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Han X, Maharjan S, Chen J, Zhao Y, Qi Y, White LE, Johnson GA, Wang N. High-resolution diffusion magnetic resonance imaging and spatial-transcriptomic in developing mouse brain. Neuroimage 2024; 297:120734. [PMID: 39032791 DOI: 10.1016/j.neuroimage.2024.120734] [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: 01/04/2024] [Revised: 07/06/2024] [Accepted: 07/11/2024] [Indexed: 07/23/2024] Open
Abstract
Brain development is a highly complex process regulated by numerous genes at the molecular and cellular levels. Brain tissue exhibits serial microstructural changes during the development process. High-resolution diffusion magnetic resonance imaging (dMRI) affords a unique opportunity to probe these changes in the developing brain non-destructively. In this study, we acquired multi-shell dMRI datasets at 32 µm isotropic resolution to investigate the tissue microstructure alterations, which we believe to be the highest spatial resolution dMRI datasets obtained for postnatal mouse brains. We adapted the Allen Developing Mouse Brain Atlas (ADMBA) to integrate quantitative MRI metrics and spatial transcriptomics. Diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), and neurite orientation dispersion and density imaging (NODDI) metrics were used to quantify brain development at different postnatal days. We demonstrated that the differential evolutions of fiber orientation distributions contribute to the distinct development patterns in white matter (WM) and gray matter (GM). Furthermore, the genes enriched in the nervous system that regulate brain structure and function were expressed in spatial correlation with age-matched dMRI. This study is the first one providing high-resolution dMRI, including DTI, DKI, and NODDI models, to trace mouse brain microstructural changes in WM and GM during postnatal development. This study also highlighted the genotype-phenotype correlation of spatial transcriptomics and dMRI, which may improve our understanding of brain microstructure changes at the molecular level.
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Affiliation(s)
- Xinyue Han
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA
| | - Jie Chen
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA
| | - Yi Zhao
- Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN, USA
| | - Yi Qi
- Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, USA
| | - Leonard E White
- Department of Neurology, Duke University Medical Center, Durham, NC, USA
| | - G Allan Johnson
- Center for In Vivo Microscopy, Department of Radiology, Duke University, Durham, NC, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA; Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA; Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, USA.
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Zhang C, Cheng M, Zhu Z, Wang K, Moon BF, Shen S, Zhang B, Wang Z, Lu L, Shang H, Qin C, Yang J, Lu Y, Zhang X, Zhao X. Associations between diffusion kurtosis imaging metrics and neurodevelopmental outcomes in neonates with low-grade germinal matrix and intraventricular hemorrhage. Sci Rep 2024; 14:16455. [PMID: 39014184 PMCID: PMC11252380 DOI: 10.1038/s41598-024-67517-5] [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: 01/29/2024] [Accepted: 07/11/2024] [Indexed: 07/18/2024] Open
Abstract
Diffusion Kurtosis Imaging (DKI)-derived metrics are recognized as indicators of maturation in neonates with low-grade germinal matrix and intraventricular hemorrhage (GMH-IVH). However, it is not yet known if these factors are associated with neurodevelopmental outcomes. The objective of this study was to acquire DKI-derived metrics in neonates with low-grade GMH-IVH, and to demonstrate their association with later neurodevelopmental outcomes. In this prospective study, neonates with low-grade GMH-IVH and control neonates were recruited, and DKI were performed between January 2020 and March 2021. These neonates underwent the Bayley Scales of Infant Development test at 18 months of age. Mean kurtosis (MK), radial kurtosis (RK) and gray matter values were measured. Spearman correlation analyses were conducted for the measured values and neurodevelopmental outcome scores. Forty controls (18 males, average gestational age (GA) 30 weeks ± 1.3, corrected GA at MRI scan 38 weeks ± 1) and thirty neonates with low-grade GMH-IVH (13 males, average GA 30 weeks ± 1.5, corrected GA at MRI scan 38 weeks ± 1). Neonates with low-grade GMH-IVH exhibited lower MK and RK values in the PLIC and the thalamus (P < 0.05). The MK value in the thalamus was associated with Mental Development Index (MDI) (r = 0.810, 95% CI 0.695-0.13; P < 0.001) and Psychomotor Development Index (PDI) (r = 0.852, 95% CI 0.722-0.912; P < 0.001) scores. RK value in the caudate nucleus significantly and positively correlated with MDI (r = 0.496, 95% CI 0.657-0.933; P < 0.001) and PDI (r = 0.545, 95% CI 0.712-0.942; P < 0.001) scores. The area under the curve (AUC) were used to assess diagnostic performance of MK and RK in thalamus (AUC = 0.866, 0.787) and caudate nucleus (AUC = 0.833, 0.671) for predicting neurodevelopmental outcomes. As quantitative neuroimaging markers, MK in thalamus and RK in caudate nucleus may help predict neurodevelopmental outcomes in neonates with low-grade GMH-IVH.
