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Irastorza-Valera L, Soria-Gómez E, Benitez JM, Montáns FJ, Saucedo-Mora L. Review of the Brain's Behaviour after Injury and Disease for Its Application in an Agent-Based Model (ABM). Biomimetics (Basel) 2024; 9:362. [PMID: 38921242 DOI: 10.3390/biomimetics9060362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 05/28/2024] [Accepted: 06/05/2024] [Indexed: 06/27/2024] Open
Abstract
The brain is the most complex organ in the human body and, as such, its study entails great challenges (methodological, theoretical, etc.). Nonetheless, there is a remarkable amount of studies about the consequences of pathological conditions on its development and functioning. This bibliographic review aims to cover mostly findings related to changes in the physical distribution of neurons and their connections-the connectome-both structural and functional, as well as their modelling approaches. It does not intend to offer an extensive description of all conditions affecting the brain; rather, it presents the most common ones. Thus, here, we highlight the need for accurate brain modelling that can subsequently be used to understand brain function and be applied to diagnose, track, and simulate treatments for the most prevalent pathologies affecting the brain.
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Affiliation(s)
- Luis Irastorza-Valera
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain
- PIMM Laboratory, ENSAM-Arts et Métiers ParisTech, 151 Bd de l'Hôpital, 75013 Paris, France
| | - Edgar Soria-Gómez
- Achúcarro Basque Center for Neuroscience, Barrio Sarriena, s/n, 48940 Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi, 5, 48009 Bilbao, Spain
- Department of Neurosciences, University of the Basque Country UPV/EHU, Barrio Sarriena, s/n, 48940 Leioa, Spain
| | - José María Benitez
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain
| | - Francisco J Montáns
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain
- Department of Mechanical and Aerospace Engineering, Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL 32611, USA
| | - Luis Saucedo-Mora
- E.T.S. de Ingeniería Aeronáutica y del Espacio, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, 28040 Madrid, Spain
- Department of Materials, University of Oxford, Parks Road, Oxford OX1 3PJ, UK
- Department of Nuclear Science and Engineering, Massachusetts Institute of Technology (MIT), 77 Massachusetts Ave, Cambridge, MA 02139, USA
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Coupeau P, Démas J, Fasquel JB, Hertz-Pannier L, Chabrier S, Dinomais M. Hand function after neonatal stroke: A graph model based on basal ganglia and thalami structure. Neuroimage Clin 2024; 41:103568. [PMID: 38277807 PMCID: PMC10832504 DOI: 10.1016/j.nicl.2024.103568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 01/28/2024]
Abstract
INTRODUCTION Neonatal arterial ischemic stroke (NAIS) is a common model to study the impact of a unilateral early brain insult on developmental brain plasticity and the appearance of long-term outcomes. Motor difficulties that may arise are typically related to poor function of the affected (contra-lesioned) hand, but surprisingly also of the ipsilesional hand. Although many longitudinal studies after NAIS have shown that predicting the occurrence of gross motor difficulties is easier, accurately predicting hand motor function (for both hands) from morphometric MRI remains complicated. The hypothesis of an association between the structural organization of the basal ganglia (BG) and thalamus with hand motor function seems intuitive given their key role in sensorimotor function. Neuroimaging studies have frequently investigated these structures to evaluate the correlation between their volumes and motor function following early brain injury. However, the results have been controversial. We hypothesize the involvement of other structural parameters. METHOD The study involves 35 children (mean age 7.3 years, SD 0.4) with middle cerebral artery NAIS who underwent a structural T1-weighted 3D MRI and clinical examination to assess manual dexterity using the Box and Blocks Test (BBT). Graphs are used to represent high-level structural information of the BG and thalami (volumes, elongations, distances) measured from the MRI. A graph neural network (GNN) is proposed to predict children's hand motor function through a graph regression. To reduce the impact of external factors on motor function (such as behavior and cognition), we calculate a BBT score ratio for each child and hand. RESULTS The results indicate a significant correlation between the score ratios predicted by our method and the actual score ratios of both hands (p < 0.05), together with a relatively high accuracy of prediction (mean L1 distance < 0.03). The structural information seems to have a different influence on each hand's motor function. The affected hand's motor function is more correlated with the volume, while the 'unaffected' hand function is more correlated with the elongation of the structures. Experiments emphasize the importance of considering the whole macrostructural organization of the basal ganglia and thalami networks, rather than the volume alone, to predict hand motor function. CONCLUSION There is a significant correlation between the structural characteristics of the basal ganglia/thalami and motor function in both hands. These results support the use of MRI macrostructural features of the basal ganglia and thalamus as an early biomarker for predicting motor function in both hands after early brain injury.
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Affiliation(s)
- Patty Coupeau
- Université d'Angers, LARIS, SFR MATHSTIC, F-49000 Angers, France.
| | - Josselin Démas
- Université d'Angers, LARIS, SFR MATHSTIC, F-49000 Angers, France; Instituts de Formation, CH Laval, France
| | | | - Lucie Hertz-Pannier
- UNIACT/Neurospin/JOLIOT/DRF/CEA-Saclay, and U1141 NeuroDiderot/Inserm, CEA, Paris University, France
| | - Stéphane Chabrier
- French Centre for Pediatric Stroke, Pediatric Physical and Rehabilitation Medicine Department, Saint-Etienne University Hospital, France
| | - Mickael Dinomais
- Université d'Angers, LARIS, SFR MATHSTIC, F-49000 Angers, France; Department of Physical and Rehabilitation Medicine, University Hospital, CHU Angers, France
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Etekochay MO, Amaravadhi AR, González GV, Atanasov AG, Matin M, Mofatteh M, Steinbusch HW, Tesfaye T, Praticò D. Unveiling New Strategies Facilitating the Implementation of Artificial Intelligence in Neuroimaging for the Early Detection of Alzheimer's Disease. J Alzheimers Dis 2024; 99:1-20. [PMID: 38640152 DOI: 10.3233/jad-231135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for AD, such as neuroimaging approaches. Neuroimaging techniques, including positron emission tomography and magnetic resonance imaging, have revolutionized the field by providing valuable insights into the structural and functional alterations in the brains of individuals with AD. These imaging modalities enable the detection of early biomarkers such as amyloid-β plaques and tau protein tangles, facilitating early and precise diagnosis. Furthermore, the emerging technologies encompassing blood-based biomarkers and neurochemical profiling exhibit promising results in the identification of specific molecular signatures for AD. The integration of machine learning algorithms and artificial intelligence has enhanced the predictive capacity of these diagnostic tools when analyzing complex datasets. In this review article, we will highlight not only some of the most used diagnostic imaging approaches in neurodegeneration research but focus much more on new tools like artificial intelligence, emphasizing their application in the realm of AD. These advancements hold immense potential for early detection and intervention, thereby paving the way for personalized therapeutic strategies and ultimately augmenting the quality of life for individuals affected by AD.
