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Kara D, Koenig K, Lowe M, Nguyen C, Sakaie K. Facilitating diffusion tensor imaging of the brain during continuous gross head motion with first and second order motion compensating diffusion gradients. Magn Reson Med 2024; 91:1556-1566. [PMID: 38073070 PMCID: PMC10872734 DOI: 10.1002/mrm.29924] [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: 06/08/2023] [Revised: 10/19/2023] [Accepted: 10/24/2023] [Indexed: 01/26/2024]
Abstract
PURPOSE To demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion. METHODS Five healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion-weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections. RESULTS In the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion-M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion-M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion-M2 data were consistent with reference data. CONCLUSION This proof-of-principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion.
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Affiliation(s)
- Danielle Kara
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic
| | | | - Mark Lowe
- Imaging Sciences, Imaging Institute, Cleveland Clinic
| | - Christopher Nguyen
- Cardiovascular Innovation Research Center, Heart, Vascular, and Thoracic Institute, Cleveland Clinic
- Imaging Sciences, Imaging Institute, Cleveland Clinic
- Biomedical Engineering, Lerner Research Institute, Cleveland Clinic and Case Western Reserve University
| | - Ken Sakaie
- Imaging Sciences, Imaging Institute, Cleveland Clinic
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2
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Neves Silva S, Aviles Verdera J, Tomi‐Tricot R, Neji R, Uus A, Grigorescu I, Wilkinson T, Ozenne V, Lewin A, Story L, De Vita E, Rutherford M, Pushparajah K, Hajnal J, Hutter J. Real-time fetal brain tracking for functional fetal MRI. Magn Reson Med 2023; 90:2306-2320. [PMID: 37465882 PMCID: PMC10952752 DOI: 10.1002/mrm.29803] [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: 03/28/2023] [Revised: 07/03/2023] [Accepted: 07/03/2023] [Indexed: 07/20/2023]
Abstract
PURPOSE To improve motion robustness of functional fetal MRI scans by developing an intrinsic real-time motion correction method. MRI provides an ideal tool to characterize fetal brain development and growth. It is, however, a relatively slow imaging technique and therefore extremely susceptible to subject motion, particularly in functional MRI experiments acquiring multiple Echo-Planar-Imaging-based repetitions, for example, diffusion MRI or blood-oxygen-level-dependency MRI. METHODS A 3D UNet was trained on 125 fetal datasets to track the fetal brain position in each repetition of the scan in real time. This tracking, inserted into a Gadgetron pipeline on a clinical scanner, allows updating the position of the field of view in a modified echo-planar imaging sequence. The method was evaluated in real-time in controlled-motion phantom experiments and ten fetal MR studies (17 + 4-34 + 3 gestational weeks) at 3T. The localization network was additionally tested retrospectively on 29 low-field (0.55T) datasets. RESULTS Our method achieved real-time fetal head tracking and prospective correction of the acquisition geometry. Localization performance achieved Dice scores of 84.4% and 82.3%, respectively for both the unseen 1.5T/3T and 0.55T fetal data, with values higher for cephalic fetuses and increasing with gestational age. CONCLUSIONS Our technique was able to follow the fetal brain even for fetuses under 18 weeks GA in real-time at 3T and was successfully applied "offline" to new cohorts on 0.55T. Next, it will be deployed to other modalities such as fetal diffusion MRI and to cohorts of pregnant participants diagnosed with pregnancy complications, for example, pre-eclampsia and congenital heart disease.
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Affiliation(s)
- Sara Neves Silva
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jordina Aviles Verdera
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Raphael Tomi‐Tricot
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUK
| | - Radhouene Neji
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUK
| | - Alena Uus
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Irina Grigorescu
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Thomas Wilkinson
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Valery Ozenne
- CNRS, CRMSB, UMR 5536, IHU LirycUniversité de BordeauxBordeauxFrance
| | - Alexander Lewin
- Institute of Neuroscience and Medicine 11, INM‐11Forschungszentrum JülichJülichGermany
- RWTHAachen UniversityAachenGermany
| | - Lisa Story
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Department of Women & Children's HealthKing's College LondonLondonUK
| | - Enrico De Vita
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- MRI Physics GroupGreat Ormond Street HospitalLondonUK
| | - Mary Rutherford
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Kuberan Pushparajah
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jo Hajnal
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
| | - Jana Hutter
- Centre for the Developing Brain, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
- Biomedical Engineering Department, School of Biomedical Engineering & Imaging SciencesKing's College LondonLondonUK
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3
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Maffei C, Gilmore N, Snider SB, Foulkes AS, Bodien YG, Yendiki A, Edlow BL. Automated detection of axonal damage along white matter tracts in acute severe traumatic brain injury. Neuroimage Clin 2022; 37:103294. [PMID: 36529035 PMCID: PMC9792957 DOI: 10.1016/j.nicl.2022.103294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 12/15/2022]
Abstract
New techniques for individualized assessment of white matter integrity are needed to detect traumatic axonal injury (TAI) and predict outcomes in critically ill patients with acute severe traumatic brain injury (TBI). Diffusion MRI tractography has the potential to quantify white matter microstructure in vivo and has been used to characterize tract-specific changes following TBI. However, tractography is not routinely used in the clinical setting to assess the extent of TAI, in part because focal lesions reduce the robustness of automated methods. Here, we propose a pipeline that combines automated tractography reconstructions of 40 white matter tracts with multivariate analysis of along-tract diffusion metrics to assess the presence of TAI in individual patients with acute severe TBI. We used the Mahalanobis distance to identify abnormal white matter tracts in each of 18 patients with acute severe TBI as compared to 33 healthy subjects. In all patients for which a FreeSurfer anatomical segmentation could be obtained (17 of 18 patients), including 13 with focal lesions, the automated pipeline successfully reconstructed a mean of 37.5 ± 2.1 white matter tracts without the need for manual intervention. A mean of 2.5 ± 2.1 tracts resulted in partial or failed reconstructions and needed to be reinitialized upon visual inspection. The pipeline detected at least one abnormal tract in all patients (mean: 9.1 ± 7.9) and accurately discriminated between patients and controls (AUC: 0.91). The number and neuroanatomic location of abnormal tracts varied across patients and levels of consciousness. The premotor, temporal, and parietal sections of the corpus callosum were the most commonly damaged tracts (in 10, 9, and 8 patients, respectively), consistent with prior histopathological studies of TAI. TAI measures were not associated with concurrent behavioral measures of consciousness. In summary, we provide proof-of-principle evidence that an automated tractography pipeline has translational potential to detect and quantify TAI in individual patients with acute severe TBI.
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Affiliation(s)
- Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
| | - Natalie Gilmore
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Samuel B Snider
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrea S Foulkes
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Brian L Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
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4
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Uchida M, Hung Y, Green A, Kelberman C, Capella J, Gaillard SL, Gabrieli JDE, Biederman J. Association between frontal cortico-limbic white-matter microstructure and risk for pediatric depression. Psychiatry Res Neuroimaging 2021; 318:111396. [PMID: 34695702 PMCID: PMC9073702 DOI: 10.1016/j.pscychresns.2021.111396] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 10/13/2021] [Accepted: 10/14/2021] [Indexed: 10/20/2022]
Abstract
This study aimed to identify white-matter microstructural characteristics associated with risk for pediatric major depressive disorder (MDD) measured by the Child Behavior Checklist (CBCL) Anxiety/Depression scores. Children (N = 32) of both sexes, aged 6-12, underwent T1-weighted whole-head anatomical and diffusion-weighted imaging. Each participant's mean diffusion measure image was generated and thinned to create an alignment-invariant tract representation. Voxel-wise analysis on the resulting map was carried out in Track Based Spatial Statistics (TBSS) using general linear models by regressing the CBCL-Anxiety/Depression score against measures of diffusion tensor imaging (DTI). We also compared these results with prior DTI findings from the same children associated with CBCL-Emotion Dysregulation profile, an indicator for bipolar disorder. TBSS voxel-wise analysis showed a significant negative correlation between fractional anisotropy (FA) and CBCL-Anxiety/Depression scores localized in the right anterior cingulum and connected corpus callosal region. The negative FA correlations in these regions were greater in CBCL-Anxiety/ Depression scores compared to CBCL-Emotional Dysregulation scores. Reduced white-matter connectivity in the anterior cingulum and connected corpus callosal region may represent a biomarker of risk for pediatric MDD. These results may help identify brain differences associated with the development of MDD, and assist with earlier clinical identification of pediatric MDD.
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Affiliation(s)
- Mai Uchida
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America.
| | - Yuwen Hung
- MIT Integrated Learning Initiative, Department of Brain and Cognitive Sciences, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Allison Green
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, United States of America
| | - Caroline Kelberman
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, United States of America
| | - James Capella
- MIT Integrated Learning Initiative, Department of Brain and Cognitive Sciences, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Schuylar L Gaillard
- MIT Integrated Learning Initiative, Department of Brain and Cognitive Sciences, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - John D E Gabrieli
- MIT Integrated Learning Initiative, Department of Brain and Cognitive Sciences, and McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Joseph Biederman
- Clinical and Research Programs in Pediatric Psychopharmacology and Adult ADHD, Massachusetts General Hospital, Boston, MA, United States of America; Department of Psychiatry, Harvard Medical School, Boston, MA, United States of America
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5
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Ware AL, Shukla A, Guo S, Onicas A, Geeraert BL, Goodyear BG, Yeates KO, Lebel C. Participant factors that contribute to magnetic resonance imaging motion artifacts in children with mild traumatic brain injury or orthopedic injury. Brain Imaging Behav 2021; 16:991-1002. [PMID: 34694520 DOI: 10.1007/s11682-021-00582-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/01/2021] [Indexed: 10/20/2022]
Abstract
Motion can compromise image quality and confound results, especially in pediatric research. This study evaluated qualitative and quantitative approaches to motion artifacts detection and correction, and whether motion artifacts relate to injury history, age, or sex in children with mild traumatic brain injury or orthopedic injury relative to typically developing children. The concordance between qualitative and quantitative motion ratings was also examined. Children aged 8-16 years with mild traumatic brain injury (n = 141) or orthopedic injury (n = 73) were recruited from the emergency department and completed an MRI scan roughly 2 weeks post-injury. Typically developing children (n = 41) completed a single MRI scan. T1- and diffusion-weighted images were visually inspected and rated for motion artifacts by trained examiners. Quantitative estimates of motion artifacts were derived from FreeSurfer and FSL. Age (younger > older) and sex (boys > girls) were significantly associated with motion artifacts on both T1- and diffusion-weighted images. Children with mild traumatic brain or orthopedic injury had significantly more motion-corrupted diffusion-weighted volumes than typically developing children, but mild traumatic brain injury and orthopedic injury groups did not differ from each other. The exclusion of motion-corrupted volumes did not significantly change diffusion tensor imaging metrics. Results indicate that automated quantitative estimates of motion artifacts, which are less labour-intensive than manual methods, are appropriate. Results have implications for the reliability of structural MRI research and highlight the importance of considering motion artifacts in studies of pediatric mild traumatic brain injury.
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Affiliation(s)
- Ashley L Ware
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada. .,Hotchkiss Brain Institute, University of Calgary, Calgary, Canada. .,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada. .,Department of Neurology, University of Utah, Salt Lake City, UT, USA.
| | - Ayushi Shukla
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, University of Calgary, Calgary, Canada
| | - Sunny Guo
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Clinical Neurosciences, University of Calgary, Calgary, Canada
| | - Adrian Onicas
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Bryce L Geeraert
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, University of Calgary, Calgary, Canada
| | - Bradley G Goodyear
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, University of Calgary, Calgary, Canada.,Seaman Family MR Research Centre, Foothills Medical Centre, Alberta Health Services, Calgary, Canada
| | - Keith Owen Yeates
- Department of Psychology, University of Calgary, 2500 University Drive NW, Calgary, AB, T2N 1N4, Canada.,Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
| | - Catherine Lebel
- Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.,Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.,Department of Radiology, University of Calgary, Calgary, Canada
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6
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Liang X, Su P, Patil SG, Elsaid NMH, Roys S, Stone M, Gullapalli RP, Prince JL, Zhuo J. Prospective motion detection and re-acquisition in diffusion MRI using a phase image-based method-Application to brain and tongue imaging. Magn Reson Med 2021; 86:725-737. [PMID: 33665929 DOI: 10.1002/mrm.28729] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 01/22/2021] [Accepted: 01/23/2021] [Indexed: 11/08/2022]
Abstract
PURPOSE To develop an image-based motion-robust diffusion MRI (dMRI) acquisition framework that is able to minimize motion artifacts caused by rigid and nonrigid motion, applicable to both brain and tongue dMRI. METHODS We developed a novel prospective motion-correction technique in dMRI using a phase image-based real-time motion-detection method (PITA-MDD) with re-acquisition of motion-corrupted images. The prospective PITA-MDD acquisition technique was tested in the brains and tongues of volunteers. The subjects were instructed to move their heads or swallow, to induce motion. Motion-detection efficacy was validated against visual inspection as the gold standard. The effect of the PITA-MDD technique on diffusion-parameter estimates was evaluated by comparing reconstructed fiber tracts using tractography with and without re-acquisition. RESULTS The prospective PITA-MDD technique was able to effectively and accurately detect motion-corrupted data as compared with visual inspection. Tractography results demonstrated that PITA-MDD motion detection followed by re-acquisition helps in recovering lost and misshaped fiber tracts in the brain and tongue that would otherwise be corrupted by motion and yield erroneous estimates of the diffusion tensor. CONCLUSION A prospective PITA-MDD technique was developed for dMRI acquisition, providing improved dMRI image quality and motion-robust diffusion estimation of the brain and tongue.