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Affiliation(s)
- Chunxiang Zhang
- Harvard Medical School, Boston, MA, USA
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan International Joint Laboratory of Neuroimaging, Zhengzhou University, Zhengzhou, China
| | - Meiying Cheng
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | | | - Kaiyu Wang
- GE Healthcare, MR Research China, Beijing, China
| | | | | | - Bohao Zhang
- Henan International Joint Laboratory of Neuroimaging, Zhengzhou University, Zhengzhou, China
| | - Zihe Wang
- Zhengzhou University, Zhengzhou, China
| | - Lin Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Honglei Shang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Chi Qin
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jinze Yang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Lu
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaoan Zhang
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
- Henan International Joint Laboratory of Neuroimaging, Zhengzhou University, Zhengzhou, China
| | - Xin Zhao
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
- Henan International Joint Laboratory of Neuroimaging, Zhengzhou University, Zhengzhou, China.
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3
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Scaravilli A, Gabusi I, Mari G, Battocchio M, Bosticardo S, Schiavi S, Bender B, Kessler C, Brais B, La Piana R, van de Warrenburg BP, Cosottini M, Timmann D, Daducci A, Schüle R, Synofzik M, Santorelli FM, Cocozza S. An MRI evaluation of white matter involvement in paradigmatic forms of spastic ataxia: results from the multi-center PROSPAX study. J Neurol 2024:10.1007/s00415-024-12505-y. [PMID: 38880819 DOI: 10.1007/s00415-024-12505-y] [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: 05/03/2024] [Revised: 06/04/2024] [Accepted: 06/07/2024] [Indexed: 06/18/2024]
Abstract
BACKGROUND Autosomal Recessive Spastic Ataxia of Charlevoix-Saguenay (ARSACS) and Spastic Paraplegia Type 7 (SPG7) are paradigmatic spastic ataxias (SPAX) with suggested white matter (WM) involvement. Aim of this work was to thoroughly disentangle the degree of WM involvement in these conditions, evaluating both macrostructure and microstructure via the analysis of diffusion MRI (dMRI) data. MATERIAL AND METHODS In this multi-center prospective study, ARSACS and SPG7 patients and Healthy Controls (HC) were enrolled, all undergoing a standardized dMRI protocol and a clinimetrics evaluation including the Scale for the Assessment and Rating of Ataxia (SARA). Differences in terms of WM volume or global microstructural WM metrics were probed, as well as the possible occurrence of a spatially defined microstructural WM involvement via voxel-wise analyses, and its correlation with patients' clinical status. RESULTS Data of 37 ARSACS (M/F = 21/16; 33.4 ± 12.4 years), 37 SPG7 (M/F = 24/13; 55.7 ± 10.7 years), and 29 HC (M/F = 13/16; 42.1 ± 17.2 years) were analyzed. While in SPG7, only a mild mean microstructural damage was found compared to HC, ARSACS patients present a severe WM involvement, with a reduced global volume (p < 0.001), an alteration of all microstructural metrics (all with p < 0.001), without a spatially defined pattern of damage but with a prominent involvement of commissural fibers. Finally, in ARSACS, a correlation between microstructural damage and SARA scores was found (p = 0.004). CONCLUSION In ARSACS, but not SPG7 patients, we observed a complex and multi-faced involvement of brain WM, with a clinically meaningful widespread loss of axonal and dendritic integrity, secondary demyelination and, overall, a reduction in cellularity and volume.
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Affiliation(s)
- Alessandra Scaravilli
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy
| | - Ilaria Gabusi
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Gaia Mari
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Matteo Battocchio
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Sara Bosticardo
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Simona Schiavi
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University of Tübingen, Tübingen, Germany
| | - Christoph Kessler
- Center for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Bernard Brais
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Roberta La Piana
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
- Department of Diagnostic Radiology, McGill University, Montreal, Canada
| | - Bart P van de Warrenburg
- Department of Neurology, Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mirco Cosottini
- Department of Translational Research on New Technologies in Medicine and Surgery, University of Pisa, Pisa, Italy
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, Essen, Germany
| | - Alessandro Daducci
- Department of Computer Science, Diffusion Imaging and Connectivity Estimation (DICE) Lab, University of Verona, Verona, Italy
| | - Rebecca Schüle
- Center for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division of Neurodegenerative Diseases, Department of Neurology, Heidelberg University Hospital and Faculty of Medicine, Heidelberg, Germany
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Center for Neurology and Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | | | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via Pansini 5, 80131, Naples, Italy.
