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Mathew D, Purohit P, Gadwal A, Anil A, Sharma RK, Meshram VP, Setia P. Integrated Assessment of GFAP and UCH-L1 for their utility in severity assessment and outcome prediction in Traumatic Brain Injury. Int J Legal Med 2024; 138:2559-2568. [PMID: 38977505 DOI: 10.1007/s00414-024-03287-z] [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: 09/12/2023] [Accepted: 07/01/2024] [Indexed: 07/10/2024]
Abstract
OBJECTIVES This study aimed to explore the potential of glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase-L1 (UCH-L1) as biomarkers for diagnosis and prognosis in mild and severe TBI cases, including TBI-related deaths. METHODS This prospective cohort study includes 40 cases each of mild, severe, fatal TBI cases, and 40 healthy controls. Serum samples were collected from live patients at 8 and 20 h post injury for UCH-L1 and GFAP respectively, and from deceased patients within 6 h of death. RESULTS Elevated levels of both GFAP and UCH-L1 were observed in patients with severe and fatal TBI cases. These biomarkers exhibited promising potential for predicting various Glasgow Outcome Scale Extended (GOSE) categories. Combining GFAP and UCH-L1 yielded higher predictive accuracy both for diagnosis and prognosis in TBI cases. The study additionally established specific cut-off levels for GFAP and UCH-L1 stratified according to the severity and prognosis. CONCLUSION GFAP and UCH-L1 individually demonstrated moderate to good discrimination capacity in predicting TBI severity and functional outcomes. However, combining these biomarkers is recommended for improved diagnostic and prognostic utility. This precision tool can enhance patient care, enabling tailored treatment plans, ultimately reducing morbidity and mortality rates in TBI cases.
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Affiliation(s)
- Deepu Mathew
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Purvi Purohit
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Ashita Gadwal
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Abhishek Anil
- Department of Pharmacology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Raghavendra Kumar Sharma
- Department of Neurosurgery, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Vikas P Meshram
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India
| | - Puneet Setia
- Department of Forensic Medicine and Toxicology, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India.
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2
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Hacker BJ, Imms PE, Dharani AM, Zhu J, Chowdhury NF, Chaudhari NN, Irimia A. Identification and Connectomic Profiling of Concussion Using Bayesian Machine Learning. J Neurotrauma 2024; 41:1883-1900. [PMID: 38482793 DOI: 10.1089/neu.2023.0509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/30/2024] Open
Abstract
Accurate early diagnosis of concussion is useful to prevent sequelae and improve neurocognitive outcomes. Early after head impact, concussion diagnosis may be doubtful in persons whose neurological, neuroradiological, and/or neurocognitive examinations are equivocal. Such individuals can benefit from novel accurate assessments that complement clinical diagnostics. We introduce a Bayesian machine learning classifier to identify concussion through cortico-cortical connectome mapping from magnetic resonance imaging in persons with quasi-normal cognition and without neuroradiological findings. Classifier features are generated from connectivity matrices specifying the mean fractional anisotropy of white matter connections linking brain structures. Each connection's saliency to classification was quantified by training individual classifier instantiations using a single feature type. The classifier was tested on a discovery sample of 92 healthy controls (HCs; 26 females, age μ ± σ: 39.8 ± 15.5 years) and 471 adult mTBI patients (158 females, age μ ± σ: 38.4 ± 5.9 years). Results were replicated in an independent validation sample of 256 HCs (149 females, age μ ± σ: 55.3 ± 12.1 years) and 126 patients with concussion (46 females, age μ ± σ: 39.0 ± 17.7 years). Classifier accuracy exceeds 99% in both samples, suggesting robust generalizability to new samples. Notably, 13 bilateral cortico-cortical connection pairs predict diagnostic status with accuracy exceeding 99% in both discovery and validation samples. Many such connection pairs are between prefrontal cortex structures, fronto-limbic and fronto-subcortical structures, and occipito-temporal structures in the ventral ("what") visual stream. This and related connectivity form a highly salient network of brain connections that is particularly vulnerable to concussion. Because these connections are important in mediating cognitive control, memory, and attention, our findings explain the high frequency of cognitive disturbances after concussion. Our classifier was trained and validated on concussed participants with cognitive profiles very similar to those of HCs. This suggests that the classifier can complement current diagnostics by providing independent information in clinical contexts where patients have quasi-normal cognition but where concussion diagnosis stands to benefit from additional evidence.
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Affiliation(s)
- Benjamin J Hacker
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Mork Family Department of Chemical Engineering and Materials Science, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Phoebe E Imms
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Ammar M Dharani
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Jessica Zhu
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Nahian F Chowdhury
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Nikhil N Chaudhari
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
| | - Andrei Irimia
- Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Corwin D. Denney Research Center, Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
- Department of Quantitative and Computational Biology, Dana and David Dornsife College of Arts and Sciences, University of Southern California, Los Angeles, California, USA
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Khaladkar SM, Julakanti S, Paidlewar S, Pandey A. Isolated Partial Absence of the Septum Pellucidum: A Case Report. Cureus 2024; 16:e67604. [PMID: 39310572 PMCID: PMC11416805 DOI: 10.7759/cureus.67604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2024] [Accepted: 08/23/2024] [Indexed: 09/25/2024] Open
Abstract
The septum pellucidum is an important thin, membranous structure in the brain that separates the anterior horns of the lateral ventricles, essential for maintaining brain anatomy and function. Here, we describe a case of a 38-year-old male with a 20-year history of seizures, occurring approximately three to four times annually and lasting 30 minutes to one hour per episode, who presented with a recent seizure three days prior. Magnetic resonance imaging (MRI) of the brain revealed an absence of the septum pellucidum in its posterior portion, mild prominence of both lateral ventricles, and an abnormal course of the crura of the fornix, leading to a diagnosis of partial absence of the septum pellucidum. This case underscores the importance of comprehensive neuroimaging in detecting structural brain anomalies, which is crucial for effective diagnosis, management, and improving patient outcomes, particularly in long-standing seizure disorders.
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Affiliation(s)
- Sanjay M Khaladkar
- Radiodiagnosis, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pune, IND
| | - Sravya Julakanti
- Radiodiagnosis, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pune, IND
| | - Sayali Paidlewar
- Radiodiagnosis, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pune, IND
| | - Ankita Pandey
- Radiodiagnosis, Dr. D. Y. Patil Medical College, Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University), Pune, IND
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Beard K, Gauff AK, Pennington AM, Marion DW, Smith J, Sloley S. Biofluid, Imaging, Physiological, and Functional Biomarkers of Mild Traumatic Brain Injury and Subconcussive Head Impacts. J Neurotrauma 2024. [PMID: 38943278 DOI: 10.1089/neu.2024.0136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2024] Open
Abstract
Post-concussive symptoms are frequently reported by individuals who sustain mild traumatic brain injuries (mTBIs) and subconcussive head impacts, even when evidence of intracranial pathology is lacking. Current strategies used to evaluate head injuries, which primarily rely on self-report, have a limited ability to predict the incidence, severity, and duration of post-concussive symptoms that will develop in an individual patient. In addition, these self-report measures have little association with the underlying mechanisms of pathology that may contribute to persisting symptoms, impeding advancement in precision treatment for TBI. Emerging evidence suggests that biofluid, imaging, physiological, and functional biomarkers associated with mTBI and subconcussive head impacts may address these shortcomings by providing more objective measures of injury severity and underlying pathology. Interest in the use of biomarker data has rapidly accelerated, which is reflected by the recent efforts of organizations such as the National Institute of Neurological Disorders and Stroke and the National Academies of Sciences, Engineering, and Medicine to prioritize the collection of biomarker data during TBI characterization in acute-care settings. Thus, this review aims to describe recent progress in the identification and development of biomarkers of mTBI and subconcussive head impacts and to discuss important considerations for the implementation of these biomarkers in clinical practice.
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Affiliation(s)
- Kryshawna Beard
- General Dynamics Information Technology Fairfax, Falls Church, Virginia, USA
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
| | - Amina K Gauff
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
- Xynergie Federal, LLC, San Juan, United States Minor Outlying Islands
| | - Ashley M Pennington
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
- Xynergie Federal, LLC, San Juan, United States Minor Outlying Islands
| | - Donald W Marion
- General Dynamics Information Technology Fairfax, Falls Church, Virginia, USA
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
| | - Johanna Smith
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
| | - Stephanie Sloley
- Traumatic Brain Injury Center of Excellence, Silver Spring, Maryland, USA
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5
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Zibetti M, Di Resta C, Banfi G, Tomaiuolo R. Value-Based Health Care Implementation: The Case Study of mTBI Biomarkers. J Pers Med 2024; 14:634. [PMID: 38929855 PMCID: PMC11204511 DOI: 10.3390/jpm14060634] [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: 05/15/2024] [Revised: 06/09/2024] [Accepted: 06/11/2024] [Indexed: 06/28/2024] Open
Abstract
Traumatic brain injury is a significant global health issue, affecting approximately 69 million people annually. Early diagnosis is crucial for effective management, and biomarkers provide a promising approach to identifying traumatic brain injury in various settings. This study investigates the perceived usefulness of biomarker testing in two distinct contexts: emergency departments and sports settings. Comprehensive interviews were conducted among healthcare professionals in emergency departments and sports-related medical staff. The interviews assessed their perceptions of the diagnostic accuracy, practicality, and overall value of traumatic brain injury biomarker testing. The findings indicate that the perceived usefulness of biomarker testing is high among professionals in both settings. However, significant differences emerged in the perceived barriers to implementation, with emergency department staff citing logistical issues and sports professionals expressing cost concerns. Addressing identified barriers could enhance the adoption and effectiveness of these tests, ultimately improving patient outcomes. Future research should focus on optimizing testing protocols and reducing implementation challenges. This study aims to evaluate the implementation of mild traumatic brain injury biomarkers within the framework of value-based health care, focusing on diagnostic accuracy and patient outcomes.
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Affiliation(s)
- Martina Zibetti
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
| | - Chiara Di Resta
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
| | - Giuseppe Banfi
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
- IRCCS Galeazzi-Sant’Ambrogio, 20157 Milan, Italy
| | - Rossella Tomaiuolo
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
- IRCCS Galeazzi-Sant’Ambrogio, 20157 Milan, Italy
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6
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Hibi A, Cusimano MD, Bilbily A, Krishnan RG, Tyrrell PN. Development of a Multimodal Machine Learning-Based Prognostication Model for Traumatic Brain Injury Using Clinical Data and Computed Tomography Scans: A CENTER-TBI and CINTER-TBI Study. J Neurotrauma 2024; 41:1323-1336. [PMID: 38279813 DOI: 10.1089/neu.2023.0446] [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: 01/29/2024] Open
Abstract
Computed tomography (CT) is an important imaging modality for guiding prognostication in patients with traumatic brain injury (TBI). However, because of the specialized expertise necessary, timely and dependable TBI prognostication based on CT imaging remains challenging. This study aimed to enhance the efficiency and reliability of TBI prognostication by employing machine learning (ML) techniques on CT images. A retrospective analysis was conducted on the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) data set (n = 1016). An ML-driven binary classifier was developed to predict favorable or unfavorable outcomes at 6 months post-injury. The prognostic performance was assessed using the area under the curve (AUC) over fivefold cross-validation and compared with conventional models that depend on clinical variables and CT scoring systems. An external validation was performed using the Comparative Indian Neurotrauma Effectiveness Research in Traumatic Brain Injury (CINTER-TBI) data set (n = 348). The developed model achieved superior performance without the necessity for manual CT assessments (AUC = 0.846 [95% CI: 0.843-0.849]) compared with the model based on the clinical and laboratory variables (AUC = 0.817 [95% CI: 0.814-0.820]) and established CT scoring systems requiring manual interpretations (AUC = 0.829 [95% CI: 0.826-0.832] for Marshall and 0.838 [95% CI: 0.835-0.841] for International Mission for Prognosis and Analysis of Clinical Trials in TBI [IMPACT]). The external validation demonstrated the prognostic capacity of the developed model to be significantly better (AUC = 0.859 [95% CI: 0.857-0.862]) than the model using clinical variables (AUC = 0.809 [95% CI: 0.798-0.820]). This study established an ML-based model that provides efficient and reliable TBI prognosis based on CT scans, with potential implications for earlier intervention and improved patient outcomes.
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Affiliation(s)
- Atsuhiro Hibi
- Institute of Medical Science, Departments of University of Toronto, Toronto, Ontario, Canada
- Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Michael D Cusimano
- Institute of Medical Science, Departments of University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Alexander Bilbily
- Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Rahul G Krishnan
- Computer Science, University of Toronto, Toronto, Ontario, Canada
- Laboratory Medicine and Pathobiology, and University of Toronto, Toronto, Ontario, Canada
| | - Pascal N Tyrrell
- Institute of Medical Science, Departments of University of Toronto, Toronto, Ontario, Canada
- Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
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7
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Esterov D, Yin Z, Persaud T, Shan X, Murphy MC, Ehman RL, Huston J, Brown AW. Association Between Anatomic and Clinical Indicators of Injury Severity After Moderate-Severe Traumatic Brain Injury: A Pilot Study Using Multiparametric Magnetic Resonance Imaging. Neurotrauma Rep 2024; 5:232-242. [PMID: 38524727 PMCID: PMC10960168 DOI: 10.1089/neur.2023.0122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024] Open
Abstract
This study sought to identify whether an anatomical indicator of injury severity as measured by multiparametric magnetic resonance imaging (MRI) including magnetic resonance elastography (MRE), is predictive of a clinical measure of injury severity after moderate-severe traumatic brain injury (TBI). Nine individuals who were admitted to acute inpatient rehabilitation after moderate-to-severe TBI completed a comprehensive MRI protocol prior to discharge from rehabilitation, which included conventional MRI with diffusion tensor imaging (DTI). Of those, five of nine also underwent brain MRE to measure the brain parenchyma stiffness. Clinical severity of injury was measured by the length of post-traumatic amnesia (PTA). MRI-assessed non-hemorrhage contusion score and hemorrhage score, DTI-measured white matter fractional anisotropy, and MRE-measured lesion stiffness were all assessed. A higher hemorrhagic score was significantly associated with a longer length of PTA (p = 0.026). Participants with a longer PTA tended to have a higher non-hemorrhage contusion score and softer contusion lesions than the contralateral control side, although the small sample size did not allow for assessment of a significant association. To our knowledge, this is the first report applying MRI/MRE imaging protocol to quantitate altered brain anatomy after moderate-severe TBI and its association with PTA, a known clinical predictor of post-acute outcome. Future larger studies could lead to the development of prediction models that integrate clinical data with anatomical (MRI), structural (DTI), and mechanical (MRE) changes caused by TBI, to inform prognosis and care planning.