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Affiliation(s)
- Xiao Liang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Pan Su
- Siemens Medical Solutions USA Inc, Malvern, Pennsylvania, USA
| | - Sunil G Patil
- Siemens Medical Solutions USA Inc, Malvern, Pennsylvania, USA
| | - Nahla M H Elsaid
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Steven Roys
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Maureen Stone
- Department of Neural and Pain Sciences and Department of Orthodontics, University of Maryland School of Dentistry, Baltimore, Maryland, USA
| | - Rao P Gullapalli
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jiachen Zhuo
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
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7
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Andronesi OC, Nicholson K, Jafari-Khouzani K, Bogner W, Wang J, Chan J, Macklin EA, Levine-Weinberg M, Breen C, Schwarzschild MA, Cudkowicz M, Rosen BR, Paganoni S, Ratai EM. Imaging Neurochemistry and Brain Structure Tracks Clinical Decline and Mechanisms of ALS in Patients. Front Neurol 2020; 11:590573. [PMID: 33343494 PMCID: PMC7744722 DOI: 10.3389/fneur.2020.590573] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 11/03/2020] [Indexed: 12/27/2022] Open
Abstract
Background: Oxidative stress and protein aggregation are key mechanisms in amyotrophic lateral sclerosis (ALS) disease. Reduced glutathione (GSH) is the most important intracellular antioxidant that protects neurons from reactive oxygen species. We hypothesized that levels of GSH measured by MR spectroscopic imaging (MRSI) in the motor cortex and corticospinal tract are linked to clinical trajectory of ALS patients. Objectives: Investigate the value of GSH imaging to probe clinical decline of ALS patients in combination with other neurochemical and structural parameters. Methods: Twenty-four ALS patients were imaged at 3 T with an advanced MR protocol. Mapping GSH levels in the brain is challenging, and for this purpose, we used an optimized spectral-edited 3D MRSI sequence with real-time motion and field correction to image glutathione and other brain metabolites. In addition, our imaging protocol included (i) an adiabatic T1ρ sequence to image macromolecular fraction of brain parenchyma, (ii) diffusion tensor imaging (DTI) for white matter tractography, and (iii) high-resolution anatomical imaging. Results: We found GSH in motor cortex (r = −0.431, p = 0.04) and corticospinal tract (r = −0.497, p = 0.016) inversely correlated with time between diagnosis and imaging. N-Acetyl-aspartate (NAA) in motor cortex inversely correlated (r = −0.416, p = 0.049), while mean water diffusivity (r = 0.437, p = 0.033) and T1ρ (r = 0.482, p = 0.019) positively correlated with disease progression measured by imputed change in revised ALS Functional Rating Scale. There is more decrease in the motor cortex than in the white matter for GSH compared to NAA, glutamate, and glutamine. Conclusions: Our study suggests that a panel of biochemical and structural imaging biomarkers defines a brain endophenotype, which can be used to time biological events and clinical progression in ALS patients. Such a quantitative brain endophenotype may stratify ALS patients into more homogeneous groups for therapeutic interventions compared to clinical criteria.
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Affiliation(s)
- Ovidiu C Andronesi
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States
| | - Katharine Nicholson
- Neurological Clinical Research Institute (NCRI), Massachusetts General Hospital, Boston, MA, United States
| | - Kourosh Jafari-Khouzani
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States
| | - Wolfgang Bogner
- High Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Jing Wang
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States.,Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - James Chan
- Biostatistics Center, Massachusetts General Hospital, Boston, MA, United States
| | - Eric A Macklin
- Biostatistics Center, Massachusetts General Hospital, Boston, MA, United States
| | - Mark Levine-Weinberg
- Neurological Clinical Research Institute (NCRI), Massachusetts General Hospital, Boston, MA, United States
| | - Christopher Breen
- Neurological Clinical Research Institute (NCRI), Massachusetts General Hospital, Boston, MA, United States
| | | | - Merit Cudkowicz
- Neurological Clinical Research Institute (NCRI), Massachusetts General Hospital, Boston, MA, United States
| | - Bruce R Rosen
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States
| | - Sabrina Paganoni
- Neurological Clinical Research Institute (NCRI), Massachusetts General Hospital, Boston, MA, United States.,Spaulding Rehabilitation Hospital, Boston, MA, United States
| | - Eva-Maria Ratai
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Harvard Medical School, Massachusetts General Hospital, Boston, MA, United States
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8
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Ferradal SL, Gagoski B, Jaimes C, Yi F, Carruthers C, Vu C, Litt JS, Larsen R, Sutton B, Grant PE, Zöllei L. System-Specific Patterns of Thalamocortical Connectivity in Early Brain Development as Revealed by Structural and Functional MRI. Cereb Cortex 2020; 29:1218-1229. [PMID: 29425270 DOI: 10.1093/cercor/bhy028] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Indexed: 01/31/2023] Open
Abstract
The normal development of thalamocortical connections plays a critical role in shaping brain connectivity in the prenatal and postnatal periods. Recent studies using advanced magnetic resonance imaging (MRI) techniques in neonates and infants have shown that abnormal thalamocortical connectivity is associated with adverse neurodevelopmental outcomes. However, all these studies have focused on a single neuroimaging modality, overlooking the dynamic relationship between structure and function at this early stage. Here, we study the relationship between structural and functional thalamocortical connectivity patterns derived from healthy full-term infants scanned with diffusion-weighted MRI and resting-state functional MRI within the first weeks of life (mean gestational age = 39.3 ± 1.2 weeks; age at scan = 24.2 ± 7.9 days). Our results show that while there is, in general, good spatial agreement between both MRI modalities, there are regional variations that are system-specific: regions involving primary-sensory cortices exhibit greater structural/functional overlap, whereas higher-order association areas such as temporal and posterior parietal cortices show divergence in spatial patterns of each modality. This variability illustrates the complementarity of both modalities and highlights the importance of multimodal approaches.
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Affiliation(s)
| | - Borjan Gagoski
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Camilo Jaimes
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Francesca Yi
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Catherine Vu
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Ryan Larsen
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Brad Sutton
- Beckman Institute, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - P Ellen Grant
- Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Lilla Zöllei
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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9
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Cingulum-Callosal white-matter microstructure associated with emotional dysregulation in children: A diffusion tensor imaging study. NEUROIMAGE-CLINICAL 2020; 27:102266. [PMID: 32408198 PMCID: PMC7218214 DOI: 10.1016/j.nicl.2020.102266] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Revised: 03/07/2020] [Accepted: 04/06/2020] [Indexed: 12/14/2022]
Abstract
Emotional dysregulation symptoms in youth frequently predispose individuals to increased risk for mood disorders and other mental health difficulties. These symptoms are also known as a behavioral risk marker in predicting pediatric mood disorders. The underlying neural mechanism of emotional dysregulation, however, remains unclear. This study used the diffusion tensor imaging (DTI) technique to identify anatomically specific variation in white-matter microstructure that is associated with pediatric emotional dysregulation severity. Thirty-two children (mean age 9.53 years) with varying levels of emotional dysregulation symptoms were recruited by the Massachusetts General Hospital and underwent the DTI scans at Massachusetts Institute of Technology. Emotional dysregulation severity was measured by the empirically-derived Child Behavior Checklist Emotional Dysregulation Profile that includes the Attention, Aggression, and Anxiety/Depression subscales. Whole-brain voxel-wise regression tests revealed significantly increased radial diffusivity (RD) and decreased fractional anisotropy (FA) in the cingulum-callosal regions linked to greater emotional dysregulation in the children. The results suggest that microstructural differences in cingulum-callosal white-matter pathways may manifest as a neurodevelopmental vulnerability for pediatric mood disorders as implicated in the clinical phenotype of pediatric emotional dysregulation. These findings may offer clinically and biologically relevant neural targets for early identification and prevention efforts for pediatric mood disorders.
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10
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Larsen B, Verstynen TD, Yeh FC, Luna B. Developmental Changes in the Integration of Affective and Cognitive Corticostriatal Pathways are Associated with Reward-Driven Behavior. Cereb Cortex 2019; 28:2834-2845. [PMID: 29106535 DOI: 10.1093/cercor/bhx162] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2017] [Indexed: 01/30/2023] Open
Abstract
The relative influence of affective and cognitive processes on behavior is increasingly understood to transform through development, from adolescence into adulthood, but the neuroanatomical mechanisms underlying this change are not well understood. We analyzed diffusion magnetic resonance imaging in 115 10- to 28-year-old participants to identify convergent corticostriatal projections from cortical systems involved in affect and cognitive control and determined the age-related differences in their relative structural integrity. Results indicate that the relative integrity of affective projections, in relation to projections from cognitive control systems, decreases with age and is positively associated with reward-driven task performance. Together, these findings provide new evidence that developmental differences in the integration of corticostriatal networks involved in affect and cognitive control underlie known developmental decreases in the propensity for reward-driven behavior into adulthood.
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Affiliation(s)
- Bart Larsen
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA.,Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
| | - Timothy D Verstynen
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.,Department of Psychology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Fang-Cheng Yeh
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.,Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beatriz Luna
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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11
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Zöllei L, Jaimes C, Saliba E, Grant PE, Yendiki A. TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain. Neuroimage 2019; 199:1-17. [PMID: 31132451 PMCID: PMC6688923 DOI: 10.1016/j.neuroimage.2019.05.051] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 05/14/2019] [Accepted: 05/18/2019] [Indexed: 10/26/2022] Open
Abstract
The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.
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Affiliation(s)
- Lilla Zöllei
- Massachusetts General Hospital, Boston, United States.
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12
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Elsaid NMH, Prince JL, Roys S, Gullapalli RP, Zhuo J. Phase Image Texture Analysis for Motion Detection in Diffusion MRI (PITA-MDD). Magn Reson Imaging 2019; 62:228-241. [PMID: 31319127 DOI: 10.1016/j.mri.2019.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Revised: 07/13/2019] [Accepted: 07/13/2019] [Indexed: 01/05/2023]
Abstract
PURPOSE Pronounced spin phase artifacts appear in diffusion-weighted imaging (DWI) with only minor subject motion. While DWI data corruption is often identified as signal drop out in diffusion-weighted (DW) magnitude images, DW phase images may have higher sensitivity for detecting subtle subject motion. METHODS This article describes a novel method to return a metric of subject motion, computed using an image texture analysis of the DW phase image. This Phase Image Texture Analysis for Motion Detection in dMRI (PITA-MDD) method is computationally fast and reliably detects subject motion from diffusion-weighted images. A threshold of the motion metric was identified to remove motion-corrupted slices, and the effect of removing corrupted slices was assessed on the reconstructed FA maps and fiber tracts. RESULTS Using a motion-metric threshold to remove the motion-corrupted slices results in superior fiber tracts and fractional anisotropy maps. When further compared to a state-of-the-art magnitude-based motion correction method, PITA-MDD was able to detect comparable corrupted slices in a more computationally efficient manner. CONCLUSION In this study, we evaluated the use of DW phase images to detect motion corruption. The proposed method can be a robust and fast alternative for automatic motion detection in the brain with multiple applications to inform prospective motion correction or as real-time feedback for data quality control during scanning, as well as after data is already acquired.
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Affiliation(s)
- Nahla M H Elsaid
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, United States.
| | - Jerry L Prince
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Steven Roys
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Rao P Gullapalli
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jiachen Zhuo
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
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13
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Dean DC, Planalp EM, Wooten W, Kecskemeti SR, Adluru N, Schmidt CK, Frye C, Birn RM, Burghy CA, Schmidt NL, Styner MA, Short SJ, Kalin NH, Goldsmith HH, Alexander AL, Davidson RJ. Association of Prenatal Maternal Depression and Anxiety Symptoms With Infant White Matter Microstructure. JAMA Pediatr 2018; 172:973-981. [PMID: 30177999 PMCID: PMC6190835 DOI: 10.1001/jamapediatrics.2018.2132] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
IMPORTANCE Maternal depression and anxiety can have deleterious and lifelong consequences on child development. However, many aspects of the association of early brain development with maternal symptoms remain unclear. Understanding the timing of potential neurobiological alterations holds inherent value for the development and evaluation of future therapies and interventions. OBJECTIVE To examine the association between exposure to prenatal maternal depression and anxiety symptoms and offspring white matter microstructure at 1 month of age. DESIGN, SETTING, AND PARTICIPANTS This cohort study of 101 mother-infant dyads used a composite of depression and anxiety symptoms measured in mothers during the third trimester of pregnancy and measures of white matter microstructure characterized in the mothers' 1-month offspring using diffusion tensor imaging and neurite orientation dispersion and density imaging performed from October 1, 2014, to November 30, 2016. Magnetic resonance imaging was performed at an academic research facility during natural, nonsedated sleep. MAIN OUTCOMES AND MEASURES Brain mapping algorithms and statistical models were used to evaluate the association between maternal depression and anxiety and 1-month infant white matter microstructure as measured by diffusion tensor imaging and neurite orientation dispersion and density imaging findings. RESULTS In the 101 mother-infant dyads (mean [SD] age of mothers, 33.22 [3.99] years; mean age of infants at magnetic resonance imaging, 33.07 days [range, 18-50 days]; 92 white mothers [91.1%]; 53 male infants [52.5%]), lower 1-month white matter microstructure (decreased neurite density and increased mean, radial, and axial diffusivity) was associated in right frontal white matter microstructure with higher prenatal maternal symptoms of depression and anxiety. Significant sex × symptom interactions with measures of white matter microstructure were also observed, suggesting that white matter development may be differentially sensitive to maternal depression and anxiety symptoms in males and females during the prenatal period. CONCLUSIONS AND RELEVANCE These data highlight the importance of the prenatal period to early brain development and suggest that the underlying white matter microstructure is associated with the continuum of prenatal maternal depression and anxiety symptoms.
