hewlett M, Petrov I, Johnson PM, Drangova M. Deep-learning-based motion correction using multichannel MRI data: a study using simulated artifacts in the fastMRI dataset. NMR IN BIOMEDICINE 2024; 37:e5179. [PMID: 38808752 DOI: 10.1002/nbm.5179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 04/21/2024] [Accepted: 04/29/2024] [Indexed: 05/30/2024]
Abstract
Deep learning presents a generalizable solution for motion correction requiring no pulse sequence modifications or additional hardware, but previous networks have all been applied to coil-combined data. Multichannel MRI data provide a degree of spatial encoding that may be useful for motion correction. We hypothesize that incorporating deep learning for motion correction prior to coil combination will improve results. A conditional generative adversarial network was trained using simulated rigid motion artifacts in brain images acquired at multiple sites with multiple contrasts (not limited to healthy subjects). We compared the performance of deep-learning-based motion correction on individual channel images (single-channel model) with that performed after coil combination (channel-combined model). We also investigate simultaneous motion correction of all channel data from an image volume (multichannel model). The single-channel model significantly (p < 0.0001) improved mean absolute error, with an average 50.9% improvement compared with the uncorrected images. This was significantly (p < 0.0001) better than the 36.3% improvement achieved by the channel-combined model (conventional approach). The multichannel model provided no significant improvement in quantitative measures of image quality compared with the uncorrected images. Results were independent of the presence of pathology, and generalizable to a new center unseen during training. Performing motion correction on single-channel images prior to coil combination provided an improvement in performance compared with conventional deep-learning-based motion correction. Improved deep learning methods for retrospective correction of motion-affected MR images could reduce the need for repeat scans if applied in a clinical setting.
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Affiliation(s)
- Miriam Hewlett
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - Ivailo Petrov
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Patricia M Johnson
- Department of Radiology, New York Medicine School of Medicine, New York, New York, USA
| | - Maria Drangova
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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3
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Christensen ZP, Freedman EG, Foxe JJ. Autism is associated with in vivo changes in gray matter neurite architecture. Autism Res 2024. [PMID: 39324563 DOI: 10.1002/aur.3239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 09/13/2024] [Indexed: 09/27/2024]
Abstract
Postmortem investigations in autism have identified anomalies in neural cytoarchitecture across limbic, cerebellar, and neocortical networks. These anomalies include narrow cell mini-columns and variable neuron density. However, difficulty obtaining sufficient post-mortem samples has often prevented investigations from converging on reproducible measures. Recent advances in processing magnetic resonance diffusion weighted images (DWI) make in vivo characterization of neuronal cytoarchitecture a potential alternative to post-mortem studies. Using extensive DWI data from the Adolescent Brain Cognitive Developmentsm (ABCD®) study 142 individuals with an autism diagnosis were compared with 8971 controls using a restriction spectrum imaging (RSI) framework that characterized total neurite density (TND), its component restricted normalized directional diffusion (RND), and restricted normalized isotropic diffusion (RNI). A significant decrease in TND was observed in autism in the right cerebellar cortex (β = -0.005, SE =0.0015, p = 0.0267), with significant decreases in RNI and significant increases in RND found diffusely throughout posterior and anterior aspects of the brain, respectively. Furthermore, these regions remained significant in post-hoc analysis when the autism sample was compared against a subset of 1404 individuals with other psychiatric conditions (pulled from the original 8971). These findings highlight the importance of characterizing neuron cytoarchitecture in autism and the significance of their incorporation as physiological covariates in future studies.
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Affiliation(s)
- Zachary P Christensen
- Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Edward G Freedman
- Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - John J Foxe
- Frederick J. and Marion A. Schindler Cognitive Neurophysiology Laboratory, The Del Monte Institute for Neuroscience, Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
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4
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MacIsaac MF, Wright JM, Vieux J, Rottgers SA, Halsey JN. Demystifying Velopharyngeal Dysfunction for Plastic Surgery Trainees Part 3: Objective Assessment and Surgical Decision-Making. J Craniofac Surg 2024:00001665-990000000-01917. [PMID: 39264201 DOI: 10.1097/scs.0000000000010607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 08/06/2024] [Indexed: 09/13/2024] Open
Abstract
Velopharyngeal dysfunction (VPD) is the inability to achieve proper closure of the velopharyngeal (VP) port, affecting speech and swallowing. After an auditory-perceptual speech evaluation by a speech-language pathologist, objective assessment of the VP port is required to determine the need for surgical intervention. This 3-part series provides a comprehensive discussion on (1) the anatomy and physiology of the velopharyngeal mechanism; (2) fundamental speech terminology and principles of perceptual speech assessment for VPD; and (3) techniques for objective evaluation of the VP port and surgical decision-making process. In part 3, the authors focus on the modalities for objective VP port assessment, including both direct and indirect methods. Direct imaging techniques such as videofluoroscopy, nasoendoscopy, and MRI are detailed for their strengths and limitations in visualizing VP port function and preoperative planning. Indirect assessments, including nasometry and aerodynamic measurements, are also briefly discussed. The decision-making process for surgical intervention is explored, emphasizing factors such as the severity and etiology of VPD, VP closure patterns, palatal length, orientation of the levator veli palatini, and other patient-specific considerations. The authors review the surgical options for repair including palatoplasty procedures (Furlow palatoplasty, straight-line intravelar veloplasty, and palatal lengthening buccal myomucosal flaps) and pharyngoplasty procedures (posterior pharyngeal flaps and sphincter pharyngoplasty), highlighting their indications, techniques, and potential complications. This series serves as an accessible resource, providing the foundational knowledge required for surgical trainees new to this topic.
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Affiliation(s)
- Molly F MacIsaac
- Division of Plastic and Reconstructive Surgery, Johns Hopkins All Children's Hospital, St. Petersburg, FL
| | - Joshua M Wright
- Division of Plastic and Reconstructive Surgery, Johns Hopkins All Children's Hospital, St. Petersburg, FL
| | - Jamilla Vieux
- Pediatric Speech-Language and Feeding Services, Johns Hopkins All Children's Hospital, St. Petersburg, FL
| | - S Alex Rottgers
- Division of Plastic and Reconstructive Surgery, Johns Hopkins All Children's Hospital, St. Petersburg, FL
| | - Jordan N Halsey
- Division of Plastic and Reconstructive Surgery, Johns Hopkins All Children's Hospital, St. Petersburg, FL
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5
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Meng Y, Allen JW, Sharghi VK, Qiu D. Motion and temporal B 0-shift corrections for QSM and R 2 * mapping using dual-echo spiral navigators and conjugate-phase reconstruction. Magn Reson Med 2024. [PMID: 39233495 DOI: 10.1002/mrm.30266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 08/03/2024] [Accepted: 08/05/2024] [Indexed: 09/06/2024]
Abstract
PURPOSE To develop an efficient navigator-based motion and temporal B0-shift correction technique for 3D multi-echo gradient-echo (ME-GRE) MRI for quantitative susceptibility mapping (QSM) andR 2 * $$ {\mathrm{R}}_2^{\ast } $$ mapping. THEORY AND METHODS A dual-echo 3D stack-of-spiral navigator was designed to interleave with the Cartesian multi-echo gradient-echo acquisitions, allowing the acquisition of both low-echo and high-echo time signals. We additionally designed a novel conjugate phase-based reconstruction method for the joint correction of motion and temporal B0 shifts. We performed numerical simulation, phantom scans, and in vivo human scans to assess the performance of the methods. RESULTS Numerical simulation and human brain scans demonstrated that the proposed technique successfully corrected artifacts induced by both head motions and temporal B0 changes. Efficient B0-change correction with conjugate-phase reconstruction can be performed on fewer than 10 clustered k-space segments. In vivo scans showed that combining temporal B0 correction with motion correction further reduced artifacts and improved image quality in bothR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and QSM images. CONCLUSION Our proposed approach of using 3D spiral navigators and a novel conjugate-phase reconstruction method can improve susceptibility-related measurements using MR.
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Affiliation(s)
- Yuguang Meng
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
| | - Jason W Allen
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA
| | | | - Deqiang Qiu
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, Georgia, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia, USA
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Curtis M, Bayat M, Garic D, Alfano AR, Hernandez M, Curzon M, Bejarano A, Tremblay P, Graziano P, Dick AS. Structural Development of Speech Networks in Young Children at Risk for Speech Disorder. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.23.609470. [PMID: 39229017 PMCID: PMC11370569 DOI: 10.1101/2024.08.23.609470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Characterizing the structural development of the neural speech network in early childhood is important for understanding speech acquisition. To investigate speech in the developing brain, 94 children aged 4-7-years-old at risk for early speech disorder were scanned using diffusion weighted imaging (DWI) magnetic resonance imaging (MRI). Additionally, each child completed the Syllable Repetition Task (SRT), a validated measure of phoneme articulation. The DWI data were modeled using multi-compartment restriction spectrum imaging (RSI) to measure restricted and hindered diffusion properties in both grey and white matter. Consequently, we analyzed the diffusion data using both whole brain analysis, and automated fiber quantification (AFQ) analysis to establish tract profiles for each of six fiber pathways thought to be important for supporting speech development. In the whole brain analysis, we found that SRT performance was associated with restricted diffusion in bilateral inferior frontal gyrus ( pars opercularis ), right pre-supplementary/ supplementary motor area (pre-SMA/SMA), and bilateral cerebellar grey matter ( p < .005). Age moderated these associations in left pars opercularis and frontal aslant tract (FAT). However, in both cases only the cerebellar findings survived a cluster correction. We also found associations between SRT performance and restricted diffusion in cortical association fiber pathways, especially left FAT, and in the cerebellar peduncles. Analyses using automatic fiber quantification (AFQ) highlighted differences in high and low performing children along specific tract profiles, most notably in left but not right FAT. These findings suggest that individual differences in speech performance are reflected in structural gray and white matter differences as measured by restricted and hindered diffusion metrics, and offer important insights into developing brain networks supporting speech in very young children.
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7
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Meisler SL, Kubota E, Grotheer M, Gabrieli JDE, Grill-Spector K. A practical guide for combining functional regions of interest and white matter bundles. Front Neurosci 2024; 18:1385847. [PMID: 39221005 PMCID: PMC11363198 DOI: 10.3389/fnins.2024.1385847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/11/2024] [Indexed: 09/04/2024] Open
Abstract
Diffusion-weighted imaging (DWI) is the primary method to investigate macro- and microstructure of neural white matter in vivo. DWI can be used to identify and characterize individual-specific white matter bundles, enabling precise analyses on hypothesis-driven connections in the brain and bridging the relationships between brain structure, function, and behavior. However, cortical endpoints of bundles may span larger areas than what a researcher is interested in, challenging presumptions that bundles are specifically tied to certain brain functions. Functional MRI (fMRI) can be integrated to further refine bundles such that they are restricted to functionally-defined cortical regions. Analyzing properties of these Functional Sub-Bundles (FSuB) increases precision and interpretability of results when studying neural connections supporting specific tasks. Several parameters of DWI and fMRI analyses, ranging from data acquisition to processing, can impact the efficacy of integrating functional and diffusion MRI. Here, we discuss the applications of the FSuB approach, suggest best practices for acquiring and processing neuroimaging data towards this end, and introduce the FSuB-Extractor, a flexible open-source software for creating FSuBs. We demonstrate our processing code and the FSuB-Extractor on an openly-available dataset, the Natural Scenes Dataset.
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Affiliation(s)
- Steven L. Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard Medical School, Boston, MA, United States
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Emily Kubota
- Department of Psychology, Stanford University, Stanford, CA, United States
| | - Mareike Grotheer
- Department of Psychology, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior – CMBB, Philipps-Universität Marburg and Justus-Liebig-Universität Giessen, Marburg, Germany
| | - John D. E. Gabrieli
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Kalanit Grill-Spector
- Department of Psychology, Stanford University, Stanford, CA, United States
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, United States
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8
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Hubbard NA, Bauer CCC, Siless V, Auerbach RP, Elam JS, Frosch IR, Henin A, Hofmann SG, Hodge MR, Jones R, Lenzini P, Lo N, Park AT, Pizzagalli DA, Vaz-DeSouza F, Gabrieli JDE, Whitfield-Gabrieli S, Yendiki A, Ghosh SS. The Human Connectome Project of adolescent anxiety and depression dataset. Sci Data 2024; 11:837. [PMID: 39095370 PMCID: PMC11297143 DOI: 10.1038/s41597-024-03629-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 07/09/2024] [Indexed: 08/04/2024] Open
Abstract
This article describes primary data and resources available from the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, a novel arm of the Human Connectome Project (HCP). Data were collected from 215 adolescents (14-17 years old), 152 of whom had current diagnoses of anxiety and/or depressive disorders at study intake. Data include cross-sectional structural (T1- and T2-weighted), functional (resting state and three tasks), and diffusion-weighted magnetic resonance images. Both unprocessed and HCP minimally-preprocessed imaging data are available within the data release packages. Adolescent and parent clinical interview data, as well as cognitive and neuropsychological data are also included within these packages. Release packages additionally provide data collected from self-report measures assessing key features of adolescent psychopathology, including: anxious and depressive symptom dimensions, behavioral inhibition/activation, exposure to stressful life events, and risk behaviors. Finally, the release packages include 6- and 12-month longitudinal data acquired from clinical measures. Data are publicly accessible through the National Institute of Mental Health Data Archive (ID: #2505).
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Affiliation(s)
- N A Hubbard
- Department of Psychology, University of Nebraska-Lincoln, Lincoln, NE, USA.