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Affiliation(s)
- Dmitry Esterov
- Department of Physical Medicine and Rehabilitation, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Ziying Yin
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Trevor Persaud
- Department of Mayo Clinic School of Graduate Medical Education, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Xiang Shan
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Mathew C. Murphy
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Richard L. Ehman
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - John Huston
- Department of Radiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
| | - Allen W. Brown
- Department of Physical Medicine and Rehabilitation, Mayo Clinic College of Medicine, Rochester, Minnesota, USA
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Bhomia M, Feng Y, Deleon P, Robertson CS, Kobeissy F, Wang KK, Knollmann-Ritschel B. Transcriptomic Signatures of Neuronally Derived Extracellular Vesicles Reveal the Presence of Olfactory Receptors in Clinical Samples from Traumatic Brain Injury Patients. Int J Mol Sci 2024; 25:2777. [PMID: 38474024 PMCID: PMC10931597 DOI: 10.3390/ijms25052777] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 03/14/2024] Open
Abstract
Traumatic brain injury (TBI) is defined as an injury to the brain by external forces which can lead to cellular damage and the disruption of normal central nervous system functions. The recently approved blood-based biomarkers GFAP and UCH-L1 can only detect injuries which are detectable on CT, and are not sensitive enough to diagnose milder injuries or concussion. Exosomes are small microvesicles which are released from the cell as a part of extracellular communication in normal as well as diseased states. The objective of this study was to identify the messenger RNA content of the exosomes released by injured neurons to identify new potential blood-based biomarkers for TBI. Human severe traumatic brain injury samples were used for this study. RNA was isolated from neuronal exosomes and total transcriptomic sequencing was performed. RNA sequencing data from neuronal exosomes isolated from serum showed mRNA transcripts of several neuronal genes. In particular, mRNAs of several olfactory receptor genes were present at elevated concentrations in the neuronal exosomes. Some of these genes were OR10A6, OR14A2, OR6F1, OR1B1, and OR1L1. RNA sequencing data from exosomes isolated from CSF showed a similar elevation of these olfactory receptors. We further validated the expression of these samples in serum samples of mild TBI patients, and a similar up-regulation of these olfactory receptors was observed. The data from these experiments suggest that damage to the neurons in the olfactory neuroepithelium as well as in the brain following a TBI may cause the release of mRNA from these receptors in the exosomes. Hence, olfactory receptors can be further explored as biomarkers for the diagnosis of TBI.
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Affiliation(s)
- Manish Bhomia
- Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA; (Y.F.); (P.D.); (B.K.-R.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817, USA
| | - Yanru Feng
- Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA; (Y.F.); (P.D.); (B.K.-R.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817, USA
| | - Piper Deleon
- Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA; (Y.F.); (P.D.); (B.K.-R.)
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20817, USA
| | | | - Firas Kobeissy
- Department of Neurobiology, Morehouse School of Medicine, Atlanta, GA 30310, USA; (F.K.); (K.K.W.)
| | - Kevin K. Wang
- Department of Neurobiology, Morehouse School of Medicine, Atlanta, GA 30310, USA; (F.K.); (K.K.W.)
| | - Barbara Knollmann-Ritschel
- Department of Pathology, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA; (Y.F.); (P.D.); (B.K.-R.)
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9
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Hazwani T, Khalifa AM, Azzubi M, Alhammad A, Aloboudi A, Jorya A, Alkhuraiji A, Alhelabi S, Shaheen N. Diffuse axonal injury on magnetic resonance imaging and its relation to neurological outcomes in pediatric traumatic brain injury. Clin Neurol Neurosurg 2024; 237:108166. [PMID: 38364490 DOI: 10.1016/j.clineuro.2024.108166] [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: 10/12/2023] [Revised: 02/04/2024] [Accepted: 02/05/2024] [Indexed: 02/18/2024]
Abstract
OBJECTIVE Diffuse axonal injury (DAI), a frequent consequence of pediatric traumatic brain injury (TBI), presents challenges in predicting long-term recovery. This study investigates the relationship between the severity of DAI and neurological outcomes in children. METHODS We conducted a retrospective analysis of 51 pediatric TBI patients diagnosed with DAI using Adam's classification. Neurological function was assessed at 2, 3, and 6 weeks, and 12 months post-injury using the Pediatric Glasgow Outcome Scale-Extended (PGOSE). RESULTS PGOSE scores significantly improved over time across all DAI grades, suggesting substantial recovery potential even in initially severe cases. Despite indicating extensive injury, patients with DAI grades II and III demonstrated significant improvement, achieving a good recovery by 12 months. Although the initial Glasgow Coma Scale (GCS) score did not show a statistically significant association with long-term outcomes in our limited sample, these findings suggest that the severity of DAI alone may not fully predict eventual recovery. CONCLUSIONS Our study highlights the potential for significant neurological recovery in pediatric patients with DAI, emphasizing the importance of long-term follow-up and individualized rehabilitation programs. Further research with larger cohorts and extended follow-up periods is crucial to refine our understanding of the complex relationships between DAI severity, injury mechanisms, and long-term neurological outcomes in children.
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Affiliation(s)
- Tarek Hazwani
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; Department of Pediatrics, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
| | - Ahmed M Khalifa
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; Department of Pediatrics, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia.
| | - Moutasem Azzubi
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; Division of Neurosurgery, Department of Pediatric Surgery, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
| | - Abdullah Alhammad
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; Department of Medical Imaging, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
| | - Abdullah Aloboudi
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; Department of Medical Imaging, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
| | - Ahmad Jorya
- King Abdullah International Medical Research Center, Riyadh, Saudi Arabia; Department of Pediatrics, Ministry of National Guard - Health Affairs, Riyadh, Saudi Arabia
| | - Arwa Alkhuraiji
- College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Sarah Alhelabi
- College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
| | - Naila Shaheen
- King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia; Department of Biostatistics and Bioinformatics, King Abdullah International Medical Research Center, Riyadh, Saudi Arabia
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10
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Alanezi ST, Almutairi WM, Cronin M, Gobbo O, O'Mara SM, Sheppard D, O'Connor WT, Gilchrist MD, Kleefeld C, Colgan N. Whole-brain traumatic controlled cortical impact to the left frontal lobe: Magnetic resonance image-based texture analysis. J Neuropathol Exp Neurol 2024; 83:94-106. [PMID: 38164986 DOI: 10.1093/jnen/nlad110] [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: 01/03/2024] Open
Abstract
This research assesses the capability of texture analysis (TA) derived from high-resolution (HR) T2-weighted magnetic resonance imaging to identify primary sequelae following 1-5 hours of controlled cortical impact mild or severe traumatic brain injury (TBI) to the left frontal cortex (focal impact) and secondary (diffuse) sequelae in the right frontal cortex, bilateral corpus callosum, and hippocampus in rats. The TA technique comprised first-order (histogram-based) and second-order statistics (including gray-level co-occurrence matrix, gray-level run length matrix, and neighborhood gray-level difference matrix). Edema in the left frontal impact region developed within 1 hour and continued throughout the 5-hour assessments. The TA features from HR images confirmed the focal injury. There was no significant difference among radiomics features between the left and right corpus callosum or hippocampus from 1 to 5 hours following a mild or severe impact. The adjacent corpus callosum region and the distal hippocampus region (s), showed no diffuse injury 1-5 hours after mild or severe TBI. These results suggest that combining HR images with TA may enhance detection of early primary and secondary sequelae following TBI.
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Affiliation(s)
- Saleh T Alanezi
- Physics Department, Faculty of Science, Northern Border University, ArAr, Saudi Arabia
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
| | - Waleed M Almutairi
- Medical Imaging Department, King Abdullah bin Abdulaziz University Hospital, Riyadh, Saudi Arabia
- Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Michelle Cronin
- Conway Institute, University College Dublin, Belfield, Dublin, Ireland
| | - Oliviero Gobbo
- School of Pharmacy and Pharmaceutical Sciences & Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Shane M O'Mara
- Institute of Neuroscience, Trinity College, Dublin, Ireland
| | - Declan Sheppard
- Department of Radiology, University Hospital Galway, Galway, Ireland
| | - William T O'Connor
- University of Limerick School of Medicine, Castletroy, Limerick, Ireland
| | - Michael D Gilchrist
- School of Mechanical & Materials Engineering, University College Dublin, Belfield, Dublin, Ireland
| | - Christoph Kleefeld
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
| | - Niall Colgan
- School of Natural Sciences, College of Science and Engineering, University of Galway, Galway, Ireland
- Department of Engineering, Technological University of the Shannon, Athlone, Ireland
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11
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Wang LLW, Gao Y, Chandran Suja V, Boucher ML, Shaha S, Kapate N, Liao R, Sun T, Kumbhojkar N, Prakash S, Clegg JR, Warren K, Janes M, Park KS, Dunne M, Ilelaboye B, Lu A, Darko S, Jaimes C, Mannix R, Mitragotri S. Preclinical characterization of macrophage-adhering gadolinium micropatches for MRI contrast after traumatic brain injury in pigs. Sci Transl Med 2024; 16:eadk5413. [PMID: 38170792 DOI: 10.1126/scitranslmed.adk5413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 11/29/2023] [Indexed: 01/05/2024]
Abstract
The choroid plexus (ChP) of the brain plays a central role in orchestrating the recruitment of peripheral leukocytes into the central nervous system (CNS) through the blood-cerebrospinal fluid (BCSF) barrier in pathological conditions, thus offering a unique niche to diagnose CNS disorders. We explored whether magnetic resonance imaging of the ChP could be optimized for mild traumatic brain injury (mTBI). mTBI induces subtle, yet influential, changes in the brain and is currently severely underdiagnosed. We hypothesized that mTBI induces sufficient alterations in the ChP to cause infiltration of circulating leukocytes through the BCSF barrier and developed macrophage-adhering gadolinium [Gd(III)]-loaded anisotropic micropatches (GLAMs), specifically designed to image infiltrating immune cells. GLAMs are hydrogel-based discoidal microparticles that adhere to macrophages without phagocytosis. We present a fabrication process to prepare GLAMs at scale and demonstrate their loading with Gd(III) at high relaxivities, a key indicator of their effectiveness in enhancing image contrast and clarity in medical imaging. In vitro experiments with primary murine and porcine macrophages demonstrated that GLAMs adhere to macrophages also under shear stress and did not affect macrophage viability or functions. Studies in a porcine mTBI model confirmed that intravenously administered macrophage-adhering GLAMs provide a differential signal in the ChP and lateral ventricles at Gd(III) doses 500- to 1000-fold lower than those used in the current clinical standard Gadavist. Under the same mTBI conditions, Gadavist did not offer a differential signal at clinically used doses. Our results suggest that macrophage-adhering GLAMs could facilitate mTBI diagnosis.
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Affiliation(s)
- Lily Li-Wen Wang
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Yongsheng Gao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Vineeth Chandran Suja
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Masen L Boucher
- Division of Emergency Medicine, Boston Children's Hospital, Boston, MA 02115, USA
| | - Suyog Shaha
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Neha Kapate
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Rick Liao
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Tao Sun
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
| | - Ninad Kumbhojkar
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Supriya Prakash
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - John R Clegg
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Kaitlyn Warren
- Division of Emergency Medicine, Boston Children's Hospital, Boston, MA 02115, USA
| | - Morgan Janes
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Kyung Soo Park
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Michael Dunne
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
| | - Bolu Ilelaboye
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
| | - Andrew Lu
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
| | - Solomina Darko
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
| | - Camilo Jaimes
- Department of Radiology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Rebekah Mannix
- Division of Emergency Medicine, Boston Children's Hospital, Boston, MA 02115, USA
- Departments of Pediatrics and Emergency Medicine, Harvard Medical School, Boston, MA 02115, USA
| | - Samir Mitragotri
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA 02134, USA
- Wyss Institute for Biologically Inspired Engineering, Boston, MA 20115, USA
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12
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Tomaiuolo R, Zibetti M, Di Resta C, Banfi G. Challenges of the Effectiveness of Traumatic Brain Injuries Biomarkers in the Sports-Related Context. J Clin Med 2023; 12:jcm12072563. [PMID: 37048647 PMCID: PMC10095236 DOI: 10.3390/jcm12072563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
Traumatic brain injury affects 69 million people every year. One of the main limitations in managing TBI patients is the lack of univocal diagnostic criteria, including the absence of standardized assessment methods and guidelines. Computerized axial tomography is the first-choice examination, despite the limited prevalence of positivity; moreover, its performance is undesirable due to the risk of radiological exposure, prolonged stay in emergency departments, inefficient use of resources, high cost, and complexity. Furthermore, immediacy and accuracy in diagnosis and management of TBIs are critically unmet medical needs. Especially in the context of sports-associated TBI, there is a strong need for prognostic indicators to help diagnose and identify at-risk subjects to avoid their returning to play while the brain is still highly vulnerable. Fluid biomarkers may emerge as new prognostic indicators to develop more accurate prediction models, improving risk stratification and clinical decision making. This review describes the current understanding of the cellular sources, temporal profile, and potential utility of leading and emerging blood-based protein biomarkers of TBI; its focus is on biomarkers that could improve the management of mild TBI cases and can be measured readily and directly in the field, as in the case of sports-related contexts.