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Affiliation(s)
| | - Amoolya Rao Amaravadhi
- Internal Medicine, Malla Reddy Institute of Medical Sciences, Jeedimetla, Hyderabad, India
| | - Gabriel Villarrubia González
- Expert Systems and Applications Laboratory (ESALAB), Faculty of Science, University of Salamanca, Salamanca, Spain
| | - Atanas G Atanasov
- Department of Biotechnology and Nutrigenomics, Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences, Jastrzebiec, Poland
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Maima Matin
- Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Vienna, Austria
| | - Mohammad Mofatteh
- School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, UK
| | - Harry Wilhelm Steinbusch
- Department of Cellular and Translational Neuroscience, School for Mental Health and Neuroscience, Faculty of Health Medicine and Life Sciences, Maastricht University, Netherlands
| | - Tadele Tesfaye
- CareHealth Medical Practice, Jimma Road, Addis Ababa, Ethiopia
| | - Domenico Praticò
- Alzheimer's Center at Temple, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA
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4
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Kim SY, Yeh PH, Ollinger JM, Morris HD, Hood MN, Ho VB, Choi KH. Military-related mild traumatic brain injury: clinical characteristics, advanced neuroimaging, and molecular mechanisms. Transl Psychiatry 2023; 13:289. [PMID: 37652994 PMCID: PMC10471788 DOI: 10.1038/s41398-023-02569-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 07/18/2023] [Accepted: 07/24/2023] [Indexed: 09/02/2023] Open
Abstract
Mild traumatic brain injury (mTBI) is a significant health burden among military service members. Although mTBI was once considered relatively benign compared to more severe TBIs, a growing body of evidence has demonstrated the devastating neurological consequences of mTBI, including chronic post-concussion symptoms and deficits in cognition, memory, sleep, vision, and hearing. The discovery of reliable biomarkers for mTBI has been challenging due to under-reporting and heterogeneity of military-related mTBI, unpredictability of pathological changes, and delay of post-injury clinical evaluations. Moreover, compared to more severe TBI, mTBI is especially difficult to diagnose due to the lack of overt clinical neuroimaging findings. Yet, advanced neuroimaging techniques using magnetic resonance imaging (MRI) hold promise in detecting microstructural aberrations following mTBI. Using different pulse sequences, MRI enables the evaluation of different tissue characteristics without risks associated with ionizing radiation inherent to other imaging modalities, such as X-ray-based studies or computerized tomography (CT). Accordingly, considering the high morbidity of mTBI in military populations, debilitating post-injury symptoms, and lack of robust neuroimaging biomarkers, this review (1) summarizes the nature and mechanisms of mTBI in military settings, (2) describes clinical characteristics of military-related mTBI and associated comorbidities, such as post-traumatic stress disorder (PTSD), (3) highlights advanced neuroimaging techniques used to study mTBI and the molecular mechanisms that can be inferred, and (4) discusses emerging frontiers in advanced neuroimaging for mTBI. We encourage multi-modal approaches combining neuropsychiatric, blood-based, and genetic data as well as the discovery and employment of new imaging techniques with big data analytics that enable accurate detection of post-injury pathologic aberrations related to tissue microstructure, glymphatic function, and neurodegeneration. Ultimately, this review provides a foundational overview of military-related mTBI and advanced neuroimaging techniques that merit further study for mTBI diagnosis, prognosis, and treatment monitoring.
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Affiliation(s)
- Sharon Y Kim
- School of Medicine, Uniformed Services University, Bethesda, MD, USA
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA
| | - Ping-Hong Yeh
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - John M Ollinger
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA
- National Intrepid Center of Excellence, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Herman D Morris
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Maureen N Hood
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Vincent B Ho
- Department of Radiology and Radiological Sciences, Uniformed Services University, Bethesda, MD, USA
- Department of Radiology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Kwang H Choi
- Program in Neuroscience, Uniformed Services University, Bethesda, MD, USA.
- Center for the Study of Traumatic Stress, Uniformed Services University, Bethesda, MD, USA.
- Department of Psychiatry, Uniformed Services University, Bethesda, MD, USA.
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5
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Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature. Neuropsychol Rev 2023; 33:42-121. [PMID: 33721207 DOI: 10.1007/s11065-021-09485-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.
