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Flusund AMH, Bø LE, Reinertsen I, Solheim O, Skandsen T, Håberg A, Andelic N, Vik A, Moen KG. Lesion Frequency Distribution Maps of Traumatic Axonal Injury on Early Magnetic Resonance Imaging After Moderate and Severe Traumatic Brain Injury and Associations to 12 Months Outcome. J Neurotrauma 2024; 41:1901-1913. [PMID: 38588255 DOI: 10.1089/neu.2023.0534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/10/2024] Open
Abstract
Traumatic axonal injury (TAI) is a common finding on magnetic resonance imaging (MRI) in patients with moderate-severe traumatic brain injury (TBI), and the burden of TAI is associated with outcome in this patient group. Lesion mapping offers a way to combine imaging findings from numerous individual patients into common lesion maps where the findings from a whole patient cohort can be assessed. The aim of this study was to evaluate the spatial distribution of TAI lesions on different MRI sequences and its associations to outcome with use of lesion mapping. Included prospectively were 269 patients (8-70 years) with moderate or severe TBI and MRI within six weeks after injury. The TAI lesions were evaluated and manually segmented on fluid-attenuated inversed recovery (FLAIR), diffusion weighted imaging (DWI), and either T2* gradient echo (T2*GRE) or susceptibility weighted imaging (SWI). The segmentations were registered to the Montreal Neurological Institute space and combined to lesion frequency distribution maps. Outcome was assessed with Glasgow Outcome Scale Extended (GOSE) score at 12 months. The frequency and distribution of TAI was assessed qualitatively by visual reading. Univariable associations to outcome were assessed qualitatively by visual reading and also quantitatively with use of voxel-based lesion-symptom mapping (VLSM). The highest frequency of TAI was found in the posterior half of corpus callosum. The frequency of TAI was higher in the frontal and temporal lobes than in the parietal and occipital lobes, and in the upper parts of the brainstem than in the lower. At the group level, all voxels in mesencephalon had TAI on FLAIR. The patients with poorest outcome (GOSE scores ≤4) had higher frequencies of TAI. On VLSM, poor outcome was associated with TAI lesions bilaterally in the splenium, the right side of tectum, tegmental mesencephalon, and pons. In conclusion, we found higher frequency of TAI in posterior corpus callosum, and TAI in splenium, mesencephalon, and pons were associated with poor outcome. If lesion frequency distribution maps containing outcome information based on imaging findings from numerous patients in the future can be compared with the imaging findings from individual patients, it would offer a new tool in the clinical workup and outcome prediction of the patient with TBI.
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Affiliation(s)
- Anne-Mari Holte Flusund
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology, Møre and Romsdal Hospital Trust, Molde Hospital, Molde, Norway
| | - Lars Eirik Bø
- SINTEF Digital, Department of Health Research, Trondheim, Norway
| | - Ingerid Reinertsen
- SINTEF Digital, Department of Health Research, Trondheim, Norway
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Ole Solheim
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Toril Skandsen
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Asta Håberg
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Nada Andelic
- Institute of Health and Society, Research Centre for Habilitation and Rehabilitation Models and Services (CHARM), Faculty of Medicine, University of Oslo, Oslo, Norway
- Department of Physical Medicine and Rehabilitation, Oslo University Hospital, Ullevål, Norway
| | - Anne Vik
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Kent Gøran Moen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Radiology, Vestre Viken Hospital Trust, Drammen Hospital, Drammen, Norway
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Colclough Z, Estrella MJ, Joyce JM, Hanafy S, Babineau J, Colantonio A, Chan V. Equity considerations in clinical practice guidelines for traumatic brain injury and the criminal justice system: A systematic review. PLoS Med 2024; 21:e1004418. [PMID: 39134041 PMCID: PMC11319042 DOI: 10.1371/journal.pmed.1004418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 05/22/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND Traumatic brain injury (TBI) is disproportionately prevalent among individuals who intersect or are involved with the criminal justice system (CJS). In the absence of appropriate care, TBI-related impairments, intersecting social determinants of health, and the lack of TBI awareness in CJS settings can lead to lengthened sentences, serious disciplinary charges, and recidivism. However, evidence suggests that most clinical practice guidelines (CPGs) overlook equity and consequently, the needs of disadvantaged groups. As such, this review addressed the research question "To what extent are (1) intersections with the CJS considered in CPGs for TBI, (2) TBI considered in CPGs for CJS, and (3) equity considered in CPGs for CJS?". METHODS AND FINDINGS CPGs were identified from electronic databases (MEDLINE, Embase, CINAHL, PsycINFO), targeted websites, Google Search, and reference lists of identified CPGs on November 2021 and March 2023 (CPGs for TBI) and May 2022 and March 2023 (CPGs for CJS). Only CPGs for TBI or CPGs for CJS were included. We calculated the proportion of CPGs that included TBI- or CJS-specific content, conducted a qualitative content analysis to understand how evidence regarding TBI and the CJS was integrated in the CPGs, and utilised equity assessment tools to understand if and how equity was considered. Fifty-seven CPGs for TBI and 6 CPGs for CJS were included in this review. Fourteen CPGs for TBI included information relevant to the CJS, but only 1 made a concrete recommendation to consider legal implications during vocational evaluation in the forensic context. Two CPGs for CJS acknowledged the prevalence of TBI among individuals in prison and one specifically recommended considering TBI during health assessments. Both CPGs for TBI and CPGs for CJS provided evidence specific to a single facet of the CJS, predominantly in policing and corrections. The use of equity best practices and the involvement of disadvantaged groups in the development process were lacking among CPGs for CJS. We acknowledge limitations of the review, including that our searches were conducted in English language and thus, we may have missed other non-English language CPGs in this review. We further recognise that we are unable to comment on evidence that is not integrated in the CPGs, as we did not systematically search for research on individuals with TBI who intersect with the CJS, outside of CPGs. CONCLUSIONS Findings from this review provide the foundation to consider CJS involvement in CPGs for TBI and to advance equity in CPGs for CJS. Conducting research, including investigating the process of screening for TBI with individuals who intersect with all facets of the CJS, and utilizing equity assessment tools in guideline development are critical steps to enhance equity in healthcare for this disadvantaged group.