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Affiliation(s)
- Rossella Tomaiuolo
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
| | - Martina Zibetti
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
| | - Chiara Di Resta
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
- Correspondence:
| | - Giuseppe Banfi
- Faculty of Medicine, Università Vita-Salute San Raffaele, 20132 Milan, Italy
- IRCCS Galeazzi-Sant’Ambrogio, 20157 Milan, Italy
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13
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Yu H, Ande SR, Batoo D, Linton J, Shankar J. Prognostic Value of Initial Diagnostic Imaging Findings for Patient Outcomes in Adult Patients with Traumatic Brain Injury: A Systematic Review and Meta-Analysis. Tomography 2023; 9:509-528. [PMID: 36961001 PMCID: PMC10037627 DOI: 10.3390/tomography9020042] [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: 01/28/2023] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 03/02/2023] Open
Abstract
INTRODUCTION Termed the "silent epidemic," traumatic brain injury (TBI) is one of the greatest global contributors not only to post-traumatic death but also to post-traumatic long-term disability. This systematic review and meta-analysis aims to specifically evaluate the prognostic value of features on initial imaging completed within 24 h of arrival in adult patients with TBI. METHOD The authors followed the PRISMA 2020 checklist for systematic review and meta-analysis design and reporting. Comprehensive searches of the Medline and Embase databases were carried out. Two independent readers extracted the following demographic, clinical and imaging information using a predetermined data abstraction form. Statistics were performed using Revman 5.4.1 and R version 4.2.0. For pooled data in meta-analysis, forest plots for sensitivity and specificity were created to calculate the diagnostic odds ratio (DOR). Summary receiver operating characteristic (SROC) curves were generated using a bivariate model, and diagnostic accuracy was determined using pooled sensitivity and specificity as well as the area under the receiver operator characteristic curve (AUC). RESULTS There were 10,733 patients over the 19 studies. Overall, most of the studies included had high levels of bias in multiple, particularly when it came to selection bias in patient sampling, bias in controlling for confounders, and reporting bias, such as in reporting missing data. Only subdural hematoma (SDH) and mortality in all TBI patients had both an AUC with 95% CI not crossing 0.5 and a DOR with 95% CI not crossing 1, at 0.593 (95% CI: 0.556-0.725) and 2.755 (95% CI: 1.474-5.148), respectively. CONCLUSION In meta-analysis, only SDH with mortality in all TBI patients had a moderate but significant association. Given the small number of studies, additional research focused on initial imaging, particularly for imaging modalities other than NECT, is required in order to confirm the findings of our meta-analysis and to further evaluate the association of imaging findings and outcome.
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Affiliation(s)
- Hang Yu
- Department of Radiology, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada
| | - Sudharsana Rao Ande
- Department of Radiology, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada
| | - Divjeet Batoo
- Department of Radiology, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada
| | - Janice Linton
- Department of Radiology, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada
| | - Jai Shankar
- Department of Radiology, University of Manitoba, GA216-820 Sherbrook Street, Winnipeg, MB R3A 1R9, Canada
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14
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Nikam RM, Kecskemethy HH, Kandula VVR, Averill LW, Langhans SA, Yue X. Abusive Head Trauma Animal Models: Focus on Biomarkers. Int J Mol Sci 2023; 24:4463. [PMID: 36901893 PMCID: PMC10003453 DOI: 10.3390/ijms24054463] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Revised: 02/07/2023] [Accepted: 02/17/2023] [Indexed: 02/26/2023] Open
Abstract
Abusive head trauma (AHT) is a serious traumatic brain injury and the leading cause of death in children younger than 2 years. The development of experimental animal models to simulate clinical AHT cases is challenging. Several animal models have been designed to mimic the pathophysiological and behavioral changes in pediatric AHT, ranging from lissencephalic rodents to gyrencephalic piglets, lambs, and non-human primates. These models can provide helpful information for AHT, but many studies utilizing them lack consistent and rigorous characterization of brain changes and have low reproducibility of the inflicted trauma. Clinical translatability of animal models is also limited due to significant structural differences between developing infant human brains and the brains of animals, and an insufficient ability to mimic the effects of long-term degenerative diseases and to model how secondary injuries impact the development of the brain in children. Nevertheless, animal models can provide clues on biochemical effectors that mediate secondary brain injury after AHT including neuroinflammation, excitotoxicity, reactive oxygen toxicity, axonal damage, and neuronal death. They also allow for investigation of the interdependency of injured neurons and analysis of the cell types involved in neuronal degeneration and malfunction. This review first focuses on the clinical challenges in diagnosing AHT and describes various biomarkers in clinical AHT cases. Then typical preclinical biomarkers such as microglia and astrocytes, reactive oxygen species, and activated N-methyl-D-aspartate receptors in AHT are described, and the value and limitations of animal models in preclinical drug discovery for AHT are discussed.
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Affiliation(s)
- Rahul M. Nikam
- Diagnostic & Research PET/MR Center, Nemours Children’s Health, Wilmington, DE 19803, USA
- Department of Radiology, Nemours Children’s Health, Wilmington, DE 19803, USA
| | - Heidi H. Kecskemethy
- Diagnostic & Research PET/MR Center, Nemours Children’s Health, Wilmington, DE 19803, USA
- Department of Radiology, Nemours Children’s Health, Wilmington, DE 19803, USA
| | - Vinay V. R. Kandula
- Department of Radiology, Nemours Children’s Health, Wilmington, DE 19803, USA
| | - Lauren W. Averill
- Diagnostic & Research PET/MR Center, Nemours Children’s Health, Wilmington, DE 19803, USA
- Department of Radiology, Nemours Children’s Health, Wilmington, DE 19803, USA
| | - Sigrid A. Langhans
- Diagnostic & Research PET/MR Center, Nemours Children’s Health, Wilmington, DE 19803, USA
- Nemours Biomedical Research, Nemours Children’s Health, Wilmington, DE 19803, USA
| | - Xuyi Yue
- Diagnostic & Research PET/MR Center, Nemours Children’s Health, Wilmington, DE 19803, USA
- Department of Radiology, Nemours Children’s Health, Wilmington, DE 19803, USA
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15
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Sharma VK, Singh TG, Mehta V, Mannan A. Biomarkers: Role and Scope in Neurological Disorders. Neurochem Res 2023; 48:2029-2058. [PMID: 36795184 DOI: 10.1007/s11064-023-03873-4] [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: 06/02/2022] [Revised: 01/19/2023] [Accepted: 01/21/2023] [Indexed: 02/17/2023]
Abstract
Neurological disorders pose a great threat to social health and are a major cause for mortality and morbidity. Effective drug development complemented with the improved drug therapy has made considerable progress towards easing symptoms associated with neurological illnesses, yet poor diagnosis and imprecise understanding of these disorders has led to imperfect treatment options. The scenario is complicated by the inability to extrapolate results of cell culture studies and transgenic models to clinical applications which has stagnated the process of improving drug therapy. In this context, the development of biomarkers has been viewed as beneficial to easing various pathological complications. A biomarker is measured and evaluated in order to gauge the physiological process or a pathological progression of a disease and such a marker can also indicate the clinical or pharmacological response to a therapeutic intervention. The development and identification of biomarkers for neurological disorders involves several issues including the complexity of the brain, unresolved discrepant data from experimental and clinical studies, poor clinical diagnostics, lack of functional endpoints, and high cost and complexity of techniques yet research in the area of biomarkers is highly desired. The present work describes existing biomarkers for various neurological disorders, provides support for the idea that biomarker development may ease our understanding underlying pathophysiology of these disorders and help to design and explore therapeutic targets for effective intervention.
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Affiliation(s)
- Vivek Kumar Sharma
- Chitkara College of Pharmacy, Chitkara University, Chandigarh, Punjab, 140401, India.,Government College of Pharmacy, Rohru, Shimla, Himachal Pradesh, 171207, India
| | - Thakur Gurjeet Singh
- Chitkara College of Pharmacy, Chitkara University, Chandigarh, Punjab, 140401, India.
| | - Vineet Mehta
- Government College of Pharmacy, Rohru, Shimla, Himachal Pradesh, 171207, India
| | - Ashi Mannan
- Chitkara College of Pharmacy, Chitkara University, Chandigarh, Punjab, 140401, India
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16
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Cole KL, Findlay MC, Kundu M, Johansen C, Rawanduzy C, Lucke-Wold B. The Role of Advanced Imaging in Neurosurgical Diagnosis. JOURNAL OF MODERN MEDICAL IMAGING 2023; 1:2. [PMID: 36908971 PMCID: PMC10003679 DOI: 10.53964/jmmi.2023002] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Neurosurgery as a specialty has developed at a rapid pace as a result of the continual advancements in neuroimaging modalities. With more sophisticated imaging options available to the modern neurosurgeon, diagnoses become more accurate and at a faster rate, allowing for greater surgical planning and precision. Herein, the authors review the current heavily used imaging modalities within neurosurgery, weighing their strengths and weaknesses, and provide a look into new advances and imaging options within the field. Of the many imaging modalities currently available to the practicing neurosurgeon, magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasonography (US) are used most heavily within the field for appropriate diagnosis of neuropathologies in question. For each, their strengths are weighed regarding appropriate capabilities in accurate diagnosis of cranial or spinal lesions. Reasoning for choosing one over the other for various pathologies is also reviewed. Current limitations of each is also assessed, providing insight for possible improvement for each. New advancements in imaging options are subsequently reviewed for best uses within neurosurgery, including the new utilization of FIESTA sequencing, glymphatic mapping, black-blood MRI, and functional MRI. The specialty of neurosurgery will continue to heavily rely on improvements within imaging options available for improved diagnosis and greater surgical outcomes for the patients treated. The synthesis of techniques provided herein may provide meaningful guidance for neurosurgeons in effectively diagnosing neurological pathologies while also helping guide future efforts in neuroimaging developments.
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Affiliation(s)
- Kyril L Cole
- School of Medicine, University of Utah, Salt Lake City, UT, USA
| | | | - Mrinmoy Kundu
- Institute of Medical Sciences & Sum Hospital, Bhubaneswar, India
| | | | - Cameron Rawanduzy
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
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17
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Doborjeh Z, Doborjeh M, Sumich A, Singh B, Merkin A, Budhraja S, Goh W, Lai EMK, Williams M, Tan S, Lee J, Kasabov N. Investigation of social and cognitive predictors in non-transition ultra-high-risk' individuals for psychosis using spiking neural networks. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2023; 9:10. [PMID: 36792634 PMCID: PMC9931713 DOI: 10.1038/s41537-023-00335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 01/26/2023] [Indexed: 02/17/2023]
Abstract
Finding predictors of social and cognitive impairment in non-transition Ultra-High-Risk individuals (UHR) is critical in prognosis and planning of potential personalised intervention strategies. Social and cognitive functioning observed in youth at UHR for psychosis may be protective against transition to clinically relevant illness. The current study used a computational method known as Spiking Neural Network (SNN) to identify the cognitive and social predictors of transitioning outcome. Participants (90 UHR, 81 Healthy Control (HC)) completed batteries of neuropsychological tests in the domains of verbal memory, working memory, processing speed, attention, executive function along with social skills-based performance at baseline and 4 × 6-month follow-up intervals. The UHR status was recorded as Remitters, Converters or Maintained. SNN were used to model interactions between variables across groups over time and classify UHR status. The performance of SNN was examined relative to other machine learning methods. Higher interaction between social and cognitive variables was seen for the Maintained, than Remitter subgroup. Findings identified the most important cognitive and social variables (particularly verbal memory, processing speed, attention, affect and interpersonal social functioning) that showed discriminative patterns in the SNN models of HC vs UHR subgroups, with accuracies up to 80%; outperforming other machine learning models (56-64% based on 18 months data). This finding is indicative of a promising direction for early detection of social and cognitive impairment in UHR individuals that may not anticipate transition to psychosis and implicate early initiated interventions to stem the impact of clinical symptoms of psychosis.
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Affiliation(s)
- Zohreh Doborjeh
- Audiology Department, School of Population Health, Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand.
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand.