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Bigler ED, Skiles M, Wade BSC, Abildskov TJ, Tustison NJ, Scheibel RS, Newsome MR, Mayer AR, Stone JR, Taylor BA, Tate DF, Walker WC, Levin HS, Wilde EA. FreeSurfer 5.3 versus 6.0: are volumes comparable? A Chronic Effects of Neurotrauma Consortium study. Brain Imaging Behav 2021; 14:1318-1327. [PMID: 30511116 DOI: 10.1007/s11682-018-9994-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Automated neuroimaging methods like FreeSurfer ( https://surfer.nmr.mgh.harvard.edu/ ) have revolutionized quantitative neuroimaging analyses. Such analyses provide a variety of metrics used for image quantification, including magnetic resonance imaging (MRI) volumetrics. With the release of FreeSurfer version 6.0, it is important to assess its comparability to the widely-used previous version 5.3. The current study used data from the initial 249 participants in the ongoing Chronic Effects of Neurotrauma Consortium (CENC) multicenter observational study to compare the volumetric output of versions 5.3 and 6.0 across various regions of interest (ROI). In the current investigation, the following ROIs were examined: total intracranial volume, total white matter volume, total ventricular volume, total gray matter volume, and right and left volumes for the thalamus, pallidum, putamen, caudate, amygdala and hippocampus. Absolute ROI volumes derived from FreeSurfer 6.0 differed significantly from those obtained using version 5.3. We also employed a clinically-based evaluation strategy to compare both versions in their prediction of age-mediated volume reductions (or ventricular increase) in the aforementioned structures. Statistical comparison involved both general linear modeling (GLM) and random forest (RF) methods, where cross-validation error was significantly higher using segmentations from FreeSurfer version 5.3 versus version 6.0 (GLM: t = 4.97, df = 99, p value = 2.706e-06; RF: t = 4.85, df = 99, p value = 4.424e-06). Additionally, the relative importance of ROIs used to predict age using RFs differed between FreeSurfer versions, indicating substantial differences in the two versions. However, from the perspective of correlational analyses, fitted regression lines and their slopes were similar between the two versions, regardless of version used. While absolute volumes are not interchangeable between version 5.3 and 6.0, ROI correlational analyses appear to yield similar results, suggesting the interchangeability of ROI volume for correlational studies.
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Affiliation(s)
- Erin D Bigler
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA.
| | - Marc Skiles
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Benjamin S C Wade
- Missouri Institute of Mental Health, University of Missouri-St. Louis, St. Louis, MO, USA.,Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA.,Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, UCLA, Los Angeles, CA, USA
| | - Tracy J Abildskov
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Nick J Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Randall S Scheibel
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | - Mary R Newsome
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | | | - James R Stone
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | | | - David F Tate
- Missouri Institute of Mental Health, University of Missouri-St. Louis, St. Louis, MO, USA
| | | | - Harvey S Levin
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | - Elisabeth A Wilde
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA.,University of Utah, Salt Lake City, UT, USA
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7
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Lai CH. Biomarkers in Panic Disorder. CURRENT PSYCHIATRY RESEARCH AND REVIEWS 2021. [DOI: 10.2174/2666082216999200918163245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
Panic disorder (PD) is a kind of anxiety disorder that impacts the life quality
and functional perspectives in patients. However, the pathophysiological study of PD seems still
inadequate and many unresolved issues need to be clarified.
Objectives:
In this review article of biomarkers in PD, the investigator will focus on the findings of
magnetic resonance imaging (MRI) of the brain in the pathophysiology study. The MRI biomarkers
would be divided into several categories, on the basis of structural and functional perspectives.
Methods:
The structural category would include the gray matter and white matter tract studies. The
functional category would consist of functional MRI (fMRI), resting-state fMRI (Rs-fMRI), and
magnetic resonance spectroscopy (MRS). The PD biomarkers revealed by the above methodologies
would be discussed in this article.
Results:
For the gray matter perspectives, the PD patients would have alterations in the volumes of
fear network structures, such as the amygdala, parahippocampal gyrus, thalamus, anterior cingulate
cortex, insula, and frontal regions. For the white matter tract studies, the PD patients seemed to have
alterations in the fasciculus linking the fear network regions, such as the anterior thalamic radiation,
uncinate fasciculus, fronto-occipital fasciculus, and superior longitudinal fasciculus. For the fMRI
studies in PD, the significant results also focused on the fear network regions, such as the amygdala,
hippocampus, thalamus, insula, and frontal regions. For the Rs-fMRI studies, PD patients seemed to
have alterations in the regions of the default mode network and fear network model. At last, the
MRS results showed alterations in neuron metabolites of the hippocampus, amygdala, occipital
cortex, and frontal regions.
Conclusion:
The MRI biomarkers in PD might be compatible with the extended fear network model
hypothesis in PD, which included the amygdala, hippocampus, thalamus, insula, frontal regions, and
sensory-related cortex.
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Affiliation(s)
- Chien-Han Lai
- Department of Psychiatry, Institute of Biophotonics, National Yang-Ming University, Taipei, Taiwan
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8
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Wright KL, Hopkins RO, Robertson FE, Bigler ED, Taylor HG, Rubin KH, Vannatta K, Stancin T, Yeates KO. Assessment of White Matter Integrity after Pediatric Traumatic Brain Injury. J Neurotrauma 2020; 37:2188-2197. [PMID: 32253971 PMCID: PMC7580640 DOI: 10.1089/neu.2019.6691] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
White matter (WM) abnormalities, such as atrophy and hyperintensities (WMH), can be accessed via magnetic resonance imaging (MRI) after pediatric traumatic brain injury (TBI). Several methods are available to classify WM abnormalities (i.e., total WM volumes and WMHs), but automated and manual volumes and clinical ratings have yet to be compared in pediatric TBI. In addition, WM integrity has been associated reliably with processing speed. Consequently, methods of assessing WM integrity should relate to processing speed to have clinical application. This study had two goals: (1) to compare Scheltens rating scale, manual tracing, FreeSurfer, and NeuroQuant® methods of assessing WM abnormalities, and (2) to relate WM methods to processing speed scores. We report findings from the Social Outcomes of Brain Injury in Kids (SOBIK) study, a multi-center study of 60 children with chronic TBI (65% male) from ages 8-13. Scheltens WMH ratings had good to excellent agreement with WMH volumes for both NeuroQuant (ICC = 0.62; r = 0.29, p = 0.005) and manual tracing (ICC = 0.82; r = 0.50, p = 0.000). NeuroQuant WMH volumes did not correlate with manually traced WMH volumes (r = 0.12, p = 0.21) and had poor agreement (ICC = 0.24). NeuroQuant and FreeSurfer total WM volumes correlated (r = 0.38, p = 0.004) and had fair agreement (ICC = 0.52). The WMH assessment methods, both ratings and volumes, were associated with processing speed scores. In contrast, total WM volume was not related to processing speed. Measures of WMH may hold clinical utility for predicting cognitive functioning after pediatric TBI.