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Affiliation(s)
- Zoe Colclough
- Department of Forensic Science, University of Toronto, Mississauga, Canada
| | - Maria Jennifer Estrella
- Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada
| | - Julie Michele Joyce
- Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada
| | - Sara Hanafy
- Rehabilitation Sciences Institute, University of Toronto, Toronto, Canada
- KITE Research Institute-Toronto Rehabilitation Institute, University Health Network, Toronto, Canada
| | - Jessica Babineau
- Library and Information Services, University Health Network, Toronto, Canada
- The Institute for Education Research, University Health Network, Toronto, Canada
| | - Angela Colantonio
- Department of Occupational Science and Occupational Therapy, University of Toronto, Toronto, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, Canada
- KITE Research Institute-Toronto Rehabilitation Institute, University Health Network, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Vincy Chan
- Rehabilitation Sciences Institute, University of Toronto, Toronto, Canada
- KITE Research Institute-Toronto Rehabilitation Institute, University Health Network, Toronto, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
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Gerhalter T, Chen AM, Dehkharghani S, Peralta R, Gajdosik M, Zarate A, Bushnik T, Silver JM, Im BS, Wall SP, Madelin G, Kirov II. Longitudinal changes in sodium concentration and in clinical outcome in mild traumatic brain injury. Brain Commun 2024; 6:fcae229. [PMID: 39035416 PMCID: PMC11258572 DOI: 10.1093/braincomms/fcae229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Revised: 06/10/2024] [Accepted: 07/09/2024] [Indexed: 07/23/2024] Open
Abstract
Ionic imbalances and sodium channel dysfunction, well-known sequelae of traumatic brain injury (TBI), promote functional impairment in affected subjects. Therefore, non-invasive measurement of sodium concentrations using 23Na MRI has the potential to detect clinically relevant injury and predict persistent symptoms. Recently, we reported diffusely lower apparent total sodium concentrations (aTSC) in mild TBI patients compared to controls, as well as correlations between lower aTSC and worse clinical outcomes. The main goal of this study was to determine whether these aTSC findings, and their changes over time, predict outcomes at 3- and 12-month from injury. Twenty-seven patients previously studied with 23Na MRI and outcome measures at 22 ± 10 days (average ± standard deviation) after injury (visit-1, v1) were contacted at 3- (visit-2, v2) and 12-month after injury (visit-3, v3) to complete the Rivermead post-concussion symptoms questionnaire (RPQ), the extended Glasgow outcome scale (GOSE), and the brief test of adult cognition by telephone (BTACT). Follow-up 1H and 23Na MRI were additionally scheduled at v2. Linear regression was used to calculate aTSC in global grey and white matters. Six hypotheses were tested in relation to the serial changes in outcome measures and in aTSC, and in relation to the cross-sectional and serial relationships between aTSC and outcome. Twenty patients contributed data at v2 and fifteen at v3. Total RPQ and composite BTACT z-scores differed significantly for v2 and v3 in comparison to v1 (each P < 0.01), reflecting longitudinally reduced symptomatology and improved performance on cognitive testing. No associations between aTSC and outcome were observed at v2. Previously lower grey and white matter aTSC normalized at v2 in comparison to controls, in line with a statistically detectable longitudinal increase in grey matter aTSC between v1 and v2 (P = 0.0004). aTSC values at v1 predicted a subset of future BTACT subtest scores, but not future RPQ scores nor GOSE-defined recovery status. Similarly, aTSC rates of change correlated with BTACT rates of change, but not with those of RPQ. Tissue aTSC, previously shown to be diffusely decreased compared to controls at v1, was no longer reduced by v2, suggesting normalization of the sodium ionic equilibrium. These changes were accompanied by marked improvement in outcome. The results support the notion that early aTSC from 23Na MRI predicts future BTACT, but not RPQ scores, nor future GOSE status.