- Center for Brain, Biology, and Behavior, University of Nebraska-Lincoln, Lincoln, NE, USA.
| | - C C C Bauer
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - V Siless
- Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - R P Auerbach
- Department of Psychiatry, Columbia University, New York, NY, USA
| | - J S Elam
- Department of Neuroscience, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - I R Frosch
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - A Henin
- Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - S G Hofmann
- Department of Psychology, Philipps University of Marburg, DEU, Germany
| | - M R Hodge
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - R Jones
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - P Lenzini
- Department of Radiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - N Lo
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - A T Park
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - D A Pizzagalli
- Harvard Medical School, Boston, MA, USA
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, MA, USA
| | - F Vaz-DeSouza
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - J D E Gabrieli
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - S Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - A Yendiki
- Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - S S Ghosh
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Harvard Medical School, Boston, MA, USA.
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Dagnew TM, Tseng CEJ, Yoo CH, Makary MM, Goodheart AE, Striar R, Meyer TN, Rattray AK, Kang L, Wolf KA, Fiedler SA, Tocci D, Shapiro H, Provost S, Sultana E, Liu Y, Ding W, Chen P, Kubicki M, Shen S, Catana C, Zürcher NR, Wey HY, Hooker JM, Weiss RD, Wang C. Toward AI-driven neuroepigenetic imaging biomarker for alcohol use disorder: A proof-of-concept study. iScience 2024; 27:110159. [PMID: 39021792 PMCID: PMC11253155 DOI: 10.1016/j.isci.2024.110159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 04/13/2024] [Accepted: 05/29/2024] [Indexed: 07/20/2024] Open
Abstract
Alcohol use disorder (AUD) is a disorder of clinical and public health significance requiring novel and improved therapeutic solutions. Both environmental and genetic factors play a significant role in its pathophysiology. However, the underlying epigenetic molecular mechanisms that link the gene-environment interaction in AUD remain largely unknown. In this proof-of-concept study, we showed, for the first time, the neuroepigenetic biomarker capability of non-invasive imaging of class I histone deacetylase (HDAC) epigenetic enzymes in the in vivo brain for classifying AUD patients from healthy controls using a machine learning approach in the context of precision diagnosis. Eleven AUD patients and 16 age- and sex-matched healthy controls completed a simultaneous positron emission tomography-magnetic resonance (PET/MR) scan with the HDAC-binding radiotracer [11C]Martinostat. Our results showed lower HDAC expression in the anterior cingulate region in AUD. Furthermore, by applying a genetic algorithm feature selection, we identified five particular brain regions whose combined [11C]Martinostat relative standard uptake value (SUVR) features could reliably classify AUD vs. controls. We validate their promising classification reliability using a support vector machine classifier. These findings inform the potential of in vivo HDAC imaging biomarkers coupled with machine learning tools in the objective diagnosis and molecular translation of AUD that could complement the current diagnostic and statistical manual of mental disorders (DSM)-based intervention to propel precision medicine forward.
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Affiliation(s)
- Tewodros Mulugeta Dagnew
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chieh-En J. Tseng
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Chi-Hyeon Yoo
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Meena M. Makary
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Systems and Biomedical Engineering Department, Cairo University, Giza, Egypt
| | - Anna E. Goodheart
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Robin Striar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tyler N. Meyer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anna K. Rattray
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Leyi Kang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kendall A. Wolf
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Stephanie A. Fiedler
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Darcy Tocci
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hannah Shapiro
- Division of Alcohol, Drugs, and Addiction, McLean Hospital, Belmont, MA, USA
| | - Scott Provost
- Division of Alcohol, Drugs, and Addiction, McLean Hospital, Belmont, MA, USA
| | - Eleanor Sultana
- Division of Alcohol, Drugs, and Addiction, McLean Hospital, Belmont, MA, USA
| | - Yan Liu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Wei Ding
- Department of Computer Science, University of Massachusetts Boston, Boston, MA, USA
| | - Ping Chen
- Department of Engineering, University of Massachusetts Boston, Boston, MA, USA
| | - Marek Kubicki
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Psychiatry Neuroimaging Laboratory, Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Shiqian Shen
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ciprian Catana
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nicole R. Zürcher
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hsiao-Ying Wey
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jacob M. Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roger D. Weiss
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Division of Alcohol, Drugs, and Addiction, McLean Hospital, Belmont, MA, USA
| | - Changning Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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10
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Hoffmann M, Hoopes A, Greve DN, Fischl B, Dalca AV. Anatomy-aware and acquisition-agnostic joint registration with SynthMorph. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2024; 2:1-33. [PMID: 39015335 PMCID: PMC11247402 DOI: 10.1162/imag_a_00197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 04/27/2024] [Accepted: 05/21/2024] [Indexed: 07/18/2024]
Abstract
Affine image registration is a cornerstone of medical-image analysis. While classical algorithms can achieve excellent accuracy, they solve a time-consuming optimization for every image pair. Deep-learning (DL) methods learn a function that maps an image pair to an output transform. Evaluating the function is fast, but capturing large transforms can be challenging, and networks tend to struggle if a test-image characteristic shifts from the training domain, such as the resolution. Most affine methods are agnostic to the anatomy the user wishes to align, meaning the registration will be inaccurate if algorithms consider all structures in the image. We address these shortcomings with SynthMorph, a fast, symmetric, diffeomorphic, and easy-to-use DL tool for joint affine-deformable registration of any brain image without preprocessing. First, we leverage a strategy that trains networks with widely varying images synthesized from label maps, yielding robust performance across acquisition specifics unseen at training. Second, we optimize the spatial overlap of select anatomical labels. This enables networks to distinguish anatomy of interest from irrelevant structures, removing the need for preprocessing that excludes content which would impinge on anatomy-specific registration. Third, we combine the affine model with a deformable hypernetwork that lets users choose the optimal deformation-field regularity for their specific data, at registration time, in a fraction of the time required by classical methods. This framework is applicable to learning anatomy-aware, acquisition-agnostic registration of any anatomy with any architecture, as long as label maps are available for training. We analyze how competing architectures learn affine transforms and compare state-of-the-art registration tools across an extremely diverse set of neuroimaging data, aiming to truly capture the behavior of methods in the real world. SynthMorph demonstrates high accuracy and is available at https://w3id.org/synthmorph, as a single complete end-to-end solution for registration of brain magnetic resonance imaging (MRI) data.
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Affiliation(s)
- Malte Hoffmann
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Andrew Hoopes
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Douglas N. Greve
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Adrian V. Dalca
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Computer Science & Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States
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11
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Sotelo E, Sharon D, Gagoski B, Ellen Grant P, Singh E, Inder TE. Insights from serial magnetic resonance imaging in neonatal encephalopathy in term infants. Pediatr Res 2024:10.1038/s41390-024-03258-5. [PMID: 38907045 DOI: 10.1038/s41390-024-03258-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/05/2024] [Accepted: 03/23/2024] [Indexed: 06/23/2024]
Abstract
BACKGROUND Limited serial neuroimaging studies use magnetic resonance imaging (MRI) to define the evolution of hypoxic-ischemic insults to the brain of term infants and encompass both the primary injury and its secondary impact on cerebral development. The optimal timing of MRI to fully evaluate the impact of hypoxic-ischemic encephalopathy on brain development and associated neurodevelopmental sequelae remains unknown. METHODS Goals: (a) review literature related to serial neuroimaging in term infants with HIE; (b) describe pilot data in two infants with HIE treated with therapeutic hypothermia who had a brain injury at day 3-5 and underwent four additional MRIs over the next 12 weeks of life and developmental evaluation at 24 months of age. RESULTS Early MRI defines primary injury on diffusion-weighted imaging, yet the full impact may not be fully apparent until after 1 month of life. CONCLUSION The full impact of an ischemic injury on the neonatal brain may not be fully visible until several weeks after the initial insult. This suggests the benefit of obtaining later time points for MRI to fully define the extent of injury and its neurodevelopmental impact. IMPACT Few studies inform the nature of the evolution of brain injury with hypothermia in HIE, limiting understanding of potential neuroprotection. MRI is the standard of care for prognosis in infants with HIE, however timing for optimal prognostic prediction remains unclear. Insights from MRI after the first week of life may assist in defining the full extent of brain injury and prognostic significance. A pilot study using five MRI timepoints up to 3 months of age, is presented. More data is required with a systematic evaluation of the impact of early brain injury on brain development in term infants with HIE following TH.
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Affiliation(s)
- Emily Sotelo
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Danielle Sharon
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Borjan Gagoski
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
| | - P Ellen Grant
- Department of Radiology, Boston Children's Hospital, Boston, MA, USA
- Department of Pediatrics, Boston Children's Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Elizabeth Singh
- Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Terrie E Inder
- Division of Neonatology, Children's Hospital of Orange County and University of California, Irvine, CA, USA.
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12
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Chang K, Fine I, Boynton GM. Improving the Reliability and Accuracy of Population Receptive Field Measures Using a Logarithmically Warped Stimulus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598529. [PMID: 38915587 PMCID: PMC11195291 DOI: 10.1101/2024.06.11.598529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
The population receptive field method, which measures the region in visual space that elicits a BOLD signal in a voxel in retinotopic cortex, is a powerful tool for investigating the functional organization of human visual cortex with fMRI (Dumoulin & Wandell, 2008). However, recent work has shown that population receptive field (pRF) estimates for early retinotopic visual areas can be biased and unreliable, especially for voxels representing the fovea. Here, we show that a 'log-bar' stimulus that is logarithmically warped along the eccentricity dimension produces more reliable estimates of pRF size and location than the traditional moving bar stimulus. The log-bar stimulus was better able to identify pRFs near the foveal representation, and pRFs were smaller in size, consistent with simulation estimates of receptive field sizes in the fovea.
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Affiliation(s)
- Kelly Chang
- Department of Psychology, University of Washington Seattle, Washington
| | - Ione Fine
- Department of Psychology, University of Washington Seattle, Washington
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13
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Fan J, Woods KJ, Jacobson JL, Taylor PA, Toich JTF, Molteno CD, Jacobson SW, Meintjes EM. Lower resting state functional connectivity partially mediates adverse effects of prenatal alcohol exposure on arithmetic performance in children. ALCOHOL, CLINICAL & EXPERIMENTAL RESEARCH 2024; 48:1050-1062. [PMID: 38697927 DOI: 10.1111/acer.15332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 03/06/2024] [Accepted: 04/03/2024] [Indexed: 05/05/2024]
Abstract
BACKGROUND Fetal alcohol spectrum disorders (FASD) include a range of neurocognitive and behavioral impairments resulting from prenatal alcohol exposure (PAE). Among the PAE-related cognitive deficits, number processing is particularly affected. This study examines alterations in number processing networks and whether changes in functional connectivity mediate the adverse effects of PAE on arithmetic performance. METHODS Magnetic resonance imaging (MRI) was acquired in 57 children (mean (SD) age = 11.3 (+0.9) yr), 38 with FASD (19 fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 heavily exposed (HE)) and 19 controls. Whole-brain correlation analyses were performed from five seeds located in regions involved in number processing. RESULTS Children with FAS/PFAS showed dose-dependent reductions in resting state functional connectivity between the seed in the right (R) posterior superior parietal lobule and a cluster in the left (L) inferior frontal gyrus, and between a seed in the R horizontal intraparietal sulcus and clusters in the R precentral gyrus and L cerebellar lobule VI. HE children showed lower resting state functional connectivity in a subset of these regions. Lower functional connectivity in the two fronto-parietal connections partially mediated the adverse effects of PAE on arithmetic performance. CONCLUSION This study demonstrates PAE-related functional connectivity impairments in functional networks involved in number processing. The weaker connectivity between the R posterior superior parietal lobule and the L inferior frontal gyrus suggests that impaired verbal processing and visuospatial working memory may play a role in number processing deficits, while weaker connectivity between the R intraparietal sulcus and the R precentral gyrus points to poorer finger-based numerical representation, which has been linked to arithmetic computational skills.
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Affiliation(s)
- Jia Fan
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Keri J Woods
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Joseph L Jacobson
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, USA
- Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Paul A Taylor
- Scientific and Statistical Computing Core, National Institutes of Health, Bethesda, Maryland, USA
| | - Jadrana T F Toich
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
| | - Christopher D Molteno
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Sandra W Jacobson
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, Michigan, USA
- Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Ernesta M Meintjes
- Division of Biomedical Engineering, Department of Human Biology, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, Cape Town, South Africa
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14
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Huang Y, Chen L, Li X, Liu J. Improved test-retest reliability of R 2 * $$ {\mathrm{R}}_2^{\ast } $$ and susceptibility quantification using multishot multi-echo 3D EPI. Magn Reson Med 2024; 91:2310-2319. [PMID: 38156825 PMCID: PMC10997481 DOI: 10.1002/mrm.29992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE This study aimed to evaluate the potential of 3D EPI for improving the reliability ofT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted data and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ decay rate and susceptibility (χ) compared with conventional gradient-echo (GRE)-based acquisition. METHODS Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ were quantified, and their interscan differences were used to evaluate the test-retest reliability. Interprotocol differences ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ between GRE and EPI were also measured voxel by voxel and in selected regions of interest to test the consistency between the two acquisition methods. RESULTS The quantifications ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE. CONCLUSION The result suggests that multishot multi-echo 3D EPI can be a useful alternative acquisition method forT 2 * $$ {\mathrm{T}}_2^{\ast } $$ -weighted MRI and quantification ofR 2 * $$ {\mathrm{R}}_2^{\ast } $$ and χ with reduced scan time, improved test-retest reliability, and similar accuracy compared with commonly used 3D GRE.