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Affiliation(s)
- Kacie L. Wright
- Psychology Department, Brigham Young University, Provo, Utah, USA
| | - Ramona O. Hopkins
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, Utah, USA
| | | | - Erin D. Bigler
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, Utah, USA
| | - H. Gerry Taylor
- Department of Pediatrics, Ohio State University and Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Kenneth H. Rubin
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Kathryn Vannatta
- Department of Pediatrics, Ohio State University and Abigail Wexner Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Terry Stancin
- Department of Pediatrics, Case Western Reserve University, and Rainbow Babies and Children's Hospital, Cleveland, Ohio, USA
| | - Keith Owen Yeates
- Department of Psychology, Alberta Children's Hospital Research Institute, and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
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9
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Holmes RB, Negus IS, Wiltshire SJ, Thorne GC, Young P. Creation of an anthropomorphic CT head phantom for verification of image segmentation. Med Phys 2020; 47:2380-2391. [PMID: 32160322 PMCID: PMC7383927 DOI: 10.1002/mp.14127] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 02/21/2020] [Accepted: 02/21/2020] [Indexed: 12/25/2022] Open
Abstract
Purpose Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, as MR has notably greater tissue contrast. Methods To investigate these issues we have created a three‐dimensional (3D) printed brain with realistic Hounsfield unit (HU) values based on tissue maps segmented directly from an individual T1 MRI scan of a normal subject. Several T1 MRI scans of normal subjects from the ADNI database were segmented using SPM12 and used to create stereolithography files of different tissues for 3D printing. The attenuation properties of several material blends were investigated, and three suitable formulations were used to print an object expected to have realistic geometry and attenuation properties. A skull was simulated by coating the object with plaster of Paris impregnated bandages. Using two CT scanners, the realism of the phantom was assessed by the measurement of HU values, SPM12 segmentation and comparison with the source data used to create the phantom. Results Realistic relative HU values were measured although a subtraction of 60 was required to obtain equivalence with the expected values (gray matter 32.9–35.8 phantom, 29.9–34.2 literature). Segmentation of images acquired at different kVps/mAs showed excellent agreement with the source data (Dice Similarity Coefficient 0.79 for gray matter). The performance of two scanners with two segmentation methods was compared, with the scanners found to have similar performance and with one segmentation method clearly superior to the other. Conclusion The ability to use 3D printing to create a realistic (in terms of geometry and attenuation properties) head phantom has been demonstrated and used in an initial assessment of CT segmentation accuracy using freely available software developed for MRI.
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Affiliation(s)
- Robin B Holmes
- Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK
| | - Ian S Negus
- Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK
| | - Sophie J Wiltshire
- Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK
| | - Gareth C Thorne
- Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK
| | - Peter Young
- Umea Functional Brain Imaging Center, Umea University, 901 87, Umea, Sweden
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10
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Rajagopalan V, Das A, Zhang L, Hillary F, Wylie GR, Yue GH. Fractal dimension brain morphometry: a novel approach to quantify white matter in traumatic brain injury. Brain Imaging Behav 2020; 13:914-924. [PMID: 29909586 DOI: 10.1007/s11682-018-9892-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Traumatic brain injury (TBI) is the main cause of disability in people younger than 35 in the United States. The mechanisms of TBI are complex resulting in both focal and diffuse brain damage. Fractal dimension (FD) is a measure that can characterize morphometric complexity and variability of brain structure especially white matter (WM) structure and may provide novel insights into the injuries evident following TBI. FD-based brain morphometry may provide information on WM structural changes after TBI that is more sensitive to subtle structural changes post injury compared to conventional MRI measurements. Anatomical and diffusion tensor imaging (DTI) data were obtained using a 3 T MRI scanner in subjects with moderate to severe TBI and in healthy controls (HC). Whole brain WM volume, grey matter volume, cortical thickness, cortical area, FD and DTI metrics were evaluated globally and for the left and right hemispheres separately. A neuropsychological test battery sensitive to cognitive impairment associated with traumatic brain injury was performed. TBI group showed lower structural complexity (FD) bilaterally (p < 0.05). No significant difference in either grey matter volume, cortical thickness or cortical area was observed in any of the brain regions between TBI and healthy controls. No significant differences in whole brain WM volume or DTI metrics between TBI and HC groups were observed. Behavioral data analysis revealed that WM FD accounted for a significant amount of variance in executive functioning and processing speed beyond demographic and DTI variables. FD therefore, may serve as a sensitive marker of injury and may play a role in outcome prediction in TBI.
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Affiliation(s)
- Venkateswaran Rajagopalan
- Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Hyderabad, India.,Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, NJ, 07103, USA
| | - Abhijit Das
- Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, NJ, 07103, USA.,Neuroscience and Neuropsychology Research, Kessler Foundation, 120 Eagle Rock Avenue, East Hanover, NJ, 07936, USA
| | | | - Frank Hillary
- Department of Psychology, Pennsylvania State University, 313 Moore Building, University Park, PA, 16801, USA
| | - Glenn R Wylie
- Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, NJ, 07103, USA.,Neuroscience and Neuropsychology Research, Kessler Foundation, 120 Eagle Rock Avenue, East Hanover, NJ, 07936, USA
| | - Guang H Yue
- Department of Physical Medicine and Rehabilitation, Rutgers New Jersey Medical School, Rutgers, the State University of New Jersey, Newark, NJ, 07103, USA. .,Human Performance and Engineering Research, Kessler Foundation, 1199 Pleasant Valley Way, West Orange, NJ, 07052, USA.