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Affiliation(s)
- Teresa Gerhalter
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Anna M Chen
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Seena Dehkharghani
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Rosemary Peralta
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Mia Gajdosik
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Alejandro Zarate
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Tamara Bushnik
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Jonathan M Silver
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Brian S Im
- Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Stephen P Wall
- Ronald O. Perelman Department of Emergency Medicine, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Guillaume Madelin
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
| | - Ivan I Kirov
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Advanced Imaging Innovation and Research (CAIR), Department of Radiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Neurology, New York University Grossman School of Medicine, New York, NY 10016, USA
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Wintermark M, Allen JW, Anzai Y, Das T, Flanders AE, Galanaud D, Gean A, Haller S, Lv H, Hirvonen J, Jordan JE, Lee R, Lui YW, Sundgren PC, Mukherjee P, Moen KG, Muto M, Ng K, Niogi SN, Rovira A, de Bruxellas NL, Smits M, Tsiouris AJ, Van Goethem J, Vyvere TV, Whitlow C, Wiesmann M, Yamada K, Zakharova N, Parizel PM. Standardized reporting for Head CT Scans in patients suspected of traumatic brain injury (TBI): An international expert endeavor. Neuroradiology 2024:10.1007/s00234-024-03410-2. [PMID: 38963424 DOI: 10.1007/s00234-024-03410-2] [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: 04/07/2024] [Accepted: 06/20/2024] [Indexed: 07/05/2024]
Abstract
BACKGROUND AND PURPOSE Traumatic brain injury (TBI) is a major source of health loss and disability worldwide. Accurate and timely diagnosis of TBI is critical for appropriate treatment and management of the condition. Neuroimaging plays a crucial role in the diagnosis and characterization of TBI. Computed tomography (CT) is the first-line diagnostic imaging modality typically utilized in patients with suspected acute mild, moderate and severe TBI. Radiology reports play a crucial role in the diagnostic process, providing critical information about the location and extent of brain injury, as well as factors that could prevent secondary injury. However, the complexity and variability of radiology reports can make it challenging for healthcare providers to extract the necessary information for diagnosis and treatment planning. METHODS/RESULTS/CONCLUSION In this article, we report the efforts of an international group of TBI imaging experts to develop a clinical radiology report template for CT scans obtained in patients suspected of TBI and consisting of fourteen different subdivisions (CT technique, mechanism of injury or clinical history, presence of scalp injuries, fractures, potential vascular injuries, potential injuries involving the extra-axial spaces, brain parenchymal injuries, potential injuries involving the cerebrospinal fluid spaces and the ventricular system, mass effect, secondary injuries, prior or coexisting pathology).
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Affiliation(s)
- Max Wintermark
- Department of Neuroradiology, The University of Teas MD Anderson Center, Houston, TX, USA.
| | - Jason W Allen
- Department of Radiology, University of Indiana, Indianapolis, IN, USA
| | - Yoshimi Anzai
- Department of Radiology, University of Utah, Salt Lake City, UT, USA
| | - Tilak Das
- Department of Radiology, Cambridge University Hospitals, Cambridge, UK
| | - Adam E Flanders
- Department of Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Damien Galanaud
- Department of Neuroradiology, Pitie Salpetrière Hospital & Sorbonne, Universite, Paris, France
| | - Alisa Gean
- Department of Radiology, University of California San Francisco, San Francisco, CA, USA
| | - Sven Haller
- Department of Imaging and Medical Informatics, University Hospitals of Geneva and Faculty of Medicine of the University of Geneva, Geneva, Switzerland
| | - Han Lv
- Department of Radiology, Capital Medical University Affiliated Beijing Friendship Hospital, Beijing, 100050, China
| | - Jussi Hirvonen
- Department of Radiology, Tampere University, Faculty of Medicine and Health Technology, and Tampere University Hospital, Tampere, Finland
| | - John E Jordan
- Providence Little Company of Mary Medical Center-Torrance, Torrance, CA, USA
| | - Roland Lee
- Radiology Department, San Diego VA Healthcare System, University of California San Diego, San Diego, CA, USA
| | - Yvonne W Lui
- FACR, Department of Radiology, NYU Langone Health / Grossman School of Medicine, New York, NY, USA
| | - Pia C Sundgren
- Diagnostic Radiology, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Medcial Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Pratik Mukherjee
- Department of Veterans Affairs, San Francisco VA Health Care System, San Francisco, CA, U.S.A
- University of California, San Francisco, CA, USA
| | - Kent Gøran Moen
- Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Mario Muto
- Chief Diagnostic and Interventional Neuroradiology, Cardarelli Hospital Naples, Naples, Italy
| | - Karelys Ng
- Section of Neuroradiology, Department of Radiology, University Hospital Vall d'Hebron, Barcelona, Spain
| | - Sumit N Niogi
- Weill Cornell Medicine, Department of Radiology, New York, NY, USA
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology, University Hospital Vall d'Hebron, Barcelona, Spain
| | | | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - A John Tsiouris
- Associate Professor of Clinical RadiologyDirector of MRIDepartment of Radiology, Section Chief, Weill Cornell Medicine, NeuroradiologyNew York, NY, USA