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Affiliation(s)
| | - Elizabeth M. Planalp
- Waisman Center, University of Wisconsin, Madison,Department of Psychology, University of Wisconsin, Madison
| | - William Wooten
- Center for Healthy Minds, University of Wisconsin, Madison
| | | | | | - Cory K. Schmidt
- Waisman Center, University of Wisconsin, Madison,Center for Healthy Minds, University of Wisconsin, Madison
| | - Corrina Frye
- Center for Healthy Minds, University of Wisconsin, Madison
| | - Rasmus M. Birn
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison,Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
| | - Cory A. Burghy
- Center for Healthy Minds, University of Wisconsin, Madison
| | | | - Martin A. Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill,Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill
| | - Sarah J. Short
- Center for Healthy Minds, University of Wisconsin, Madison
| | - Ned H. Kalin
- Waisman Center, University of Wisconsin, Madison,Department of Psychology, University of Wisconsin, Madison,Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
| | - H. Hill Goldsmith
- Waisman Center, University of Wisconsin, Madison,Department of Psychology, University of Wisconsin, Madison
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin, Madison,Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison,Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
| | - Richard J. Davidson
- Waisman Center, University of Wisconsin, Madison,Department of Psychology, University of Wisconsin, Madison,Center for Healthy Minds, University of Wisconsin, Madison,Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
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14
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Brain white matter structural networks in patients with non-neuropsychiatric systemic lupus erythematosus. Brain Imaging Behav 2018; 12:142-155. [PMID: 28190161 DOI: 10.1007/s11682-017-9681-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Previous neuroimaging studies have revealed cognitive dysfunction in patients with systemic lupus erythematosus (SLE) and suggested that it may be related to disrupted brain white matter (WM) connectivity. However, no study has examined the topological properties of brain WM structural networks in SLE patients, especially in patients with non-neuropsychiatric SLE (non-NPSLE). In this study, we acquired DTI datasets from 28 non-NPSLE patients and 24 healthy controls, constructed their brain WM structural networks by using a deterministic fiber tracking approach, estimated the topological parameters of their structural networks, and compared their group differences. We reached the following results: 1) At the global level, the non-NPSLE patients showed significantly increased characteristic path length, normalized clustering coefficient and small-worldness, but significantly decreased global efficiency and local efficiency compared to the controls; 2) At the nodal level, the non-NPSLE patients had significantly decreased nodal efficiency in regions related to movement control, executive control, and working memory (bilateral precentral gyri, bilateral middle frontal gyri, bilateral inferior parietal lobes, left median cingulate gyrus and paracingulate gyrus, and right middle temporal gyrus). In addition, to pinpointing the injured WM fiber tracts in the non-NPSLE patients, we reconstructed the major brain WM pathways connecting the abnormal regions at the nodal level with the corticospinal tract (CST), superior longitudinal fasciculus-parietal terminations (SLFP), and superior longitudinal fasciculus-temporal terminations (SLFT). By analyzing the diffusion parameters along these WM fiber pathways, we detected abnormal diffusion parameters in the bilateral CST and right SLFT in the non-NPSLE patients. These results seem to indicate that injured brain WM connectivity exists in SLE patients even in the absence of neuropsychiatric symptoms.
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15
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Hung Y, Saygin ZM, Biederman J, Hirshfeld-Becker D, Uchida M, Doehrmann O, Han M, Chai XJ, Kenworthy T, Yarmak P, Gaillard SL, Whitfield-Gabrieli S, Gabrieli JDE. Impaired Frontal-Limbic White Matter Maturation in Children at Risk for Major Depression. Cereb Cortex 2018; 27:4478-4491. [PMID: 27578495 DOI: 10.1093/cercor/bhw250] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 07/19/2016] [Indexed: 01/01/2023] Open
Abstract
Depression is among the most common neuropsychiatric disorders. It remains unclear whether brain abnormalities associated with depression reflect the pathological state of the disease or neurobiological traits predisposing individuals to depression. Parental history of depression is a risk factor that more than triples the risk of depression. We compared white matter (WM) microstructure cross-sectionally in 40 children ages 8-14 with versus without parental history of depression (At-Risk vs. Control). There were significant differences in age-related changes of fractional anisotropy (FA) between the groups, localized in the anterior fronto-limbic WM pathways, including the anterior cingulum and the genu of the corpus callosum. Control children exhibited typical increasing FA with age, whereas At-Risk children exhibited atypical decreasing FA with age in these fronto-limbic regions. Furthermore, dorsal cingulate FA significantly correlated with depressive symptoms for At-Risk children. The results suggest maturational WM microstructure differences in mood-regulatory neurocircuitry that may contribute to neurodevelopmental risk for depression. The study provides new insights into neurodevelopmental susceptibility to depression and related disabilities that may promote early preventive intervention approaches.
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Affiliation(s)
- Yuwen Hung
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Zeynep M Saygin
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Joseph Biederman
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.,Clinical and Research Program in Pediatric Psychopharmacology, Massachusetts General Hospital, Boston, MA 02114, USA
| | | | - Mai Uchida
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.,Clinical and Research Program in Pediatric Psychopharmacology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Oliver Doehrmann
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Michelle Han
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Xiaoqian J Chai
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Tara Kenworthy
- Clinical and Research Program in Pediatric Psychopharmacology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Pavel Yarmak
- Psychology and Neuroscience, University of Toronto, Toronto, Canada, ON M5S 1A1
| | | | - Susan Whitfield-Gabrieli
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - John D E Gabrieli
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.,Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.,Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA.,Institute for Medical Engineering and Science, MIT, Cambridge, MA 02139, USA
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16
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Karahanoğlu FI, Baran B, Nguyen QTH, Meskaldji DE, Yendiki A, Vangel M, Santangelo SL, Manoach DS. Diffusion-weighted imaging evidence of altered white matter development from late childhood to early adulthood in Autism Spectrum Disorder. Neuroimage Clin 2018; 19:840-847. [PMID: 29946509 PMCID: PMC6008282 DOI: 10.1016/j.nicl.2018.06.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 05/18/2018] [Accepted: 06/03/2018] [Indexed: 12/01/2022]
Abstract
Autism Spectrum Disorder (ASD) is thought to reflect disrupted development of brain connectivity characterized by white matter abnormalities and dyscoordination of activity across brain regions that give rise to core features. But there is little consensus about the nature, timing and location of white matter abnormalities as quantified with diffusion-weighted MRI. Inconsistent findings likely reflect small sample sizes, motion confounds and sample heterogeneity, particularly different age ranges across studies. We examined the microstructural integrity of major white matter tracts in relation to age in 38 high functioning ASD and 35 typically developing (TD) participants, aged 8-25, whose diffusion-weighted scans met strict data-quality criteria and survived group matching for motion. While there were no overall group differences in diffusion measures, the groups showed different relations with age. Only the TD group showed the expected positive correlations of fractional anisotropy with age. In parallel, axial diffusivity was unrelated to age in TD, but showed inverse correlations with age in ASD. Younger participants with ASD tended to have higher fractional anisotropy and axial diffusivity than their TD peers, while the opposite was true for older participants. Most of the affected tracts - cingulum bundle, inferior and superior longitudinal fasciculi - are association bundles related to cognitive, social and emotional functions that are abnormal in ASD. The manifestations of abnormal white matter development in ASD as measured by diffusion-weighted MRI depend on age and this may contribute to inconsistent findings across studies. We conclude that ASD is characterized by altered white matter development from childhood to early adulthood that may underlie abnormal brain function and contribute to core features.
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Affiliation(s)
- Fikret Işık Karahanoğlu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States.
| | - Bengi Baran
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Quynh Trang Huong Nguyen
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Djalel-Eddine Meskaldji
- Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Susan L Santangelo
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Maine Medical Center Research Institute, Scarborough, ME, United States; Tufts University School of Medicine, Department of Psychiatry, Boston, MA, United States
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
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17
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Castella R, Arn L, Dupuis E, Callaghan MF, Draganski B, Lutti A. Controlling motion artefact levels in MR images by suspending data acquisition during periods of head motion. Magn Reson Med 2018; 80:2415-2426. [DOI: 10.1002/mrm.27214] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Revised: 02/20/2018] [Accepted: 03/18/2018] [Indexed: 01/28/2023]
Affiliation(s)
- Rémi Castella
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
| | - Lionel Arn
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
- Ecole Polytechnique Fédérale de Lausanne; Lausanne Switzerland
| | - Estelle Dupuis
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
| | - Martina F. Callaghan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology; University College London; London United Kingdom
| | - Bogdan Draganski
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
- Max Planck Institute for Human Cognitive and Brain Sciences; Leipzig Germany
| | - Antoine Lutti
- LREN, Department for Clinical Neurosciences; CHUV; Lausanne Switzerland
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18
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McLaughlin K, Travers BG, Dadalko OI, Dean DC, Tromp D, Adluru N, Destiche D, Freeman A, Prigge MD, Froehlich A, Duffield T, Zielinski BA, Bigler ED, Lange N, Anderson JS, Alexander AL, Lainhart JE. Longitudinal development of thalamic and internal capsule microstructure in autism spectrum disorder. Autism Res 2018; 11:450-462. [PMID: 29251836 PMCID: PMC5867209 DOI: 10.1002/aur.1909] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Revised: 11/22/2017] [Accepted: 11/28/2017] [Indexed: 01/02/2023]
Abstract
The thalamus is a key sensorimotor relay area that is implicated in autism spectrum disorder (ASD). However, it is unknown how the thalamus and white-matter structures that contain thalamo-cortical fiber connections (e.g., the internal capsule) develop from childhood into adulthood and whether this microstructure relates to basic motor challenges in ASD. We used diffusion weighted imaging in a cohort-sequential design to assess longitudinal development of the thalamus, and posterior- and anterior-limbs of the internal capsule (PLIC and ALIC, respectively) in 89 males with ASD and 56 males with typical development (3-41 years; all verbal). Our results showed that the group with ASD exhibited different developmental trajectories of microstructure in all regions, demonstrating childhood group differences that appeared to approach and, in some cases, surpass the typically developing group in adolescence and adulthood. The PLIC (but not ALIC nor thalamus) mediated the relation between age and finger-tapping speed in both groups. Yet, the gap in finger-tapping speed appeared to widen at the same time that the between-group gap in the PLIC appeared to narrow. Overall, these results suggest that childhood group differences in microstructure of the thalamus and PLIC become less robust in adolescence and adulthood. Further, finger-tapping speed appears to be mediated by the PLIC in both groups, but group differences in motor speed that widen during adolescence and adulthood suggest that factors beyond the microstructure of the thalamus and internal capsule may contribute to atypical motor profiles in ASD. Autism Res 2018, 11: 450-462. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY Microstructure of the thalamus, a key sensory and motor brain area, appears to develop differently in individuals with autism spectrum disorder (ASD). Microstructure is important because it informs us of the density and organization of different brain tissues. During childhood, thalamic microstructure was distinct in the ASD group compared to the typically developing group. However, these group differences appeared to narrow with age, suggesting that the thalamus continues to dynamically change in ASD into adulthood.