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Affiliation(s)
- Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
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15
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Cline TL, Morfini F, Tinney E, Makarewycz E, Lloyd K, Olafsson V, Bauer CC, Kramer AF, Raine LB, Gabard-Durnam LJ, Whitfield-Gabrieli S, Hillman CH. Resting-State Functional Connectivity Change in Frontoparietal and Default Mode Networks After Acute Exercise in Youth. Brain Plast 2024; 9:5-20. [PMID: 39081665 PMCID: PMC11234706 DOI: 10.3233/bpl-240003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/29/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND A single bout of aerobic exercise can provide acute benefits to cognition and emotion in children. Yet, little is known about how acute exercise may impact children's underlying brain networks' resting-state functional connectivity (rsFC). OBJECTIVE Using a data-driven multivariate pattern analysis, we investigated the effects of a single dose of exercise on acute rsFC changes in 9-to-13-year-olds. METHODS On separate days in a crossover design, participants (N = 21) completed 20-mins of acute treadmill walking at 65-75% heart rate maximum (exercise condition) and seated reading (control condition), with pre- and post-fMRI scans. Multivariate pattern analysis was used to investigate rsFC change between conditions. RESULTS Three clusters in the left lateral prefrontal cortex (lPFC) of the frontoparietal network (FPN) had significantly different rsFC after the exercise condition compared to the control condition. Post-hoc analyses revealed that from before to after acute exercise, activity of these FPN clusters became more correlated with bilateral lPFC and the left basal ganglia. Additionally, the left lPFC became more anti-correlated with the precuneus of the default mode network (DMN). An opposite pattern was observed from before to after seated reading. CONCLUSIONS The findings suggest that a single dose of exercise increases connectivity within the FPN, FPN integration with subcortical regions involved in movement and cognition, and segregation of FPN and DMN. Such patterns, often associated with healthier cognitive and emotional control, may underlie the transient mental benefits observed following acute exercise in youth.
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Affiliation(s)
- Trevor L. Cline
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
| | - Francesca Morfini
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
| | - Emma Tinney
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
| | - Ethan Makarewycz
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Katherine Lloyd
- Department of Psychology, Northeastern University, Boston, MA, USA
| | - Valur Olafsson
- Northeastern University Biomedical Imaging Center, Northeastern University, Boston, MA, USA
| | - Clemens C.C. Bauer
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Arthur F. Kramer
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
- Beckman Institute for Advanced Science & Technology, University of Illinois, Urbana, Il, USA
| | - Lauren B. Raine
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
- Department of Physical Therapy, Movement & Rehabilitation Sciences, Northeastern University, Boston, MA, USA
| | - Laurel J. Gabard-Durnam
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
- Department of Brain and Cognitive Sciences and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Charles H. Hillman
- Department of Psychology, Northeastern University, Boston, MA, USA
- Center for Cognitive & Brain Health, Northeastern University, Boston, MA
- Department of Physical Therapy, Movement & Rehabilitation Sciences, Northeastern University, Boston, MA, USA
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16
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Wampl S, Körner T, Meyerspeer M, Zaitsev M, Wolf M, Trattnig S, Wolzt M, Bogner W, Schmid AI. A modular motion compensation pipeline for prospective respiratory motion correction of multi-nuclear MR spectroscopy. Sci Rep 2024; 14:10781. [PMID: 38734781 PMCID: PMC11088657 DOI: 10.1038/s41598-024-61403-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 05/06/2024] [Indexed: 05/13/2024] Open
Abstract
Magnetic resonance (MR) acquisitions of the torso are frequently affected by respiratory motion with detrimental effects on signal quality. The motion of organs inside the body is typically decoupled from surface motion and is best captured using rapid MR imaging (MRI). We propose a pipeline for prospective motion correction of the target organ using MR image navigators providing absolute motion estimates in millimeters. Our method is designed to feature multi-nuclear interleaving for non-proton MR acquisitions and to tolerate local transmit coils with inhomogeneous field and sensitivity distributions. OpenCV object tracking was introduced for rapid estimation of in-plane displacements in 2D MR images. A full three-dimensional translation vector was derived by combining displacements from slices of multiple and arbitrary orientations. The pipeline was implemented on 3 T and 7 T MR scanners and tested in phantoms and volunteers. Fast motion handling was achieved with low-resolution 2D MR image navigators and direct implementation of OpenCV into the MR scanner's reconstruction pipeline. Motion-phantom measurements demonstrate high tracking precision and accuracy with minor processing latency. The feasibility of the pipeline for reliable in-vivo motion extraction was shown on heart and kidney data. Organ motion was manually assessed by independent operators to quantify tracking performance. Object tracking performed convincingly on 7774 navigator images from phantom scans and different organs in volunteers. In particular the kernelized correlation filter (KCF) achieved similar accuracy (74%) as scored from inter-operator comparison (82%) while processing at a rate of over 100 frames per second. We conclude that fast 2D MR navigator images and computer vision object tracking can be used for accurate and rapid prospective motion correction. This and the modular structure of the pipeline allows for the proposed method to be used in imaging of moving organs and in challenging applications like cardiac magnetic resonance spectroscopy (MRS) or magnetic resonance imaging (MRI) guided radiotherapy.
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Affiliation(s)
- Stefan Wampl
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Tito Körner
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Martin Meyerspeer
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Marcos Wolf
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria
| | - Siegfried Trattnig
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Michael Wolzt
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Albrecht Ingo Schmid
- High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.
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17
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Gilmore N, Tseng CEJ, Maffei C, Tromly SL, Deary KB, McKinney IR, Kelemen JN, Healy BC, Hu CG, Ramos-Llordén G, Masood M, Cali RJ, Guo J, Belanger HG, Yao EF, Baxter T, Fischl B, Foulkes AS, Polimeni JR, Rosen BR, Perl DP, Hooker JM, Zürcher NR, Huang SY, Kimberly WT, Greve DN, Mac Donald CL, Dams-O’Connor K, Bodien YG, Edlow BL. Impact of repeated blast exposure on active-duty United States Special Operations Forces. Proc Natl Acad Sci U S A 2024; 121:e2313568121. [PMID: 38648470 PMCID: PMC11087753 DOI: 10.1073/pnas.2313568121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 03/22/2024] [Indexed: 04/25/2024] Open
Abstract
United States (US) Special Operations Forces (SOF) are frequently exposed to explosive blasts in training and combat, but the effects of repeated blast exposure (RBE) on SOF brain health are incompletely understood. Furthermore, there is no diagnostic test to detect brain injury from RBE. As a result, SOF personnel may experience cognitive, physical, and psychological symptoms for which the cause is never identified, and they may return to training or combat during a period of brain vulnerability. In 30 active-duty US SOF, we assessed the relationship between cumulative blast exposure and cognitive performance, psychological health, physical symptoms, blood proteomics, and neuroimaging measures (Connectome structural and diffusion MRI, 7 Tesla functional MRI, [11C]PBR28 translocator protein [TSPO] positron emission tomography [PET]-MRI, and [18F]MK6240 tau PET-MRI), adjusting for age, combat exposure, and blunt head trauma. Higher blast exposure was associated with increased cortical thickness in the left rostral anterior cingulate cortex (rACC), a finding that remained significant after multiple comparison correction. In uncorrected analyses, higher blast exposure was associated with worse health-related quality of life, decreased functional connectivity in the executive control network, decreased TSPO signal in the right rACC, and increased cortical thickness in the right rACC, right insula, and right medial orbitofrontal cortex-nodes of the executive control, salience, and default mode networks. These observations suggest that the rACC may be susceptible to blast overpressure and that a multimodal, network-based diagnostic approach has the potential to detect brain injury associated with RBE in active-duty SOF.
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Affiliation(s)
- Natalie Gilmore
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Chieh-En J. Tseng
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Chiara Maffei
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Samantha L. Tromly
- Institute of Applied Engineering, University of South Florida, Tampa, FL33612
| | | | - Isabella R. McKinney
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Jessica N. Kelemen
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Brian C. Healy
- Harvard T.H. Chan School of Public Health, Boston, MA02115
| | - Collin G. Hu
- United States Army Special Operations Aviation Command, Fort Liberty, NC28307
- Department of Family Medicine, F. Edward Hebert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD20814
| | - Gabriel Ramos-Llordén
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Maryam Masood
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Ryan J. Cali
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Jennifer Guo
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Heather G. Belanger
- Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL33613
| | - Eveline F. Yao
- Office of the Air Force Surgeon General, Falls Church, VA22042
| | - Timothy Baxter
- Institute of Applied Engineering, University of South Florida, Tampa, FL33612
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | | | - Jonathan R. Polimeni
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Bruce R. Rosen
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Daniel P. Perl
- Department of Pathology, F. Edward Hébert School of Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD20814
| | - Jacob M. Hooker
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Nicole R. Zürcher
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Susie Y. Huang
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - W. Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
| | - Douglas N. Greve
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | | | - Kristen Dams-O’Connor
- Department of Rehabilitation and Human Performance, Icahn School of Medicine at Mount Sinai, New York, NY10029
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY10029
| | - Yelena G. Bodien
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA02129
| | - Brian L. Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA02114
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA02114
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
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18
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Ulrich T, Riedel M, Pruessmann KP. Servo navigators: Linear regression and feedback control for rigid-body motion correction. Magn Reson Med 2024; 91:1876-1892. [PMID: 38234052 DOI: 10.1002/mrm.29967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 11/05/2023] [Accepted: 11/24/2023] [Indexed: 01/19/2024]
Abstract
PURPOSE Navigator-based correction of rigid-body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing. METHODS A short orbital navigator (2.3 ms) is inserted in a three-dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex-valued model built either from three reference navigators or in a reference-less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run-time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion-corrected imaging in vivo. RESULTS The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B0 . It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single-digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality. CONCLUSION The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run-time computation, and minimal demand for reference data.
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Affiliation(s)
- Thomas Ulrich
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Malte Riedel
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Klaas P Pruessmann
- Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland
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Brackenier Y, Wang N, Liao C, Cao X, Schauman S, Yurt M, Cordero-Grande L, Malik SJ, Kerr A, Hajnal JV, Setsompop K. Rapid and accurate navigators for motion and B 0 tracking using QUEEN: Quantitatively enhanced parameter estimation from navigators. Magn Reson Med 2024; 91:2028-2043. [PMID: 38173304 DOI: 10.1002/mrm.29976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 11/28/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To develop a framework that jointly estimates rigid motion and polarizing magnetic field (B0 ) perturbations (δ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ ) for brain MRI using a single navigator of a few milliseconds in duration, and to additionally allow for navigator acquisition at arbitrary timings within any type of sequence to obtain high-temporal resolution estimates. THEORY AND METHODS Methods exist that match navigator data to a low-resolution single-contrast image (scout) to estimate either motion orδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . In this work, called QUEEN (QUantitatively Enhanced parameter Estimation from Navigators), we propose combined motion andδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ estimation from a fast, tailored trajectory with arbitrary-contrast navigator data. To this end, the concept of a quantitative scout (Q-Scout) acquisition is proposed from which contrast-matched scout data is predicted for each navigator. Finally, navigator trajectories, contrast-matched scout, andδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ are integrated into a motion-informed parallel-imaging framework. RESULTS Simulations and in vivo experiments show the need to modelδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ to obtain accurate motion parameters estimated in the presence of strongδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . Simulations confirm that tailored navigator trajectories are needed to robustly estimate both motion andδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ . Furthermore, experiments show that a contrast-matched scout is needed for parameter estimation from multicontrast navigator data. A retrospective, in vivo reconstruction experiment shows improved image quality when using the proposed Q-Scout and QUEEN estimation. CONCLUSIONS We developed a framework to jointly estimate rigid motion parameters andδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ from navigators. Combing a contrast-matched scout with the proposed trajectory allows for navigator deployment in almost any sequence and/or timing, which allows for higher temporal-resolution motion andδ B 0 $$ \delta {\mathbf{B}}_{\mathbf{0}} $$ estimates.
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Affiliation(s)
| | - Nan Wang
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Congyu Liao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Xiaozhi Cao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Sophie Schauman
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Mahmut Yurt
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Lucilio Cordero-Grande
- Biomedical Image Technologies, ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BNN, Madrid, Spain
| | - Shaihan J Malik
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Adam Kerr
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
- Cognitive and Neurobiological Imaging, Stanford University, Stanford, California, USA
| | - Joseph V Hajnal
- Biomedical Engineering Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
- Center for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, California, USA
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
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20
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Adanyeguh IM, Bikkamane Jayadev N, Henry PG, Deelchand DK. Fast high-resolution prospective motion correction for single-voxel spectroscopy. Magn Reson Med 2024; 91:1301-1313. [PMID: 38084392 PMCID: PMC10872424 DOI: 10.1002/mrm.29950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 10/27/2023] [Accepted: 11/10/2023] [Indexed: 01/04/2024]
Abstract
PURPOSE To develop a fast high-resolution image-based motion correction method using spiral navigators with multislice-to-volume registration. METHODS A semi-LASER sequence was modified to include a multislice spiral navigator for prospective motion correction (∼305 ms including acquisition, processing, and feedback) as well as shim and frequency navigators for prospective shim and frequency correction (∼100 ms for each). MR spectra were obtained in the prefrontal cortex in five healthy subjects at 3 T with and without prospective motion and shim correction. The effect of key navigator parameters (number of slices, image resolution, and excitation flip angle) on registration accuracy was assessed using simulations. RESULTS Without prospective motion and shim correction, spectral quality degraded significantly in the presence of voluntary motion. In contrast, with prospective motion and shim correction, spectral quality was improved (metabolite linewidth = 6.7 ± 0.6 Hz, SNR= 67 ± 9) and in good agreement with baseline data without motion (metabolite linewidth = 6.9 ± 0.9 Hz, SNR = 73 ± 9). In addition, there was no significant difference in metabolites concentrations measured without motion and with prospective motion and shim correction in the presence of motion. Simulations showed that the registration precision was comparable when using three navigator slices with 3 mm resolution and when using the entire volume (all slices) with 8 mm resolution. CONCLUSION The proposed motion correction scheme allows fast and precise prospective motion and shim correction for single-voxel spectroscopy at 3 T. With 3 mm resolution, only a few navigator slices are necessary to achieve excellent motion correction performance.