| | - Johan Van Goethem
- Department of Medical and Molecular Imaging, University Hospital of Antwerp, Antwerp, Belgium
| | - Thijs Vande Vyvere
- Department of Rehabilitation Sciences and Physiotherapy, MOVANT, University of Antwerp, Antwerp, Belgium
- Pain in Motion International Research Group, Brussels, Belgium
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
| | - Chris Whitlow
- Department of Radiology, Wake Forest University, Winston-Salem, USA
| | - Martin Wiesmann
- Department of Neuroradiology, University Hospital Aachen, Aachen, Germany
| | - Kei Yamada
- Department of Radiology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Natalia Zakharova
- N.N. Burdenko National Medical Research Center of Neurosurgery, Federal State Autonomous Institution, Moscow, Russian Federation
| | - Paul M Parizel
- FRANZCR Dept of Radiology, Royal Perth Hospital (RPH), Medical School, University of Western Australia (UWA), Perth, WA, Australia
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Cook R, Zima L, Khazaal J, Williams J. Low-velocity penetrating brain injury: a review of the literature and illustrative case. Brain Inj 2024; 38:668-674. [PMID: 38555515 DOI: 10.1080/02699052.2024.2336067] [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: 01/22/2024] [Accepted: 03/22/2024] [Indexed: 04/02/2024]
Abstract
INTRODUCTION Low-velocity penetrating brain injury (LVPBI) is a class of brain injury where a foreign object violates the skull and damages the brain. Such injuries are rare and consequently understudied. CASE As such, we report an illustrative case of a 29-year-old female with a dense, plastic spike penetrating her right orbit and into her midbrain. After assessment with a CT scan and angiography, the object was removed with careful attention to possible vascular injury. The patient had an uncomplicated post-operative course and received antibiotic and antiepileptic prophylaxis. She was discharged on post-operative day 5, experiencing only mild left-sided weakness. DISCUSSION Common concerns regarding LVPBI include infection, post-traumatic epilepsy, and vascular injury. A review of published LVPBI cases over the past 20 years demonstrated that most cases (55.2%) are due to accidents. Of patients undergoing surgery, 43.4% underwent a craniotomy, and 22.8% underwent a craniectomy. Despite the grave nature of LVPBI, only 13.5% of the patients died. Additionally, 6.5% of patients developed an infection over their clinical course. CONCLUSION In all, more reported cases further paint a picture of the current state of management and outcomes regarding LVPBI, paving the way for more cohesive guidelines to ensure the best possible patient outcomes.
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Affiliation(s)
- Richard Cook
- Department of Neurosurgery, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Laura Zima
- Department of Neurosurgery, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Jawad Khazaal
- Department of Neurosurgery, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - John Williams
- Department of Neurosurgery, McGovern Medical School at the University of Texas Health Science Center at Houston, Houston, Texas, USA
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Eryilmaz A, Sahin T. Comparison of scoring systems for patients with head injury presenting to the emergency department. Eur J Trauma Emerg Surg 2024:10.1007/s00068-024-02589-6. [PMID: 38940949 DOI: 10.1007/s00068-024-02589-6] [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: 11/16/2023] [Accepted: 06/14/2024] [Indexed: 06/29/2024]
Abstract
PURPOSE The present study aimed to compare the National Emergency X-Radiography Utilization Study II (NEXUS-II), New Orleans Criteria (NOC), Canadian Computed Tomography (CT) Head Rule (CCTHR) scoring systems, and Advanced Trauma Life Support (ATLS®) 10th edition algorithm in patients with head injury presenting to the emergency department and to investigate the effectiveness of these scoring systems in determining injury severity and the need for cranial CT scanning. METHODS This prospective and observational study was conducted in a tertiary care emergency medicine clinic. The study included 794 adult patients who had a Glasgow Coma Scale (GCS) score ≥ 13, and were considered as having minor head injury. Patients included in the study were categorized as having low or high risk according to the CCTHR, NOC, NEXUS-II scores, and ATLS algorithm. RESULTS The mean age of the patients was 40.7 ± 18.7 years, and 592 (74.6%) were male. The proportion of patients considered as having high risk was 27.7%, 84.8%, and 34.5% according to CCTHR, NOC, and NEXUS-II, respectively. According to the ATLS, 14.7% and 14.1% of the patients were considered at medium risk and high risk, respectively. CT scanning was performed in 757 (95.3%) patients, and pathologic findings were detected in 18 patients (2.3%). NOC in contrary showed a sensitivity of 100% but a specificity of 15.6%. CONCLUSION In our region, there was no significant difference among the CCTHR, NEXUS-II systems, and ATLS algorithm regarding the accuracy of pathological findings in patients with head injury; any of these systems can be used in clinical practice and determining CT scan necessity. Although the sensitivity of the NOC system is very high, it has been observed that its low specificity may lead to a large number of unnecessary CT scans, which may increase the patient-based cost and waiting time in the emergency department.
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Affiliation(s)
- Alihan Eryilmaz
- Emergency Medicine Clinic, Inegol State Hospital, Bursa, Türkiye, Turkey
| | - Taner Sahin
- Department of Emergency Medicine, University of Health Science Kayseri Medicine Faculty, Kayseri, Türkiye, Turkey.