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Affiliation(s)
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison
- Occupational Therapy Program in Kinesiology, University of Wisconsin-Madison
| | | | | | - Do Tromp
- Waisman Center, University of Wisconsin-Madison
| | | | | | | | - Molly D. Prigge
- Waisman Center, University of Wisconsin-Madison
- Pediatrics, University of Utah
| | | | - Tyler Duffield
- Psychology/Neuroscience Center, Brigham Young University
| | | | - Erin D. Bigler
- Psychology/Neuroscience Center, Brigham Young University
| | | | | | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison
- Psychiatry, University of Wisconsin-Madison
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison
- Psychiatry, University of Wisconsin-Madison
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19
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Boets B, Van Eylen L, Sitek K, Moors P, Noens I, Steyaert J, Sunaert S, Wagemans J. Alterations in the inferior longitudinal fasciculus in autism and associations with visual processing: a diffusion-weighted MRI study. Mol Autism 2018; 9:10. [PMID: 29449909 PMCID: PMC5806238 DOI: 10.1186/s13229-018-0188-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2017] [Accepted: 01/10/2018] [Indexed: 11/10/2022] Open
Abstract
Background One of the most reported neural features of autism spectrum disorder (ASD) is the alteration of multiple long-range white matter fiber tracts, as assessed by diffusion-weighted imaging and indexed by reduced fractional anisotropy (FA). Recent methodological advances, however, have shown that this same pattern of reduced FA may be an artifact resulting from excessive head motion and poorer data quality and that aberrant structural connectivity in children with ASD is confined to the right inferior longitudinal fasciculus (ILF). This study aimed at replicating the observation of reduced FA along the right ILF in ASD, while controlling for group differences in head motion and data quality. In addition, we explored associations between reduced FA in the right ILF and quantitative ASD characteristics, and the involvement of the right ILF in visual processing, which is known to be altered in ASD. Method Global probabilistic tractography was performed on diffusion-weighted imaging data of 17 adolescent boys with ASD and 17 typically developing boys, matched for age, performance IQ, handedness, and data quality. Four tasks were administered to measure various aspects of visual information processing, together with questionnaires assessing ASD characteristics. Group differences were examined and the neural data were integrated with previously published findings using Bayesian statistics to quantify evidence for replication and to pool data and thus increase statistical power. (Partial) correlations were calculated to investigate associations between measures. Results The ASD group showed consistently reduced FA only in the right ILF and slower performance on the visual search task. Bayesian statistics pooling data across studies confirmed that group differences in FA were confined to the right ILF only, with the evidence for altered FA in the left ILF being indecisive. Lower FA in the right ILF tended to covary with slower visual search and a more fragmented part-oriented processing style. Individual differences in FA of the right ILF were not reliably associated with the severity of ASD traits after controlling for clinical status. Conclusion Our findings support the growing evidence for reduced FA along a specific fiber tract in ASD, the right ILF.
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Affiliation(s)
- Bart Boets
- 1Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Kapucijnenvoer 7h, PB 7001, 3000 Leuven, Belgium.,2Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium.,3Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA
| | - Lien Van Eylen
- 1Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Kapucijnenvoer 7h, PB 7001, 3000 Leuven, Belgium.,2Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
| | - Kevin Sitek
- 3Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139 USA.,4Speech and Hearing Bioscience and Technology, Division of Medical Sciences, Harvard Medical School, Boston, MA 02115 USA
| | - Pieter Moors
- 5Laboratory of Experimental Psychology, KU Leuven, 3000 Leuven, Belgium
| | - Ilse Noens
- 6Parenting and Special Education Research Unit, KU Leuven, 3000 Leuven, Belgium
| | - Jean Steyaert
- 1Center for Developmental Psychiatry, Department of Neurosciences, KU Leuven, Kapucijnenvoer 7h, PB 7001, 3000 Leuven, Belgium.,2Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium
| | | | - Johan Wagemans
- 2Leuven Autism Research (LAuRes), KU Leuven, 3000 Leuven, Belgium.,5Laboratory of Experimental Psychology, KU Leuven, 3000 Leuven, Belgium
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20
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Tamnes CK, Roalf DR, Goddings AL, Lebel C. Diffusion MRI of white matter microstructure development in childhood and adolescence: Methods, challenges and progress. Dev Cogn Neurosci 2017; 33:161-175. [PMID: 29229299 PMCID: PMC6969268 DOI: 10.1016/j.dcn.2017.12.002] [Citation(s) in RCA: 101] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 05/18/2017] [Accepted: 12/04/2017] [Indexed: 12/13/2022] Open
Abstract
Diffusion magnetic resonance imaging (dMRI) continues to grow in popularity as a useful neuroimaging method to study brain development, and longitudinal studies that track the same individuals over time are emerging. Over the last decade, seminal work using dMRI has provided new insights into the development of brain white matter (WM) microstructure, connections and networks throughout childhood and adolescence. This review provides an introduction to dMRI, both diffusion tensor imaging (DTI) and other dMRI models, as well as common acquisition and analysis approaches. We highlight the difficulties associated with ascribing these imaging measurements and their changes over time to specific underlying cellular and molecular events. We also discuss selected methodological challenges that are of particular relevance for studies of development, including critical choices related to image acquisition, image analysis, quality control assessment, and the within-subject and longitudinal reliability of dMRI measurements. Next, we review the exciting progress in the characterization and understanding of brain development that has resulted from dMRI studies in childhood and adolescence, including brief overviews and discussions of studies focusing on sex and individual differences. Finally, we outline future directions that will be beneficial to the field.
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Affiliation(s)
| | - David R Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Catherine Lebel
- Department of Radiology, Cumming School of Medicine, and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
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21
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Dosenbach NUF, Koller JM, Earl EA, Miranda-Dominguez O, Klein RL, Van AN, Snyder AZ, Nagel BJ, Nigg JT, Nguyen AL, Wesevich V, Greene DJ, Fair DA. Real-time motion analytics during brain MRI improve data quality and reduce costs. Neuroimage 2017; 161:80-93. [PMID: 28803940 PMCID: PMC5731481 DOI: 10.1016/j.neuroimage.2017.08.025] [Citation(s) in RCA: 168] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 08/04/2017] [Accepted: 08/07/2017] [Indexed: 11/30/2022] Open
Abstract
Head motion systematically distorts clinical and research MRI data. Motion artifacts have biased findings from many structural and functional brain MRI studies. An effective way to remove motion artifacts is to exclude MRI data frames affected by head motion. However, such post-hoc frame censoring can lead to data loss rates of 50% or more in our pediatric patient cohorts. Hence, many scanner operators collect additional 'buffer data', an expensive practice that, by itself, does not guarantee sufficient high-quality MRI data for a given participant. Therefore, we developed an easy-to-setup, easy-to-use Framewise Integrated Real-time MRI Monitoring (FIRMM) software suite that provides scanner operators with head motion analytics in real-time, allowing them to scan each subject until the desired amount of low-movement data has been collected. Our analyses show that using FIRMM to identify the ideal scan time for each person can reduce total brain MRI scan times and associated costs by 50% or more.
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Affiliation(s)
- Nico U F Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA; Program in Occupational Therapy, Washington University, St. Louis, MO, USA.
| | - Jonathan M Koller
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Eric A Earl
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - Oscar Miranda-Dominguez
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA
| | - Rachel L Klein
- Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Andrew N Van
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Bonnie J Nagel
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Joel T Nigg
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA
| | - Annie L Nguyen
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA; Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
| | - Victoria Wesevich
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna J Greene
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Damien A Fair
- Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR, USA; Department of Psychiatry, Oregon Health & Science University, Portland, OR, USA; Advanced Imaging Research Center, Oregon Health & Science University, Portland, OR, USA.
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22
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Solders SK, Carper RA, Müller RA. White matter compromise in autism? Differentiating motion confounds from true differences in diffusion tensor imaging. Autism Res 2017; 10:1606-1620. [PMID: 28503904 PMCID: PMC5648623 DOI: 10.1002/aur.1807] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2016] [Revised: 04/01/2017] [Accepted: 04/10/2017] [Indexed: 12/24/2022]
Abstract
Common findings from diffusion tensor imaging (DTI) in autism spectrum disorder (ASD) include reduced fractional anisotropy (FA), and increased mean and radial diffusivity (MD, RD) of white matter tracts. However, findings may be confounded by head motion. We examined how group-level motion matching affects DTI comparisons between ASD and typically developing (TD) groups. We included 57 ASD and 50 TD participants, comparing three subsets at increasing levels of motion-matching stringency: full sample (FS); quality-controlled (QC); and quantitatively-matched (QM). Groups were compared on diffusivity measures using Tract-Based Spatial Statistics (TBSS) and probabilistic tractography. Two methods for estimating diffusivity were compared: dti-fit and restore. TBSS: In set FS, FA was reduced in the ASD compared to the TD group throughout the right hemisphere. This effect was less extensive in set QC and absent in set QM. However, effect sizes remained stable or increased with better quality-control in some regions. Tractography: In set QM, MD was significantly higher in ASD overall and RD was higher in bilateral ILF. Effects were more robust in QM than in FS or QC sets. Effect sizes in several tracts increased with stringent quality matching. Restore improved tensor estimates, with some increases in effect sizes, but did not fully compensate for reduced quality. Findings suggest that some previously reported DTI findings for ASD may have been confounded by motion. However, effects in the tightly matched subset indicate that tract-specific anomalies probably do exist in ASD. Our results highlight the need for careful quality-control and motion-matching. Autism Res 2017, 10: 1606-1620. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.
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Affiliation(s)
- Seraphina K Solders
- Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Ruth A Carper
- Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Ralph-Axel Müller
- Brain Development Imaging Laboratory, Department of Psychology, San Diego State University, San Diego, CA, USA
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23
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Fjell AM, Sneve MH, Grydeland H, Storsve AB, Walhovd KB. The Disconnected Brain and Executive Function Decline in Aging. Cereb Cortex 2017; 27:2303-2317. [PMID: 27073220 DOI: 10.1093/cercor/bhw082] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Higher order speeded cognitive abilities depend on efficient coordination of activity across the brain, rendering them vulnerable to age reductions in structural and functional brain connectivity. The concept of "disconnected aging" has been invoked, suggesting that degeneration of connections between distant brain regions cause cognitive reductions. However, it has not been shown that changes in cognitive functions over time can be explained by simultaneous changes in brain connectivity. We followed 119 young and middle-aged (23-52 years) and older (63-86 years) adults for 3.3 years with repeated assessments of structural and functional brain connectivity and executive functions. We found unique age-related longitudinal reductions in executive function over and above changes in more basic cognitive processes. Intriguingly, 82.5% of the age-related decline in executive function could be explained by changes in connectivity over time. While both structural and functional connectivity changes were related to longitudinal reductions in executive function, only structural connectivity change could explain the age-specific decline. This suggests that the major part of the age-related reductions in executive function can be attributed to micro- and macrostructural alterations in brain connectivity. Although correlational in nature, we believe the present results constitute evidence for a "disconnected brain" view on cognitive aging.
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Affiliation(s)
- Anders M Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway.,Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, Oslo, Norway
| | - Markus H Sneve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Håkon Grydeland
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Andreas B Storsve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway
| | - Kristine B Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Oslo 0373, Norway.,Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, Oslo, Norway
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24
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Stramaglia S, Pellicoro M, Angelini L, Amico E, Aerts H, Cortés JM, Laureys S, Marinazzo D. Ising model with conserved magnetization on the human connectome: Implications on the relation structure-function in wakefulness and anesthesia. CHAOS (WOODBURY, N.Y.) 2017; 27:047407. [PMID: 28456159 DOI: 10.1063/1.4978999] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Dynamical models implemented on the large scale architecture of the human brain may shed light on how a function arises from the underlying structure. This is the case notably for simple abstract models, such as the Ising model. We compare the spin correlations of the Ising model and the empirical functional brain correlations, both at the single link level and at the modular level, and show that their match increases at the modular level in anesthesia, in line with recent results and theories. Moreover, we show that at the peak of the specific heat (the critical state), the spin correlations are minimally shaped by the underlying structural network, explaining how the best match between the structure and function is obtained at the onset of criticality, as previously observed. These findings confirm that brain dynamics under anesthesia shows a departure from criticality and could open the way to novel perspectives when the conserved magnetization is interpreted in terms of a homeostatic principle imposed to neural activity.
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Affiliation(s)
- S Stramaglia
- Dipartimento di Fisica, Università degli Studi di Bari, Bari, Italy
| | - M Pellicoro
- Dipartimento di Fisica, Università degli Studi di Bari, Bari, Italy
| | - L Angelini
- Dipartimento di Fisica, Università degli Studi di Bari, Bari, Italy
| | - E Amico
- Coma Science Group, University of Liège, Liège, Belgium
| | - H Aerts
- Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium
| | - J M Cortés
- Ikerbasque, The Basque Foundation for Science, E-48011 Bilbao, Spain
| | - S Laureys
- Coma Science Group, University of Liège, Liège, Belgium
| | - D Marinazzo
- Faculty of Psychology and Educational Sciences, Department of Data Analysis, Ghent University, Ghent, Belgium
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25
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Hoinkiss DC, Porter DA. Prospective motion correction in diffusion-weighted imaging using intermediate pseudo-trace-weighted images. Neuroimage 2017; 149:1-14. [PMID: 28011251 DOI: 10.1016/j.neuroimage.2016.12.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Revised: 11/12/2016] [Accepted: 12/19/2016] [Indexed: 10/20/2022] Open
Abstract
Subject head motion is a major challenge in diffusion-weighted imaging, which requires a precise alignment of images from different time points to allow a reliable quantification of diffusion parameters within each voxel. The technique requires long measurement times, making it highly sensitive to long-term subject motion, even when head restraint is used. Current methods of data analysis rely on retrospective motion correction, but there are potential benefits to using prospective motion correction, in which motion is tracked and compensated for during data acquisition. This technique is regularly used to enhance image quality in blood-oxygen-level dependent (BOLD) imaging, but its application to diffusion-weighted imaging has been limited by the contrast variation between images acquired with different diffusion-gradient directions. This paper describes a novel approach to this topic that exploits the rotational invariance of the trace of the diffusion tensor to reduce the effect of this contrast variation, making it possible to perform a fast image registration using a least-squares cost function. This results in an image-based motion detection algorithm that can be applied in real time during data acquisition to adapt the slice position and orientation in response to subject motion. The motion detection capabilities of the technique were evaluated in a study of ten subjects with b-values up to 3000s/mm². The resulting motion-parameter estimates were in close agreement with reference values provided by interleaved low-b-value images with a correlation coefficient of R=0.9634 for the voxel displacements measured across all subjects and b-values. The technique was also used to perform prospective motion correction on a standard clinical MRI system with b-values up to 2000s/mm². The correction was evaluated in 3 subjects using interleaved low-b-value images, retrospective image registration using the AFNI processing package and mean diffusivity histogram analysis. Compared to acquisitions without motion correction, prospective motion correction based on pseudo-trace-weighted images was found to provide a robust method for substantially reducing the level of misregistration between volumes. In most cases, misregistrations were reduced to less than 0.2mm of translation and 0.2° of rotation for an isotropic voxel size of 2mm, yielding high-quality diffusion parameter maps even in the absence of head restraint and post-acquisition image registration.