- School of Psychology, The University of Waikato, Hamilton, New Zealand.
| | - Maryam Doborjeh
- Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand.
| | - Alexander Sumich
- School of Psychology, Nottingham Trent University, Nottingham, UK
- Department of Psychology and Neuroscience, Auckland University of Technology, Auckland, New Zealand
| | - Balkaran Singh
- Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand
| | - Alexander Merkin
- Institute for Stroke and Applied Neurosciences, Auckland University of Technology, Auckland, New Zealand
- Research Methods, Assessment & Science, Department of Psychology, University of Konstanz, Konstanz, Germany
| | - Sugam Budhraja
- Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand
| | - Wilson Goh
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Center for Biomedical Informatics, Nanyang Technological University, Singapore, Singapore
| | - Edmund M-K Lai
- Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand
| | - Margaret Williams
- Department of Public Health and Psychosocial Studies, Auckland University of Technology, Auckland, New Zealand
| | - Samuel Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Jimmy Lee
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Institute of Mental Health & Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Nikola Kasabov
- Knowledge Engineering and Discovery Research Institute, School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, 1010, New Zealand
- Intelligent Systems Research Centre, Ulster University, Londonderry, UK
- Institute for Information and Communication Technologies (IICT), Bulgarian Academy of Sciences, Sofia, Bulgaria
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18
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Chary K, Manninen E, Claessens J, Ramirez-Manzanares A, Gröhn O, Sierra A. Diffusion MRI approaches for investigating microstructural complexity in a rat model of traumatic brain injury. Sci Rep 2023; 13:2219. [PMID: 36755032 PMCID: PMC9908904 DOI: 10.1038/s41598-023-29010-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 01/30/2023] [Indexed: 02/10/2023] Open
Abstract
Our study explores the potential of conventional and advanced diffusion MRI techniques including diffusion tensor imaging (DTI), and single-shell 3-tissue constrained spherical deconvolution (SS3T-CSD) to investigate complex microstructural changes following severe traumatic brain injury in rats at a chronic phase. Rat brains after sham-operation or lateral fluid percussion (LFP) injury were scanned ex vivo in a 9.4 T scanner. Our region-of-interest-based approach of tensor-, and SS3T-CSD derived fixel-, 3-tissue signal fraction maps were sensitive to changes in both white matter (WM) and grey matter (GM) areas. Tensor-based measures, such as fractional anisotropy (FA) and radial diffusivity (RD), detected more changes in WM and GM areas as compared to fixel-based measures including apparent fiber density (AFD), peak FOD amplitude and primary fiber bundle density, while 3-tissue signal fraction maps revealed distinct changes in WM, GM, and phosphate-buffered saline (PBS) fractions highlighting the complex tissue microstructural alterations post-trauma. Track-weighted imaging demonstrated changes in track morphology including reduced curvature and average pathlength distal from the primary lesion in severe TBI rats. In histological analysis, changes in the diffusion MRI measures could be associated to decreased myelin density, loss of myelinated axons, and increased cellularity, revealing progressive microstructural alterations in these brain areas five months after injury. Overall, this study highlights the use of combined conventional and advanced diffusion MRI measures to obtain more precise insights into the complex tissue microstructural alterations in chronic phase of severe brain injury.
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Affiliation(s)
- Karthik Chary
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
- Department of Radiology, University of Cambridge, Cambridge, UK
| | - Eppu Manninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Jade Claessens
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | | | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland
| | - Alejandra Sierra
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, P.O. Box 1627, 70211, Neulaniementie 2, Kuopio, Finland.
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19
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Ma Y, Ren F, Li W, Yu N, Zhang D, Li Y, Ke M. IHA-Net: An automatic segmentation framework for computer-tomography of tiny intracerebral hemorrhage based on improved attention U-net. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104320] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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20
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Harris G, Rickard JJS, Butt G, Kelleher L, Blanch RJ, Cooper J, Oppenheimer PG. Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury. IEEE Rev Biomed Eng 2023; 16:530-559. [PMID: 35320105 PMCID: PMC9888755 DOI: 10.1109/rbme.2022.3161352] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 02/11/2022] [Accepted: 03/15/2022] [Indexed: 11/06/2022]
Abstract
The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.
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Affiliation(s)
- Georgia Harris
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
| | - Jonathan James Stanley Rickard
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
- Department of Physics, Cavendish LaboratoryUniversity of CambridgeCB3 0HECambridgeU.K.
| | - Gibran Butt
- Ophthalmology DepartmentUniversity Hospitals Birmingham NHS Foundation TrustB15 2THBirminghamU.K.
| | - Liam Kelleher
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
| | - Richard James Blanch
- Department of Military Surgery and TraumaRoyal Centre for Defence MedicineB15 2THBirminghamU.K.
- Neuroscience and Ophthalmology, Department of Ophthalmology, University Hospitals Birmingham NHS Foundation TrustcBirminghamU.K.
| | - Jonathan Cooper
- School of Biomedical EngineeringUniversity of GlasgowG12 8LTGlasgowU.K.
| | - Pola Goldberg Oppenheimer
- School of Chemical Engineering, Advanced Nanomaterials Structures and Applications Laboratories, College of Engineering and Physical SciencesUniversity of BirminghamB15 2TTBirminghamU.K.
- Healthcare Technologies Institute, Institute of Translational MedicineB15 2THBirminghamU.K.
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21
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Pasipanodya EC, Teranishi R, Dirlikov B, Duong T, Huie H. Characterizing Profiles of TBI Severity: Predictors of Functional Outcomes and Well-Being. J Head Trauma Rehabil 2023; 38:E65-E78. [PMID: 35617636 DOI: 10.1097/htr.0000000000000791] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
OBJECTIVE To identify profiles of acute traumatic brain injury (TBI) severity and relate profiles to functional and well-being outcomes. SETTING Acute inpatient rehabilitation and general community settings. PARTICIPANTS Three hundred and seventy-nine individuals with moderate-severe TBI participating in the Traumatic Brain Injury Model Systems. DESIGN Longitudinal observational study. MAIN MEASURES At discharge-length of stay, Functional Independence Measure (FIM), and Disability Rating Scale (DRS). One-year post-injury-Glasgow Outcome Scale-Extended (GOS-E), FIM, and Satisfaction with Life Scale (SWLS). RESULTS Latent profile analysis (LPA) was used to identify subgroups with similar patterns across 12 indicators of acute injury severity, including duration of posttraumatic amnesia, Glasgow Coma Scale, time to follow commands, and head CT variables. LPA identified 4 latent classes, least to most severe TBI (Class 1: n = 75, 20.3%; Class 2: n = 124, 33.5%; Class 3: n = 144, 38.9%; Class 4: n = 27, 7.3%); younger age, lower education, rural residence, injury in motor vehicle accidents, and earlier injury years were associated with worse acute severity. Latent classes were related to outcomes. Compared with Class 1, hospital stays were longer, FIM scores lower, and DRS scores larger at discharge among individuals in Class 3 and Class 4 (all P s < .01). One-year post-injury, GOS-E and FIM scores were significantly lower among individuals in Class 3 and Class 4 than those in Class 1 ( P s < .01). SWLS scores were lower only among individuals in Class 3 ( P = .036) compared with Class 1; other comparisons relative to Class 1 were not significant. CONCLUSIONS Meaningful profiles of TBI severity can be identified from acute injury characteristics and may suggest etiologies, like injury in motor vehicle accidents, and premorbid characteristics, including younger age, rural residence, and lower education, that heighten risk for worse injuries. Improving classification may help focus on those at elevated risk for severe injury and inform clinical management and prognosis.
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Affiliation(s)
- Elizabeth C Pasipanodya
- Rehabilitation Research Center, Santa Clara Valley Medical Center, San Jose, California (Dr Pasipanodya and Mr Dirlikov); Department of Physical Medicine and Rehabilitation, Atrium Health Carolinas Rehabilitation, Charlotte, North Carolina (Dr Teranishi); and Department of Physical Medicine and Rehabilitation, Santa Clara Valley Medical Center, San Jose, California (Drs Duong and Huie)
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22
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Temporary or Permanent? A Clinical Challenge in the Evaluation of Traumatic Brain Injury Patients with Unconsciousness and Normal Initial Head CT. World J Surg 2022; 46:2882-2889. [PMID: 36131183 DOI: 10.1007/s00268-022-06747-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/10/2022] [Indexed: 01/14/2023]
Abstract
BACKGROUND Traumatic brain injury (TBI) patients with unconsciousness and normal initial head computed tomography (CT) present a clinical dilemma for physicians and neurosurgeons in the emergency department (ED). We recorded how long it took for patients to regain consciousness and evaluated the patients' characteristics. METHODS From 2018 to 2020, TBI patients with unconsciousness and normal initial head CT [Glasgow coma scale (GCS) score < 13, negative CT scan and normal laboratory test results] were evaluated. Patients who regained consciousness were analyzed. Multivariate logistic regression (MLR) analyses were used to evaluate independent factors for regaining consciousness. RESULTS A total of 77 patients were included in this study. Fifty-eight (75.3%) patients regained consciousness, most within one day (43.1%). Nineteen (24.7%) patients never regained consciousness. MLR analysis showed that initial GCS score (odds 1.85, p = 0.017), early airway protection in ED (odds 25.02, p = 0.018) and 72-h GCS score improvement by two points (odds 0.02, p = 0.001) were independent factors for regaining consciousness. Overall, 94.1% of patients who received early airway protection and improved 2 points in 72-h GCS score regained consciousness. The association between days to M5 status and days to M6 status (consciousness) was highly significant. Fewer days to M5 status were highly associated with needing fewer days to regain consciousness. CONCLUSIONS For TBI patients with unconsciousness and normal initial head CT, a higher probability of regaining consciousness was observed in those who underwent early airway protection and who improved 2 points in 72-h GCS score. Regaining consciousness within a short period could be expected in patients with M5 status.
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23
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Omer M, Posti JP, Gissler M, Merikukka M, Hoffmann I, Bärnighausen T, Wilson ML. The effect of birth order on length of hospitalization for pediatric traumatic brain injury: an analysis of the 1987 Finnish birth cohort. Arch Public Health 2022; 80:167. [PMID: 35820924 PMCID: PMC9275049 DOI: 10.1186/s13690-022-00919-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 06/24/2022] [Indexed: 11/15/2022] Open
Abstract
Purpose This study examines the relationship between birth order and length of hospitalization due to pediatric traumatic brain injury (TBI). Methods We prospectively followed 59,469 Finnish newborns from 1987 until age 18 years. Data on first diagnosis of TBI was recorded within the 1987 Finnish Birth Cohort (FBC). Hospitalization period was divided into two categories: 2 days or less and more than 2 days. The latter was considered in this study as longer hospitalization. Results Compared with first born siblings, later born siblings had an increased risk of a longer hospitalization for TBI (12.7% of fourth or higher born birth children diagnosed with TBI were hospitalized for 2 or more days, 11.3% of first born, 10.4% of third born and 9.0% of second born). Fourth or higher born children were more likely to experience a repeat TBI; 13.4% of fourth or higher born children diagnosed with TBI had 2–3 TBIs during the study period compared to 9% of third born, 7.8% of second born and 8.8% of the first born. Injuries in the traffic environment and falls were the most common contributors to pediatric TBI and occurred most frequently in the fourth or higher birth category; 29.3% of TBIs among fourth or higher birth order were due to transport accidents and 21% were due to falls. Conclusions This study revealed a significant increase in risk for longer hospitalization due to TBI among later born children within the same sibling group. The study provides epidemiological evidence on birth order as it relates to TBI, and its potential to help to explain some of the statistical variability in pediatric TBI hospitalization over time in this population. Supplementary Information The online version contains supplementary material available at 10.1186/s13690-022-00919-x.
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24
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Even KM, Hymel KP, Armijo-Garcia V, Musick M, Weeks K, Haney SB, Marinello M, Herman BE, Frazier TN, Carroll CL, Liang M, Wang M. The association of subcortical brain injury and abusive head trauma. CHILD ABUSE & NEGLECT 2022; 134:105917. [PMID: 36308893 DOI: 10.1016/j.chiabu.2022.105917] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/21/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Abusive head trauma (AHT) remains a major pediatric problem with diagnostic challenges. A small pilot study previously associated subcortical brain injury with AHT. OBJECTIVES To investigate the association of subcortical injury on neuroimaging with the diagnosis of AHT. PARTICIPANTS AND SETTING Children <3 years with acute TBI admitted to 18 PICUs between 2011 and 2021. METHODS Secondary analysis of existing, combined, de-identified, cross-sectional dataset. RESULTS Deepest location of visible injury was characterized as scalp/skull/epidural (n = 170), subarachnoid/subdural (n = 386), cortical brain (n = 170), or subcortical brain (n = 247) (total n = 973). Subcortical injury was significantly associated with AHT using both physicians' diagnostic impression (OR: 8.41 [95 % CI: 5.82-12.44]) and a priori definitional criteria (OR: 5.99 [95 % CI: 4.31-8.43]). Caregiver reports consistent with the child's gross motor skills and historically consistent with repetition decreased as deepest location of injury increased, p < 0.001. Patients with subcortical injuries were significantly more likely to have traumatic extracranial injuries such as rib fractures (OR 3.36, 95 % CI 2.30-4.92) or retinal hemorrhages (OR 5.97, 95 % CI 4.35-8.24), respiratory compromise (OR 12.12, 95 % CI 8.49-17.62), circulatory compromise (OR 6.71, 95 % CI 4.87-9.29), seizures (OR 3.18, 95 % CI 2.35-4.29), and acute encephalopathy (OR 12.44, 95 % CI 8.16-19.68). CONCLUSIONS Subcortical injury is associated with a diagnosis of AHT, historical inaccuracies concerning for abuse, traumatic extracranial injuries, and increased severity of illness including respiratory and circulatory compromise, seizures, and prolonged loss of consciousness. Presence of subcortical injury should be considered as one component of the complex AHT diagnostic process.