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Nair AK, Adluru N, Finley AJ, Gresham LK, Skinner SE, Alexander AL, Davidson RJ, Ryff CD, Schaefer SM. Purpose in life as a resilience factor for brain health: diffusion MRI findings from the Midlife in the U.S. study. Front Psychiatry 2024; 15:1355998. [PMID: 38505799 PMCID: PMC10948414 DOI: 10.3389/fpsyt.2024.1355998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/09/2024] [Indexed: 03/21/2024] Open
Abstract
Introduction A greater sense of purpose in life is associated with several health benefits relevant for active aging, but the mechanisms remain unclear. We evaluated if purpose in life was associated with indices of brain health. Methods We examined data from the Midlife in the United States (MIDUS) Neuroscience Project. Diffusion weighted magnetic resonance imaging data (n=138; mean age 65.2 years, age range 48-95; 80 females; 37 black, indigenous, and people of color) were used to estimate microstructural indices of brain health such as axonal density, and axonal orientation. The seven-item purpose in life scale was used. Permutation analysis of linear models was used to examine associations between purpose in life scores and the diffusion metrics in white matter and in the bilateral hippocampus, adjusting for age, sex, education, and race. Results and discussion Greater sense of purpose in life was associated with brain microstructural features consistent with better brain health. Positive associations were found in both white matter and the right hippocampus, where multiple convergent associations were detected. The hippocampus is a brain structure involved in learning and memory that is vulnerable to stress but retains the capacity to grow and adapt through old age. Our findings suggest pathways through which an enhanced sense of purpose in life may contribute to better brain health and promote healthy aging. Since purpose in life is known to decline with age, interventions and policy changes that facilitate a greater sense of purpose may extend and improve the brain health of individuals and thus improve public health.
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Affiliation(s)
- Ajay Kumar Nair
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Anna J. Finley
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Lauren K. Gresham
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Sarah E. Skinner
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, United States
| | - Richard J. Davidson
- Center for Healthy Minds, University of Wisconsin-Madison, Madison, WI, United States
| | - Carol D. Ryff
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Stacey M. Schaefer
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
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Weaver JM, DiPiero M, Rodrigues PG, Cordash H, Davidson RJ, Planalp EM, Dean DC. Automated motion artifact detection in early pediatric diffusion MRI using a convolutional neural network. IMAGING NEUROSCIENCE (CAMBRIDGE, MASS.) 2023; 1:10.1162/imag_a_00023. [PMID: 38344118 PMCID: PMC10854394 DOI: 10.1162/imag_a_00023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
Diffusion MRI (dMRI) is a widely used method to investigate the microstructure of the brain. Quality control (QC) of dMRI data is an important processing step that is performed prior to analysis using models such as diffusion tensor imaging (DTI) or neurite orientation dispersion and density imaging (NODDI). When processing dMRI data from infants and young children, where intra-scan motion is common, the identification and removal of motion artifacts is of the utmost importance. Manual QC of dMRI data is (1) time-consuming due to the large number of diffusion directions, (2) expensive, and (3) prone to subjective errors and observer variability. Prior techniques for automated dMRI QC have mostly been limited to adults or school-age children. Here, we propose a deep learning-based motion artifact detection tool for dMRI data acquired from infants and toddlers. The proposed framework uses a simple three-dimensional convolutional neural network (3DCNN) trained and tested on an early pediatric dataset of 2,276 dMRI volumes from 121 exams acquired at 1 month and 24 months of age. An average classification accuracy of 95% was achieved following four-fold cross-validation. A second dataset with different acquisition parameters and ages ranging from 2-36 months (consisting of 2,349 dMRI volumes from 26 exams) was used to test network generalizability, achieving 98% classification accuracy. Finally, to demonstrate the importance of motion artifact volume removal in a dMRI processing pipeline, the dMRI data were fit to the DTI and NODDI models and the parameter maps were compared with and without motion artifact removal.