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26
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Dean DC, Lange N, Travers BG, Prigge MB, Matsunami N, Kellett KA, Freeman A, Kane KL, Adluru N, Tromp DPM, Destiche DJ, Samsin D, Zielinski BA, Fletcher PT, Anderson JS, Froehlich AL, Leppert MF, Bigler ED, Lainhart JE, Alexander AL. Multivariate characterization of white matter heterogeneity in autism spectrum disorder. Neuroimage Clin 2017; 14:54-66. [PMID: 28138427 PMCID: PMC5257193 DOI: 10.1016/j.nicl.2017.01.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 12/21/2016] [Accepted: 01/03/2017] [Indexed: 12/20/2022]
Abstract
The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.
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Affiliation(s)
- D C Dean
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - N Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, MA, USA; Child and Adolescent Psychiatry, McLean Hospital, Belmont, MA, USA
| | - B G Travers
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, WI, USA
| | - M B Prigge
- Department of Radiology, University of Utah, Salt Lake City, UT, USA; Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, UT, USA
| | - N Matsunami
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - K A Kellett
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychology, University of Wisconsin-Madison, Madison, WI, USA
| | - A Freeman
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - K L Kane
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - N Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - D P M Tromp
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - D J Destiche
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - D Samsin
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - B A Zielinski
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, UT, USA; Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - P T Fletcher
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA; School of Computing, University of Utah, Salt Lake City, UT, USA
| | - J S Anderson
- Department of Radiology, University of Utah, Salt Lake City, UT, USA; Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
| | - A L Froehlich
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | - M F Leppert
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - E D Bigler
- Department of Psychology, Brigham Young University, Provo, UT, USA; Neuroscience Center, Brigham Young University, Provo, UT 84602, USA
| | - J E Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - A L Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, USA; Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA; Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
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27
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Reduced Hemispheric Asymmetry of White Matter Microstructure in Autism Spectrum Disorder. J Am Acad Child Adolesc Psychiatry 2016; 55:1073-1080. [PMID: 27871642 PMCID: PMC5125511 DOI: 10.1016/j.jaac.2016.09.491] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2016] [Revised: 09/11/2016] [Accepted: 09/21/2016] [Indexed: 01/26/2023]
Abstract
OBJECTIVE Many past studies have suggested atypical functional and anatomical hemispheric asymmetries in autism spectrum disorder (ASD). However, almost all of these have examined only language-related asymmetries. Here, we conduct a comprehensive investigation of microstructural asymmetries across a large number of fiber tracts in ASD. METHOD We used diffusion tensor imaging for a comprehensive investigation of anatomical white matter asymmetries across the entire white matter skeleton, using tract-based spatial statistics in 41 children and adolescents with ASD and a matched group of 44 typically developing (TD) participants. RESULTS We found significant asymmetries in the TD group, being rightward for fractional anisotropy and leftward for mean diffusivity (with concordant asymmetries for radial and axial diffusivity). These asymmetries were significantly reduced in the group with ASD: in whole brain analysis for fractional anisotropy, and in a region where several major association and projection tracts travel in close proximity within occipital white matter for mean diffusivity, axial diffusivity, and radial diffusivity. No correlations between global white matter asymmetry and age or socio-communicative abilities were detected. CONCLUSION Our findings in TD children and adolescents can be interpreted as reflecting different processing modes (more integrative in the right and more specialized in the left hemisphere). These asymmetries and the "division of labor" between hemispheres implied by them appear to be diminished in autism spectrum disorder.
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28
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Taylor PA, Alhamud A, van der Kouwe A, Saleh MG, Laughton B, Meintjes E. Assessing the performance of different DTI motion correction strategies in the presence of EPI distortion correction. Hum Brain Mapp 2016; 37:4405-4424. [PMID: 27436169 DOI: 10.1002/hbm.23318] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2015] [Revised: 06/16/2016] [Accepted: 07/05/2016] [Indexed: 11/07/2022] Open
Abstract
Diffusion tensor imaging (DTI) is susceptible to several artifacts due to eddy currents, echo planar imaging (EPI) distortion and subject motion. While several techniques correct for individual distortion effects, no optimal combination of DTI acquisition and processing has been determined. Here, the effects of several motion correction techniques are investigated while also correcting for EPI distortion: prospective correction, using navigation; retrospective correction, using two different popular packages (FSL and TORTOISE); and the combination of both methods. Data from a pediatric group that exhibited incidental motion in varying degrees are analyzed. Comparisons are carried while implementing eddy current and EPI distortion correction. DTI parameter distributions, white matter (WM) maps and probabilistic tractography are examined. The importance of prospective correction during data acquisition is demonstrated. In contrast to some previous studies, results also show that the inclusion of retrospective processing also improved ellipsoid fits and both the sensitivity and specificity of group tractographic results, even for navigated data. Matches with anatomical WM maps are highest throughout the brain for data that have been both navigated and processed using TORTOISE. The inclusion of both prospective and retrospective motion correction with EPI distortion correction is important for DTI analysis, particularly when studying subject populations that are prone to motion. Hum Brain Mapp 37:4405-4424, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Paul A Taylor
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa.,African Institute for Mathematical Sciences, Muizenberg, Western Cape, South Africa.,Scientific and Statistical Computing Core, National Institutes of Health, Bethesda, Maryland
| | - A Alhamud
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
| | - Andre van der Kouwe
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts
| | - Muhammad G Saleh
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
| | - Barbara Laughton
- Department of Paediatrics and Child Health, Stellenbosch University, Children's Infection Diseases Clinical Research Unit, South Africa
| | - Ernesta Meintjes
- Department of Human Biology, Faculty of Health Sciences, MRC/UCT Medical Imaging Research Unit, University of Cape Town, South Africa
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29
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Storsve AB, Fjell AM, Yendiki A, Walhovd KB. Longitudinal Changes in White Matter Tract Integrity across the Adult Lifespan and Its Relation to Cortical Thinning. PLoS One 2016; 11:e0156770. [PMID: 27253393 PMCID: PMC4890742 DOI: 10.1371/journal.pone.0156770] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 05/19/2016] [Indexed: 02/02/2023] Open
Abstract
A causal link between decreases in white matter (WM) integrity and cortical degeneration is assumed, but there is scarce knowledge on the relationship between these changes across the adult human lifespan. We investigated changes in thickness throughout the cortical mantle and WM tract integrity derived from T1 and diffusion weighted magnetic resonance imaging (MRI) scans in 201 healthy adults aged 23-87 years over a mean interval of 3.6 years. Fractional anisotropy (FA), mean (MD), radial (RD) and axial (AD) diffusivity changes were calculated for forceps minor and major and eight major white matter tracts in each hemisphere by use of a novel automated longitudinal tractography constrained by underlying anatomy (TRACULA) approach. We hypothesized that increasing MD and decreasing FA across tracts would relate to cortical thinning, with some anatomical specificity. WM integrity decreased across tracts non-uniformly, with mean annual percentage decreases ranging from 0.20 in the Inferior Longitudinal Fasciculus to 0.65 in the Superior Longitudinal Fasciculus. For most tracts, greater MD increases and FA decreases related to more cortical thinning, in areas in part overlapping with but also outside the projected tract endings. The findings indicate a combination of global and tract-specific relationships between WM integrity and cortical thinning.
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Affiliation(s)
- Andreas B. Storsve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Oslo, Norway
| | - Anders M. Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Oslo, Norway
- Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, 0424, Oslo, Norway
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States of America
| | - Kristine B. Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Oslo, Norway
- Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, 0424, Oslo, Norway
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30
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Dean DC, Travers BG, Adluru N, Tromp DP, Destiche DJ, Samsin D, Prigge MB, Zielinski BA, Fletcher PT, Anderson JS, Froehlich AL, Bigler ED, Lange N, Lainhart JE, Alexander AL. Investigating the Microstructural Correlation of White Matter in Autism Spectrum Disorder. Brain Connect 2016; 6:415-33. [PMID: 27021440 PMCID: PMC4913512 DOI: 10.1089/brain.2015.0385] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
White matter microstructure forms a complex and dynamical system that is critical for efficient and synchronized brain function. Neuroimaging findings in children with autism spectrum disorder (ASD) suggest this condition is associated with altered white matter microstructure, which may lead to atypical macroscale brain connectivity. In this study, we used diffusion tensor imaging measures to examine the extent that white matter tracts are interrelated within ASD and typical development. We assessed the strength of inter-regional white matter correlations between typically developing and ASD diagnosed individuals. Using hierarchical clustering analysis, clustering patterns of the pairwise white matter correlations were constructed and revealed to be different between the two groups. Additionally, we explored the use of graph theory analysis to examine the characteristics of the patterns formed by inter-regional white matter correlations and compared these properties between ASD and typical development. We demonstrate that the ASD sample has significantly less coherence in white matter microstructure across the brain compared to that in the typical development sample. The ASD group also presented altered topological characteristics, which may implicate less efficient brain networking in ASD. These findings highlight the potential of graph theory based network characteristics to describe the underlying networks as measured by diffusion magnetic resonance imaging and furthermore indicates that ASD may be associated with altered brain network characteristics. Our findings are consistent with those of a growing number of studies and hypotheses that have suggested disrupted brain connectivity in ASD.
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Affiliation(s)
- Douglas C. Dean
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Brittany G. Travers
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, Wisconsin
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Do P.M. Tromp
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | | | - Danica Samsin
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
| | - Molly B. Prigge
- Department of Radiology, University of Utah, Salt Lake City, Utah
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, Utah
| | - Brandon A. Zielinski
- Department of Pediatrics, University of Utah and Primary Children's Medical Center, Salt Lake City, Utah
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | - P. Thomas Fletcher
- Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, Utah
- School of Computing, University of Utah, Salt Lake City, Utah
| | - Jeffrey S. Anderson
- Department of Radiology, University of Utah, Salt Lake City, Utah
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, Utah
| | | | - Erin D. Bigler
- Department of Psychology, Brigham Young University, Provo, Utah
- Neuroscience Center, Brigham Young University, Provo, Utah
| | - Nicholas Lange
- Department of Psychiatry, Harvard School of Medicine, Boston, Massachusetts
- Neurostatistics Laboratory, McLean Hospital, Belmont, Massachusetts
| | - Janet E. Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Psychiatry, University of Wisconsin-Madison, Madison, Wisconsin
- Department of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin
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Phillips OR, Joshi SH, Piras F, Orfei MD, Iorio M, Narr KL, Shattuck DW, Caltagirone C, Spalletta G, Di Paola M. The superficial white matter in Alzheimer's disease. Hum Brain Mapp 2016; 37:1321-34. [PMID: 26801955 PMCID: PMC5125444 DOI: 10.1002/hbm.23105] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Revised: 12/03/2015] [Accepted: 12/17/2015] [Indexed: 12/24/2022] Open
Abstract
White matter abnormalities have been shown in the large deep fibers of Alzheimer's disease patients. However, the late myelinating superficial white matter comprised of intracortical myelin and short-range association fibers has not received much attention. To investigate this area, we extracted a surface corresponding to the superficial white matter beneath the cortex and then applied a cortical pattern-matching approach which allowed us to register and subsequently sample diffusivity along thousands of points at the interface between the gray matter and white matter in 44 patients with Alzheimer's disease (Age: 71.02 ± 5.84, 16M/28F) and 47 healthy controls (Age 69.23 ± 4.45, 19M/28F). In patients we found an overall increase in the axial and radial diffusivity across most of the superficial white matter (P < 0.001) with increases in diffusivity of more than 20% in the bilateral parahippocampal regions and the temporal and frontal lobes. Furthermore, diffusivity correlated with the cognitive deficits measured by the Mini-Mental State Examination scores (P < 0.001). The superficial white matter has a unique microstructure and is critical for the integration of multimodal information during brain maturation and aging. Here we show that there are major abnormalities in patients and the deterioration of these fibers relates to clinical symptoms in Alzheimer's disease.