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Affiliation(s)
- Isaac M Adanyeguh
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Nutandev Bikkamane Jayadev
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Dinesh K Deelchand
- Center for Magnetic Resonance Research and Department of Radiology, University of Minnesota Medical School, Minneapolis, Minnesota, USA
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21
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Hewlett M, Oran O, Liu J, Drangova M. Prospective motion correction for brain MRI using spherical navigators. Magn Reson Med 2024; 91:1528-1540. [PMID: 38174443 DOI: 10.1002/mrm.29961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 10/24/2023] [Accepted: 11/20/2023] [Indexed: 01/05/2024]
Abstract
PURPOSE To demonstrate for the first time the feasibility of performing prospective motion correction using spherical navigators (SNAVs). METHODS SNAVs were interleaved in a 3D FLASH sequence with an additional short baseline scan (6.8 s) for fast rotation estimation. Assessment of SNAV-based prospective motion correction was performed in six volunteers. Participant motion was guided using randomly generated stepwise prompts as well as prompts derived from real motion cases. Experiments were performed on a 3 T MRI scanner using a 32-channel head coil. RESULTS When optimized for real-time application, SNAV-based motion estimates were computed in 25.8 ± 1.3 ms. Phantom-based quantification of rotation and translation accuracy indicated mean absolute errors of 0.10 ± 0.09° and 0.25 ± 0.14 mm, respectively. Implementing SNAV-based motion estimates for prospective motion correction led to a clear improvement in image quality with minimal increase in scan time (<5%). CONCLUSION Optimization of SNAV processing for real-time application enables prospective motion correction with low latency and minimal scan time requirements.
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Affiliation(s)
- Miriam Hewlett
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
| | - Omer Oran
- Siemens Healthcare Limited, Oakville, Ontario, Canada
| | - Junmin Liu
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
| | - Maria Drangova
- Robarts Research Institute, The University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, The University of Western Ontario, London, Ontario, Canada
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22
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Wallace TE, Piccini D, Kober T, Warfield SK, Afacan O. Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI. Magn Reson Med 2024; 91:1057-1066. [PMID: 37929608 PMCID: PMC10843402 DOI: 10.1002/mrm.29899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/15/2023] [Accepted: 10/06/2023] [Indexed: 11/07/2023]
Abstract
PURPOSE To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-encoded FID navigator) in each radial spoke. METHODS A forward model was created from low-resolution calibration data to simulate the effect of relative motion between the coil sensitivity profiles and the underlying object on the self-encoded FID navigator signal. Trajectory deviations were included in the model as low spatial-order field variations. Three volunteers were imaged at 3 T using a modified 3D gradient-echo sequence acquired with a Kooshball trajectory while performing abrupt and continuous head motion. Rigid body-motion parameters were estimated from the central k-space signal of each spoke using a least-squares fitting algorithm. The accuracy of self-navigated motion parameters was assessed relative to an established external tracking system. Quantitative image quality metrics were computed for images with and without retrospective correction using external and self-navigated motion measurements. RESULTS Self-encoded FID navigators achieved mean absolute errors of 0.69 ± 0.82 mm and 0.73 ± 0.87° relative to external tracking for maximum motion amplitudes of 12 mm and 10°. Retrospective correction of the 3D radial data resulted in substantially improved image quality for both abrupt and continuous motion paradigms, comparable to external tracking results. CONCLUSIONS Accurate rigid body motion parameters can be rapidly obtained from self-encoded FID navigator signals in 3D radial MRI to continuously correct for head movements. This approach is suitable for robust neuroanatomical imaging in subjects that exhibit patterns of large and frequent motion.
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Affiliation(s)
| | - Davide Piccini
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Simon K. Warfield
- Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Onur Afacan
- Department of Radiology, Boston Children’s Hospital, Boston, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
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23
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Fang A, Baran B, Feusner JD, Phan KL, Beatty CC, Crane J, Jacoby RJ, Manoach DS, Wilhelm S. Self-focused brain predictors of cognitive behavioral therapy response in a transdiagnostic sample. J Psychiatr Res 2024; 171:108-115. [PMID: 38266332 PMCID: PMC10922639 DOI: 10.1016/j.jpsychires.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2023] [Revised: 01/09/2024] [Accepted: 01/15/2024] [Indexed: 01/26/2024]
Abstract
BACKGROUND Effective biomarkers of cognitive behavioral therapy (CBT) response provide information beyond available behavioral or self-report measures and may optimize treatment selection for patients based on likelihood of benefit. No single biomarker reliably predicts CBT response. In this study, we evaluated patterns of brain connectivity associated with self-focused attention (SFA) as biomarkers of CBT response for anxiety and obsessive-compulsive disorders. We hypothesized that pre-treatment as well as pre-to post-treatment changes in functional connectivity would be associated with improvement during CBT in a transdiagnostic sample. METHODS Twenty-seven patients with primary social anxiety disorder (n = 14) and primary body dysmorphic disorder (n = 13) were scanned before and after 12 sessions of CBT targeting their primary disorder. Eligibility was based on elevated trait SFA scores on the Public Self-Consciousness Scale. Seed-based resting state functional connectivity associated with symptom improvement was computed using a seed in the posterior cingulate cortex of the default mode network. RESULTS At pre-treatment, stronger positive connectivity of the seed with the cerebellum, and stronger negative connectivity with the putamen, were associated with greater clinical improvement. Between pre-to post-treatment, greater anticorrelation between the seed and postcentral gyrus, extending into the inferior parietal lobule and precuneus/superior parietal lobule was associated with clinical improvement, although this did not survive thresholding. CONCLUSIONS Pre-treatment functional connectivity with the default mode network was associated with CBT response. Behavioral and self-report measures of SFA did not contribute to predictions, thus highlighting the value of neuroimaging-based measures of SFA. CLINICAL TRIALS REGISTRATION ClinicalTrials.gov Identifier: NCT02808702 https://clinicaltrials.gov/ct2/show/NCT02808702.
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Affiliation(s)
- Angela Fang
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525, USA.
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242-1407, USA
| | - Jamie D Feusner
- Centre for Addiction and Mental Health, Brain Imaging Health Center, Ontario, Toronto, Canada, M5T1R8; Department of Psychiatry, University of Toronto, Ontario, Toronto, Canada, M5T1R8; Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, 43210-1240, USA
| | - Clare C Beatty
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500, USA
| | - Jessica Crane
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525, USA
| | - Ryan J Jacoby
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, USA; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129-2020, USA
| | - Sabine Wilhelm
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696, USA
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24
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Vieites V, Ralph Y, Reeb-Sutherland B, Dick AS, Mattfeld AT, Pruden SM. Neurite density of the hippocampus is associated with trace eyeblink conditioning latency in 4- to 6-year-olds. Eur J Neurosci 2024; 59:358-369. [PMID: 38092417 PMCID: PMC10872972 DOI: 10.1111/ejn.16217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 11/16/2023] [Accepted: 11/19/2023] [Indexed: 02/06/2024]
Abstract
Limited options exist to evaluate the development of hippocampal function in young children. Research has established that trace eyeblink conditioning (EBC) relies on a functional hippocampus. Hence, we set out to investigate whether trace EBC is linked to hippocampal structure, potentially serving as a valuable indicator of hippocampal development. Our study explored potential associations between individual differences in hippocampal volume and neurite density with trace EBC performance in young children. We used onset latency of conditioned responses (CR) and percentage of conditioned responses (% CR) as measures of hippocampal-dependent associative learning. Using a sample of typically developing children aged 4 to 6 years (N = 30; 14 girls; M = 5.70 years), participants underwent T1- and diffusion-weighted MRI scans and completed a 15-min trace eyeblink conditioning task conducted outside the MRI. % CR and CR onset latency were calculated based on all trials involving tone-puff presentations and tone-alone trials. Findings revealed a connection between greater left hippocampal neurite density and delayed CR onset latency. Children with higher neurite density in the left hippocampus tended to blink closer to the onset of the unconditioned stimulus, indicating that structural variations in the hippocampus were associated with more precise timing of conditioned responses. No other relationships were observed between hippocampal volume, cerebellum volume or neurite density, hippocampal white matter connectivity and any EBC measures. Preliminary results suggest that trace EBC may serve as a straightforward yet innovative approach for studying hippocampal development in young children and populations with atypical development.
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Affiliation(s)
- Vanessa Vieites
- Department of Psychology, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USA
| | - Yvonne Ralph
- Department of Psychology, University of Texas at Tyler, Tyler, Texas, USA
| | | | - Anthony Steven Dick
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Aaron T Mattfeld
- Department of Psychology, Florida International University, Miami, Florida, USA
| | - Shannon M Pruden
- Department of Psychology, Florida International University, Miami, Florida, USA
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25
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Teghil A, Boccia M. Brain connectivity patterns associated with individual differences in the access to experience-near personal semantics: a resting-state fMRI study. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2024; 24:87-99. [PMID: 38200283 PMCID: PMC10827898 DOI: 10.3758/s13415-023-01149-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 12/13/2023] [Indexed: 01/12/2024]
Abstract
It has been proposed that a continuum of specificity exists between episodic and semantic autobiographical memory. Personal semantics have been theorized to situate intermediately on this continuum, with more "experience-near" personal semantics (enPS) closer to the episodic end. We used individual differences in behavior as a model to investigate brain networks associated with the access to episodic autobiographical (EAM) and enPS information, assessing the relation between performance in the EAM and enPS conditions of the Autobiographical Fluency Task (AFT) and intrinsic brain connectivity. Results of an intrinsic connectivity contrast analysis showed that the global connectivity of two clusters in the left and right posterior cingulate cortex (PCC) was predicted by performance in the enPS conditions. Moreover, enPS scores predicted the connectivity strength of the right PCC with the bilateral anterior hippocampus (aHC), anterior middle temporal gyrus (aMTG) and medial orbitofrontal cortex, and the left aMTG and PCC. enPS scores also predicted the connectivity strength of the left PCC with the bilateral HC and MTG. The network highlighted involves parts of the core and of the dorsal medial subsystems of the Default Mode Network, in line with the proposal that enPS represents an intermediate entity between episodic and semantic memory.
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Affiliation(s)
- Alice Teghil
- Department of Psychology, "Sapienza" University of Rome, Via dei Marsi, 78, 00185, Rome, Italy.
- Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Rome, Italy.
| | - Maddalena Boccia
- Department of Psychology, "Sapienza" University of Rome, Via dei Marsi, 78, 00185, Rome, Italy
- Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Rome, Italy
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26
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Bayat M, Hernandez M, Curzon M, Garic D, Graziano P, Dick AS. Reduced recruitment of inhibitory control regions in very young children with ADHD during a modified Kiddie Continuous Performance Task: a fMRI study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.17.576033. [PMID: 38293209 PMCID: PMC10827162 DOI: 10.1101/2024.01.17.576033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) symptom profiles are known to undergo changes throughout development, rendering the neurobiological assessment of ADHD challenging across different developmental stages. Particularly in young children (ages 4 to 7 years), measuring inhibitory control network activity in the brain has been a formidable task due to the lack of child-friendly functional Magnetic Resonance Imaging (fMRI) paradigms. This study aims to address these difficulties by focusing on measuring inhibitory control in very young children within the MRI environment. A total of 56 children diagnosed with ADHD and 78 typically developing (TD) 4-7-year-old children were examined using a modified version of the Kiddie-Continuous Performance Test (K-CPT) during BOLD fMRI to assess inhibitory control. We concurrently evaluated their performance on the established and standardized K-CPT outside the MRI scanner. Our findings suggest that the modified K-CPT effectively elicited robust and expected brain activity related to inhibitory control in both groups. Comparisons between the two groups revealed subtle differences in brain activity, primarily observed in regions associated with inhibitory control, such as the inferior frontal gyrus, anterior insula, dorsal striatum, medial pre-supplementary motor area (pre-SMA), and cingulate cortex. Notably, increased activity in the right anterior insula was associated with improved response time (RT) and reduced RT variability on the K-CPT administered outside the MRI environment, although this did not survive statistical correction for multiple comparisons. In conclusion, our study successfully overcame the challenges of measuring inhibitory control in very young children within the MRI environment by utilizing a modified K-CPT during BOLD fMRI. These findings shed light on the neurobiological correlates of inhibitory control in ADHD and TD children, provide valuable insights for understanding ADHD across development, and potentially inform ADHD diagnosis and intervention strategies. The research also highlights remaining challenges with task fMRI in very young clinical samples.