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Affiliation(s)
- Jayse Merle Weaver
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Marissa DiPiero
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin–Madison, Madison, WI, United States
| | | | - Hassan Cordash
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Richard J. Davidson
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Psychology, University of Wisconsin–Madison, Madison, WI, United States
- Center for Healthy Minds, University of Wisconsin–Madison, Madison WI, United States
- Department of Psychiatry, University of Wisconsin–Madison, Madison, WI, United States
| | - Elizabeth M. Planalp
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Medicine, University of Wisconsin–Madison, Madison, WI, United States
| | - Douglas C. Dean
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Pediatrics, University of Wisconsin–Madison, Madison, WI, United States
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Wang X, Wang Y, Gao D, Zhao Z, Wang H, Wang S, Liu S. Characterizing the penumbras of white matter hyperintensities in patients with cerebral small vessel disease. Jpn J Radiol 2023; 41:928-937. [PMID: 37160589 PMCID: PMC10468925 DOI: 10.1007/s11604-023-01419-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 03/24/2023] [Indexed: 05/11/2023]
Abstract
PURPOSE The white matter hyperintensity penumbra (WMH-P) is the subtly changed normal-appearing white matter (NAWM) that surrounds white matter hyperintensities (WMHs). The goal of this study was to define WMH-P in cerebral small vessel disease (CSVD) by arterial spin labeling (ASL) and diffusion tensor imaging (DTI)/diffusion kurtosis imaging (DKI). MATERIALS AND METHODS We prospectively analyzed 42 patients with CSVD. To determine the range of cerebral blood flow (CBF) and DTI/DKI penumbras around white matter hyperintensities, we generated NAWM layer masks from periventricular WMHs (PVWMHs) and deep WMHs (DWMHs). Mean values of CBF, fractional anisotropy, mean diffusivity, axial diffusivity, radial diffusivity, mean kurtosis, axial kurtosis, and radial kurtosis within the WMHs and their corresponding NAWM layer masks were analyzed. Paired sample t tests were used for analysis, and differences were considered statistically significant if the associated p value was ≤ 0.05. RESULTS For DWMHs, the CBF penumbras were 13 mm, and the DTI/DKI penumbras were 8 mm. For PVWMHs, the CBF penumbras were 14 mm, and the DTI/DKI penumbras were 14 mm. CONCLUSIONS Our findings revealed that DTI/DKI and ASL can show structural and blood flow changes in brain tissue surrounding WMHs. In DWMHs, the blood flow penumbra was larger than the structural penumbra, while in PVWMHs, the blood flow penumbra was almost the same as the structural penumbra.
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Affiliation(s)
- Xin Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China.
| | - Yu Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Deyu Gao
- North China University of Technology, Tangshan City, 063000, Hebei Province, China
| | - Zhichao Zhao
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Haiping Wang
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Sujie Wang
- Department of Neurology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
| | - Shiguang Liu
- Department of Radiology, Tangshan Gongren Hospital, 27 Wenhua Road, Tangshan City, 063000, Hebei Province, China
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Lima Santos JP, Jia-Richards M, Kontos AP, Collins MW, Versace A. Emotional Regulation and Adolescent Concussion: Overview and Role of Neuroimaging. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6274. [PMID: 37444121 PMCID: PMC10341732 DOI: 10.3390/ijerph20136274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 06/16/2023] [Accepted: 06/29/2023] [Indexed: 07/15/2023]
Abstract
Emotional dysregulation symptoms following a concussion are associated with an increased risk for emotional dysregulation disorders (e.g., depression and anxiety), especially in adolescents. However, predicting the emergence or worsening of emotional dysregulation symptoms after concussion and the extent to which this predates the onset of subsequent psychiatric morbidity after injury remains challenging. Although advanced neuroimaging techniques, such as functional magnetic resonance imaging and diffusion magnetic resonance imaging, have been used to detect and monitor concussion-related brain abnormalities in research settings, their clinical utility remains limited. In this narrative review, we have performed a comprehensive search of the available literature regarding emotional regulation, adolescent concussion, and advanced neuroimaging techniques in electronic databases (PubMed, Scopus, and Google Scholar). We highlight clinical evidence showing the heightened susceptibility of adolescents to experiencing emotional dysregulation symptoms following a concussion. Furthermore, we describe and provide empirical support for widely used magnetic resonance imaging modalities (i.e., functional and diffusion imaging), which are utilized to detect abnormalities in circuits responsible for emotional regulation. Additionally, we assess how these abnormalities relate to the emotional dysregulation symptoms often reported by adolescents post-injury. Yet, it remains to be determined if a progression of concussion-related abnormalities exists, especially in brain regions that undergo significant developmental changes during adolescence. We conclude that neuroimaging techniques hold potential as clinically useful tools for predicting and, ultimately, monitoring the treatment response to emotional dysregulation in adolescents following a concussion.
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Affiliation(s)
- João Paulo Lima Santos
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
| | - Meilin Jia-Richards
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
| | - Anthony P. Kontos
- Department of Orthopaedic Surgery, UPMC Sports Concussion Program, University of Pittsburgh, Pittsburgh, PA 15213, USA; (A.P.K.); (M.W.C.)
| | - Michael W. Collins
- Department of Orthopaedic Surgery, UPMC Sports Concussion Program, University of Pittsburgh, Pittsburgh, PA 15213, USA; (A.P.K.); (M.W.C.)
| | - Amelia Versace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA; (M.J.-R.); (A.V.)
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