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Affiliation(s)
- Owen R Phillips
- Morphology and Morphometry for NeuroImaging Lab, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
- Neuroscience Dept. University of Rome“Tor Vergata”Italy
| | - Shantanu H. Joshi
- Ahmanson Lovelace Brain Mapping CenterNeurology Dept. UCLACaliforniaUSA
| | - Fabrizio Piras
- Museo Storico della Fisica e Centro di Studi e Ricerche “Enrico Fermi”RomeItaly
- Neuropsychiatry Laboratory, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
| | - Maria Donata Orfei
- Neuropsychiatry Laboratory, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
| | - Mariangela Iorio
- Neuropsychiatry Laboratory, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
| | - Katherine L. Narr
- Ahmanson Lovelace Brain Mapping CenterNeurology Dept. UCLACaliforniaUSA
| | - David W. Shattuck
- Ahmanson Lovelace Brain Mapping CenterNeurology Dept. UCLACaliforniaUSA
| | - Carlo Caltagirone
- Neuroscience Dept. University of Rome“Tor Vergata”Italy
- Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
| | - Gianfranco Spalletta
- Neuropsychiatry Laboratory, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
| | - Margherita Di Paola
- Morphology and Morphometry for NeuroImaging Lab, Clinical and Behavioural Neurology Dept. IRCCS Santa Lucia FoundationRomeItaly
- Human Studies Dept. LUMSA UniversityRomeItaly
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Roalf DR, Quarmley M, Elliott MA, Satterthwaite TD, Vandekar SN, Ruparel K, Gennatas ED, Calkins ME, Moore TM, Hopson R, Prabhakaran K, Jackson CT, Verma R, Hakonarson H, Gur RC, Gur RE. The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort. Neuroimage 2016; 125:903-919. [PMID: 26520775 PMCID: PMC4753778 DOI: 10.1016/j.neuroimage.2015.10.068] [Citation(s) in RCA: 151] [Impact Index Per Article: 18.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2015] [Revised: 10/19/2015] [Accepted: 10/24/2015] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8-21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics. METHODS All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep. RESULTS TSNR (AUC=0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. CONCLUSION Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development.
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Affiliation(s)
- David R Roalf
- Neuropsychiatry Section, Department of Psychiatry, USA.
| | | | - Mark A Elliott
- Department of Radiology, University of Pennsylvania, Perelman School of Medicine, USA
| | | | - Simon N Vandekar
- Neuropsychiatry Section, Department of Psychiatry, USA; Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kosha Ruparel
- Neuropsychiatry Section, Department of Psychiatry, USA
| | | | | | - Tyler M Moore
- Neuropsychiatry Section, Department of Psychiatry, USA
| | - Ryan Hopson
- Neuropsychiatry Section, Department of Psychiatry, USA
| | | | | | - Ragini Verma
- Department of Radiology, University of Pennsylvania, Perelman School of Medicine, USA; Section of Biomedical Image Analysis, University of Pennsylvania, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C Gur
- Neuropsychiatry Section, Department of Psychiatry, USA; Department of Radiology, University of Pennsylvania, Perelman School of Medicine, USA
| | - Raquel E Gur
- Neuropsychiatry Section, Department of Psychiatry, USA; Department of Radiology, University of Pennsylvania, Perelman School of Medicine, USA
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33
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Anderson LC, Rice K, Chrabaszcz J, Redcay E. Tracking the Neurodevelopmental Correlates of Mental State Inference in Early Childhood. Dev Neuropsychol 2016; 40:379-94. [PMID: 26731628 DOI: 10.1080/87565641.2015.1119836] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Between ages 4 and 6, children become better at inferring what others are thinking and feeling. However, the neural correlates of these advances are understudied. The current study investigated the relation between performance on a face-based mental state inference task and white matter characteristics. Two tracts of interest, the uncinate fasciculus (UF) and inferior longitudinal fasciculus, were analyzed due to their involvement in social-emotional and face processing, respectively. Findings demonstrate a significant relation between fractional anisotropy in the UF and task performance in 4- but not 6-year-old children. Findings have implications for typical and atypical populations.
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Affiliation(s)
- Laura C Anderson
- a Department of Psychology , University of Maryland , College Park , Maryland
| | - Katherine Rice
- a Department of Psychology , University of Maryland , College Park , Maryland
| | - Jeffrey Chrabaszcz
- b Program in Neuroscience and Cognitive Science , University of Maryland , College Park , Maryland
| | - Elizabeth Redcay
- a Department of Psychology , University of Maryland , College Park , Maryland
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Elhabian S, Vachet C, Piven J, Styner M, Gerig G. Compressive Sensing Based Q-Space Resampling for Handling Fast Bulk Motion in Hardi Acquisitions. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2016; 2016:907-910. [PMID: 29492184 DOI: 10.1109/isbi.2016.7493412] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Diffusion-weighted (DW) MRI has become a widely adopted imaging modality to reveal the underlying brain connectivity. Long acquisition times and/or non-cooperative patients increase the chances of motion-related artifacts. Whereas slow bulk motion results in inter-gradient misalignment which can be handled via retrospective motion correction algorithms, fast bulk motion usually affects data during the application of a single diffusion gradient causing signal dropout artifacts. Common practices opt to discard gradients bearing signal attenuation due to the difficulty of their retrospective correction, with the disadvantage to lose full gradients for further processing. Nonetheless, such attenuation might only affect limited number of slices within a gradient volume. Q-space resampling has recently been proposed to recover corrupted slices while saving gradients for subsequent reconstruction. However, few corrupted gradients are implicitly assumed which might not hold in case of scanning unsedated infants or patients in pain. In this paper, we propose to adopt recent advances in compressive sensing based reconstruction of the diffusion orientation distribution functions (ODF) with under sampled measurements to resample corrupted slices. We make use of Simple Harmonic Oscillator based Reconstruction and Estimation (SHORE) basis functions which can analytically model ODF from arbitrary sampled signals. We demonstrate the impact of the proposed resampling strategy compared to state-of-art resampling and gradient exclusion on simulated intra-gradient motion as well as samples from real DWI data.
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Affiliation(s)
- Shireen Elhabian
- Scientific Computing and Imaging Institute, Salt Lake City, UT, USA
| | - Clement Vachet
- Scientific Computing and Imaging Institute, Salt Lake City, UT, USA
| | - Joseph Piven
- Dept. of Psychiatry, University of North Carolina, NC, USA
| | | | - Martin Styner
- Dept. of Psychiatry, University of North Carolina, NC, USA.,Dept. of Computer Science, University of North Carolina, NC, USA
| | - Guido Gerig
- Tandon School of Engineering, Department of Computer Science & Engineering, NYU, USA
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Alhamud A, Taylor PA, van der Kouwe AJW, Meintjes EM. Real-time measurement and correction of both B0 changes and subject motion in diffusion tensor imaging using a double volumetric navigated (DvNav) sequence. Neuroimage 2015; 126:60-71. [PMID: 26584865 DOI: 10.1016/j.neuroimage.2015.11.022] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Revised: 09/18/2015] [Accepted: 11/09/2015] [Indexed: 11/19/2022] Open
Abstract
Diffusion tensor imaging (DTI) requires a set of diffusion weighted measurements in order to acquire enough information to characterize local structure. The MRI scanner automatically performs a shimming process by acquiring a field map before the start of a DTI scan. Changes in B0, which can occur throughout the DTI acquisition due to several factors (including heating of the iron shim coils or subject motion), cause significant signal distortions that result in warped diffusion tensor (DT) parameter estimates. In this work we introduce a novel technique to simultaneously measure, report and correct in real time subject motion and changes in B0 field homogeneity, both in and through the imaging plane. This is achieved using double volumetric navigators (DvNav), i.e. a pair of 3D EPI acquisitions, interleaved with the DTI pulse sequence. Changes in the B0 field are evaluated in terms of zero-order (frequency) and first-order (linear gradients) shim. The ability of the DvNav to accurately estimate the shim parameters was first validated in a water phantom. Two healthy subjects were scanned both in the presence and absence of motion using standard, motion corrected (single navigator, vNav), and DvNav DTI sequences. The difference in performance between the proposed 3D EPI field maps and the standard 3D gradient echo field maps of the MRI scanner was also evaluated in a phantom and two healthy subjects. The DvNav sequence was shown to accurately measure and correct changes in B0 following manual adjustments of the scanner's central frequency and the linear shim gradients. Compared to other methods, the DvNav produced DTI results that showed greater spatial overlap with anatomical references, particularly in scans with subject motion. This is largely due to the ability of the DvNav system to correct shim changes and subject motion between each volume acquisition, thus reducing shear distortion.
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Affiliation(s)
- A Alhamud
- MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, South Africa.
| | - Paul A Taylor
- MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, South Africa; African Institute for Mathematical Sciences (AIMS), South Africa
| | - Andre J W van der Kouwe
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Department of Radiology, Harvard Medical School, Brookline, MA, USA
| | - Ernesta M Meintjes
- MRC/UCT Medical Imaging Research Unit, Department of Human Biology, University of Cape Town, South Africa
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Hasbahceci M, Akcakaya A, Memmi N, Turkmen I, Cipe G, Yildiz P, Arici DS, Muslumanoglu M. Diffusion MRI on lymph node staging of gastric adenocarcinoma. Quant Imaging Med Surg 2015; 5:392-400. [PMID: 26029642 DOI: 10.3978/j.issn.2223-4292.2015.03.06] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2014] [Accepted: 03/06/2015] [Indexed: 12/14/2022]
Abstract
OBJECTIVE The purpose of this study was to evaluate the accuracy of diffusion weighted magnetic resonance imaging (MRI) in preoperative assessment of metastatic lymph nodes of gastric cancer. METHODS A total of 23 gastric cancer patients with a mean age of 59.4±10.9 years were analyzed. Lymph nodes were grouped as perigastric lesser curvature (Group Ia), perigastric greater curvature (Group Ib), D1+/D2 lymph nodes (Group II). Identification of histologically metastatic lymph nodes by diffusion weighted MRI was regarded as the main outcome. RESULTS A total of 1,056 lymph nodes including 180 histologically proven metastatic lymph nodes were dissected. Although diffusion weighted MRI could identify the metastatic lymph nodes in 18 out of 23 patients (77.8%), only 69 of total 1,056 nodes (6.53%), either metastatic or non-metastatic, could be detected. There was no correlation between histopathology and diffusion weighted MRI with regard to lymph node groups (P>0.05 for all). Overall accuracy was calculated as 69.56, 65.21 and 52.17 for Groups II, Ib and Ia lymph nodes, respectively. Apparent diffusion coefficient (ADC) values could not be helpful to differentiate metastatic lymph nodes (P=0.673). CONCLUSIONS Diffusion weighted MRI has low accuracy to detect or to differentiate metastatic and non-metastatic lymph nodes based on their ADC values in gastric cancer.
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Affiliation(s)
- Mustafa Hasbahceci
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Adem Akcakaya
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Naim Memmi
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Ihsan Turkmen
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Gokhan Cipe
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Pelin Yildiz
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Dilek Sema Arici
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
| | - Mahmut Muslumanoglu
- 1 Department of General Surgery, 2 Department of Radiology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey ; 3 Department of General Surgery, Fatih University Faculty of Medicine, Fatih, Istanbul 34500, Turkey ; 4 Department of Pathology, Bezmialem Vakif University Faculty of Medicine, Fatih, Istanbul 34093, Turkey
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Elvsåshagen T, Norbom LB, Pedersen PØ, Quraishi SH, Bjørnerud A, Malt UF, Groote IR, Westlye LT. Widespread changes in white matter microstructure after a day of waking and sleep deprivation. PLoS One 2015; 10:e0127351. [PMID: 26020651 PMCID: PMC4447359 DOI: 10.1371/journal.pone.0127351] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2014] [Accepted: 04/14/2015] [Indexed: 12/12/2022] Open
Abstract
Background Elucidating the neurobiological effects of sleep and waking remains an important goal of the neurosciences. Recently, animal studies indicated that sleep is important for cell membrane and myelin maintenance in the brain and that these structures are particularly susceptible to insufficient sleep. Here, we tested the hypothesis that a day of waking and sleep deprivation would be associated with changes in diffusion tensor imaging (DTI) indices of white matter microstructure sensitive to axonal membrane and myelin alterations. Methods Twenty-one healthy adult males underwent DTI in the morning [7:30AM; time point (TP)1], after 14 hours of waking (TP2), and then after another 9 hours of waking (TP3). Whole brain voxel-wise analysis was performed with tract based spatial statistics. Results A day of waking was associated with widespread increases in white matter fractional anisotropy, which were mainly driven by radial diffusivity reductions, and sleep deprivation was associated with widespread fractional anisotropy decreases, which were mainly explained by reductions in axial diffusivity. In addition, larger decreases in axial diffusivity after sleep deprivation were associated with greater sleepiness. All DTI changes remained significant after adjusting for hydration measures. Conclusions This is the first DTI study of sleep deprivation in humans. Although previous studies have observed localized changes in DTI indices of cerebral microstructure over the course of a few hours, further studies are needed to confirm widespread DTI changes within hours of waking and to clarify whether such changes in white matter microstructure serve as neurobiological substrates of sleepiness.