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Koziarz A, Koziarz F, Shen R, Gopee-Ramanan P, Black SE, Worsley D, Chan IYM, Streiner DL, Zukotynski KA. Diagnostic Accuracy of SPECT for Mild Traumatic Brain Injury: A Systematic Review and Meta-analysis. Clin Nucl Med 2024:00003072-990000000-01188. [PMID: 38914012 DOI: 10.1097/rlu.0000000000005328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
PURPOSE This study examines the diagnostic accuracy of brain perfusion SPECT for mild traumatic brain injury (mTBI). PATIENTS AND METHODS A systematic review and meta-analysis was performed according to PRISMA guidelines (PROSPERO: CRD42023484636). Five databases were searched for studies evaluating brain perfusion SPECT in adult patients with mTBI (GCS 13-15). Study quality was assessed using a modified QUADAS-2 tool. A meta-analysis was performed to pool proportions of hypoperfusion abnormalities across brain lobes. RESULTS Of 4735 records, 22 studies (5 longitudinal [40% high quality], 17 cross-sectional [24% high quality]) were included totaling 800 patients (mean age, 37.4 ± 12.6 years; 36.4% female). Meta-analysis of proportions indicated that the frontal lobe most frequently showed hypoperfusion on brain perfusion SPECT (pooled proportion 40.1% [95% confidence interval, 31.2% to 49.8%], 99/254, I2 = 54.5%), followed by the temporal lobe (26.1% [95% confidence interval, 19.9% to 33.6%], 68/254, I2 = 30.7%). Several studies found that hypoperfusion abnormalities were associated with neuropsychological findings. Also, brain perfusion SPECT could detect abnormalities not seen on MRI. Abnormalities in perfusion on brain perfusion SPECT may be more readily detected with a quantitative assessment compared with a visual assessment alone, although there appears to be no consensus on the optimal method for image interpretation. Evidence evaluating the sensitivity and specificity of brain perfusion SPECT for mTBI was limited. Using the GRADE framework, the evidence was rated as low. CONCLUSIONS Although perfusion abnormalities can be seen in patients with mTBI, commonly in the frontal and temporal lobes, the findings are nonspecific and may derive from various factors. Ultimately, brain perfusion SPECT provides additional information for mTBI, but the final added value for the detection of mTBI is unknown.
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Affiliation(s)
- Alex Koziarz
- From the Department of Medical Imaging, McMaster University, Hamilton, Ontario, Canada
| | - Frank Koziarz
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - Rui Shen
- Center for Bioethics, Harvard Medical School, Boston, MA
| | | | | | - Daniel Worsley
- Department of Nuclear Medicine, Vancouver General Hospital, Vancouver, British Columbia, Canada
| | - Ian Y M Chan
- Department of Diagnostic Imaging, Trillium Health Partners, Mississauga, Ontario, Canada
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Popescu CM, Marina V, Avram G, Cristescu Budala CL. Spectrum of Magnetic Resonance Imaging Findings in Acute Pediatric Traumatic Brain Injury - A Pictorial Essay. J Multidiscip Healthc 2024; 17:2921-2934. [PMID: 38911614 PMCID: PMC11193985 DOI: 10.2147/jmdh.s466044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/26/2024] [Indexed: 06/25/2024] Open
Abstract
Head trauma (HT) in pediatric patients is the number one cause of mortality and morbidity in children. Although computer tomography (CT) imaging provides ample information in assessing acute traumatic brain injuries (TBIs), there are instances when magnetic resonance imaging (MRI) is needed. Due to its high sensitivity in diagnosing small bleeds, MRI offers a well-documented evaluation of primary acute TBIs. Our pictorial essay aims to present some of the latest imaging protocols employed in head trauma and review some practical considerations. Injury mechanisms in accidental HT, lesions' topography, and hematoma signal variability over time are also discussed. Acute primary intra- and extra-axial lesions and their MRI aspect are showcased using images from patients in our hospital. This pictorial essay has an educational purpose. It is intended to guide young emergency and intensive care unit doctors, neurologists, and neurosurgeons in diagnosing acute primary TBIs on MRI while waiting for the official radiologist's report. The presentation focuses on the most frequent traumatic lesions encountered in acute pediatric head trauma.