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Affiliation(s)
- Katelyn M Even
- Department of Pediatrics, Penn State College of Medicine, Penn State Health Children's Hospital, 600 University Drive, Hershey, PA 17033, USA.
| | - Kent P Hymel
- Department of Pediatrics, Penn State College of Medicine, Penn State Health Children's Hospital, 600 University Drive, Hershey, PA 17033, USA
| | - Veronica Armijo-Garcia
- University of Texas Health Sciences Center at San Antonio, 7703 Floyd Curl Drive, San Antonio, TX 78229, USA
| | - Matthew Musick
- Department of Pediatrics, Baylor College of Medicine, Texas Children's Hospital, 6621 Fannin Street, Houston, TX 77030, USA.
| | - Kerri Weeks
- Department of Pediatrics, University of Kansas School of Medicine, 3243 East Murdoch, Wichita, KS 67208, USA
| | - Suzanne B Haney
- Department of Pediatrics, University of Nebraska Medical Center, Children's Hospital and Medical Center, 8200 Dodge Street, Omaha, NE 68114, USA.
| | - Mark Marinello
- Department of Pediatrics, Children's Hospital of Richmond at VCU, 1250 East Marshall Street, Richmond, VA 23219, USA.
| | - Bruce E Herman
- Department of Pediatrics, University of Utah School of Medicine, Primary Children's Hospital, 100 North Mario Capecchie Drive, Salt Lake City, UT 84113, USA.
| | - Terra N Frazier
- Department of Pediatrics, Children's Mercy Hospital, 2401 Gillham Road, Kansas City, MO 64108, USA.
| | - Christopher L Carroll
- Department of Pediatrics, Connecticut Children's Medical Center, 282 Washington Street, Hartford, CT 06106, USA.
| | - Menglu Liang
- Department of Public Health Sciences, Penn State College of Medicine, 700 HMC Crescent Road, Hershey, PA 17033, USA.
| | - Ming Wang
- Department of Public Health Sciences, Penn State College of Medicine, 700 HMC Crescent Road, Hershey, PA 17033, USA.
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25
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Kuoy E, Glavis-Bloom J, Hovis G, Yep B, Biswas A, Masudathaya LA, Norrick LA, Limfueco J, Soun JE, Chang PD, Chu E, Akbari Y, Yaghmai V, Fox JC, Yu W, Chow DS. Point-of-Care Brain MRI: Preliminary Results from a Single-Center Retrospective Study. Radiology 2022; 305:666-671. [PMID: 35916678 PMCID: PMC9713449 DOI: 10.1148/radiol.211721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 05/13/2022] [Accepted: 06/03/2022] [Indexed: 11/11/2022]
Abstract
Background Point-of-care (POC) MRI is a bedside imaging technology with fewer than five units in clinical use in the United States and a paucity of scientific studies on clinical applications. Purpose To evaluate the clinical and operational impacts of deploying POC MRI in emergency department (ED) and intensive care unit (ICU) patient settings for bedside neuroimaging, including the turnaround time. Materials and Methods In this preliminary retrospective study, all patients in the ED and ICU at a single academic medical center who underwent noncontrast brain MRI from January 2021 to June 2021 were investigated to determine the number of patients who underwent bedside POC MRI. Turnaround time, examination limitations, relevant findings, and potential CT and fixed MRI findings were recorded for patients who underwent POC MRI. Descriptive statistics were used to describe clinical variables. The Mann-Whitney U test was used to compare the turnaround time between POC MRI and fixed MRI examinations. Results Of 638 noncontrast brain MRI examinations, 36 POC MRI examinations were performed in 35 patients (median age, 66 years [IQR, 57-77 years]; 21 women), with one patient undergoing two POC MRI examinations. Of the 36 POC MRI examinations, 13 (36%) occurred in the ED and 23 (64%) in the ICU. There were 12 of 36 (33%) POC MRI examinations interpreted as negative, 14 of 36 (39%) with clinically significant imaging findings, and 10 of 36 (28%) deemed nondiagnostic for reasons such as patient motion. Of 23 diagnostic POC MRI examinations with comparison CT available, three (13%) demonstrated acute infarctions not apparent on CT scans. Of seven diagnostic POC MRI examinations with subsequent fixed MRI examinations, two (29%) demonstrated missed versus interval subcentimeter infarctions, while the remaining demonstrated no change. The median turnaround time of POC MRI was 3.4 hours in the ED and 5.3 hours in the ICU. Conclusion Point-of-care (POC) MRI was performed rapidly in the emergency department and intensive care unit. A few POC MRI examinations demonstrated acute infarctions not apparent at standard-of-care CT examinations. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Anzai and Moy in this issue.
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Affiliation(s)
- Edward Kuoy
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Justin Glavis-Bloom
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Gabrielle Hovis
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Brian Yep
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Arabdha Biswas
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Lu-Aung Masudathaya
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Lori A. Norrick
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Julie Limfueco
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Jennifer E. Soun
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Peter D. Chang
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Eleanor Chu
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Yama Akbari
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Vahid Yaghmai
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - John C. Fox
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Wengui Yu
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
| | - Daniel S. Chow
- From the Department of Radiological Sciences (E.K., J.G.B., B.Y.,
L.A.N., J.L., J.E.S., P.D.C., E.C., V.Y., D.S.C.), Center for Artificial
Intelligence in Diagnostic Medicine (A.B., L.A.M., P.D.C., D.S.C.), Department
of Neurology (Y.A., W.Y.), and Department of Emergency Medicine (J.C.F.),
University of California, Irvine, 101 The City Drive South, Orange, CA 92868;
and University of California, Irvine School of Medicine, Irvine, Calif
(G.H.)
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26
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Hibi A, Jaberipour M, Cusimano MD, Bilbily A, Krishnan RG, Aviv RI, Tyrrell PN. Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet? Medicine (Baltimore) 2022; 101:e31848. [PMID: 36451512 PMCID: PMC9704869 DOI: 10.1097/md.0000000000031848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 10/26/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in traumatic brain injury (TBI). METHODS Systematic review, in accordance with PRISMA 2020 and SPIRIT-AI extension guidelines, with a search of 4 databases (Medline, Embase, IEEE Xplore, and Web of Science) was performed to find AI studies that automated the clinical tasks for identifying and quantifying CT findings of TBI-related abnormalities. RESULTS A total of 531 unique publications were reviewed, which resulted in 66 articles that met our inclusion criteria. The following components for identification and quantification regarding TBI were covered and automated by existing AI studies: identification of TBI-related abnormalities; classification of intracranial hemorrhage types; slice-, pixel-, and voxel-level localization of hemorrhage; measurement of midline shift; and measurement of hematoma volume. Automated identification of obliterated basal cisterns was not investigated in the existing AI studies. Most of the AI algorithms were based on deep neural networks that were trained on 2- or 3-dimensional CT imaging datasets. CONCLUSION We identified several important TBI-related CT findings that can be automatically identified and quantified with AI. A combination of these techniques may provide useful tools to enhance reproducibility of TBI identification and quantification by supporting radiologists and clinicians in their TBI assessments and reducing subjective human factors.
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Affiliation(s)
- Atsuhiro Hibi
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Majid Jaberipour
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
| | - Michael D. Cusimano
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Division of Neurosurgery, St Michael’s Hospital, University of Toronto, Toronto, Canada
| | - Alexander Bilbily
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Rahul G. Krishnan
- Department of Computer Science, University of Toronto, Toronto, Ontario, Canada
- Department of Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Richard I. Aviv
- Department of Radiology, Radiation Oncology and Medical Physics, University of Ottawa, Ottawa, Ontario, Canada
| | - Pascal N. Tyrrell
- Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
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27
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Al-Taei O, Al-Mirza A, Ali M, Al-Kalbani H, Al-Saadi T. Prevalence and Outcomes of Geriatric Traumatic Brain Injury in Developing Countries: A Retrospective Study. INDIAN JOURNAL OF NEUROTRAUMA 2022. [DOI: 10.1055/s-0041-1740942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Abstract
Introduction The world populace is aging and it is anticipated that 2 billion people will be older than 60 years by 2050. Traumatic brain injury (TBI) is a major cause of death and disability worldwide. In the United States, 2.8 million people pursue medical attention yearly. TBI exemplifies a leading cause of mortality and morbidity among the geriatric age group worldwide.
Methods A retrospective study of geriatric cases who were admitted to the Neurosurgery Department in Khoula Hospital from January 1, 2016, to December 31, 2019, was conducted. Patients' demographics, risk factors, neuro-vital sign, diagnosis, Glasgow coma scale (GCS) on arrival, treatment types, and length of stay (LOS) were recorded.
Results Two hundred and thirty-four patients were admitted due to TBI in four years period. Seventy-five percent of the study cohort were more than 75 years old. Male to female ratio was 2.4:1. Subdural hematoma (SDH) was the most common TBI diagnosis based on computed tomography (77.4%). Most of the patients were having GCS scores of 14 to 15 (67.9%). Sixteen percent of the patients received antiepileptic medications. The majority of the patients underwent surgical intervention (70.5%). Eighty percent of the patients stayed in the hospital for less than 15 days. There was a significant difference between the LOS and type of surgery. Subarachnoid hemorrhage was found to have the highest mean age (79.7 years). Intracerebral hemorrhage patients had the longest LOS in the hospital with a mean of 44.2 days. There was no significant difference between the age of patients and type of surgery.
Conclusion The number of TBI in the elderly population is increasing annually. The most common type of TBI in our cohort was SDH and most of the patients were treated with burr hole surgery.
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Affiliation(s)
- Omar Al-Taei
- Sultan Qaboos University College of Medicine, Sultanate of Oman-Muscat, Al-Khoudh, Oman
| | - Abdulrahman Al-Mirza
- Sultan Qaboos University College of Medicine, Sultanate of Oman-Muscat, Al-Khoudh, Oman
| | - Mohammed Ali
- Neurosurgery Department, Khoula Hospital, Muscat, Oman
| | - Humaid Al-Kalbani
- Department of Ophthalmology, Al-Buraimi Hospital, Ministry of Health, Sultanate of Oman, Oman
| | - Tariq Al-Saadi
- Neurosurgery Department, Khoula Hospital, Muscat, Oman
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, Faculty of Medicine, McGill University, Quebec, Canada
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Neurovascular Unit-Derived Extracellular Vesicles: From Their Physiopathological Roles to Their Clinical Applications in Acute Brain Injuries. Biomedicines 2022; 10:biomedicines10092147. [PMID: 36140248 PMCID: PMC9495841 DOI: 10.3390/biomedicines10092147] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 08/26/2022] [Accepted: 08/28/2022] [Indexed: 11/16/2022] Open
Abstract
Extracellular vesicles (EVs) form a heterogeneous group of membrane-enclosed structures secreted by all cell types. EVs export encapsulated materials composed of proteins, lipids, and nucleic acids, making them a key mediator in cell–cell communication. In the context of the neurovascular unit (NVU), a tightly interacting multicellular brain complex, EVs play a role in intercellular communication and in maintaining NVU functionality. In addition, NVU-derived EVs can also impact peripheral tissues by crossing the blood–brain barrier (BBB) to reach the blood stream. As such, EVs have been shown to be involved in the physiopathology of numerous neurological diseases. The presence of NVU-released EVs in the systemic circulation offers an opportunity to discover new diagnostic and prognostic markers for those diseases. This review outlines the most recent studies reporting the role of NVU-derived EVs in physiological and pathological mechanisms of the NVU, focusing on neuroinflammation and neurodegenerative diseases. Then, the clinical application of EVs-containing molecules as biomarkers in acute brain injuries, such as stroke and traumatic brain injuries (TBI), is discussed.
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Klimo KR, Stern-Green EA, Shelton E, Day E, Jordan L, Robich M, Racine J, McDaniel CE, VanNasdale DA, Yuhas PT. Structure and function of retinal ganglion cells in subjects with a history of repeated traumatic brain injury. Front Neurol 2022; 13:963587. [PMID: 36034275 PMCID: PMC9412167 DOI: 10.3389/fneur.2022.963587] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 07/22/2022] [Indexed: 01/21/2023] Open
Abstract
This study tested whether repeated traumatic brain injuries (TBIs) alter the objective structure or the objective function of retinal ganglion cells (RGCs) in human subjects recruited from an optometry clinic. Case subjects (n = 25) with a history of repeated TBIs (4.12 ± 2.76 TBIs over 0-41 years) and healthy pair-matched control subjects (n = 30) were prospectively recruited. Retinal nerve fiber layer (RNFL) thickness was quantified with spectral-domain optical coherence tomography, and scanning laser polarimetry measured RNFL phase retardation. Measurements of the photopic negative response were made using full-field flash electroretinography. There was no statistically significant difference (p = 0.42) in global RNFL thickness between the case cohort (96.6 ± 9.4 microns) and the control cohort (94.9 ± 7.0 microns). There was no statistically significant difference (p = 0.80) in global RNFL phase retardation between the case cohort (57.9 ± 5.7 nm) and the control cohort (58.2 ± 4.6 nm). There were no statistically significant differences in the peak time (p = 0.95) of the PhNR or in the amplitude (p = 0.11) of the PhNR between the case cohort (69.9 ± 6.9 ms and 24.1 ± 5.1 μV, respectively) and the control cohort (70.1 ± 8.9 ms and 27.8 ± 9.1 μV, respectively). However, PhNR amplitude was more variable (p < 0.025) in the control cohort than in the case cohort. Within the case cohort, there was a strong positive (r = 0.53), but not statistically significant (p = 0.02), association between time since last TBI and PhNR amplitude. There was also a modest positive (r = 0.45), but not statistically significant (p = 0.04), association between time since first TBI and PhNR amplitude. Our results suggest that there were no statistically significant differences in the objective structure or in the objective function of RGCs between the case cohort and the control cohort. Future large, longitudinal studies will be necessary to confirm our negative results and to more fully investigate the potential interaction between PhNR amplitude and time since first or last TBI.