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27
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Kashyap S, Oliveira ÍAF, Uludağ K. Feasibility of high-resolution perfusion imaging using arterial spin labeling MRI at 3 Tesla. Front Physiol 2024; 14:1271254. [PMID: 38235379 PMCID: PMC10791866 DOI: 10.3389/fphys.2023.1271254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 11/27/2023] [Indexed: 01/19/2024] Open
Abstract
Cerebral blood flow (CBF) is a critical physiological parameter of brain health, and it can be non-invasively measured with arterial spin labeling (ASL) MRI. In this study, we evaluated and optimized whole-brain, high-resolution ASL as an alternative to the low-resolution ASL employed in the routine assessment of CBF in both healthy participants and patients. Two high-resolution protocols (i.e., pCASL and FAIR-Q2TIPS (PASL) with 2 mm isotropic voxels) were compared to a default clinical pCASL protocol (3.4 × 3.4 × 4 mm 3), all of whom had an acquisition time of ≈ 5 min. We assessed the impact of high-resolution acquisition on reducing partial voluming and improving sensitivity to the perfusion signal, and evaluated the effectiveness of z-deblurring on the ASL data. We compared the quality of whole-brain ASL acquired using three available head coils with differing number of receive channels (i.e., 20, 32, and 64ch). We found that using higher coil counts (32 and 64ch coils as compared to 20ch) offers improved signal-to-noise ratio (SNR) and acceleration capabilities that are beneficial for ASL imaging at 3 Tesla (3 T). The inherent reduction in partial voluming effects with higher resolution acquisitions improves the resolving power of perfusion without impacting the sensitivity. In conclusion, our results suggest that high-resolution ASL (2 to 2.5 mm isotropic voxels) has the potential to become a new standard for perfusion imaging at 3 T and increase its adoption into clinical research and cognitive neuroscience applications.
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Affiliation(s)
- Sriranga Kashyap
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | | | - Kâmil Uludağ
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
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28
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Dhakal K, Rosenthal ES, Kulpanowski AM, Dodelson JA, Wang Z, Cudemus-Deseda G, Villien M, Edlow BL, Presciutti AM, Januzzi JL, Ning M, Taylor Kimberly W, Amorim E, Brandon Westover M, Copen WA, Schaefer PW, Giacino JT, Greer DM, Wu O. Increased task-relevant fMRI responsiveness in comatose cardiac arrest patients is associated with improved neurologic outcomes. J Cereb Blood Flow Metab 2024; 44:50-65. [PMID: 37728641 PMCID: PMC10905635 DOI: 10.1177/0271678x231197392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 09/21/2023]
Abstract
Early prediction of the recovery of consciousness in comatose cardiac arrest patients remains challenging. We prospectively studied task-relevant fMRI responses in 19 comatose cardiac arrest patients and five healthy controls to assess the fMRI's utility for neuroprognostication. Tasks involved instrumental music listening, forward and backward language listening, and motor imagery. Task-specific reference images were created from group-level fMRI responses from the healthy controls. Dice scores measured the overlap of individual subject-level fMRI responses with the reference images. Task-relevant responsiveness index (Rindex) was calculated as the maximum Dice score across the four tasks. Correlation analyses showed that increased Dice scores were significantly associated with arousal recovery (P < 0.05) and emergence from the minimally conscious state (EMCS) by one year (P < 0.001) for all tasks except motor imagery. Greater Rindex was significantly correlated with improved arousal recovery (P = 0.002) and consciousness (P = 0.001). For patients who survived to discharge (n = 6), the Rindex's sensitivity was 75% for predicting EMCS (n = 4). Task-based fMRI holds promise for detecting covert consciousness in comatose cardiac arrest patients, but further studies are needed to confirm these findings. Caution is necessary when interpreting the absence of task-relevant fMRI responses as a surrogate for inevitable poor neurological prognosis.
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Affiliation(s)
- Kiran Dhakal
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Annelise M Kulpanowski
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Jacob A Dodelson
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Zihao Wang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Gaston Cudemus-Deseda
- Department of Cardiac Anesthesiology and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Marjorie Villien
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Brian L Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Alexander M Presciutti
- Department of Psychiatry, Center for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, MA, USA
| | - James L Januzzi
- Department of Medicine, Cardiology Division, Massachusetts General Hospital and Baim Institute for Clinical Research, Boston, MA, USA
| | - MingMing Ning
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - W Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Edilberto Amorim
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - William A Copen
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, Boston, MA, USA
| | - Pamela W Schaefer
- Department of Radiology, Neuroradiology Division, Massachusetts General Hospital, Boston, MA, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Charlestown, MA, USA
| | - David M Greer
- Department of Neurology, Boston University School of Medicine, Boston Medical Center, Boston, MA, USA
| | - Ona Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
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Brooks JO, Kruse JL, Kubicki A, Hellemann G, Espinoza RT, Irwin MR, Narr KL. Structural brain plasticity and inflammation are independently related to changes in depressive symptoms six months after an index ECT course. Psychol Med 2024; 54:108-116. [PMID: 36600668 DOI: 10.1017/s0033291722003555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is effective for treatment-resistant depression and leads to short-term structural brain changes and decreases in the inflammatory response. However, little is known about how brain structure and inflammation relate to the heterogeneity of treatment response in the months following an index ECT course. METHODS A naturalistic six-month study following an index ECT course included 20 subjects with treatment-resistant depression. Upon conclusion of the index ECT course and again after six months, structural magnetic resonance imaging scans and peripheral inflammation measures [interleukin-6 (IL-6), IL-8, tumor necrosis factor (TNF-α), and C-reactive protein] were obtained. Voxel-based morphometry processed with the CAT-12 Toolbox was used to estimate changes in gray matter volume. RESULTS Between the end of the index ECT course and the end of follow-up, we found four clusters of significant decreases in gray matter volume (p < 0.01, FWE) and no regions of increased volume. Decreased HAM-D scores were significantly related only to reduced IL-8 level. Decreased volume in one cluster, which included the right insula and Brodmann's Area 22, was related to increased HAM-D scores over six months. IL-8 levels did not mediate or moderate the relationship between volumetric change and depression. CONCLUSIONS Six months after an index ECT course, multiple regions of decreased gray matter volume were observed in a naturalistic setting. The independent relations between brain volume and inflammation to depressive symptoms suggest novel explanations of the heterogeneity of longer-term ECT treatment response.
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Affiliation(s)
- John O Brooks
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Jennifer L Kruse
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Antoni Kubicki
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, Geffen School of Medicine at the University of California, Los Angeles, CA, USA
| | | | - Randall T Espinoza
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Michael R Irwin
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Katherine L Narr
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, Geffen School of Medicine at the University of California, Los Angeles, CA, USA
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Elliott ML, Nielsen JA, Hanford LC, Hamadeh A, Hilbert T, Kober T, Dickerson BC, Hyman BT, Mair RW, Eldaief MC, Buckner RL. Precision Brain Morphometry Using Cluster Scanning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.23.23300492. [PMID: 38234845 PMCID: PMC10793507 DOI: 10.1101/2023.12.23.23300492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.
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Affiliation(s)
- Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jared A Nielsen
- Department of Psychology, Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Lindsay C Hanford
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Aya Hamadeh
- Baylor College of Medicine, Houston, TX 77030
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Bradley T Hyman
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
| | - Ross W Mair
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Athinoula A. Martinos Center for Biomedical Imaging
| | - Mark C Eldaief
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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Khoury JE, Ahtam B, Ou Y, Jenkins E, Klengel T, Enlow MB, Grant E, Lyons-Ruth K. Linking maternal disrupted interaction and infant limbic volumes: The role of infant cortisol output. Psychoneuroendocrinology 2023; 158:106379. [PMID: 37683305 DOI: 10.1016/j.psyneuen.2023.106379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 08/22/2023] [Accepted: 08/29/2023] [Indexed: 09/10/2023]
Abstract
Despite a large animal literature documenting the role of low maternal nurturance and elevated glucocorticoid production on offspring limbic development, these pathways have not yet been assessed during human infancy. Informed by animal models, the present study examined whether 1) maternal disrupted interaction is related to infant cortisol levels, 2) infant cortisol levels are associated with infant limbic volumes, and 3) infant cortisol levels mediate associations between maternal disrupted interaction and infant limbic volumes. Participants included 57 mother-infant dyads. Infant saliva was measured at one time point before and two time points after the Still-Face Paradigm (SFP) at age 4 months. Five aspects of maternal disrupted interaction were coded during the SFP reunion episode. Between 4 and 25 months (M age = 11.74 months, SD = 6.12), under natural sleep, infants completed an MRI. Amygdala and hippocampal volumes were calculated via automated segmentation. Results indicated that 1) maternal disrupted interaction, and specifically disoriented interaction, with the infant was associated with higher infant salivary cortisol (AUCg) levels during the SFP, 2) higher infant AUCg was related to enlarged bilateral amygdala and hippocampal volumes, and 3) infant AUCg mediated the relation between maternal disrupted interaction and infant amygdala and hippocampal volumes. Findings are consistent with controlled animal studies and provide evidence of a link between increased cortisol levels and enlarged limbic volumes in human infants. Results further suggest that established interventions to decrease maternal disrupted interaction could impact both infant cortisol levels and infant limbic volumes.
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Affiliation(s)
| | - Banu Ahtam
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, United States
| | - Yangming Ou
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, United States; Department of Radiology, Boston Children's Hospital, Harvard Medical School, United States
| | | | - Torsten Klengel
- Department of Psychiatry, McLean Hospital, Harvard Medical School, United States
| | - Michelle Bosquet Enlow
- Department of Psychiatry and Behavioral Sciences, Boston Children's Hospital, Department of Psychiatry, Harvard Medical School, United States
| | - Ellen Grant
- Fetal-Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, United States
| | - Karlen Lyons-Ruth
- Department of Psychiatry, Cambridge Hospital, Harvard Medical School, United States
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Lyons-Ruth K, Li FH, Khoury JE, Ahtam B, Sisitsky M, Ou Y, Enlow MB, Grant E. Maternal Childhood Abuse Versus Neglect Associated with Differential Patterns of Infant Brain Development. Res Child Adolesc Psychopathol 2023; 51:1919-1932. [PMID: 37160577 PMCID: PMC10661793 DOI: 10.1007/s10802-023-01041-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/09/2023] [Indexed: 05/11/2023]
Abstract
Severity of maternal childhood maltreatment has been associated with lower infant grey matter volume and amygdala volume during the first two years of life. A developing literature argues that effects of threat (abuse) and of deprivation (neglect) should be assessed separately because these distinct aspects of adversity may have different impacts on developmental outcomes. However, distinct effects of threat versus deprivation have not been assessed in relation to intergenerational effects of child maltreatment. The objective of this study was to separately assess the links of maternal childhood abuse and neglect with infant grey matter volume (GMV), white matter volume (WMV), amygdala and hippocampal volume. Participants included 57 mother-infant dyads. Mothers were assessed for childhood abuse and neglect using the Adverse Childhood Experiences (ACE) questionnaire in a sample enriched for childhood maltreatment. Between 4 and 24 months (M age = 12.28 months, SD = 5.99), under natural sleep, infants completed an MRI using a 3.0 T Siemens scanner. GMV, WMV, amygdala and hippocampal volumes were extracted via automated segmentation. Maternal history of neglect, but not abuse, was associated with lower infant GMV. Maternal history of abuse, but not neglect, interacted with age such that abuse was associated with smaller infant amygdala volume at older ages. Results are consistent with a threat versus deprivation framework, in which threat impacts limbic regions central to the stress response, whereas deprivation impacts areas more central to cognitive function. Further studies are needed to identify mechanisms contributing to these differential intergenerational associations of threat versus deprivation.
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Affiliation(s)
- Karlen Lyons-Ruth
- Department of Psychiatry, Harvard Medical School, Cambridge Hospital, 1493 Cambridge St., Cambridge, MA, USA.
| | - Frances Haofei Li
- Department of Psychiatry, Harvard Medical School, Cambridge Hospital, 1493 Cambridge St., Cambridge, MA, USA
| | - Jennifer E Khoury
- Department of Psychiatry, Harvard Medical School, Cambridge Hospital, 1493 Cambridge St., Cambridge, MA, USA
- Department of Psychology, Mount Saint Vincent University, Halifax, NS, Canada
| | - Banu Ahtam
- Department of Pediatrics, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
| | - Michaela Sisitsky
- Department of Pediatrics, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
| | - Yangming Ou
- Department of Pediatrics, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
| | - Michelle Bosquet Enlow
- Department of Psychiatry, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
| | - Ellen Grant
- Department of Pediatrics, Harvard Medical School, Boston Children's Hospital, Boston, MA, USA
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Mewton L, Davies S, Sunderland M, Champion K, Hoy N, Newton N, Teesson M, Squeglia LM. Longitudinal relationships between lifestyle risk factors and neurodevelopment in early adolescence. Health Psychol 2023; 42:904-912. [PMID: 37616102 PMCID: PMC10840638 DOI: 10.1037/hea0001248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/25/2023]
Abstract
OBJECTIVE The goal of this study is to investigate the cross-sectional and longitudinal relationships between clustered lifestyle risk factors (sleep, physical activity, body mass index [BMI], and screen time) and neurodevelopment over the early adolescent period. METHOD Data from the ABCD Study Data Release 3.0 consisted of 11,878 participants (aged 9-10 years) at baseline and 6,571 participants (aged 11-12 years) at 2-year follow-up. The interrelationships between lifestyle risk factors and brain structure were analyzed using bivariate multiple indicator latent change score models. Using confirmatory factor analysis, a single lifestyle risk factor domain (measured by sleep, physical activity, BMI, and screen time) was shown to fit the data well. Using exploratory and confirmatory factor analysis, seven brain structure domains were extracted and labeled as temporal-parietal, frontotemporal, occipital, orbitofrontal, temporal, cingulate, parietal, and cuneus domains. All bivariate latent change score models accounted for age, sex at birth, race/ethnicity, parental education, and marital status. RESULTS Higher lifestyle risk was associated with smaller brain volume at baseline. Higher baseline lifestyle risk was also associated with a greater rate of change (i.e., greater decreases) in brain volume for the temporal-parietal, frontotemporal, orbitofrontal, parietal, and cuneus domains. Effects were not reciprocal; baseline brain volume did not predict changes in lifestyle behaviors over time. CONCLUSION These findings are important for understanding the biological mechanisms underpinning health risk factors and can be used to target interventions and improve brain health during this critical developmental phase. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Affiliation(s)
- Louise Mewton
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Sarah Davies
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Matthew Sunderland
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Katrina Champion
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Nicholas Hoy
- Centre for Healthy Brain Ageing, School of Psychiatry and Mental Health, University of New South Wales, Sydney, Australia
| | - Nicola Newton
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Maree Teesson
- The Matilda Centre for Mental Health and Substance Use, University of Sydney, Sydney, Australia
| | - Lindsay M. Squeglia
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, South Carolina
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Seginer A, Schmidt R. Messing up to clean up: Semi-randomized frequency selective space-filling curves to suppress physiological signal fluctuations in MRI. Magn Reson Med 2023; 90:2275-2289. [PMID: 37448104 DOI: 10.1002/mrm.29790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/19/2023] [Accepted: 06/20/2023] [Indexed: 07/15/2023]
Abstract
PURPOSE Rapid 3D steady-state sequences are widely used but are also known to be sensitive to semi-periodic physiological signal fluctuations due to, for example, cardiac pulsation, breathing, and eye/eyelids movement. This semi-periodicity results in repeating artifacts in the image whose intensity depends on the scan parameters. The purpose of this study is to design a reordering of the 2D phase encodes (within the 3D acquisition) that reduces these artifacts. METHODS A randomized order of the phase encodes can suppress repeating artifact but may also introduce its own apparent noise, for example, in cases of slow subject movement or gradual changes in eddy currents. In a new design a semi-randomized space-filling curve is generated by scrambling the local order of the phase encodes to achieve a controlled frequency selective effect, that is, eliminating artifacts above a chosen (fluctuation) frequency threshold while leaving lower frequencies untouched, thus overcoming the limitations of a randomized order. The method was characterized in simulations and substantiated by human brain imaging at 7 T using two steady-state gradient echo variants that suffer from pulsation, either near blood vessels or near the ventricles. RESULTS The simulations with a point source show that the maximum artifact intensity can be reduced by factors of 10-50 depending on the scan parameters. In human scanning, the new approach drastically reduced physiologically induced artifacts and was superior in this regard to both full randomization and a generalized Hilbert curve, another semi-randomized approach. CONCLUSION The phase-encodes reordering presented here effectively removes artifacts arising from local fluctuations.