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Affiliation(s)
- Cristina-Mihaela Popescu
- Dental-Medicine Department, Faculty of Medicine and Pharmacy, “dunărea de Jos” University, Galați, 800201, Romania
| | - Virginia Marina
- Medical Department of Occupational Health, Faculty of Medicine and Pharmacy, “Dunărea de Jos” University, Galați, 800201, Romania
| | - Georgiana Avram
- “sf. Ioan” Clinical Emergency Children’s Hospital, Galați, 800487, Romania
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9
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Moen KG, Flusund AMH, Moe HK, Andelic N, Skandsen T, Håberg A, Kvistad KA, Olsen Ø, Saksvoll EH, Abel-Grüner S, Anke A, Follestad T, Vik A. The prognostic importance of traumatic axonal injury on early MRI: the Trondheim TAI-MRI grading and quantitative models. Eur Radiol 2024:10.1007/s00330-024-10841-1. [PMID: 38896232 DOI: 10.1007/s00330-024-10841-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 03/25/2024] [Accepted: 04/06/2024] [Indexed: 06/21/2024]
Abstract
OBJECTIVES We analysed magnetic resonance imaging (MRI) findings after traumatic brain injury (TBI) aiming to improve the grading of traumatic axonal injury (TAI) to better reflect the outcome. METHODS Four-hundred sixty-three patients (8-70 years) with mild (n = 158), moderate (n = 129), or severe (n = 176) TBI and early MRI were prospectively included. TAI presence, numbers, and volumes at predefined locations were registered on fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted imaging, and presence and numbers on T2*GRE/SWI. Presence and volumes of contusions were registered on FLAIR. We assessed the outcome with the Glasgow Outcome Scale Extended. Multivariable logistic and elastic-net regression analyses were performed. RESULTS The presence of TAI differed between mild (6%), moderate (70%), and severe TBI (95%). In severe TBI, bilateral TAI in mesencephalon or thalami and bilateral TAI in pons predicted worse outcomes and were defined as the worst grades (4 and 5, respectively) in the Trondheim TAI-MRI grading. The Trondheim TAI-MRI grading performed better than the standard TAI grading in severe TBI (pseudo-R2 0.19 vs. 0.16). In moderate-severe TBI, quantitative models including both FLAIR volume of TAI and contusions performed best (pseudo-R2 0.19-0.21). In patients with mild TBI or Glasgow Coma Scale (GCS) score 13, models with the volume of contusions performed best (pseudo-R2 0.25-0.26). CONCLUSIONS We propose the Trondheim TAI-MRI grading (grades 1-5) with bilateral TAI in mesencephalon or thalami, and bilateral TAI in pons as the worst grades. The predictive value was highest for the quantitative models including FLAIR volume of TAI and contusions (GCS score <13) or FLAIR volume of contusions (GCS score ≥ 13), which emphasise artificial intelligence as a potentially important future tool. CLINICAL RELEVANCE STATEMENT The Trondheim TAI-MRI grading reflects patient outcomes better in severe TBI than today's standard TAI grading and can be implemented after external validation. The prognostic importance of volumetric models is promising for future use of artificial intelligence technologies. KEY POINTS Traumatic axonal injury (TAI) is an important injury type in all TBI severities. Studies demonstrating which MRI findings that can serve as future biomarkers are highly warranted. This study proposes the most optimal MRI models for predicting patient outcome at 6 months after TBI; one updated pragmatic model and a volumetric model. The Trondheim TAI-MRI grading, in severe TBI, reflects patient outcome better than today's standard grading of TAI and the prognostic importance of volumetric models in all severities of TBI is promising for future use of AI.
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Affiliation(s)
- Kent Gøran Moen
- Department of Circulation and Medical Imaging, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.
- Department of Radiology, Vestre Viken Hospital Trust, Drammen Hospital, 3004, Drammen, Norway.
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway.
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway.
| | - Anne-Mari Holte Flusund
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
- Department of Radiology, Møre and Romsdal Hospital Trust, Molde Hospital, 6412, Molde, Norway
| | - Hans Kristian Moe
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
- Department of Neurosurgery, Oslo University Hospital, Rikshospitalet, P.O. Box 4950 Nydalen, 0424, Oslo, Norway
| | - Nada Andelic
- Institute of Health and Society, Research Centre for Habilitation and Rehabilitation Models and Services (CHARM), Faculty of Medicine, University of Oslo, P.O. Box 1130 Blindern, 0318, Oslo, Norway
- Department of Physical Medicine and Rehabilitation, Oslo University Hospital, Ullevål Hospital, P.O. Box 4956 Nydalen, 0424, Oslo, Norway
| | - Toril Skandsen
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
| | - Asta Håberg
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
- MI Lab and Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Kjell Arne Kvistad
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
| | - Øystein Olsen
- Department of Radiology, Nord-Trøndelag Hospital Trust, Levanger Hospital, 7600, Levanger, Norway
| | - Elin Hildrum Saksvoll
- Department of Radiology, Nord-Trøndelag Hospital Trust, Levanger Hospital, 7600, Levanger, Norway
| | - Sebastian Abel-Grüner
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
| | - Audny Anke
- Department of Rehabilitation, University Hospital of North Norway, 9038, Tromsø, Norway
- Faculty of Health Sciences, Department of Clinical Medicine, UiT- The Arctic University of Norway, 9038, Tromsø, Norway
| | - Turid Follestad
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- Clinical Research Unit Central Norway, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
| | - Anne Vik
- Department of Neurosurgery, St. Olavs Hospital, Trondheim University Hospital, 7006, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
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Popescu CM, Marina V, Munteanu A, Popescu F. Acute Computer Tomography Findings in Pediatric Accidental Head Trauma-Review. Pediatric Health Med Ther 2024; 15:231-241. [PMID: 38882239 PMCID: PMC11179670 DOI: 10.2147/phmt.s461121] [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: 01/31/2024] [Accepted: 05/20/2024] [Indexed: 06/18/2024] Open
Abstract
Head trauma in paediatric patients is a worldwide and constant issue. It is the number one cause for childhood mortality and morbidity. Children of all ages are susceptible to sustaining head trauma and the anatomical characteristics of the region put them in a high-risk category for developing severe traumatic brain injuries. Boys are more frequently victims of accidental head traumas, and their injuries are more severe than those encountered in girls. The mechanisms of the trauma are a determining factor for the types of lesions we find. The traumatic injuries fall into two categories, primary and secondary. Primary traumatic injuries can be severe and life threatening, and their presence needs to be documented in order to set the correct therapeutic conduct. Due to their importance, this pictorial review focuses on them and the images used herein are selected from the database of our hospital. It is important to distinguish each of the different injuries that can be encountered. At the same time, radiologists are advised to remember that for children up to five years of age, some non-accidental imaging findings may appear to coincide with those found in accidental head trauma.