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Affiliation(s)
- Kelly R. Klimo
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | | | - Erica Shelton
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | - Elizabeth Day
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | - Lisa Jordan
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | - Matthew Robich
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | - Julie Racine
- Department of Ophthalmology, Nationwide Children's Hospital, Columbus, OH, United States
| | | | - Dean A. VanNasdale
- College of Optometry, The Ohio State University, Columbus, OH, United States
| | - Phillip T. Yuhas
- College of Optometry, The Ohio State University, Columbus, OH, United States,*Correspondence: Phillip T. Yuhas
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Akira M, Yuichi T, Tomotaka U, Takaaki K, Kenichi M, Chimi M. The Outcome of Neurorehabilitation Efficacy and Management of Traumatic Brain Injury. Front Hum Neurosci 2022; 16:870190. [PMID: 35814948 PMCID: PMC9256961 DOI: 10.3389/fnhum.2022.870190] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Accepted: 05/31/2022] [Indexed: 11/13/2022] Open
Abstract
For public health professionals, traumatic brain injury (TBI) and its possible protracted repercussions are a significant source of worry. In opposed to patient neurorehabilitation with developed brain abnormalities of different etiologies, neurorehabilitation of affected persons has several distinct features. The clinical repercussions of the various types of TBI injuries will be discussed in detail in this paper. During severe TBI, the medical course frequently follows a familiar first sequence of coma, accompanied by disordered awareness, followed by agitation and forgetfulness, followed by return of function. Clinicians must be aware of common medical issues that might occur throughout the various stages of neurorehabilitation, for example, posttraumatic hydrocephalus, paroxysmal sympathetic hyperactivity and posttraumatic neuroendocrine disorders, at each step of the process. Furthermore, we address problems about the scheduling of various rehabilitation programs as well as the availability of current data for comprehensive rehabilitative neuropsychology techniques.
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Affiliation(s)
- Miyamoto Akira
- Faculty of Rehabilitation Sciences, Nishikyushu University, Kanzaki, Japan
| | - Takata Yuichi
- Faculty of Human Science, Hokkaido Bunkyo University, Eniwa, Japan
| | - Ueda Tomotaka
- Faculty of Rehabilitation Sciences, Nishikyushu University, Kanzaki, Japan
| | - Kubo Takaaki
- Division of Physical Therapy, Department of Rehabilitation, Faculty of Health Science, Kumamoto Health Science University, Kumamoto, Japan
| | - Mori Kenichi
- Omote Orthopedic Osteoporosis Clinic, Toyonaka, Japan
| | - Miyamoto Chimi
- Department of Occupational Therapy, Faculty of Health Science, Aino University, Ibaraki, Japan
- *Correspondence: Miyamoto Chimi,
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Sethi NK, Neidecker J. Neuroimaging in professional combat sports: consensus statement from the association of ringside physicians. PHYSICIAN SPORTSMED 2022:1-8. [PMID: 35678314 DOI: 10.1080/00913847.2022.2083922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Professional boxing, kickboxing, and mixed martial arts (MMA) are popular sports with substantial risk for both acute and chronic traumatic brain injury (TBI). Although rare, combat sports athletes have died in the ring or soon after the completion of a bout. Deaths in these instances are usually the result of an acute catastrophic neurological event such as an acute subdural hematoma (SDH). Other causes may include acute epidural hematoma (EDH), subarachnoid hemorrhage (SAH), intraparenchymal hemorrhage (IPH), or a controversial, rare, and still disputed clinical entity called second-impact syndrome (SIS). Neuroimaging or brain imaging is currently included in the process of registering for a license to compete in combat sports in some jurisdictions of the United States of America and around the world. However, the required imaging specifics and frequency vary with no consensus guidelines. The Association of Ringside Physicians (an international, nonprofit organization dedicated to the health and safety of the combat sports athlete) sets forth this consensus statement to establish neuroimaging guidelines in combat sports. Commissions, ringside physicians, combat sports athletes, trainers, promoters, sanctioning bodies, and other healthcare professionals can use this statement for risk stratification of a professional combat sports athlete prior to licensure, identifying high-risk athletes and for prognostication of the brain health of these athletes over the course of their career. Guidelines are also put forth regarding neuroimaging requirements in the immediate aftermath of a bout.
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Affiliation(s)
- Nitin K Sethi
- Department of Neurology, New York-Presbyterian Hospital, Weill Cornell Medical Center, New York, NY, USA
| | - John Neidecker
- Department of Sports Medicine, Orthopedic Specialists of North Carolina, Raleigh NC, USA
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32
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Battaglini D, Lopes-Pacheco M, Castro-Faria-Neto HC, Pelosi P, Rocco PRM. Laboratory Biomarkers for Diagnosis and Prognosis in COVID-19. Front Immunol 2022; 13:857573. [PMID: 35572561 PMCID: PMC9091347 DOI: 10.3389/fimmu.2022.857573] [Citation(s) in RCA: 79] [Impact Index Per Article: 39.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/31/2022] [Indexed: 01/08/2023] Open
Abstract
Severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) causes a wide spectrum of clinical manifestations, with progression to multiorgan failure in the most severe cases. Several biomarkers can be altered in coronavirus disease 2019 (COVID-19), and they can be associated with diagnosis, prognosis, and outcomes. The most used biomarkers in COVID-19 include several proinflammatory cytokines, neuron-specific enolase (NSE), lactate dehydrogenase (LDH), aspartate transaminase (AST), neutrophil count, neutrophils-to-lymphocytes ratio, troponins, creatine kinase (MB), myoglobin, D-dimer, brain natriuretic peptide (BNP), and its N-terminal pro-hormone (NT-proBNP). Some of these biomarkers can be readily used to predict disease severity, hospitalization, intensive care unit (ICU) admission, and mortality, while others, such as metabolomic and proteomic analysis, have not yet translated to clinical practice. This narrative review aims to identify laboratory biomarkers that have shown significant diagnostic and prognostic value for risk stratification in COVID-19 and discuss the possible clinical application of novel analytic strategies, like metabolomics and proteomics. Future research should focus on identifying a limited but essential number of laboratory biomarkers to easily predict prognosis and outcome in severe COVID-19.
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Affiliation(s)
- Denise Battaglini
- Anesthesia and Intensive Care, San Martino Policlinico Hospital, Instituto di Ricovero e Cura a Carattere Scientifico (IRCCS) for Oncology and Neuroscience, Genoa, Italy.,Department of Surgical Science and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy.,Department of Medicine, University of Barcelona, Barcelona, Spain
| | - Miquéias Lopes-Pacheco
- Laboratory of Pulmonary Investigation, Carlos Chagas Filho Biophysics Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Paolo Pelosi
- Anesthesia and Intensive Care, San Martino Policlinico Hospital, Instituto di Ricovero e Cura a Carattere Scientifico (IRCCS) for Oncology and Neuroscience, Genoa, Italy.,Department of Surgical Science and Integrated Diagnostics (DISC), University of Genoa, Genoa, Italy
| | - Patricia R M Rocco
- Laboratory of Pulmonary Investigation, Carlos Chagas Filho Biophysics Institute, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.,COVID-19 Virus Network from Brazilian Council for Scientific and Technological Development, Brasília, Brazil.,COVID-19 Virus Network from Foundation Carlos Chagas Filho Research Support of the State of Rio de Janeiro, Rio de Janeiro, Brazil
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Canseco JA, Franks RR, Karamian BA, Divi SN, Reyes AA, Mao JZ, Al Saiegh F, Donnally CJ, Schroeder GD, Harrop JS, Pepe MD, Vaccaro AR. Overview of Traumatic Brain Injury in American Football Athletes. Clin J Sport Med 2022; 32:236-247. [PMID: 33797476 DOI: 10.1097/jsm.0000000000000918] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 12/17/2020] [Indexed: 02/02/2023]
Abstract
OBJECTIVE The aim of this review is to provide a summary of the epidemiology, clinical presentation, pathophysiology, and treatment of traumatic brain injury in collision athletes, particularly those participating in American football. DATA SOURCES A literature search was conducted using the PubMed/MEDLINE and Google Scholar databases for publications between 1990 and 2019. The following search phrases were used: "concussion," "professional athletes," "collision athletes," "mild traumatic brain injury," "severe traumatic brain injury," "management of concussion," "management of severe traumatic brain injury," and "chronic traumatic encephalopathy." Publications that did not present epidemiology, clinical presentation, pathophysiology, radiological evaluation, or management were omitted. Classic articles as per senior author recommendations were retrieved through reference review. RESULTS The results of the literature review yielded 147 references: 21 articles discussing epidemiology, 16 discussing clinical presentation, 34 discussing etiology and pathophysiology, 10 discussing radiological evaluation, 34 articles for on-field management, and 32 articles for medical and surgical management. CONCLUSION Traumatic brain injuries are frequent in professional collision athletes, and more severe injuries can have devastating and lasting consequences. Although sport-related concussions are well studied in professional American football, there is limited literature on the epidemiology and management of severe traumatic brain injuries. This article reviews the epidemiology, as well as the current practices in sideline evaluation, acute management, and surgical treatment of concussions and severe traumatic brain injury in professional collision athletes. Return-to-play decisions should be based on individual patient symptoms and recovery.
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Affiliation(s)
- Jose A Canseco
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - R Robert Franks
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
- Rothman Sports Concussion Institute, Rothman Institute, Philadelphia, Pennsylvania; and
| | - Brian A Karamian
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Srikanth N Divi
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Ariana A Reyes
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Jennifer Z Mao
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Fadi Al Saiegh
- Department of Neurological Surgery, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Chester J Donnally
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Gregory D Schroeder
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - James S Harrop
- Department of Neurological Surgery, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Matthew D Pepe
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Alexander R Vaccaro
- Rothman Orthopaedic Institute at Thomas Jefferson University, Philadelphia, Pennsylvania
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Correa MA, Cardona S, Fernández LL, Griswold DP, Olaya SL, Sánchez DM, Rubiano AM. Implementation of the infrascanner in the detection of post-traumatic intracranial bleeding: A narrative review. BRAIN DISORDERS 2022. [DOI: 10.1016/j.dscb.2021.100026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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35
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Automated Intracranial Hematoma Classification in Traumatic Brain Injury (TBI) Patients Using Meta-Heuristic Optimization Techniques. INFORMATICS 2022. [DOI: 10.3390/informatics9010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Traumatic Brain Injury (TBI) is a devastating and life-threatening medical condition that can result in long-term physical and mental disabilities and even death. Early and accurate detection of Intracranial Hemorrhage (ICH) in TBI is crucial for analysis and treatment, as the condition can deteriorate significantly with time. Hence, a rapid, reliable, and cost-effective computer-aided approach that can initially capture the hematoma features is highly relevant for real-time clinical diagnostics. In this study, the Gray Level Occurrence Matrix (GLCM), the Gray Level Run Length Matrix (GLRLM), and Hu moments are used to generate the texture features. The best set of discriminating features are obtained using various meta-heuristic algorithms, and these optimal features are subjected to different classifiers. The synthetic samples are generated using ADASYN to compensate for the data imbalance. The proposed CAD system attained 95.74% accuracy, 96.93% sensitivity, and 94.67% specificity using statistical and GLRLM features along with KNN classifier. Thus, the developed automated system can enhance the accuracy of hematoma detection, aid clinicians in the fast interpretation of CT images, and streamline triage workflow.
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36
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Mohamed MAK, Alamri A, Smith B, Uff C. Applying Convolutional Neural Networks to Neuroimaging Classification Tasks: A Practical Guide in Python. ACTA NEUROCHIRURGICA. SUPPLEMENT 2021; 134:161-169. [PMID: 34862540 DOI: 10.1007/978-3-030-85292-4_20] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
In this chapter, we describe the process of obtaining medical imaging data and its storage protocol. The authors also explain in a step-by-step approach how to extract and prepare the medical imaging data for machine learning algorithms. And finally, the process of building and assessing a convolutional neural network for medical imaging data is illustrated.
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Affiliation(s)
- Moumin A K Mohamed
- Department of Neurosurgery, Royal London Hospital, London, UK. .,The London Neuro-Machine Learning Institute, Barts Health NHS Trust, London, UK.
| | - Alexander Alamri
- Department of Neurosurgery, Royal London Hospital, London, UK. .,The London Neuro-Machine Learning Institute, Barts Health NHS Trust, London, UK.
| | - Brandon Smith
- The London Neuro-Machine Learning Institute, Barts Health NHS Trust, London, UK
| | - Christopher Uff
- Department of Neurosurgery, Royal London Hospital, London, UK.,The London Neuro-Machine Learning Institute, Barts Health NHS Trust, London, UK
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37
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Perkins J, Shreffler J, Kamenec D, Bequer A, Ziemba C, O'Brien D, Shoff H, Smith J, Nash N, Huecker M. Short Observation Period and Aggressive Discharge of Patients With Head Injury and Serial CT Scans. Am Surg 2021:31348211063539. [PMID: 34823406 DOI: 10.1177/00031348211063539] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: Many patients undergo two head computed tomography (CT) scans after mild traumatic brain injury (TBI). Radiographic progression without clinical deterioration does not usually alter management. Evidence-based guidelines offer potential for limited repeat imaging and safe discharge. This study characterizes patients who had two head CTs in the Emergency Department (ED), determines the change between initial and repeat CTs, and describes timing of repeat scans.Methods: This retrospective series includes all patients with head CTs during the same ED visit at an urban trauma center between May 1st, 2016 and April 30th, 2018. Radiographic interpretation was coded as positive, negative, or equivocal.Results: Of 241 subjects, the number of positive, negative, and equivocal initial CT results were 154, 50, and 37, respectively. On repeat CT, 190 (78.8%) interpretations were congruent with the original scan. Out of the 21.2% of repeat scans that diverged from the original read, 14 (5.8%) showed positive to negative conversion, 1 (.4%) showed positive to equivocal conversion, 2 (.88%) showed negative to positive conversion, 20 (8.3%) showed equivocal to negative conversion, and 14 (5.8%) showed equivocal to positive conversion. Average time between scans was 4.4 hours, and median length of stay was 10.2 hours.Conclusions: In this retrospective review, most repeat CT scans had no new findings. A small percentage converted to positive, rarely altering clinical management. This study demonstrates the need for continued prospective research to update clinical guidelines that could reduce admission and serial CT scanning for mild TBI.