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Affiliation(s)
- Torbjørn Elvsåshagen
- Department of Psychosomatic Medicine, Institution of Oslo University Hospital, Oslo, Norway
- Department of Neurology, Institution of Oslo University Hospital, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT)/KG Jebsen Centre for Psychosis Research, Institution of Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- * E-mail:
| | - Linn B. Norbom
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Per Ø. Pedersen
- Department of Psychosomatic Medicine, Institution of Oslo University Hospital, Oslo, Norway
| | - Sophia H. Quraishi
- Barnard College, Columbia University, New York, NY, United States of America
| | - Atle Bjørnerud
- The Intervention Centre, Institution of Oslo University Hospital, Oslo, Norway
- Department of Physics (AB), University of Oslo, Oslo, Norway
| | - Ulrik F. Malt
- Department of Psychosomatic Medicine, Institution of Oslo University Hospital, Oslo, Norway
- Department of Research and Education, Institution of Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Inge R. Groote
- The Intervention Centre, Institution of Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Lars T. Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT)/KG Jebsen Centre for Psychosis Research, Institution of Oslo University Hospital, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
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38
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Fjell AM, Sneve MH, Storsve AB, Grydeland H, Yendiki A, Walhovd KB. Brain Events Underlying Episodic Memory Changes in Aging: A Longitudinal Investigation of Structural and Functional Connectivity. Cereb Cortex 2015; 26:1272-1286. [PMID: 25994960 DOI: 10.1093/cercor/bhv102] [Citation(s) in RCA: 89] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Episodic memories are established and maintained by close interplay between hippocampus and other cortical regions, but degradation of a fronto-striatal network has been suggested to be a driving force of memory decline in aging. We wanted to directly address how changes in hippocampal-cortical versus striatal-cortical networks over time impact episodic memory with age. We followed 119 healthy participants (20-83 years) for 3.5 years with repeated tests of episodic verbal memory and magnetic resonance imaging for quantification of functional and structural connectivity and regional brain atrophy. While hippocampal-cortical functional connectivity predicted memory change in young, changes in cortico-striatal functional connectivity were related to change in recall in older adults. Within each age group, effects of functional and structural connectivity were anatomically closely aligned. Interestingly, the relationship between functional connectivity and memory was strongest in the age ranges where the rate of reduction of the relevant brain structure was lowest, implying selective impacts of the different brain events on memory. Together, these findings suggest a partly sequential and partly simultaneous model of brain events underlying cognitive changes in aging, where different functional and structural events are more or less important in various time windows, dismissing a simple uni-factorial view on neurocognitive aging.
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Affiliation(s)
- Anders M Fjell
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Norway.,Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, 0424, Norway
| | - Markus H Sneve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Norway
| | - Andreas B Storsve
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Norway
| | - Håkon Grydeland
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Norway
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Kristine B Walhovd
- Research Group for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, 0373, Norway.,Department of Physical Medicine and Rehabilitation, Unit of Neuropsychology, Oslo University Hospital, 0424, Norway
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39
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Travers BG, Tromp DPM, Adluru N, Lange N, Destiche D, Ennis C, Nielsen JA, Froehlich AL, Prigge MBD, Fletcher PT, Anderson JS, Zielinski BA, Bigler ED, Lainhart JE, Alexander AL. Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation. Mol Autism 2015; 6:15. [PMID: 25774283 PMCID: PMC4359536 DOI: 10.1186/s13229-015-0001-8] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2014] [Accepted: 01/26/2015] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND The corpus callosum is the largest white matter structure in the brain, and it is the most consistently reported to be atypical in diffusion tensor imaging studies of autism spectrum disorder. In individuals with typical development, the corpus callosum is known to undergo a protracted development from childhood through young adulthood. However, no study has longitudinally examined the developmental trajectory of corpus callosum in autism past early childhood. METHODS The present study used a cohort sequential design over 9 years to examine age-related changes of the corpus callosum in 100 males with autism and 56 age-matched males with typical development from early childhood (when autism can first be reliably diagnosed) to mid-adulthood (after development of the corpus callosum has been completed) (3 to 41 years of age). RESULTS The group with autism demonstrated a different developmental trajectory of white matter microstructure in the anterior corpus callosum's (genu and body) fractional anisotropy, which suggests atypical brain maturation in these regions in autism. When analyses were broken down by age group, atypical developmental trajectories were present only in the youngest participants (10 years of age and younger). Significant main effects for group were found in terms of decreased fractional anisotropy across all three subregions of the corpus callosum (genu, body, and splenium) and increased mean diffusivity, radial diffusivity, and axial diffusivity in the posterior corpus callosum. CONCLUSIONS These longitudinal results suggest atypical early childhood development of the corpus callosum microstructure in autism that transitions into sustained group differences in adolescence and adulthood. This pattern of results provides longitudinal evidence consistent with a growing number of published studies and hypotheses regarding abnormal brain connectivity across the life span in autism.
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Affiliation(s)
- Brittany G Travers
- />Occupational Therapy Program, Department of Kinesiology, University of Wisconsin-Madison, Madison, WI USA
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
| | - Do P M Tromp
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
- />Department of Psychiatry, University of Wisconsin-Madison, Madison, WI USA
| | - Nagesh Adluru
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
| | - Nicholas Lange
- />Department of Psychiatry, Harvard School of Medicine, Boston, MA USA
- />Neurostatistics Laboratory, McLean Hospital, Belmont, MA USA
| | - Dan Destiche
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
| | - Chad Ennis
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
| | - Jared A Nielsen
- />Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT USA
| | - Alyson L Froehlich
- />Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT USA
| | - Molly B D Prigge
- />Department of Radiology, University of Utah, Salt Lake City, UT USA
- />Department of Pediatrics, University of Utah and Primary Children’s Medical Center, Salt Lake City, UT USA
| | - P Thomas Fletcher
- />Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT USA
- />School of Computing, University of Utah, Salt Lake City, UT USA
| | - Jeffrey S Anderson
- />Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT USA
- />Department of Radiology, University of Utah, Salt Lake City, UT USA
| | - Brandon A Zielinski
- />Department of Pediatrics, University of Utah and Primary Children’s Medical Center, Salt Lake City, UT USA
- />Department of Neurology, University of Utah, Salt Lake City, UT USA
| | - Erin D Bigler
- />Department of Psychology, Brigham Young University, Provo, UT USA
- />Neuroscience Center, Brigham Young University, Provo, UT 84602 USA
| | - Janet E Lainhart
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
- />Department of Psychiatry, University of Wisconsin-Madison, Madison, WI USA
| | - Andrew L Alexander
- />Waisman Center, University of Wisconsin-Madison, 1500 Highland Avenue, Madison, WI 53705 USA
- />Department of Psychiatry, University of Wisconsin-Madison, Madison, WI USA
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Elhabian S, Gur Y, Vachet C, Piven J, Styner M, Leppert IR, Pike GB, Gerig G. Subject-Motion Correction in HARDI Acquisitions: Choices and Consequences. Front Neurol 2014; 5:240. [PMID: 25538672 PMCID: PMC4260507 DOI: 10.3389/fneur.2014.00240] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2014] [Accepted: 11/05/2014] [Indexed: 11/16/2022] Open
Abstract
Diffusion-weighted imaging (DWI) is known to be prone to artifacts related to motion originating from subject movement, cardiac pulsation, and breathing, but also to mechanical issues such as table vibrations. Given the necessity for rigorous quality control and motion correction, users are often left to use simple heuristics to select correction schemes, which involves simple qualitative viewing of the set of DWI data, or the selection of transformation parameter thresholds for detection of motion outliers. The scientific community offers strong theoretical and experimental work on noise reduction and orientation distribution function (ODF) reconstruction techniques for HARDI data, where post-acquisition motion correction is widely performed, e.g., using the open-source DTIprep software (1), FSL (the FMRIB Software Library) (2), or TORTOISE (3). Nonetheless, effects and consequences of the selection of motion correction schemes on the final analysis, and the eventual risk of introducing confounding factors when comparing populations, are much less known and far beyond simple intuitive guessing. Hence, standard users lack clear guidelines and recommendations in practical settings. This paper reports a comprehensive evaluation framework to systematically assess the outcome of different motion correction choices commonly used by the scientific community on different DWI-derived measures. We make use of human brain HARDI data from a well-controlled motion experiment to simulate various degrees of motion corruption and noise contamination. Choices for correction include exclusion/scrubbing or registration of motion corrupted directions with different choices of interpolation, as well as the option of interpolation of all directions. The comparative evaluation is based on a study of the impact of motion correction using four metrics that quantify (1) similarity of fiber orientation distribution functions (fODFs), (2) deviation of local fiber orientations, (3) global brain connectivity via graph diffusion distance (GDD), and (4) the reproducibility of prominent and anatomically defined fiber tracts. Effects of various motion correction choices are systematically explored and illustrated, leading to a general conclusion of discouraging users from setting ad hoc thresholds on the estimated motion parameters beyond which volumes are claimed to be corrupted.
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Affiliation(s)
- Shireen Elhabian
- Scientific Computing and Imaging Institute , Salt Lake City, UT , USA ; Faculty of Computers and Information, Cairo University , Cairo , Egypt
| | - Yaniv Gur
- IBM Almaden Research Center , San Jose, CA , USA
| | - Clement Vachet
- Scientific Computing and Imaging Institute , Salt Lake City, UT , USA
| | - Joseph Piven
- Department of Psychiatry, University of North Carolina , Chapel Hill, NC , USA
| | - Martin Styner
- Department of Psychiatry, University of North Carolina , Chapel Hill, NC , USA ; Department of Computer Science, University of North Carolina , Chapel Hill, NC , USA
| | - Ilana R Leppert
- Department of Neurology and Neurosurgery, Montreal Neurological Institute , Montreal, QC , Canada
| | - G Bruce Pike
- Department of Neurology and Neurosurgery, Montreal Neurological Institute , Montreal, QC , Canada ; Department of Radiology, University of Calgary , Calgary, AB , Canada
| | - Guido Gerig
- Scientific Computing and Imaging Institute , Salt Lake City, UT , USA
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Alhamud A, Taylor PA, Laughton B, van der Kouwe AJW, Meintjes EM. Motion artifact reduction in pediatric diffusion tensor imaging using fast prospective correction. J Magn Reson Imaging 2014; 41:1353-64. [PMID: 24935904 DOI: 10.1002/jmri.24678] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2014] [Revised: 05/30/2014] [Accepted: 05/30/2014] [Indexed: 11/08/2022] Open
Abstract
PURPOSE To evaluate the patterns of head motion in scans of young children and to examine the influence of corrective techniques, both qualitatively and quantitatively. We investigate changes that both retrospective (with and without diffusion table reorientation) and prospective (implemented with a short navigator sequence) motion correction induce in the resulting diffusion tensor measures. MATERIALS AND METHODS Eighteen pediatric subjects (aged 5-6 years) were scanned using 1) a twice-refocused, 2D diffusion pulse sequence, 2) a prospectively motion-corrected, navigated diffusion sequence with reacquisition of a maximum of five corrupted diffusion volumes, and 3) a T1 -weighted structural image. Mean fractional anisotropy (FA) values in white and gray matter regions, as well as tractography in the brainstem and projection fibers, were evaluated to assess differences arising from retrospective (via FLIRT in FSL) and prospective motion correction. In addition to human scans, a stationary phantom was also used for further evaluation. RESULTS In several white and gray matter regions retrospective correction led to significantly (P < 0.05) reduced FA means and altered distributions compared to the navigated sequence. Spurious tractographic changes in the retrospectively corrected data were also observed in subject data, as well as in phantom and simulated data. CONCLUSION Due to the heterogeneity of brain structures and the comparatively low resolution (∼2 mm) of diffusion data using 2D single shot sequencing, retrospective motion correction is susceptible to distortion from partial voluming. These changes often negatively bias diffusion tensor imaging parameters. Prospective motion correction was shown to produce smaller changes.
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Affiliation(s)
- A Alhamud
- MRC/UCT Medical Imaging Research Unit, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Observatory, Cape Town, South Africa
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Gumus K, Keating B, Poser BA, Armstrong B, Chang L, Maclaren J, Prieto T, Speck O, Zaitsev M, Ernst T. Prevention of motion-induced signal loss in diffusion-weighted echo-planar imaging by dynamic restoration of gradient moments. Magn Reson Med 2014; 71:2006-13. [PMID: 23821373 PMCID: PMC4420624 DOI: 10.1002/mrm.24857] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2013] [Revised: 05/10/2013] [Accepted: 06/05/2013] [Indexed: 11/11/2022]
Abstract
PURPOSE Head motion is a significant problem in diffusion-weighted imaging as it may cause signal attenuation due to residual dephasing during strong diffusion encoding gradients even in single-shot acquisitions. Here, we present a new real-time method to prevent motion-induced signal loss in DWI of the brain. METHODS The method requires a fast motion tracking system (optical in the current implementation). Two alterations were made to a standard diffusion-weighted echo-planar imaging sequence: first, real-time motion correction ensures that slices are correctly aligned relative to the moving brain. Second, the tracking data are used to calculate the motion-induced gradient moment imbalance which occurs during the diffusion encoding periods, and a brief gradient blip is inserted immediately prior to the signal readout to restore the gradient moment balance. RESULTS Phantom experiments show that the direction as well as magnitude of the gradient moment imbalance affects the characteristics of unwanted signal attenuation. In human subjects, the addition of a moment-restoring blip prevented signal loss and improved the reproducibility and reliability of diffusion tensor measures even in the presence of substantial head movements. CONCLUSION The method presented can improve robustness for clinical routine scanning in populations that are prone to head movements, such as children and uncooperative adult patients.