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Affiliation(s)
- Cristina-Mihaela Popescu
- Dental-Medicine Department, Faculty of Medicine and Pharmacy, "Dunărea de Jos" University, Galati, 800201, Romania
| | - Virginia Marina
- Medical Department of Occupational Health, Faculty of Medicine and Pharmacy, "Dunărea de Jos" University, Galati, 800201, Romania
| | | | - Floriana Popescu
- Department of English, Faculty of Letters, "Dunărea de Jos" University, Galati, 800201, Romania
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11
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Losa L, Peruzzo D, Galbiati S, Locatelli F, Agarwal N. Enhancing T1 signal of normal-appearing white matter with divided subtracted inversion recovery: A pilot study in mild traumatic brain injury. NMR IN BIOMEDICINE 2024:e5175. [PMID: 38757789 DOI: 10.1002/nbm.5175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 03/28/2024] [Accepted: 04/22/2024] [Indexed: 05/18/2024]
Abstract
Magnetic resonance imaging (MRI) and cognitive profiles in patients with mild traumatic brain injury (mTBI) are often discordant. Conventional MRI seldom captures the full extent of pathological changes in the normal-appearing white matter (NAWM). The divided subtracted inversion recovery (dSIR) technique may enhance T1 differences in NAWM, making them easily visible. We aimed to implement dSIR on a clinical scanner and tested results in mTBI patients. To produce dSIR images, Inversion Recovery-Turbo Spin Echo sequences were modified using six different inversion times (TI) on a 3-T scanner in healthy participants and patients with mTBI. The multiple TIs determined normal white (TIshort) and gray matter (TIlong) nulling points in healthy subjects, which were used to create dSIR images. In one patient, the protocol was repeated at 3 months to identify changes after rehabilitation. Diffusion tensor imaging (DTI)-derived mean diffusivity (MD) and fractional anisotropy (FA) maps were aligned to dSIR images to ensure that signal was not artefactual. Ten healthy participants (five females; age 24 ± 3 [95% CI: 21, 26] years) were included. TIshort and TIlong were set at 450 and 750 ms, respectively. In both patients (one male, age 17 years; one female, age 14 years), dSIR images revealed areas with increased T1 in the NAWM not visible on conventional MRI. dSIR-based hyperintensities corresponded to elevated MD and reduced FA. Substantial changes were found at follow-up with improvement in DTI-based parameters. dSIR images enhance subtle changes in the NAWM of patients with mTBI by amplifying their intrinsic T1 signal.
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Affiliation(s)
- Letizia Losa
- Neuroimaging Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
| | - Denis Peruzzo
- Neuroimaging Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
| | - Sara Galbiati
- Acquired Brain Injury Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
| | - Federica Locatelli
- Acquired Brain Injury Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
| | - Nivedita Agarwal
- Neuroimaging Unit, Scientific Institute IRCCS E. Medea, Bosisio Parini, Italy
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12
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Clarke GJB, Follestad T, Skandsen T, Zetterberg H, Vik A, Blennow K, Olsen A, Håberg AK. Chronic immunosuppression across 12 months and high ability of acute and subacute CNS-injury biomarker concentrations to identify individuals with complicated mTBI on acute CT and MRI. J Neuroinflammation 2024; 21:109. [PMID: 38678300 PMCID: PMC11056044 DOI: 10.1186/s12974-024-03094-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Accepted: 04/05/2024] [Indexed: 04/29/2024] Open
Abstract
BACKGROUND Identifying individuals with intracranial injuries following mild traumatic brain injury (mTBI), i.e. complicated mTBI cases, is important for follow-up and prognostication. The main aims of our study were (1) to assess the temporal evolution of blood biomarkers of CNS injury and inflammation in individuals with complicated mTBI determined on computer tomography (CT) and magnetic resonance imaging (MRI); (2) to assess the corresponding discriminability of both single- and multi-biomarker panels, from acute to chronic phases after injury. METHODS Patients with mTBI (n = 207), defined as Glasgow Coma Scale score between 13 and 15, loss of consciousness < 30 min and post-traumatic amnesia < 24 h, were included. Complicated mTBI - i.e., presence of any traumatic intracranial injury on neuroimaging - was present in 8% (n = 16) on CT (CT+) and 12% (n = 25) on MRI (MRI+). Blood biomarkers were sampled at four timepoints following injury: admission (within 72 h), 2 weeks (± 3 days), 3 months (± 2 weeks) and 12 months (± 1 month). CNS biomarkers included were glial fibrillary acidic protein (GFAP), neurofilament light (NFL) and tau, along with 12 inflammation markers. RESULTS The most discriminative single biomarkers of traumatic intracranial injury were GFAP at admission (CT+: AUC = 0.78; MRI+: AUC = 0.82), and NFL at 2 weeks (CT+: AUC = 0.81; MRI+: AUC = 0.89) and 3 months (MRI+: AUC = 0.86). MIP-1β and IP-10 concentrations