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Affiliation(s)
- Jordan Perkins
- 12254University of Louisville School of Medicine, Louisville, KY, USA
| | - Jacob Shreffler
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
| | - Danielle Kamenec
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
| | - Alexandra Bequer
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
| | - Corey Ziemba
- 12254University of Louisville School of Medicine, Louisville, KY, USA
| | - Dan O'Brien
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
| | - Hugh Shoff
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
| | - Jason Smith
- Department of Surgery, 5170University of Louisville, Louisville, KY, USA
| | - Nicholas Nash
- Department of Surgery, 5170University of Louisville, Louisville, KY, USA
| | - Martin Huecker
- Department of Emergency Medicine, 5170University of Louisville, Louisville, KY, USA
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Lee H, Yang Y, Xu J, Ware JB, Liu B. Use of Magnetic Resonance Imaging in Acute Traumatic Brain Injury Patients is Associated with Lower Inpatient Mortality. J Clin Imaging Sci 2021; 11:53. [PMID: 34754593 PMCID: PMC8571198 DOI: 10.25259/jcis_148_2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 09/13/2021] [Indexed: 11/26/2022] Open
Abstract
Objectives: While magnetic resonance imaging (MRI) has higher sensitivity than computed tomography for certain types of traumatic brain injury (TBI), it remains unknown whether the increased detection of intracranial injuries leads to improved clinical outcomes in acute TBI patients, especially given the resource requirements involved in performing MRI. We leveraged a large national patient database to examine associations between brain MRI utilization and inpatient clinical outcomes in hospitalized TBI patients. Material and Methods: The National Inpatient Sample database was queried to find 3,075 and 340,090 hospitalized TBI patients with and without brain MRI, respectively, between 2012 and 2014 in the United States. Multivariate regression analysis was performed to independently evaluate the association between brain MRI utilization and inpatient mortality rate, complications, and resource requirements. Results: The MRI group had a lower unadjusted mortality rate of 0.75% compared to 2.54% in the non-MRI group. On multivariate regression analysis, inpatient brain MRI was independently associated with lower mortality (adjusted OR 0.32, 95% CI 0.12–0.86), as well as higher rates of intracranial hemorrhage (adjusted OR 2.20, 95% CI 1.27–3.81) and non-home discharge (adjusted OR 1.33, 95% CI 1.07–1.67). Brain MRI was independently associated with 3.4 days (P < 0.001) and $8,934 (P < 0.001) increase in the total length and cost of hospital stay, respectively. Conclusion: We present the first evidence that inpatient brain MRI in TBI patients is associated with lower inpatient mortality, but with increased hospital resource utilization and likelihood of non-home discharge.
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Affiliation(s)
- Hwan Lee
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Yifeng Yang
- Department of Internal Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - Jiehui Xu
- Division of Biostatistics, New York University Grossman School of Medicine, New York, United States
| | - Jeffrey B Ware
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | - Baogiong Liu
- Department of Internal Medicine, University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Frank D, Gruenbaum BF, Shelef I, Zvenigorodsky V, Benjamin Y, Shapoval O, Gal R, Zlotnik A, Melamed I, Boyko M. A Novel Histological Technique to Assess Severity of Traumatic Brain Injury in Rodents: Comparisons to Neuroimaging and Neurological Outcomes. Front Neurosci 2021; 15:733115. [PMID: 34720861 PMCID: PMC8549653 DOI: 10.3389/fnins.2021.733115] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 09/13/2021] [Indexed: 12/19/2022] Open
Abstract
Here we evaluate an alternative protocol to histologically examine blood-brain barrier (BBB) breakdown, brain edema, and lesion volume following traumatic brain injury (TBI) in the same set of rodent brain samples. We further compare this novel histological technique to measurements determined by magnetic resonance imaging (MRI) and a neurological severity score (NSS). Sixty-six rats were randomly assigned to a sham-operated, mild TBI, moderate TBI, or severe TBI group. 48 h after TBI, NSS, MRI and histological techniques were performed to measure TBI severity outcome. Both the histological and MRI techniques were able to detect measurements of severity outcome, but histologically determined outcomes were more sensitive. The two most sensitive techniques for determining the degree of injury following TBI were NSS and histologically determined BBB breakdown. Our results demonstrate that BBB breakdown, brain edema, and lesion volume following TBI can be accurately measured by histological evaluation of the same set of brain samples.
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Affiliation(s)
- Dmitry Frank
- Department of Anesthesiology and Critical Care, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Benjamin F Gruenbaum
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Jacksonville, FL, United States
| | - Ilan Shelef
- Department of Radiology, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Vladislav Zvenigorodsky
- Department of Radiology, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Yair Benjamin
- Department of Anesthesiology and Critical Care, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Olha Shapoval
- Department of Physiology, Faculty of Biology, Ecology and Medicine, Dnepropetrovsk State University, Dnepropetrovsk, Ukraine
| | - Ron Gal
- Department of Anesthesiology and Critical Care, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Alexander Zlotnik
- Department of Anesthesiology and Critical Care, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Israel Melamed
- Department of Neurosurgery, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Matthew Boyko
- Department of Anesthesiology and Critical Care, Soroka University Medical Center, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Saleem GT, Fitzpatrick JM, Haider MN, Valera EM. COVID-19-induced surge in the severity of gender-based violence might increase the risk for acquired brain injuries. SAGE Open Med 2021; 9:20503121211050197. [PMID: 34707866 PMCID: PMC8543566 DOI: 10.1177/20503121211050197] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 09/14/2021] [Indexed: 12/18/2022] Open
Abstract
While initial reports have emphasized a global rise in the frequency of intimate partner violence following COVID-19, emerging data are now showing a concerning surge in the severity of COVID-19-induced physical intimate partner violence. One of the most dangerous, frequent, yet hidden consequences of severe physical intimate partner violence is acquired brain injury, including repetitive mild traumatic brain injury and hypoxic brain injury. Although the increase in high-risk physical abuse during COVID-19 is gaining recognition, what still remains absent is the urgent discussion on intimate partner violence-related acquired brain injury during these times. The potential analogous surge in intimate partner violence-related acquired brain injury may have implications for both healthcare providers and healthcare actions/policies as repeated brain injuries have been associated with residual functional deficits and chronic disability. In addition, even in the pre-pandemic times, intimate partner violence-related acquired brain injury is likely unrecognized and/or misclassified due to overlap in symptoms with other comorbid disorders. This review aimed to raise awareness about intimate partner violence-related acquired brain injury within the context of COVID-19. Health actions and policies that should be considered as part of the pandemic response to minimize adverse outcomes associated with intimate partner violence-related acquired brain injury have also been discussed.
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41
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Schwab N, Leung E, Hazrati LN. Cellular Senescence in Traumatic Brain Injury: Evidence and Perspectives. Front Aging Neurosci 2021; 13:742632. [PMID: 34650425 PMCID: PMC8505896 DOI: 10.3389/fnagi.2021.742632] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/03/2021] [Indexed: 12/14/2022] Open
Abstract
Mild traumatic brain injury (mTBI) can lead to long-term neurological dysfunction and increase one's risk of neurodegenerative disease. Several repercussions of mTBI have been identified and well-studied, including neuroinflammation, gliosis, microgliosis, excitotoxicity, and proteinopathy – however the pathophysiological mechanisms activating these pathways after mTBI remains controversial and unclear. Emerging research suggests DNA damage-induced cellular senescence as a possible driver of mTBI-related sequalae. Cellular senescence is a state of chronic cell-cycle arrest and inflammation associated with physiological aging, mood disorders, dementia, and various neurodegenerative pathologies. This narrative review evaluates the existing studies which identify DNA damage or cellular senescence after TBI (including mild, moderate, and severe TBI) in both experimental animal models and human studies, and outlines how cellular senescence may functionally explain both the molecular and clinical manifestations of TBI. Studies on this subject clearly show accumulation of various forms of DNA damage (including oxidative damage, single-strand breaks, and double-strand breaks) and senescent cells after TBI, and indicate that cellular senescence may be an early event after TBI. Further studies are required to understand the role of sex, cell-type specific mechanisms, and temporal patterns, as senescence may be a pathway of interest to target for therapeutic purposes including prognosis and treatment.
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Affiliation(s)
- Nicole Schwab
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.,The Hospital for Sick Children, Toronto, ON, Canada
| | - Emily Leung
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.,The Hospital for Sick Children, Toronto, ON, Canada
| | - Lili-Naz Hazrati
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.,The Hospital for Sick Children, Toronto, ON, Canada
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Vanishing White Matter Disease Diagnosis After Athletic Concussion in an Adolescent Male Patient. Clin J Sport Med 2021; 31:e207-e209. [PMID: 31688083 DOI: 10.1097/jsm.0000000000000783] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2019] [Accepted: 06/19/2019] [Indexed: 02/02/2023]
Abstract
We report the recognition of a diagnosis of leukoencephalopathy with vanishing white matter, also known as vanishing white matter disease in an adolescent male patient after a sports-related concussion. The patient's atypical symptoms after the concussion led to imaging and subsequent neurological consultation. The objective of this clinical case is to highlight the importance of considering imaging in patients who present with atypical symptoms that may be present after a concussion and to raise awareness of this rare disorder which can present after head trauma.
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43
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V. V, Gudigar A, Raghavendra U, Hegde A, Menon GR, Molinari F, Ciaccio EJ, Acharya UR. Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:6499. [PMID: 34208596 PMCID: PMC8296416 DOI: 10.3390/ijerph18126499] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/07/2021] [Accepted: 06/09/2021] [Indexed: 12/17/2022]
Abstract
Traumatic brain injury (TBI) occurs due to the disruption in the normal functioning of the brain by sudden external forces. The primary and secondary injuries due to TBI include intracranial hematoma (ICH), raised intracranial pressure (ICP), and midline shift (MLS), which can result in significant lifetime disabilities and death. Hence, early diagnosis of TBI is crucial to improve patient outcome. Computed tomography (CT) is the preferred modality of choice to assess the severity of TBI. However, manual visualization and inspection of hematoma and its complications from CT scans is a highly operator-dependent and time-consuming task, which can lead to an inappropriate or delayed prognosis. The development of computer aided diagnosis (CAD) systems could be helpful for accurate, early management of TBI. In this paper, a systematic review of prevailing CAD systems for the detection of hematoma, raised ICP, and MLS in non-contrast axial CT brain images is presented. We also suggest future research to enhance the performance of CAD for early and accurate TBI diagnosis.
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Affiliation(s)
- Vidhya V.
- Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India;
| | - Anjan Gudigar
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India;
| | - U. Raghavendra
- Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India;
| | - Ajay Hegde
- Institute of Neurological Sciences, Glasgow G51 4LB, UK;
- Department of Neurosurgery, Kasturba Medical College, Manipal Academy of Higher Education, Manipal 576104, India;
| | - Girish R. Menon
- Department of Neurosurgery, Kasturba Medical College, Manipal Academy of Higher Education, Manipal 576104, India;
| | - Filippo Molinari
- Department of Electronics, Politecnico di Torino, 24 Corso Duca degli Abruzzi, 10129 Torino, Italy;
| | - Edward J. Ciaccio
- Department of Medicine, Columbia University, New York, NY 10032, USA;
| | - U. Rajendra Acharya
- School of Engineering, Ngee Ann Polytechnic, 535 Clementi Road, Singapore 599489, Singapore;
- Department of Biomedical Engineering, School of Science and Technology, SUSS University, 463 Clementi Road, Singapore 599491, Singapore
- Department of Bioinformatics and Medical Engineering, Asia University, Taichung 41354, Taiwan
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44
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Paek AY, Brantley JA, Evans BJ, Contreras-Vidal JL. Concerns in the Blurred Divisions between Medical and Consumer Neurotechnology. IEEE SYSTEMS JOURNAL 2021; 15:3069-3080. [PMID: 35126800 PMCID: PMC8813044 DOI: 10.1109/jsyst.2020.3032609] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Neurotechnology has traditionally been central to the diagnosis and treatment of neurological disorders. While these devices have initially been utilized in clinical and research settings, recent advancements in neurotechnology have yielded devices that are more portable, user-friendly, and less expensive. These improvements allow laypeople to monitor their brain waves and interface their brains with external devices. Such improvements have led to the rise of wearable neurotechnology that is marketed to the consumer. While many of the consumer devices are marketed for innocuous applications, such as use in video games, there is potential for them to be repurposed for medical use. How do we manage neurotechnologies that skirt the line between medical and consumer applications and what can be done to ensure consumer safety? Here, we characterize neurotechnology based on medical and consumer applications and summarize currently marketed uses of consumer-grade wearable headsets. We lay out concerns that may arise due to the similar claims associated with both medical and consumer devices, the possibility of consumer devices being repurposed for medical uses, and the potential for medical uses of neurotechnology to influence commercial markets related to employment and self-enhancement.