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Affiliation(s)
- Amir Seginer
- Life Sciences Core Facilities, Weizmann Institute of Science, Rehovot, Israel
- The Azrieli National Institute for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
| | - Rita Schmidt
- The Azrieli National Institute for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot, Israel
- Department of Brain Sciences, Weizmann Institute of Science, Rehovot, Israel
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35
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Li B, Li N, Wang Z, Balan R, Ernst T. Simultaneous multislice EPI prospective motion correction by real-time receiver phase correction and coil sensitivity map interpolation. Magn Reson Med 2023; 90:1932-1948. [PMID: 37448116 PMCID: PMC10795703 DOI: 10.1002/mrm.29789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 06/13/2023] [Accepted: 06/16/2023] [Indexed: 07/15/2023]
Abstract
PURPOSE To improve the image reconstruction for prospective motion correction (PMC) of simultaneous multislice (SMS) EPI of the brain, an update of receiver phase and resampling of coil sensitivities are proposed and evaluated. METHODS A camera-based system was used to track head motion (3 translations and 3 rotations) and dynamically update the scan position and orientation. We derived the change in receiver phase associated with a shifted field of view (FOV) and applied it in real-time to each k-space line of the EPI readout trains. Second, for the SMS reconstruction, we adapted resampled coil sensitivity profiles reflecting the movement of slices. Single-shot gradient-echo SMS-EPI scans were performed in phantoms and human subjects for validation. RESULTS Brain SMS-EPI scans in the presence of motion with PMC and no phase correction for scan plane shift showed noticeable artifacts. These artifacts were visually and quantitatively attenuated when corrections were enabled. Correcting misaligned coil sensitivity maps improved the temporal SNR (tSNR) of time series by 24% (p = 0.0007) for scans with large movements (up to ˜35 mm and 30°). Correcting the receiver phase improved the tSNR of a scan with minimal head movement by 50% from 50 to 75 for a United Kingdom biobank protocol. CONCLUSION Reconstruction-induced motion artifacts in single-shot SMS-EPI scans acquired with PMC can be removed by dynamically adjusting the receiver phase of each line across EPI readout trains and updating coil sensitivity profiles during reconstruction. The method may be a valuable tool for SMS-EPI scans in the presence of subject motion.
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Affiliation(s)
- Bo Li
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD, United States
| | - Ningzhi Li
- U.S. Food Drug Administration, Silver Spring, MD, United States
| | - Ze Wang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD, United States
| | - Radu Balan
- Department of Mathematics, University of Maryland, College Park, MD, United States
| | - Thomas Ernst
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland, Baltimore, MD, United States
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Karl V, Rohe T. Structural brain changes in emotion recognition across the adult lifespan. Soc Cogn Affect Neurosci 2023; 18:nsad052. [PMID: 37769357 PMCID: PMC10627307 DOI: 10.1093/scan/nsad052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 06/22/2023] [Accepted: 09/19/2023] [Indexed: 09/30/2023] Open
Abstract
Emotion recognition (ER) declines with increasing age, yet little is known whether this observation is based on structural brain changes conveyed by differential atrophy. To investigate whether age-related ER decline correlates with reduced grey matter (GM) volume in emotion-related brain regions, we conducted a voxel-based morphometry analysis using data of the Human Connectome Project-Aging (N = 238, aged 36-87) in which facial ER was tested. We expected to find brain regions that show an additive or super-additive age-related change in GM volume indicating atrophic processes that reduce ER in older adults. The data did not support our hypotheses after correction for multiple comparisons. Exploratory analyses with a threshold of P < 0.001 (uncorrected), however, suggested that relationships between GM volume and age-related general ER may be widely distributed across the cortex. Yet, small effect sizes imply that only a small fraction of the decline of ER in older adults can be attributed to local GM volume changes in single voxels or their multivariate patterns.
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Affiliation(s)
- Valerie Karl
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo 0424, Norway
- PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Tim Rohe
- Institute of Psychology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen 91054, Germany
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37
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Robinson SD, Bachrata B, Eckstein K, Bollmann S, Bollmann S, Hodono S, Cloos M, Tourell M, Jin J, O'Brien K, Reutens DC, Trattnig S, Enzinger C, Barth M. Improved dynamic distortion correction for fMRI using single-echo EPI and a readout-reversed first image (REFILL). Hum Brain Mapp 2023; 44:5095-5112. [PMID: 37548414 PMCID: PMC10502646 DOI: 10.1002/hbm.26440] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 06/01/2023] [Accepted: 07/12/2023] [Indexed: 08/08/2023] Open
Abstract
The boundaries between tissues with different magnetic susceptibilities generate inhomogeneities in the main magnetic field which change over time due to motion, respiration and system instabilities. The dynamically changing field can be measured from the phase of the fMRI data and corrected. However, methods for doing so need multi-echo data, time-consuming reference scans and/or involve error-prone processing steps, such as phase unwrapping, which are difficult to implement robustly on the MRI host. The improved dynamic distortion correction method we propose is based on the phase of the single-echo EPI data acquired for fMRI, phase offsets calculated from a triple-echo, bipolar reference scan of circa 3-10 s duration using a method which avoids the need for phase unwrapping and an additional correction derived from one EPI volume in which the readout direction is reversed. This Reverse-Encoded First Image and Low resoLution reference scan (REFILL) approach is shown to accurately measure B0 as it changes due to shim, motion and respiration, even with large dynamic changes to the field at 7 T, where it led to a > 20% increase in time-series signal to noise ratio compared to data corrected with the classic static approach. fMRI results from REFILL-corrected data were free of stimulus-correlated distortion artefacts seen when data were corrected with static field mapping. The method is insensitive to shim changes and eddy current differences between the reference scan and the fMRI time series, and employs calculation steps that are simple and robust, allowing most data processing to be performed in real time on the scanner image reconstruction computer. These improvements make it feasible to routinely perform dynamic distortion correction in fMRI.
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Affiliation(s)
- Simon Daniel Robinson
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- Department of NeurologyMedical University of GrazGrazAustria
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal ImagingViennaAustria
| | - Beata Bachrata
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
- Karl Landsteiner Institute for Clinical Molecular MR in Musculoskeletal ImagingViennaAustria
- Department of Medical EngineeringCarinthia University of Applied SciencesKlagenfurtAustria
| | - Korbinian Eckstein
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Saskia Bollmann
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
| | - Steffen Bollmann
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
| | - Shota Hodono
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Martijn Cloos
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Monique Tourell
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- Siemens Healthcare Pty Ltd.BrisbaneAustralia
| | - Jin Jin
- Siemens Healthcare Pty Ltd.BrisbaneAustralia
| | | | - David C. Reutens
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- ARC Training Centre for Innovation in Biomedical Imaging Technology (CIBIT)The University of QueenslandBrisbaneAustralia
| | - Siegfried Trattnig
- High Field MR Centre, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | | | - Markus Barth
- Centre of Advanced ImagingUniversity of QueenslandBrisbaneAustralia
- School of Information Technology and Electrical EngineeringThe University of QueenslandBrisbaneAustralia
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Marchetto E, Murphy K, Glimberg SL, Gallichan D. Robust retrospective motion correction of head motion using navigator-based and markerless motion tracking techniques. Magn Reson Med 2023; 90:1297-1315. [PMID: 37183791 PMCID: PMC7615144 DOI: 10.1002/mrm.29705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 04/05/2023] [Accepted: 04/26/2023] [Indexed: 05/16/2023]
Abstract
PURPOSE This study investigated the artifacts arising from different types of head motion in brain MR images and how well these artifacts can be compensated using retrospective correction based on two different motion-tracking techniques. METHODS MPRAGE images were acquired using a 3 T MR scanner on a cohort of nine healthy participants. Subjects moved their head to generate circular motion (4 or 6 cycles/min), stepwise motion (small and large) and "simulated realistic" motion (nodding and slow diagonal motion), based on visual instructions. One MPRAGE scan without deliberate motion was always acquired as a "no motion" reference. Three dimensional fat-navigator (FatNavs) and a Tracoline markerless device (TracInnovations) were used to obtain motion estimates and images were separately reconstructed retrospectively from the raw data based on these different motion estimates. RESULTS Image quality was recovered from both motion tracking techniques in our stepwise and slow diagonal motion scenarios in almost all cases, with the apparent visual image quality comparable to the no-motion case. FatNav-based motion correction was further improved in the case of stepwise motion using a skull masking procedure to exclude non-rigid motion of the neck from the co-registration step. In the case of circular motion, both methods struggled to correct for all motion artifacts. CONCLUSION High image quality could be recovered in cases of stepwise and slow diagonal motion using both motion estimation techniques. The circular motion scenario led to more severe image artifacts that could not be fully compensated by the retrospective motion correction techniques used.
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Affiliation(s)
- Elisa Marchetto
- CUBRIC/School of Engineering, Cardiff University, Cardiff, UK
| | - Kevin Murphy
- CUBRIC/School of Physics and Astronomy, Cardiff University, Cardiff, UK
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Fang A, Baran B, Feusner JD, Phan KL, Beatty CC, Crane J, Jacoby RJ, Manoach DS, Wilhelm S. Self-Focused Brain Predictors of Cognitive Behavioral Therapy Response in a Transdiagnostic Sample. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.30.23294878. [PMID: 37693433 PMCID: PMC10491350 DOI: 10.1101/2023.08.30.23294878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Background Effective biomarkers of cognitive behavioral therapy (CBT) response provide information beyond available behavioral or self-report measures and may optimize treatment selection for patients based on likelihood of benefit. No single biomarker reliably predicts CBT response. In this study, we evaluated patterns of brain connectivity associated with self-focused attention (SFA) as biomarkers of CBT response for anxiety and obsessive-compulsive disorders. We hypothesized that pre-treatment as well as pre- to post-treatment changes in functional connectivity would be associated with improvement during CBT in a transdiagnostic sample. Methods Twenty-seven patients with primary social anxiety disorder (n=14) and primary body dysmorphic disorder (n=13) were scanned before and after 12 sessions of CBT targeting their primary disorder. Eligibility was based on elevated trait SFA scores on the Public Self-Consciousness Scale. Seed-based resting state functional connectivity associated with symptom improvement was computed using a seed in the posterior cingulate cortex/precuneus that delineated a self-other functional network. Results At pre-treatment, stronger positive connectivity of the seed with the cerebellum, insula, middle occipital gyrus, postcentral gyrus, and precuneus/superior parietal lobule, and stronger negative connectivity with the putamen, were associated with greater clinical improvement. Between pre- to post-treatment, greater anticorrelation between the seed and precuneus/superior parietal lobule was associated with clinical improvement, although this did not survive thresholding. Conclusions Pre-treatment functional connectivity between regions involved in attentional salience, self-generated thoughts, and external attention predicted greater CBT response. Behavioral and self-report measures of SFA did not contribute to predictions, thus highlighting the value of neuroimaging-based measures of SFA. Clinical Trials Registration ClinicalTrials.gov Identifier: NCT02808702 https://clinicaltrials.gov/ct2/show/NCT02808702.