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11
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Green RR, Bigler ED, Froehlich A, Prigge MBD, Zielinski BA, Travers BG, Anderson JS, Alexander A, Lange N, Lainhart JE. Beery VMI and Brain Volumetric Relations in Autism Spectrum Disorder. JOURNAL OF PEDIATRIC NEUROPSYCHOLOGY 2019; 5:77-84. [PMID: 32953403 PMCID: PMC7497806 DOI: 10.1007/s40817-019-00069-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2019] [Revised: 07/20/2019] [Accepted: 08/02/2019] [Indexed: 11/29/2022]
Abstract
Although diminished proficiency on tasks that require visual-motor integration (VMI) has been reported in individuals with autism spectrum disorder (ASD), very few studies have examined the association between VMI performance and neuroanatomical regions of interest (ROI) involved in motor and perceptual functioning. To address these issues, the current study included an all-male sample of 41 ASD (ages 3-23 years) and 27 typically developing (TD) participants (ages 5-26 years) who completed the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI) as part of a comprehensive neuropsychological battery. All participants underwent 3.0 T magnetic resonance imaging (MRI) with image quantification (FreeSurfer software v5.3). The groups were statistically matched on age, handedness, and intracranial volume (ICV). ASD participants performed significantly lower on VMI and IQ measures compared with the TD group. VMI performance was significantly correlated with FSIQ and PIQ in the TD group only. No pre-defined neuroanatomical ROIs were significantly different between groups. Significant correlations were observed in the TD group between VMI and total precentral gyrus gray matter volume (r = .51, p = .006) and total frontal lobe gray matter volume (r = .46, p = .017). There were no significant ROI correlations with Beery VMI performance in ASD participants. At the group level, despite ASD participants exhibiting reduced visuomotor abilities, no systematic relation with motor or sensory-perceptual ROIs was observed. In the TD group, results were consistent with the putative role of the precentral gyrus in motor control along with frontal involvement in planning, organization, and execution monitoring, all essential for VMI performance. Given that similar associations between VMI and ROIs were not observed in those with ASD, neurodevelopment in ASD group participants may not follow homogenous patterns making correlations in these brain regions unlikely to be observed.
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Affiliation(s)
- Ryan R. Green
- Department of Psychology, Brigham Young University, 1001 SWKT, Provo, UT 84602, USA
| | - Erin D. Bigler
- Department of Psychology, Brigham Young University, 1001 SWKT, Provo, UT 84602, USA
- Neuroscience Center, Brigham Young University, Provo, UT, USA
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Alyson Froehlich
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | | | - Brandon A. Zielinski
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
- Department of Pediatrics, University of Utah, Salt Lake City, UT, USA
| | - Brittany G. Travers
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
- Occupational Therapy Program, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Andrew Alexander
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Nicholas Lange
- Departments of Psychiatry and Biostatistics, Harvard University, Boston, MA, USA
- Neurostatistics Laboratory, McLean Hospital, Belmont, MA, USA
| | - Janet E. Lainhart
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
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12
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Sullivan EV, Pfefferbaum A. Brain-behavior relations and effects of aging and common comorbidities in alcohol use disorder: A review. Neuropsychology 2019; 33:760-780. [PMID: 31448945 PMCID: PMC7461729 DOI: 10.1037/neu0000557] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE Alcohol use disorder (AUD) is a complex, dynamic condition that waxes and wanes with unhealthy drinking episodes and varies in drinking patterns and effects on brain structure and function with age. Its excessive use renders chronically heavy drinkers vulnerable to direct alcohol toxicity and a variety of comorbidities attributable to nonalcohol drug misuse, viral infections, and accelerated or premature aging. AUD affects widespread brain systems, commonly, frontolimbic, frontostriatal, and frontocerebellar networks. METHOD AND RESULTS Multimodal assessment using selective neuropsychological testing and whole-brain neuroimaging provides evidence for AUD-related specific brain structure-function relations established with double dissociations. Longitudinal study using noninvasive imaging provides evidence for brain structural and functional improvement with sustained sobriety and further decline with relapse. Functional imaging suggests the possibility that some alcoholics in recovery can compensate for impairment by invoking brain systems typically not used for a target task but that can enable normal-level performance. CONCLUSIONS Evidence for AUD-aging interactions, indicative of accelerated aging, together with increasing alcohol consumption in middle-age and older adults, put aging drinkers at special risk for developing cognitive decline and possibly dementia. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
- Edith V. Sullivan
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA
| | - Adolf Pfefferbaum
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA
- Center for Health Sciences, SRI International, Menlo Park, CA
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13
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Subcortical shape and neuropsychological function among U.S. service members with mild traumatic brain injury. Brain Imaging Behav 2019; 13:377-388. [PMID: 29564659 DOI: 10.1007/s11682-018-9854-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
In a recent manuscript, our group demonstrated shape differences in the thalamus, nucleus accumbens, and amygdala in a cohort of U.S. Service Members with mild traumatic brain injury (mTBI). Given the significant role these structures play in cognitive function, this study directly examined the relationship between shape metrics and neuropsychological performance. The imaging and neuropsychological data from 135 post-deployed United States Service Members from two groups (mTBI and orthopedic injured) were examined. Two shape features modeling local deformations in thickness (RD) and surface area (JD) were defined vertex-wise on parametric mesh-representations of 7 bilateral subcortical gray matter structures. Linear regression was used to model associations between subcortical morphometry and neuropsychological performance as a function of either TBI status or, among TBI patients, subjective reporting of initial concussion severity (CS). Results demonstrated several significant group-by-cognition relationships with shape metrics across multiple cognitive domains including processing speed, memory, and executive function. Higher processing speed was robustly associated with more dilation of caudate surface area among patients with mTBI who reported more than one CS variables (loss of consciousness (LOC), alteration of consciousness (AOC), and/or post-traumatic amnesia (PTA)). These significant patterns indicate the importance of subcortical structures in cognitive performance and support a growing functional neuroanatomical literature in TBI and other neurologic disorders. However, prospective research will be required before exact directional evolution and progression of shape can be understood and utilized in predicting or tracking cognitive outcomes in this patient population.