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Affiliation(s)
- Andrew Y Paek
- Department of Electrical & Computer Engineering and the IUCRC BRAIN Center at the University of Houston, Houston, TX, USA
| | - Justin A Brantley
- Department of Electrical & Computer Engineering and the IUCRC BRAIN Center at the University of Houston. He is now with the Department of Bioengineering at the University of Pennsylvania, Philadelphia, PA, USA
| | - Barbara J Evans
- Law Center and IUCRC BRAIN Center at the University of Houston. University of Houston, Houston, TX. She is now with the Wertheim College of Engineering and Levin College of Law at the University of Florida, Gainesville, FL, USA
| | - Jose L Contreras-Vidal
- Department of Electrical & Computer Engineering and the IUCRC BRAIN Center at the University of Houston, Houston, TX, USA
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45
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Fryc AM, Raudales AM, Nelson-Aguiar RR, Risi MM, Weiss NH. The Role of Presumed Head and Neck Injuries in Emotion Dysregulation Among Community Women With a History of Physical Intimate Partner Violence. Violence Against Women 2021; 28:417-442. [PMID: 34018422 DOI: 10.1177/10778012211005568] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Intimate partner violence (IPV) is prevalent among women and associated with negative outcomes, including emotion dysregulation. Limited research has examined factors that contribute to emotion dysregulation in this population. This study explores the potential influence of presumed head and neck injuries from IPV on five dimensions of emotion dysregulation. Participants were 352 community women who responded to an online survey. Results of a path analysis indicated that presumed head and neck injuries from IPV were significantly associated with lack of emotional clarity and difficulties engaging in goal-directed behaviors when experiencing emotions. Findings suggest an association between presumed head and neck injuries from IPV and emotion dysregulation, underscoring the potential need for considering both neurological and psychological factors in the assessment and treatment of emotion dysregulation in this population.
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46
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Nikam RM, Yue X, Kandula VV, Paudyal B, Langhans SA, Averill LW, Choudhary AK. Unravelling neuroinflammation in abusive head trauma with radiotracer imaging. Pediatr Radiol 2021; 51:966-970. [PMID: 33999238 DOI: 10.1007/s00247-021-04995-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 12/07/2020] [Accepted: 01/27/2021] [Indexed: 01/07/2023]
Abstract
Abusive head trauma (AHT) is a leading cause of mortality and morbidity in child abuse, with a mortality rate of approximately 25%. In survivors, the prognosis remains dismal, with high prevalence of cerebral palsy, epilepsy and neuropsychiatric disorders. Early and accurate diagnosis of AHT is challenging, both clinically and radiologically, with up to one-third of cases missed on initial examination. Moreover, most of the management in AHT is supportive, reflective of the lack of clear understanding of specific pathogenic mechanisms underlying secondary insult, with approaches targeted toward decreasing intracranial hypertension and reducing cerebral metabolism, cell death and excitotoxicity. Multiple studies have elucidated the role of pro- and anti-inflammatory cytokines and chemokines with upregulation/recruitment of microglia/macrophages, oligodendrocytes and astrocytes in severe traumatic brain injury (TBI). In addition, recent studies in animal models of AHT have demonstrated significant upregulation of microglia, with a potential role of inflammatory cascade contributing to secondary insult. Despite the histological and biochemical evidence, there is a significant dearth of specific imaging approaches to identify this neuroinflammation in AHT. The primary motivation for development of such imaging approaches stems from the need to therapeutically target neuroinflammation and establish its utility in monitoring and prognostication. In the present paper, we discuss the available data suggesting the potential role of neuroinflammation in AHT and role of radiotracer imaging in aiding diagnosis and patient management.
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Affiliation(s)
- Rahul M Nikam
- Department of Medical Imaging, Nemours Alfred I. duPont Hospital for Children, 1600 Rockland Road, Wilmington, DE, 19803, USA. .,Katzin Diagnostic & Research PET/MR Center, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA.
| | - Xuyi Yue
- Katzin Diagnostic & Research PET/MR Center, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA
| | - Vinay V Kandula
- Department of Medical Imaging, Nemours Alfred I. duPont Hospital for Children, 1600 Rockland Road, Wilmington, DE, 19803, USA
| | - Bishnuhari Paudyal
- Katzin Diagnostic & Research PET/MR Center, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA
| | - Sigrid A Langhans
- Katzin Diagnostic & Research PET/MR Center, Nemours Alfred I. duPont Hospital for Children, Wilmington, DE, USA
| | - Lauren W Averill
- Department of Medical Imaging, Nemours Alfred I. duPont Hospital for Children, 1600 Rockland Road, Wilmington, DE, 19803, USA
| | - Arabinda K Choudhary
- Department of Radiology, University of Arkansas for Medical Sciences (UAMS), Little Rock, AR, USA
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47
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Hecht S, Anderson KM, Castel A, Griffin JF, Hespel AM, Nelson N, Sun X. Agreement of Magnetic Resonance Imaging With Computed Tomography in the Assessment for Acute Skull Fractures in a Canine and Feline Cadaver Model. Front Vet Sci 2021; 8:603775. [PMID: 33969028 PMCID: PMC8100023 DOI: 10.3389/fvets.2021.603775] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 03/26/2021] [Indexed: 12/05/2022] Open
Abstract
Computed tomography (CT) is the imaging modality of choice to evaluate patients with acute head trauma. However, magnetic resonance imaging (MRI) may be chosen in select cases. The objectives of this study were to evaluate the agreement of MRI with CT in the assessment for presence or absence of acute skull fractures in a canine and feline cadaver model, compare seven different MRI sequences (T1-W, T2-W, T2-FLAIR, PD-W, T2*-W, “SPACE” and “VIBE”), and determine agreement of four different MRI readers with CT data. Pre- and post-trauma CT and MRI studies were performed on 10 canine and 10 feline cadaver heads. Agreement of MRI with CT as to presence or absence of a fracture was determined for 26 individual osseous structures and four anatomic regions (cranium, face, skull base, temporomandibular joint). Overall, there was 93.5% agreement in assessing a fracture as present or absent between MRI and CT, with a significant difference between the pre and post trauma studies (99.4 vs. 87.6%; p < 0.0001; OR 0.042; 95% CI 0.034–0.052). There was no significant difference between dogs and cats. The agreement for the different MRI sequences with CT ranged from 92.6% (T2*-W) to 94.4% (PD-W). There was higher agreement of MRI with CT in the evaluation for fractures of the face than other anatomic regions. Agreement with CT for individual MRI readers ranged from 92.6 to 94.7%. A PD-W sequence should be added to the MR protocol when evaluating the small animal head trauma patient.
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Affiliation(s)
- Silke Hecht
- Department of Small Animal Clinical Sciences, University of Tennessee, Knoxville, TN, United States
| | - Kimberly M Anderson
- Department of Small Animal Clinical Sciences, University of Tennessee, Knoxville, TN, United States
| | - Aude Castel
- Department of Small Animal Clinical Sciences, University of Tennessee, Knoxville, TN, United States
| | - John F Griffin
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, United States
| | - Adrien-Maxence Hespel
- Department of Small Animal Clinical Sciences, University of Tennessee, Knoxville, TN, United States
| | - Nathan Nelson
- Department of Molecular and Biomedical Sciences, North Carolina State University, Raleigh, NC, United States
| | - Xiaocun Sun
- Office of Information Technology, University of Tennessee, Knoxville, TN, United States
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48
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Dhillon NS, Sutandi A, Vishwanath M, Lim MM, Cao H, Si D. A Raspberry Pi-Based Traumatic Brain Injury Detection System for Single-Channel Electroencephalogram. SENSORS 2021; 21:s21082779. [PMID: 33920805 PMCID: PMC8071098 DOI: 10.3390/s21082779] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 04/09/2021] [Accepted: 04/13/2021] [Indexed: 12/25/2022]
Abstract
Traumatic Brain Injury (TBI) is a common cause of death and disability. However, existing tools for TBI diagnosis are either subjective or require extensive clinical setup and expertise. The increasing affordability and reduction in the size of relatively high-performance computing systems combined with promising results from TBI related machine learning research make it possible to create compact and portable systems for early detection of TBI. This work describes a Raspberry Pi based portable, real-time data acquisition, and automated processing system that uses machine learning to efficiently identify TBI and automatically score sleep stages from a single-channel Electroencephalogram (EEG) signal. We discuss the design, implementation, and verification of the system that can digitize the EEG signal using an Analog to Digital Converter (ADC) and perform real-time signal classification to detect the presence of mild TBI (mTBI). We utilize Convolutional Neural Networks (CNN) and XGBoost based predictive models to evaluate the performance and demonstrate the versatility of the system to operate with multiple types of predictive models. We achieve a peak classification accuracy of more than 90% with a classification time of less than 1 s across 16–64 s epochs for TBI vs. control conditions. This work can enable the development of systems suitable for field use without requiring specialized medical equipment for early TBI detection applications and TBI research. Further, this work opens avenues to implement connected, real-time TBI related health and wellness monitoring systems.
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Affiliation(s)
- Navjodh Singh Dhillon
- Computing and Software Systems, University of Washington, Bothell, WA 98011, USA; (N.S.D.); (A.S.)
| | - Agustinus Sutandi
- Computing and Software Systems, University of Washington, Bothell, WA 98011, USA; (N.S.D.); (A.S.)
| | - Manoj Vishwanath
- Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA;
| | - Miranda M. Lim
- VA Portland Health Care System, Portland, OR 97239, USA;
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA
| | - Hung Cao
- Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA;
- Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA
- Correspondence: (H.C.); (D.S.); Tel.: +1-949-824-8478 (H.C.); +1-425-352-5389 (D.S.)
| | - Dong Si
- Computing and Software Systems, University of Washington, Bothell, WA 98011, USA; (N.S.D.); (A.S.)
- Correspondence: (H.C.); (D.S.); Tel.: +1-949-824-8478 (H.C.); +1-425-352-5389 (D.S.)
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49
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Russell-Schulz B, Vavasour IM, Zhang J, MacKay AL, Purcell V, Muller AM, Brucar LR, Torres IJ, Panenka WJ, Virji-Babul N. Myelin water fraction decrease in individuals with chronic mild traumatic brain injury and persistent symptoms. Heliyon 2021; 7:e06709. [PMID: 33898831 PMCID: PMC8056430 DOI: 10.1016/j.heliyon.2021.e06709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 12/11/2020] [Accepted: 03/31/2021] [Indexed: 11/18/2022] Open
Abstract
The diffuse and continually evolving secondary changes after mild traumatic brain injury (mTBI) make it challenging to assess alterations in brain-behaviour relationships. In this study we used myelin water imaging to evaluate changes in myelin water fraction (MWF) in individuals with chronic mTBI and persistent symptoms and measured their cognitive status using the NIH Toolbox Cognitive Battery. Fifteen adults with mTBI with persistent symptoms and twelve age, gender and education matched healthy controls took part in this study. We found a significant decrease in global white matter MWF in patients compared to the healthy controls. Significantly lower MWF was evident in most white matter region of interest (ROIs) examined including the corpus callosum (separated into genu, body and splenium), minor forceps, right anterior thalamic radiation, left inferior longitudinal fasciculus; and right and left superior longitudinal fasciculus and corticospinal tract. Although patients showed lower cognitive functioning, no significant correlations were found between MWF and cognitive measures. These results suggest that individuals with chronic mTBI who have persistent symptoms have reduced MWF.
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Affiliation(s)
- Bretta Russell-Schulz
- UBC MRI Research Centre, Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Irene M. Vavasour
- UBC MRI Research Centre, Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Jing Zhang
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Alex L. MacKay
- UBC MRI Research Centre, Department of Radiology, University of British Columbia, Vancouver, BC, Canada
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada
| | - Victoria Purcell
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Angela M. Muller
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Leyla R. Brucar
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Ivan J. Torres
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
- BC Mental Health and Substance Use Services, Vancouver, BC, Canada
| | - William J. Panenka
- BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, BC, Canada
| | - Naznin Virji-Babul
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
- Department of Physical Therapy, University of British Columbia, Vancouver, BC, Canada
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50
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Fischer VE, Boulter JH, Bell RS, Ikeda DS. Paradoxical Contralateral Herniation Detected by Pupillometry in Acute Syndrome of the Trephined. Mil Med 2021; 185:532-536. [PMID: 32236451 DOI: 10.1093/milmed/usz409] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 08/22/2019] [Accepted: 10/15/2019] [Indexed: 12/23/2022] Open
Abstract
Severe traumatic brain injury has historically been a non-survivable injury. Recent advances in neurosurgical care, however, have demonstrated that these patients not only can survive, but they also can recover functionally when they undergo appropriate cerebral decompression within hours of injury. At the present, general surgeons are deployed further forward than neurosurgeons (Role 2 compared to Role 3) and have been provided with guidelines that stipulate conditions where they may have to perform decompressive craniectomies. Unfortunately, Role 2 medical facilities do not have access to computed tomography imaging or intracranial pressure monitoring capabilities rendering the decision to proceed with craniectomy based solely on exam findings. Utilizing a case transferred from downrange to our institution, we demonstrate the utility of a small, highly portable quantitative pupillometer to obtain reliable and reproducible data about a patient's intracranial pressures. Following the case presentation, the literature supporting quantitative pupillometry for surgical decision-making is reviewed.
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Affiliation(s)
- Victoria E Fischer
- University of Texas Health Science Center at San Antonio, Division of Neurosurgery, 7703 Floyd Curl Drive, MC 7843, San Antonio, TX 78229
| | - Jason H Boulter
- Walter Reed National Military Medical Center, Division of Neurosurgery, 8901 Rockville Pike, Bethesda, MD 20814
| | - Randy S Bell
- Walter Reed National Military Medical Center, Division of Neurosurgery, 8901 Rockville Pike, Bethesda, MD 20814
| | - Daniel S Ikeda
- Walter Reed National Military Medical Center, Division of Neurosurgery, 8901 Rockville Pike, Bethesda, MD 20814
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