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Affiliation(s)
- Angela Fang
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, 52242-1407
| | - Jamie D. Feusner
- Centre for Addiction and Mental Health, Brain Imaging Health Center, Ontario, Toronto, Canada, M5T1R8
- Department of Psychiatry, University of Toronto, Ontario, Toronto, Canada, M5T1R8
- Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
| | - K. Luan Phan
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, 43210-1240
| | - Clare C. Beatty
- Department of Psychology, Stony Brook University, Stony Brook, NY, 11794-2500
| | - Jessica Crane
- Department of Psychology, University of Washington, Seattle, WA, 98195-1525
| | - Ryan J. Jacoby
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, 02129-2020
| | - Sabine Wilhelm
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114-2696
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Huang Y, Chen L, Li X, Liu J. Improved test-retest reliability of R2* and susceptibility quantification using multi-shot multi-echo 3D EPI. ARXIV 2023:arXiv:2308.07811v1. [PMID: 37645047 PMCID: PMC10462177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
This study aimed to evaluate the potential of 3D echo-planar imaging (EPI) for improving the reliability of T2*-weighted (T2*w) data and quantification of R2* decay rate and susceptibility (χ) compared to conventional gradient echo (GRE)-based acquisition. Eight healthy subjects in a wide age range were recruited. Each subject received repeated scans for both GRE and EPI acquisitions with an isotropic 1 mm resolution at 3 T. Maps of R2* and χ were quantified and compared using their inter-scan difference to evaluate the test-retest reliability. Inter-protocol differences of R2* and χ between GRE and EPI were also measured voxel by voxel and in selected ROIs to test the consistency between the two acquisition methods. The quantifications of R2* and χ using EPI protocols showed increased test-retest reliability with higher EPI factors up to 5 as performed in the experiment and were consistent with those based on GRE. This result suggested multi-shot multi-echo 3D EPI can be a useful alternative acquisition method for T2*w MRI and quantification of R2* and χ with reduced scan time, improved test-retest reliability and similar accuracy compared to commonly used 3D GRE.
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Affiliation(s)
- Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
- Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA
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Lyons‐Ruth K, Ahtam B, Li FH, Dickerman S, Khoury JE, Sisitsky M, Ou Y, Bosquet Enlow M, Teicher MH, Grant PE. Negative versus withdrawn maternal behavior: Differential associations with infant gray and white matter during the first 2 years of life. Hum Brain Mapp 2023; 44:4572-4589. [PMID: 37417795 PMCID: PMC10365238 DOI: 10.1002/hbm.26401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Revised: 05/30/2023] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Distinct neural effects of threat versus deprivation emerge by childhood, but little data are available in infancy. Withdrawn versus negative parenting may represent dimensionalized indices of early deprivation versus early threat, but no studies have assessed neural correlates of withdrawn versus negative parenting in infancy. The objective of this study was to separately assess the links of maternal withdrawal and maternal negative/inappropriate interaction with infant gray matter volume (GMV), white matter volume (WMV), amygdala, and hippocampal volume. Participants included 57 mother-infant dyads. Withdrawn and negative/inappropriate aspects of maternal behavior were coded from the Still-Face Paradigm at four months infant age. Between 4 and 24 months (M age = 12.28 months, SD = 5.99), during natural sleep, infants completed an MRI using a 3.0 T Siemens scanner. GMV, WMV, amygdala, and hippocampal volumes were extracted via automated segmentation. Diffusion weighted imaging volumetric data were also generated for major white matter tracts. Maternal withdrawal was associated with lower infant GMV. Negative/inappropriate interaction was associated with lower overall WMV. Age did not moderate these effects. Maternal withdrawal was further associated with reduced right hippocampal volume at older ages. Exploratory analyses of white matter tracts found that negative/inappropriate maternal behavior was specifically associated with reduced volume in the ventral language network. Results suggest that quality of day-to-day parenting is related to infant brain volumes during the first two years of life, with distinct aspects of interaction associated with distinct neural effects.
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Affiliation(s)
- Karlen Lyons‐Ruth
- Department of PsychiatryCambridge Hospital, Harvard Medical SchoolCambridgeMassachusettsUSA
| | - Banu Ahtam
- Fetal‐Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Frances Haofei Li
- Department of PsychiatryCambridge Hospital, Harvard Medical SchoolCambridgeMassachusettsUSA
| | - Sarah Dickerman
- Department of Psychiatry, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Jennifer E. Khoury
- Department of PsychiatryCambridge Hospital, Harvard Medical SchoolCambridgeMassachusettsUSA
- Present address:
Department of PsychologyMount Saint Vincent UniversityHalifaxNova ScotiaCanada
| | - Michaela Sisitsky
- Fetal‐Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Yangming Ou
- Fetal‐Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Department of Radiology, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Michelle Bosquet Enlow
- Department of PsychiatryCambridge Hospital, Harvard Medical SchoolCambridgeMassachusettsUSA
- Department of Psychiatry, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Martin H. Teicher
- Department of PsychiatryMcLean Hospital, Harvard Medical SchoolBelmontMassachusettsUSA
| | - P. Ellen Grant
- Fetal‐Neonatal Neuroimaging & Developmental Science Center, Division of Newborn Medicine, Department of Pediatrics, Boston Children's HospitalHarvard Medical SchoolBostonMassachusettsUSA
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Boroshok AL, McDermott CL, Fotiadis P, Park AT, Tooley UA, Gataviņš MM, Tisdall MD, Bassett DS, Mackey AP. Individual differences in T1w/T2w ratio development during childhood. Dev Cogn Neurosci 2023; 62:101270. [PMID: 37348147 PMCID: PMC10439503 DOI: 10.1016/j.dcn.2023.101270] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/12/2023] [Accepted: 06/15/2023] [Indexed: 06/24/2023] Open
Abstract
Myelination is a key developmental process that promotes rapid and efficient information transfer. Myelin also stabilizes existing brain networks and thus may constrain neuroplasticity, defined here as the brain's potential to change in response to experiences rather than the canonical definition as the process of change. Characterizing individual differences in neuroplasticity may shed light on mechanisms by which early experiences shape learning, brain and body development, and response to interventions. The T1-weighted/T2-weighted (T1w/T2w) MRI signal ratio is a proxy measure of cortical microstructure and thus neuroplasticity. Here, in pre-registered analyses, we investigated individual differences in T1w/T2w ratios in children (ages 4-10, n = 157). T1w/T2w ratios were positively associated with age within early-developing sensorimotor and attention regions. We also tested whether socioeconomic status, cognition (crystallized knowledge or fluid reasoning), and biological age (as measured with molar eruption) were related to T1w/T2w signal but found no significant effects. Associations among T1w/T2w ratios, early experiences, and cognition may emerge later in adolescence and may not be strong enough to detect in moderate sample sizes.
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Affiliation(s)
- Austin L Boroshok
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Panagiotis Fotiadis
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Anne T Park
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - Ursula A Tooley
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Washington University in St. Louis, USA; Department of Neurology, Washington University in St. Louis, USA
| | - Mārtiņš M Gataviņš
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Electrical & Systems Engineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Physics & Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Santa Fe Institute, Santa Fe, NM, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA; Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
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Taraku B, Zavaliangos-Petropulu A, Loureiro JR, Al-Sharif NB, Kubicki A, Joshi SH, Woods RP, Espinoza R, Narr KL, Sahib AK. White matter microstructural perturbations after total sleep deprivation in depression. Front Psychiatry 2023; 14:1195763. [PMID: 37457774 PMCID: PMC10345348 DOI: 10.3389/fpsyt.2023.1195763] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 06/06/2023] [Indexed: 07/18/2023] Open
Abstract
Background Total sleep deprivation (TSD) transiently reverses depressive symptoms in a majority of patients with depression. How TSD modulates diffusion tensor imaging (DTI) measures of white matter (WM) microstructure, which may be linked with TSD's rapid antidepressant effects, remains uncharacterized. Methods Patients with depression (N = 48, mean age = 33, 26 women) completed diffusion-weighted imaging and Hamilton Depression Rating (HDRS) and rumination scales before and after >24 h of TSD. Healthy controls (HC) (N = 53, 23 women) completed the same assessments at baseline, and after receiving TSD in a subset of HCs (N = 15). Tract based spatial statistics (TBSS) investigated voxelwise changes in fractional anisotropy (FA) across major WM pathways pre-to-post TSD in patients and HCs and between patients and HCs at baseline. Post hoc analyses tested for TSD effects for other diffusion metrics, and the relationships between change in diffusion measures with change in mood and rumination symptoms. Results Significant improvements in mood and rumination occurred in patients with depression (both p < 0.001), but not in HCs following TSD. Patients showed significant (p < 0.05, corrected) decreases in FA values in multiple WM tracts, including the body of the corpus callosum and anterior corona radiata post-TSD. Significant voxel-level changes in FA were not observed in HCs who received TSD (p > 0.05). However, differential effects of TSD between HCs and patients were found in the superior corona radiata, frontal WM and the posterior thalamic radiation (p < 0.05, corrected). A significant (p < 0.05) association between change in FA and axial diffusivity within the right superior corona radiata and improvement in rumination was found post-TSD in patients. Conclusion Total sleep deprivation leads to rapid microstructural changes in WM pathways in patients with depression that are distinct from WM changes associated with TSD observed in HCs. WM tracts including the superior corona radiata and posterior thalamic radiation could be potential biomarkers of the rapid therapeutic effects of TSD. Changes in superior corona radiata FA, in particular, may relate to improvements in maladaptive rumination.
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Affiliation(s)
- Brandon Taraku
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Artemis Zavaliangos-Petropulu
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Joana R. Loureiro
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Noor B. Al-Sharif
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Antoni Kubicki
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Shantanu H. Joshi
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Roger P. Woods
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Randall Espinoza
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Katherine L. Narr
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Ashish K. Sahib
- Department of Neurology, Ahmanson-Lovelace Brain Mapping Center, University of California, Los Angeles, Los Angeles, CA, United States
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Conti M, Teghil A, Di Vita A, Boccia M. Lifelong impairment in episodic re-experiencing: Neuropsychological and neuroimaging examination of a new case of Severely Deficient Autobiographical Memory. Cortex 2023; 163:80-91. [PMID: 37075508 DOI: 10.1016/j.cortex.2023.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 02/13/2023] [Accepted: 03/02/2023] [Indexed: 03/29/2023]
Abstract
Autobiographical memory (AM) represents a complex and multimodal cognitive function, that allows an individual to collect and retrieve personal events and facts, enabling to develop and maintain the continuity of the self over time. Here we describe the case of DR (acronym of the fictional name Doriana Rossi), a 53-year-old woman, who complains of a specific and lifelong deficit in recalling autobiographical episodes. Along with an extensive neuropsychological assessment, DR underwent a structural and functional MRI examination to further define this impairment. The neuropsychological assessment revealed a deficit in episodic re-experiencing of her own personal life events. DR showed reduced cortical thickness in the Retrosplenial Complex in the left hemisphere, and in the Lateral Occipital Cortex, in the Prostriate Cortex and the Angular Gyrus in the right hemisphere. An altered pattern of activity in the calcarine cortex was detected during ordering of autobiographical events according to her own personal timeline. The present study provides further evidence about the existence of a severely deficient autobiographical memory condition in neurologically healthy people, with otherwise preserved cognitive functioning. Furthermore, the present data provide new important insights into neurocognitive mechanisms underpinning such a developmental condition.
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Affiliation(s)
- Matilde Conti
- Department of Psychology, Sapienza University of Rome, Rome, Italy.
| | - Alice Teghil
- Department of Psychology, Sapienza University of Rome, Rome, Italy; Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Antonella Di Vita
- Department of Human Neuroscience, Sapienza University of Rome, Rome, Italy
| | - Maddalena Boccia
- Department of Psychology, Sapienza University of Rome, Rome, Italy; Cognitive and Motor Rehabilitation and Neuroimaging Unit, IRCCS Fondazione Santa Lucia, Rome, Italy
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Pollak C, Kügler D, Breteler MMB, Reuter M. Quantifying MR Head Motion in the Rhineland Study - A Robust Method for Population Cohorts. Neuroimage 2023; 275:120176. [PMID: 37209757 DOI: 10.1016/j.neuroimage.2023.120176] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/22/2023] [Accepted: 05/15/2023] [Indexed: 05/22/2023] Open
Abstract
Head motion during MR acquisition reduces image quality and has been shown to bias neuromorphometric analysis. The quantification of head motion, therefore, has both neuroscientific as well as clinical applications, for example, to control for motion in statistical analyses of brain morphology, or as a variable of interest in neurological studies. The accuracy of markerless optical head tracking, however, is largely unexplored. Furthermore, no quantitative analysis of head motion in a general, mostly healthy population cohort exists thus far. In this work, we present a robust registration method for the alignment of depth camera data that sensitively estimates even small head movements of compliant participants. Our method outperforms the vendor-supplied method in three validation experiments: 1. similarity to fMRI motion traces as a low-frequency reference, 2. recovery of the independently acquired breathing signal as a high-frequency reference, and 3. correlation with image-based quality metrics in structural T1-weighted MRI. In addition to the core algorithm, we establish an analysis pipeline that computes average motion scores per time interval or per sequence for inclusion in downstream analyses. We apply the pipeline in the Rhineland Study, a large population cohort study, where we replicate age and body mass index (BMI) as motion correlates and show that head motion significantly increases over the duration of the scan session. We observe weak, yet significant interactions between this within-session increase and age, BMI, and sex. High correlations between fMRI and camera-based motion scores of proceeding sequences further suggest that fMRI motion estimates can be used as a surrogate score in the absence of better measures to control for motion in statistical analyses.