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14
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Sandbank M, Cascio C. Using a motion-tracking device to facilitate motion control in children with ASD for neuroimaging. Dev Neurorehabil 2019; 22:365-375. [PMID: 30081715 DOI: 10.1080/17518423.2018.1502831] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Purpose: Conducting neurological scans of children with disabilities is difficult because participants exhibit excessive motion. We examined whether a motion-tracking system that combined real-time visual feedback with positive reinforcement and shaping could facilitate motion control in two children with autism spectrum disorder. Methods: Using a modified changing criterion design, we evaluated whether the intervention could facilitate decreases in the participants' range of motion and increases in duration of motion control in a mock scanner. Results: Participants restricted head motion to increasingly smaller distance windows for 2 min. Once participants limited head displacement to 3 mm for 2 min, duration of motion control increased to a range of 7-20 min. Summary-level data from the actual scan suggests increases in motion control generalized outside of the intervention context. Conclusion: This study adds to the limited research on the use of behavioral interventions to increase motion control for neuroimaging in children with disabilities.
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Affiliation(s)
- Micheal Sandbank
- a Special Education Department , The University of Texas at Austin , Austin , TX , USA
| | - Carissa Cascio
- b Department of Psychiatry, Department of Psychology and Human Development, Vanderbilt Brain Institute, Vanderbilt Kennedy Center , Vanderbilt University Medical Center , Nashville , TN , USA
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15
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Loh WY, Anderson PJ, Cheong JLY, Spittle AJ, Chen J, Lee KJ, Molesworth C, Inder TE, Connelly A, Doyle LW, Thompson DK. Longitudinal growth of the basal ganglia and thalamus in very preterm children. Brain Imaging Behav 2019; 14:998-1011. [DOI: 10.1007/s11682-019-00057-z] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
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16
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Santhanam P, Wilson SH, Oakes TR, Weaver LK. Accelerated age-related cortical thinning in mild traumatic brain injury. Brain Behav 2019; 9:e01161. [PMID: 30488646 PMCID: PMC6346670 DOI: 10.1002/brb3.1161] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Revised: 10/11/2018] [Accepted: 10/14/2018] [Indexed: 01/11/2023] Open
Abstract
INTRODUCTION Mild traumatic brain injury (mTBI) can result in many structural abnormalities in the cerebral cortex. While thinning of the cortex has been shown in mTBI patients, there is high regional variability in reported findings. High-resolution imaging can elucidate otherwise unnoticed changes in cortical measures following injury. This study examined age-related patterns of cortical thickness in U.S. active duty service members and veterans with a history of mTBI (n = 66) as compared to a normative population (n = 67). METHODS Using a fully automated cortical parcellation methodology, cortical thickness measures were extracted from 31 bilateral cortical regions for all participants. RESULTS The effect of diagnosis and age on cortical thickness (group × age interaction) was found to be significant (p < 0.05) for many regions, including bilateral parietal and left frontal and temporal cortices. Findings held for a male-only subset, and there was no effect of time since injury in any regions. CONCLUSIONS The presence of mTBI appeared to accelerate age-related cortical thinning across the cortex in our study population.
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Affiliation(s)
| | | | - Terrence R. Oakes
- Madison School of Medicine and Public HealthUniversity of WisconsinMadisonWisconsin
| | - Lindell K. Weaver
- Division of Hyperbaric Medicine Intermountain Medical CenterMurray, UT and Intermountain LDS HospitalSalt Lake CityUtah
- Department of MedicineUniversity of Utah School of MedicineSalt LakeUtah
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17
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Bigler ED. Structural neuroimaging in sport-related concussion. Int J Psychophysiol 2018; 132:105-123. [DOI: 10.1016/j.ijpsycho.2017.09.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 09/03/2017] [Accepted: 09/07/2017] [Indexed: 10/18/2022]
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18
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Bednarz HM, Kana RK. Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders. Neurosci Biobehav Rev 2018; 90:50-69. [PMID: 29608989 DOI: 10.1016/j.neubiorev.2018.03.025] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Revised: 02/26/2018] [Accepted: 03/22/2018] [Indexed: 10/17/2022]
Abstract
Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.
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Affiliation(s)
- Haley M Bednarz
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rajesh K Kana
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA.
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19
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Lalani SJ, Duffield TC, Trontel HG, Bigler ED, Abildskov TJ, Froehlich A, Prigge MBD, Travers BG, Anderson JS, Zielinski BA, Alexander A, Lange N, Lainhart JE. Auditory attention in autism spectrum disorder: An exploration of volumetric magnetic resonance imaging findings. J Clin Exp Neuropsychol 2017; 40:502-517. [PMID: 29072106 DOI: 10.1080/13803395.2017.1373746] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Studies have shown that individuals with autism spectrum disorder (ASD) tend to perform significantly below typically developing individuals on standardized measures of attention, even when controlling for IQ. The current study sought to examine within ASD whether anatomical correlates of attention performance differed between those with average to above-average IQ (AIQ group) and those with low-average to borderline ability (LIQ group) as well as in comparison to typically developing controls (TDC). Using automated volumetric analyses, we examined regional volume of classic attention areas including the superior frontal gyrus, anterior cingulate cortex, and precuneus in ASD AIQ (n = 38) and LIQ (n = 18) individuals along with 30 TDC. Auditory attention performance was assessed using subtests of the Test of Memory and Learning (TOMAL) compared among the groups and then correlated with regional brain volumes. Analyses revealed group differences in attention. The three groups did not differ significantly on any auditory attention-related brain volumes; however, trends toward significant size-attention function interactions were observed. Negative correlations were found between the volume of the precuneus and auditory attention performance for the AIQ ASD group, indicating larger volume related to poorer performance. Implications for general attention functioning and dysfunctional neural connectivity in ASD are discussed.