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Affiliation(s)
- Kazim Gumus
- Department of Medicine, JABSOM, University of Hawaii, Honolulu, Hawaii, USA
| | - Brian Keating
- Department of Medicine, JABSOM, University of Hawaii, Honolulu, Hawaii, USA
| | - Benedikt A. Poser
- Department of Medicine, JABSOM, University of Hawaii, Honolulu, Hawaii, USA
| | - Brian Armstrong
- Department of Electrical Engineering and Computer Science, University of Wisconsin Milwaukee, Milwaukee, Wisconsin, USA
| | - Linda Chang
- Department of Medicine, JABSOM, University of Hawaii, Honolulu, Hawaii, USA
| | - Julian Maclaren
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Thomas Prieto
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Oliver Speck
- Biomedical Magnetic Resonance, Otto von Guericke University, Magde burg, Germany
- Leibniz Institute for Neurobiology, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Maxim Zaitsev
- Department of Radiology, University Medical Center Freiburg, Freiburg, Germany
| | - Thomas Ernst
- Department of Medicine, JABSOM, University of Hawaii, Honolulu, Hawaii, USA
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Taylor PA, Saad ZS. FATCAT: (an efficient) Functional and Tractographic Connectivity Analysis Toolbox. Brain Connect 2014; 3:523-35. [PMID: 23980912 DOI: 10.1089/brain.2013.0154] [Citation(s) in RCA: 152] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
We present a suite of software tools for facilitating the combination of functional magnetic resonance imaging (FMRI) and diffusion-based tractography from a network-focused point of view. The programs have been designed for investigating functionally derived gray matter networks and related structural white matter networks. The software comprises the Functional and Tractographic Connectivity Analysis Toolbox (FATCAT), now freely distributed with AFNI. This toolbox supports common file formats and has been designed to integrate as easily as possible with existing standard FMRI pipelines and diffusion software, such as AFNI, FSL, and TrackVis. The programs are efficient, run by commandline for facilitating group processing, and produce several visualizable outputs. Here, we present the programs and their underlying methods, and we also provide a test example of resting-state FMRI analysis combined with tractography. Tractography results are compared with existing methods, showing significantly reduced runtime and generally similar connectivity, but with important differences such as more circumscribed tract regions and more physiologically identifiable paths produced between several region-of-interest pairs. Currently, FATCAT uses only diffusion tensor-based tractography (one direction per voxel), but higher-order models will soon be included.
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Affiliation(s)
- Paul A Taylor
- 1 African Institute for Mathematical Sciences , Muizenberg, Western Cape, South Africa
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Differences in the right inferior longitudinal fasciculus but no general disruption of white matter tracts in children with autism spectrum disorder. Proc Natl Acad Sci U S A 2014; 111:1981-6. [PMID: 24449864 DOI: 10.1073/pnas.1324037111] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
One of the most widely cited features of the neural phenotype of autism is reduced "integrity" of long-range white matter tracts, a claim based primarily on diffusion imaging studies. However, many prior studies have small sample sizes and/or fail to address differences in data quality between those with autism spectrum disorder (ASD) and typical participants, and there is little consensus on which tracts are affected. To overcome these problems, we scanned a large sample of children with autism (n = 52) and typically developing children (n = 73). Data quality was variable, and worse in the ASD group, with some scans unusable because of head motion artifacts. When we follow standard data analysis practices (i.e., without matching head motion between groups), we replicate the finding of lower fractional anisotropy (FA) in multiple white matter tracts. However, when we carefully match data quality between groups, all these effects disappear except in one tract, the right inferior longitudinal fasciculus (ILF). Additional analyses showed the expected developmental increases in the FA of fiber tracts within ASD and typical groups individually, demonstrating that we had sufficient statistical power to detect known group differences. Our data challenge the widely claimed general disruption of white matter tracts in autism, instead implicating only one tract, the right ILF, in the ASD phenotype.
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Yendiki A, Koldewyn K, Kakunoori S, Kanwisher N, Fischl B. Spurious group differences due to head motion in a diffusion MRI study. Neuroimage 2013; 88:79-90. [PMID: 24269273 DOI: 10.1016/j.neuroimage.2013.11.027] [Citation(s) in RCA: 369] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2013] [Revised: 11/11/2013] [Accepted: 11/14/2013] [Indexed: 02/02/2023] Open
Abstract
Diffusion-weighted MRI (DW-MRI) has become a popular imaging modality for probing the microstructural properties of white matter and comparing them between populations in vivo. However, the contrast in DW-MRI arises from the microscopic random motion of water molecules in brain tissues, which makes it particularly sensitive to macroscopic head motion. Although this has been known since the introduction of DW-MRI, most studies that use this modality for group comparisons do not report measures of head motion for each group and rely on registration-based correction methods that cannot eliminate the full effects of head motion on the DW-MRI contrast. In this work we use data from children with autism and typically developing children to investigate the effects of head motion on differences in anisotropy and diffusivity measures between groups. We show that group differences in head motion can induce group differences in DW-MRI measures, and that this is the case even when comparing groups that include control subjects only, where no anisotropy or diffusivity differences are expected. We also show that such effects can be more prominent in some white-matter pathways than others, and that they can be ameliorated by including motion as a nuisance regressor in the analyses. Our results demonstrate the importance of taking head motion into account in any population study where one group might exhibit more head motion than the other.
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Affiliation(s)
- Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Kami Koldewyn
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sita Kakunoori
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Nancy Kanwisher
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
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Kociemba A, Pyda M, Katulska K, Łanocha M, Siniawski A, Janus M, Grajek S. Comparison of diffusion-weighted with T2-weighted imaging for detection of edema in acute myocardial infarction. J Cardiovasc Magn Reson 2013; 15:90. [PMID: 24098944 PMCID: PMC3852828 DOI: 10.1186/1532-429x-15-90] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2013] [Accepted: 10/01/2013] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Recent studies, performed with the use of a commercially available diffusion weighted imaging (DWI) sequence, showed that they are sensitive to the increase of water content in the myocardium and may be used as an alternative to the standard T2-weighted sequences. The aim of this study was to compare two methods of myocardial edema imaging: DWI and T2-TIRM. METHODS The study included 91 acute and post STEMI patients. We applied a qualitative and quantitative image analysis. The qualitative analysis consisted of evaluation of the quality of blood suppression, presence of artifacts and occurrence of high signal (edema) areas. On the basis of edema detection in AMI and control (post STEMI) group, the sensitivity and specificity of TIRM and DWI were determined. Two contrast to noise ratios (CNR) were calculated: CNR1--the contrast between edema and healthy myocardium and CNR2--the contrast between edema and intraventricular blood pool. The area of edema was measured for both TIRM and DWI sequences and compared with the infarct size in LGE images. RESULTS Edema occurred more frequently in the DWI sequence. A major difference was observed in the inferior wall, where an edema-high signal was observed in 46% in T2-TIRM, whereas in the DWI sequence in 85%. An analysis of the image quality parameters showed that the use of DWI sequence allows complete blood signal suppression in the left ventricular cavity and reduces the occurrence of motion artifacts. However, it is connected with a higher incidence of magnetic susceptibility artifacts and image distortion. An analysis of the CNRs showed that CNR1 in T2-TIRM sequence depends on the infarct location and has the lowest value for the inferior wall. The area of edema measured on DWI images was significantly larger than in T2-TIRM. CONCLUSIONS DWI is a new technique for edema detection in patients with acute myocardial infarction which may be recommended for the diagnosis of acute injuries, especially in patients with slow-flow artifacts in TIRM images.
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Affiliation(s)
- Anna Kociemba
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
| | - Małgorzta Pyda
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
| | | | - Magdalena Łanocha
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
| | - Andrzej Siniawski
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
| | - Magdalena Janus
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
| | - Stefan Grajek
- Magnetic Resonance Unit, I’st Department of Cardiology, University of Medical Sciences, Poznan, Poland
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O'Brien K, Daducci A, Kickler N, Lazeyras F, Gruetter R, Feiweier T, Krueger G. 3-D residual eddy current field characterisation: applied to diffusion weighted magnetic resonance imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2013; 32:1515-1525. [PMID: 23674437 DOI: 10.1109/tmi.2013.2259249] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Clinical use of the Stejskal-Tanner diffusion weighted images is hampered by the geometric distortions that result from the large residual 3-D eddy current field induced. In this work, we aimed to predict, using linear response theory, the residual 3-D eddy current field required for geometric distortion correction based on phantom eddy current field measurements. The predicted 3-D eddy current field induced by the diffusion-weighting gradients was able to reduce the root mean square error of the residual eddy current field to ~1 Hz. The model's performance was tested on diffusion weighted images of four normal volunteers, following distortion correction, the quality of the Stejskal-Tanner diffusion-weighted images was found to have comparable quality to image registration based corrections (FSL) at low b-values. Unlike registration techniques the correction was not hindered by low SNR at high b-values, and results in improved image quality relative to FSL. Characterization of the 3-D eddy current field with linear response theory enables the prediction of the 3-D eddy current field required to correct eddy current induced geometric distortions for a wide range of clinical and high b-value protocols.
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Affiliation(s)
- Kieran O'Brien
- Department ofRadiology,University of Geneva, 1211 Geneva, Switzerland and the Advanced Clinical Imaging Technology, CIBMS Siemens Suisse SA, 1015 Lausanne, Switzerland.
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Motion Detection in Diffusion MRI via Online ODF Estimation. Int J Biomed Imaging 2013; 2013:849363. [PMID: 23509445 PMCID: PMC3594974 DOI: 10.1155/2013/849363] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2012] [Revised: 12/31/2012] [Accepted: 01/04/2013] [Indexed: 11/18/2022] Open
Abstract
The acquisition of high angular resolution diffusion MRI is particularly long and subject motion can become an issue. The orientation distribution function (ODF) can be reconstructed online incrementally from diffusion-weighted MRI with a Kalman filtering framework. This online reconstruction provides real-time feedback throughout the acquisition process. In this article, the Kalman filter is first adapted to the reconstruction of the ODF in constant solid angle. Then, a method called STAR (STatistical Analysis of Residuals) is presented and applied to the online detection of motion in high angular resolution diffusion images. Compared to existing techniques, this method is image based and is built on top of a Kalman filter. Therefore, it introduces no additional scan time and does not require additional hardware. The performance of STAR is tested on simulated and real data and compared to the classical generalized likelihood ratio test. Successful detection of small motion is reported (rotation under 2°) with no delay and robustness to noise.
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Iima M, Yamamoto A, Brion V, Okada T, Kanagaki M, Togashi K, Le Bihan D. Reduced-distortion diffusion MRI of the craniovertebral junction. AJNR Am J Neuroradiol 2012; 33:1321-5. [PMID: 22383239 DOI: 10.3174/ajnr.a2969] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE CVJ lesion suffers from a high sensitivity to susceptibility and distortion artifacts, which sometimes makes diffusion image difficult to interpret. Our purpose was to evaluate the potential for diffusion MR imaging using RS-EPI compared with SS-EPI in the assessment of the CVJ. MATERIALS AND METHODS RS-EPI and SS-EPI DTI images were acquired from 10 healthy volunteers using 3T MRI with a 32-channel head coil. For both sequences, the following parameters were used: 1-mm(2) in-plane resolution; 3-mm section thickness; TR = 5200 ms; 1 acquisition at b = 0 and 12 different encoding directions at b = 1000 seconds/mm(2). The RS-EPI sequence scan time was 9.44 minutes (1 average). The SS-EPI sequence was 9.37 minutes (8 averages). Diffusion tensor calculation and image analysis were performed using DTIStudio software. Diffusion trace images and color-coded fiber orientation maps were evaluated by 2 independent readers for distortion and delineation of fine structure using a semiquantitative scale in selected landmark locations. The absolute distances between the temporal base and the cerebellar contour between the T2-weighted images and the diffusion trace images obtained with RS-EPI and SS-EPI were also compared. RESULTS The contours of the temporal lobe and cerebellum were better delineated and distortion artifacts were clearly reduced with the RS-EPI sequence. More fine structures were also visible in the brain stem and cerebellum with the RS-EPI sequence. The amount of distortion was significantly reduced with RS-EPI compared with SS-EPI (P < .01). CONCLUSIONS The RS-EPI DTI sequence was less prone to geometric distortion than the SS-EPI sequence and allowed a better delineation of CVJ internal structure. Although the acquisition time is still relatively long, the RS-EPI appears as a promising approach to perform DTI studies in CVJ lesions, such as brain stem ischemia, neurodegenerative diseases, brain and skull base tumors, or inflammation.
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Affiliation(s)
- M Iima
- Department of Diagnostic Imaging and Nuclear Medicine and Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan.
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Holdsworth SJ, Aksoy M, Newbould RD, Yeom K, Van AT, Ooi MB, Barnes PD, Bammer R, Skare S. Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging. J Magn Reson Imaging 2012; 36:961-71. [PMID: 22689498 DOI: 10.1002/jmri.23710] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2012] [Accepted: 04/30/2012] [Indexed: 11/06/2022] Open
Abstract
PURPOSE To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high-quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts. MATERIALS AND METHODS We implemented an in-house built generalized autocalibrating partially parallel acquisitions (GRAPPA)-accelerated diffusion tensor (DT) echo-planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid-body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b-matrix correction for large motion. RESULTS The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high-quality data for routine evaluation. CONCLUSION This work suggests that, apart from the rare instance of continuous motion throughout the scan, high-quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data.
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