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Affiliation(s)
- Clemens Pollak
- AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - David Kügler
- AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Martin Reuter
- AI in Medical Imaging, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany; A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
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46
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Polak D, Hossbach J, Splitthoff DN, Clifford B, Lo WC, Tabari A, Lang M, Huang SY, Conklin J, Wald LL, Cauley S. Motion guidance lines for robust data consistency-based retrospective motion correction in 2D and 3D MRI. Magn Reson Med 2023; 89:1777-1790. [PMID: 36744619 PMCID: PMC10518424 DOI: 10.1002/mrm.29534] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 10/06/2022] [Accepted: 10/31/2022] [Indexed: 02/07/2023]
Abstract
PURPOSE To develop a robust retrospective motion-correction technique based on repeating k-space guidance lines for improving motion correction in Cartesian 2D and 3D brain MRI. METHODS The motion guidance lines are inserted into the standard sequence orderings for 2D turbo spin echo and 3D MPRAGE to inform a data consistency-based motion estimation and reconstruction, which can be guided by a low-resolution scout. The extremely limited number of required guidance lines are repeated during each echo train and discarded in the final image reconstruction. Thus, integration within a standard k-space acquisition ordering ensures the expected image quality/contrast and motion sensitivity of that sequence. RESULTS Through simulation and in vivo 2D multislice and 3D motion experiments, we demonstrate that respectively 2 or 4 optimized motion guidance lines per shot enables accurate motion estimation and correction. Clinically acceptable reconstruction times are achieved through fully separable on-the-fly motion optimizations (˜1 s/shot) using standard scanner GPU hardware. CONCLUSION The addition of guidance lines to scout accelerated motion estimation facilitates robust retrospective motion correction that can be effectively introduced without perturbing standard clinical protocols and workflows.
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Affiliation(s)
- Daniel Polak
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Siemens Healthcare GmbH, Erlangen, Germany
| | | | | | | | | | - Azadeh Tabari
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Min Lang
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Susie Y. Huang
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - John Conklin
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Lawrence L. Wald
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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Gimbel BA, Roediger DJ, Ernst AM, Anthony ME, de Water E, Rockhold MN, Mueller BA, Mattson SN, Jones KL, Riley EP, Lim KO, Wozniak JR. Atypical developmental trajectories of white matter microstructure in prenatal alcohol exposure: Preliminary evidence from neurite orientation dispersion and density imaging. Front Neurosci 2023; 17:1172010. [PMID: 37168930 PMCID: PMC10165006 DOI: 10.3389/fnins.2023.1172010] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 03/30/2023] [Indexed: 05/13/2023] Open
Abstract
Introduction Fetal alcohol spectrum disorder (FASD), a life-long condition resulting from prenatal alcohol exposure (PAE), is associated with structural brain anomalies and neurobehavioral differences. Evidence from longitudinal neuroimaging suggest trajectories of white matter microstructure maturation are atypical in PAE. We aimed to further characterize longitudinal trajectories of developmental white matter microstructure change in children and adolescents with PAE compared to typically-developing Controls using diffusion-weighted Neurite Orientation Dispersion and Density Imaging (NODDI). Materials and methods Participants: Youth with PAE (n = 34) and typically-developing Controls (n = 31) ages 8-17 years at enrollment. Participants underwent formal evaluation of growth and facial dysmorphology. Participants also completed two study visits (17 months apart on average), both of which involved cognitive testing and an MRI scan (data collected on a Siemens Prisma 3 T scanner). Age-related changes in the orientation dispersion index (ODI) and the neurite density index (NDI) were examined across five corpus callosum (CC) regions defined by tractography. Results While linear trajectories suggested similar overall microstructural integrity in PAE and Controls, analyses of symmetrized percent change (SPC) indicated group differences in the timing and magnitude of age-related increases in ODI (indexing the bending and fanning of axons) in the central region of the CC, with PAE participants demonstrating atypically steep increases in dispersion with age compared to Controls. Participants with PAE also demonstrated greater increases in ODI in the mid posterior CC (trend-level group difference). In addition, SPC in ODI and NDI was differentially correlated with executive function performance for PAE participants and Controls, suggesting an atypical relationship between white matter microstructure maturation and cognitive function in PAE. Discussion Preliminary findings suggest subtle atypicality in the timing and magnitude of age-related white matter microstructure maturation in PAE compared to typically-developing Controls. These findings add to the existing literature on neurodevelopmental trajectories in PAE and suggest that advanced biophysical diffusion modeling (NODDI) may be sensitive to biologically-meaningful microstructural changes in the CC that are disrupted by PAE. Findings of atypical brain maturation-behavior relationships in PAE highlight the need for further study. Further longitudinal research aimed at characterizing white matter neurodevelopmental trajectories in PAE will be important.
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Affiliation(s)
- Blake A. Gimbel
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Donovan J. Roediger
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Abigail M. Ernst
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Mary E. Anthony
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Erik de Water
- Great Lakes Neurobehavioral Center, Edina, MN, United States
| | | | - Bryon A. Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | - Sarah N. Mattson
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Kenneth L. Jones
- Department of Pediatrics, University of California, San Diego, San Diego, CA, United States
| | - Edward P. Riley
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Kelvin O. Lim
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
| | | | - Jeffrey R. Wozniak
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Twin Cities, Minneapolis, MN, United States
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van Gelderen P, Li X, de Zwart JA, Beck ES, Okar SV, Huang Y, Lai K, Sulam J, van Zijl PCM, Reich DS, Duyn JH, Liu J. Effect of motion, cortical orientation and spatial resolution on quantitative imaging of cortical R 2* and magnetic susceptibility at 0.3 mm in-plane resolution at 7 T. Neuroimage 2023; 270:119992. [PMID: 36858332 PMCID: PMC10278242 DOI: 10.1016/j.neuroimage.2023.119992] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 02/17/2023] [Accepted: 02/25/2023] [Indexed: 03/03/2023] Open
Abstract
MR images of the effective relaxation rate R2* and magnetic susceptibility χ derived from multi-echo T2*-weighted (T2*w) MRI can provide insight into iron and myelin distributions in the brain, with the potential of providing biomarkers for neurological disorders. Quantification of R2* and χ at submillimeter resolution in the cortex in vivo has been difficult because of challenges such as head motion, limited signal to noise ratio, long scan time, and motion related magnetic field fluctuations. This work aimed to improve the robustness for quantifying intracortical R2* and χ and analyze the effects from motion, spatial resolution, and cortical orientation. T2*w data was acquired with a spatial resolution of 0.3 × 0.3 × 0.4 mm3 at 7 T and downsampled to various lower resolutions. A combined correction for motion and B0 changes was deployed using volumetric navigators. Such correction improved the T2*w image quality rated by experienced image readers and test-retest reliability of R2* and χ quantification with reduced median inter-scan differences up to 10 s-1 and 5 ppb, respectively. R2* and χ near the line of Gennari, a cortical layer high in iron and myelin, were as much as 10 s-1 and 10 ppb higher than the region at adjacent cortical depth. In addition, a significant effect due to the cortical orientation relative to the static field (B0) was observed in χ with a peak-to-peak amplitude of about 17 ppb. In retrospectively downsampled data, the capability to distinguish different cortical depth regions based on R2* or χ contrast remained up to isotropic 0.5 mm resolution. This study highlights the unique characteristics of R2* and χ along the cortical depth at submillimeter resolution and the need for motion and B0 corrections for their robust quantification in vivo.
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Affiliation(s)
- Peter van Gelderen
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Xu Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Jacco A de Zwart
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Erin S Beck
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York City, NY, United States of America
| | - Serhat V Okar
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Yujia Huang
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America
| | - KuoWei Lai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America; Department of Electrical & Computer Engineering, Georgia Institute of Technology, Atlanta, GA, United States of America
| | - Jeremias Sulam
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States of America
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, United States of America; Department of Radiology and Radiological Sciences, Johns Hopkins University, Baltimore, MD, United States of America
| | - Daniel S Reich
- Translational Neurology Section, NINDS, NIH, Bethesda, MD, United States of America
| | - Jeff H Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States of America
| | - Jiaen Liu
- Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, United States of America.
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Levitt J, van der Kouwe A, Jeong H, Lewis LD, Bonmassar G. The MotoNet: A 3 Tesla MRI-Conditional EEG Net with Embedded Motion Sensors. SENSORS (BASEL, SWITZERLAND) 2023; 23:3539. [PMID: 37050598 PMCID: PMC10098760 DOI: 10.3390/s23073539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/20/2023] [Accepted: 03/23/2023] [Indexed: 06/19/2023]
Abstract
We introduce a new electroencephalogram (EEG) net, which will allow clinicians to monitor EEG while tracking head motion. Motion during MRI limits patient scans, especially of children with epilepsy. EEG is also severely affected by motion-induced noise, predominantly ballistocardiogram (BCG) noise due to the heartbeat. METHODS The MotoNet was built using polymer thick film (PTF) EEG leads and motion sensors on opposite sides in the same flex circuit. EEG/motion measurements were made with a standard commercial EEG acquisition system in a 3 Tesla (T) MRI. A Kalman filtering-based BCG correction tool was used to clean the EEG in healthy volunteers. RESULTS MRI safety studies in 3 T confirmed the maximum heating below 1 °C. Using an MRI sequence with spatial localization gradients only, the position of the head was linearly correlated with the average motion sensor output. Kalman filtering was shown to reduce the BCG noise and recover artifact-clean EEG. CONCLUSIONS The MotoNet is an innovative EEG net design that co-locates 32 EEG electrodes with 32 motion sensors to improve both EEG and MRI signal quality. In combination with custom gradients, the position of the net can, in principle, be determined. In addition, the motion sensors can help reduce BCG noise.
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Affiliation(s)
- Joshua Levitt
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - André van der Kouwe
- Athinoula A. Martinos Center for Biomedical Engineering, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Hongbae Jeong
- Athinoula A. Martinos Center for Biomedical Engineering, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Laura D. Lewis
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
- Athinoula A. Martinos Center for Biomedical Engineering, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Giorgio Bonmassar
- Athinoula A. Martinos Center for Biomedical Engineering, Massachusetts General Hospital, Charlestown, MA 02129, USA
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50
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Ibrahim A, Warton FL, Fry S, Cotton MF, Jacobson SW, Jacobson JL, Molteno CD, Little F, van der Kouwe AJW, Laughton B, Meintjes EM, Holmes MJ. Maternal ART throughout gestation prevents caudate volume reductions in neonates who are HIV exposed but uninfected. Front Neurosci 2023; 17:1085589. [PMID: 36968507 PMCID: PMC10035579 DOI: 10.3389/fnins.2023.1085589] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 01/25/2023] [Indexed: 03/12/2023] Open
Abstract
IntroductionSuccessful programmes for prevention of vertical HIV transmission have reduced the risk of infant HIV infection in South Africa from 8% in 2008 to below 1% in 2018/2019, resulting in an increasing population of children exposed to HIV perinatally but who are uninfected (HEU). However, the long-term effects of HIV and antiretroviral treatment (ART) exposure on the developing brain are not well understood. Whereas children who are HEU perform better than their HIV-infected counterparts, they demonstrate greater neurodevelopmental delay than children who are HIV unexposed and uninfected (HUU), especially in resource-poor settings. Here we investigate subcortical volumetric differences related to HIV and ART exposure in neonates.MethodsWe included 120 infants (59 girls; 79 HEU) born to healthy women with and without HIV infection in Cape Town, South Africa, where HIV sero-prevalence approaches 30%. Of the 79 HEU infants, 40 were exposed to ART throughout gestation (i.e., mothers initiated ART pre conception; HEU-pre), and 39 were exposed to ART for part of gestation (i.e., mothers initiated ART post conception; HEU-post). Post-conception mothers had a mean (± SD) gestational age (GA) of 15.4 (± 5.7) weeks at ART initiation. Mothers with HIV received standard care fixed drug combination ART (Tenofovir/Efavirenz/Emtricitabine). Infants were imaged unsedated on a 3T Skyra (Siemens, Erlangen, Germany) at mean GA equivalent of 41.5 (± 1.0) weeks. Selected regions (caudate, putamen, pallidum, thalamus, cerebellar hemispheres and vermis, and corpus callosum) were manually traced on T1-weighted images using Freeview.ResultsHEU neonates had smaller left putamen volumes than HUU [β (SE) = −90.3 (45.3), p = 0.05] and caudate volume reductions that depended on ART exposure duration in utero. While the HEU-pre group demonstrated no caudate volume reductions compared to HUU, the HEU-post group had smaller caudate volumes bilaterally [β (SE) = −145.5 (45.1), p = 0.002, and −135.7 (49.7), p = 0.008 for left and right caudate, respectively].DiscussionThese findings from the first postnatal month suggest that maternal ART throughout gestation is protective to the caudate nuclei. In contrast, left putamens were smaller across all HEU newborns, despite maternal ART.
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Affiliation(s)
- Abdulmumin Ibrahim
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Fleur L. Warton
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- *Correspondence: Fleur L. Warton,
| | - Samantha Fry
- Department of Paediatrics and Child Health and Tygerberg Children’s Hospital, Faculty of Medicine and Health Sciences, Family Centre for Research with Ubuntu, Stellenbosch University, Stellenbosch, South Africa
| | - Mark F. Cotton
- Department of Paediatrics and Child Health and Tygerberg Children’s Hospital, Faculty of Medicine and Health Sciences, Family Centre for Research with Ubuntu, Stellenbosch University, Stellenbosch, South Africa
| | - Sandra W. Jacobson
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Joseph L. Jacobson
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Christopher D. Molteno
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
| | - Francesca Little
- Department of Statistical Sciences, University of Cape Town, Cape Town, South Africa
| | - Andre J. W. van der Kouwe
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
| | - Barbara Laughton
- Department of Paediatrics and Child Health and Tygerberg Children’s Hospital, Faculty of Medicine and Health Sciences, Family Centre for Research with Ubuntu, Stellenbosch University, Stellenbosch, South Africa
| | - Ernesta M. Meintjes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Cape Universities Body Imaging Centre, University of Cape Town, Cape Town, South Africa
- Ernesta M. Meintjes,
| | - Martha J. Holmes
- Division of Biomedical Engineering, Department of Human Biology, Faculty of Health Sciences, Biomedical Engineering Research Centre, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
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