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Affiliation(s)
- Sanam J Lalani
- a Department of Psychology , Brigham Young University , Provo , UT , USA
| | - Tyler C Duffield
- a Department of Psychology , Brigham Young University , Provo , UT , USA
| | - Haley G Trontel
- a Department of Psychology , Brigham Young University , Provo , UT , USA
| | - Erin D Bigler
- a Department of Psychology , Brigham Young University , Provo , UT , USA.,b Neuroscience Center , Brigham Young University , Provo , UT , USA.,c Department of Psychology , University of Utah , Salt Lake City , UT , USA.,d Department of Pediatrics , University of Utah , Salt Lake City , UT , USA
| | - Tracy J Abildskov
- a Department of Psychology , Brigham Young University , Provo , UT , USA
| | - Alyson Froehlich
- c Department of Psychology , University of Utah , Salt Lake City , UT , USA
| | - Molly B D Prigge
- d Department of Pediatrics , University of Utah , Salt Lake City , UT , USA
| | - Brittany G Travers
- e Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin-Madison , Madison , WI , USA.,f Department of Kinesiology , University of Wisconsin-Madison , Madison , WI , USA
| | - Jeffrey S Anderson
- g Department of Radiology , University of Utah , Salt Lake City , UT , USA
| | - Brandon A Zielinski
- d Department of Pediatrics , University of Utah , Salt Lake City , UT , USA.,h Department of Neurology, School of Medicine , University of Utah , Salt Lake City , UT , USA
| | - Andrew Alexander
- e Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin-Madison , Madison , WI , USA.,i Department of Medical Physics , University of Wisconsin-Madison , Madison , WI , USA.,j Department of Psychiatry , University of Wisconsin-Madison , Madison , WI , USA
| | - Nicholas Lange
- k Department of Psychiatry , Harvard Medical School , Boston , MA , USA.,l Neurostatistics Laboratory , McLean Hospital , Belmont , MA , USA
| | - Janet E Lainhart
- e Waisman Laboratory for Brain Imaging and Behavior , University of Wisconsin-Madison , Madison , WI , USA.,j Department of Psychiatry , University of Wisconsin-Madison , Madison , WI , USA
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20
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Bigler ED, Zielinski BA, Goodrich-Hunsaker N, Black GM, Huff BST, Christiansen Z, Wood DM, Abildskov TJ, Dennis M, Taylor HG, Rubin K, Vannatta K, Gerhardt CA, Stancin T, Yeates KO. The Relation of Focal Lesions to Cortical Thickness in Pediatric Traumatic Brain Injury. J Child Neurol 2016; 31:1302-11. [PMID: 27342577 PMCID: PMC5525324 DOI: 10.1177/0883073816654143] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 05/09/2016] [Indexed: 12/22/2022]
Abstract
In a sample of children with traumatic brain injury, this magnetic resonance imaging (MRI)-based investigation examined whether presence of a focal lesion uniquely influenced cortical thickness in any brain region. Specifically, the study explored the relation of cortical thickness to injury severity as measured by Glasgow Coma Scale score and length of stay, along with presence of encephalomalacia, focal white matter lesions or presence of hemosiderin deposition as a marker of shear injury. For comparison, a group of children without head injury but with orthopedic injury of similar age and sex were also examined. Both traumatic brain injury and orthopedic injury children had normally reduced cortical thickness with age, assumed to reflect neuronal pruning. However, the reductions observed within the traumatic brain injury sample were similar to those in the orthopedic injury group, suggesting that in this sample traumatic brain injury, per se, did not uniquely alter cortical thickness in any brain region at the group level. Injury severity in terms of Glasgow Coma Scale or longer length of stay was associated with greater reductions in frontal and occipitoparietal cortical thickness. However, presence of focal lesions were not related to unique changes in cortical thickness despite having a prominent distribution of lesions within frontotemporal regions among children with traumatic brain injury. Because focal lesions were highly heterogeneous, their association with cortical thickness and development appeared to be idiosyncratic, and not associated with group level effects.
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Affiliation(s)
- Erin D Bigler
- Department of Psychology and the Neuroscience Center, Brigham Young University, Provo, UT, USA Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Brandon A Zielinski
- Departments of Pediatrics and Neurology, University of Utah, Salt Lake City, UT, USA
| | | | - Garrett M Black
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | - B S Trevor Huff
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | | | - Dawn-Marie Wood
- Department of Psychology, Brigham Young University, Provo, UT, USA
| | | | - Maureen Dennis
- Program in Neuroscience & Mental Health, The Hospital for Sick Children, Toronto, Canada Department of Surgery and Department of Psychology, University of Toronto, Toronto, Canada
| | - H Gerry Taylor
- Department of Pediatrics, Case Western Reserve University and Rainbow Babies & Children's Hospital, University Hospitals Case Medical Center, Cleveland, OH, USA
| | - Kenneth Rubin
- Department of Psychology, University of Maryland, College Park, MD, USA
| | - Kathryn Vannatta
- Department of Pediatrics, The Ohio State University, Columbus, OH, USA Center for Behavioral Health, Columbus Children's Research Institute, Columbus, OH, USA
| | - Cynthia A Gerhardt
- Department of Pediatrics, The Ohio State University, Columbus, OH, USA Center for Behavioral Health, Columbus Children's Research Institute, Columbus, OH, USA
| | - Terry Stancin
- Department of Pediatrics, Case Western Reserve University and Rainbow Babies & Children's Hospital, University Hospitals Case Medical Center, Cleveland, OH, USA Department of Psychiatry, MetroHealth Medical Center, Cleveland, OH, USA
| | - Keith Owen Yeates
- Department of Pediatrics, The Ohio State University, Columbus, OH, USA Center for Biobehavioral Health, The Research Institute at Nationwide Children's Hospital, Columbus, OH, USA
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21
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Tate DF, Wade BSC, Velez CS, Drennon AM, Bolzenius J, Gutman BA, Thompson PM, Lewis JD, Wilde EA, Bigler ED, Shenton ME, Ritter JL, York GE. Volumetric and shape analyses of subcortical structures in United States service members with mild traumatic brain injury. J Neurol 2016; 263:2065-79. [PMID: 27435967 PMCID: PMC5564450 DOI: 10.1007/s00415-016-8236-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Revised: 07/07/2016] [Accepted: 07/08/2016] [Indexed: 10/21/2022]
Abstract
Mild traumatic brain injury (mTBI) is a significant health concern. The majority who sustain mTBI recover, although ~20 % continue to experience symptoms that can interfere with quality of life. Accordingly, there is a critical need to improve diagnosis, prognostic accuracy, and monitoring (recovery trajectory over time) of mTBI. Volumetric magnetic resonance imaging (MRI) has been successfully utilized to examine TBI. One promising improvement over standard volumetric approaches is to analyze high-dimensional shape characteristics of brain structures. In this study, subcortical shape and volume in 76 Service Members with mTBI was compared to 59 Service Members with orthopedic injury (OI) and 17 with post-traumatic stress disorder (PTSD) only. FreeSurfer was used to quantify structures from T1-weighted 3 T MRI data. Radial distance (RD) and Jacobian determinant (JD) were defined vertex-wise on parametric mesh-representations of subcortical structures. Linear regression was used to model associations between morphometry (volume and shape), TBI status, and time since injury (TSI) correcting for age, sex, intracranial volume, and level of education. Volumetric data was not significantly different between the groups. JD was significantly increased in the accumbens and caudate and significantly reduced in the thalamus of mTBI participants. Additional significant associations were noted between RD of the amygdala and TSI. Positive trend-level associations between TSI and the amygdala and accumbens were observed, while a negative association was observed for third ventricle. Our findings may aid in the initial diagnosis of mTBI, provide biological targets for functional examination, and elucidate regions that may continue remodeling after injury.
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Affiliation(s)
- David F Tate
- Missouri Institute of Mental Health, University of Missouri, St. Louis, 4633 World Parkway Circle, Berkeley, MO, 63134-3115, USA.
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA.
| | - Benjamin S C Wade
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - Carmen S Velez
- Missouri Institute of Mental Health, University of Missouri, St. Louis, 4633 World Parkway Circle, Berkeley, MO, 63134-3115, USA
| | - Ann Marie Drennon
- Defense and Veterans Brain Injury Centers, San Antonio Military Medical Center, San Antonio, TX, USA
| | - Jacob Bolzenius
- Missouri Institute of Mental Health, University of Missouri, St. Louis, 4633 World Parkway Circle, Berkeley, MO, 63134-3115, USA
| | - Boris A Gutman
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA
| | - Jeffrey D Lewis
- Department of Neurology, Uniformed Services University of the Health Sciences School of Medicine, Bethesda, MD, USA
| | - Elisabeth A Wilde
- Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
- Michael E. DeBakey VA Medical Center, Houston, TX, USA
| | - Erin D Bigler
- Departments of Psychology and Neuroscience, Brigham Young University, Provo, UT, USA
| | - Martha E Shenton
- Psychiatry Neuroimaging Laboratory, Department of Psychiatry and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Brockton Division, VA Boston Healthcare System, Brockton, MA, USA
| | - John L Ritter
- Department of Radiology, Brooke Army Medical Center, San Antonio, TX, USA
| | - Gerald E York
- Alaska Radiology Associates, TBI Imaging and Research, Anchorage, AK, USA
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22
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Bigler ED. Systems Biology, Neuroimaging, Neuropsychology, Neuroconnectivity and Traumatic Brain Injury. Front Syst Neurosci 2016; 10:55. [PMID: 27555810 PMCID: PMC4977319 DOI: 10.3389/fnsys.2016.00055] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Accepted: 06/08/2016] [Indexed: 01/03/2023] Open
Abstract
The patient who sustains a traumatic brain injury (TBI) typically undergoes neuroimaging studies, usually in the form of computed tomography (CT) and magnetic resonance imaging (MRI). In most cases the neuroimaging findings are clinically assessed with descriptive statements that provide qualitative information about the presence/absence of visually identifiable abnormalities; though little if any of the potential information in a scan is analyzed in any quantitative manner, except in research settings. Fortunately, major advances have been made, especially during the last decade, in regards to image quantification techniques, especially those that involve automated image analysis methods. This review argues that a systems biology approach to understanding quantitative neuroimaging findings in TBI provides an appropriate framework for better utilizing the information derived from quantitative neuroimaging and its relation with neuropsychological outcome. Different image analysis methods are reviewed in an attempt to integrate quantitative neuroimaging methods with neuropsychological outcome measures and to illustrate how different neuroimaging techniques tap different aspects of TBI-related neuropathology. Likewise, how different neuropathologies may relate to neuropsychological outcome is explored by examining how damage influences brain connectivity and neural networks. Emphasis is placed on the dynamic changes that occur following TBI and how best to capture those pathologies via different neuroimaging methods. However, traditional clinical neuropsychological techniques are not well suited for interpretation based on contemporary and advanced neuroimaging methods and network analyses. Significant improvements need to be made in the cognitive and behavioral assessment of the brain injured individual to better interface with advances in neuroimaging-based network analyses. By viewing both neuroimaging and neuropsychological processes within a systems biology perspective could represent a significant advancement for the field.
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Affiliation(s)
- Erin D. Bigler
- Department of Psychology, Neuroscience Center, Brigham Young UniversityProvo, UT, USA
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