were significantly lower across follow-up period in individuals who were CT+ and MRI+. Eotaxin and IL-9 were significantly lower in individuals who were MRI+ only. FGF-basic concentrations increased over time in MRI- individuals and were significantly higher than MRI+ individuals at 3 and 12 months. Multi-biomarker panels improved discriminability over single biomarkers at all timepoints (AUCs > 0.85 for admission and 2-week models classifying CT+ and AUC ≈ 0.90 for admission, 2-week and 3-month models classifying MRI+). CONCLUSIONS The CNS biomarkers GFAP and NFL were useful single diagnostic biomarkers of complicated mTBI, especially in acute and subacute phases after mTBI. Several inflammation markers were suppressed in patients with complicated versus uncomplicated mTBI and remained so even after 12 months. Multi-biomarker panels improved diagnostic accuracy at all timepoints, though at acute and 2-week timepoints, the single biomarkers GFAP and NFL, respectively, displayed similar accuracy compared to multi-biomarker panels.
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Affiliation(s)
- Gerard Janez Brett Clarke
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Neuromedicine and Movement Sciences, NTNU, Trondheim, Norway
| | - Turid Follestad
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, N-7491, Norway
| | - Toril Skandsen
- Department of Neuromedicine and Movement Sciences, NTNU, Trondheim, Norway
- Clinic of Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Sha Tin, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne Vik
- Department of Neuromedicine and Movement Sciences, NTNU, Trondheim, Norway
- Department of Neurosurgery, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Alexander Olsen
- Clinic of Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, Norway
- NorHEAD - Norwegian Centre for Headache Research, Trondheim, Norway
| | - Asta Kristine Håberg
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
- Department of Neuromedicine and Movement Sciences, NTNU, Trondheim, Norway.
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13
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Vande Vyvere T, Pisică D, Wilms G, Claes L, Van Dyck P, Snoeckx A, van den Hauwe L, Pullens P, Verheyden J, Wintermark M, Dekeyzer S, Mac Donald CL, Maas AIR, Parizel PM. Imaging Findings in Acute Traumatic Brain Injury: a National Institute of Neurological Disorders and Stroke Common Data Element-Based Pictorial Review and Analysis of Over 4000 Admission Brain Computed Tomography Scans from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study. J Neurotrauma 2024. [PMID: 38482818 DOI: 10.1089/neu.2023.0553] [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: 04/20/2024] Open
Abstract
In 2010, the National Institute of Neurological Disorders and Stroke (NINDS) created a set of common data elements (CDEs) to help standardize the assessment and reporting of imaging findings in traumatic brain injury (TBI). However, as opposed to other standardized radiology reporting systems, a visual overview and data to support the proposed standardized lexicon are lacking. We used over 4000 admission computed tomography (CT) scans of patients with TBI from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study to develop an extensive pictorial overview of the NINDS TBI CDEs, with visual examples and background information on individual pathoanatomical lesion types, up to the level of supplemental and emerging information (e.g., location and estimated volumes). We documented the frequency of lesion occurrence, aiming to quantify the relative importance of different CDEs for characterizing TBI, and performed a critical appraisal of our experience with the intent to inform updating of the CDEs. In addition, we investigated the co-occurrence and clustering of lesion types and the distribution of six CT classification systems. The median age of the 4087 patients in our dataset was 50 years (interquartile range, 29-66; range, 0-96), including 238 patients under 18 years old (5.8%). Traumatic subarachnoid hemorrhage (45.3%), skull fractures (37.4%), contusions (31.3%), and acute subdural hematoma (28.9%) were the most frequently occurring CT findings in acute TBI. The ranking of these lesions was the same in patients with mild TBI (baseline Glasgow Coma Scale [GCS] score 13-15) compared with those with moderate-severe TBI (baseline GCS score 3-12), but the frequency of occurrence was up to three times higher in moderate-severe TBI. In most TBI patients with CT abnormalities, there was co-occurrence and clustering of different lesion types, with significant differences between mild and moderate-severe TBI patients. More specifically, lesion patterns were more complex in moderate-severe TBI patients, with more co-existing lesions and more frequent signs of mass effect. These patients also had higher and more heterogeneous CT score distributions, associated with worse predicted outcomes. The critical appraisal of the NINDS CDEs was highly positive, but revealed that full assessment can be time consuming, that some CDEs had very low frequencies, and identified a few redundancies and ambiguity in some definitions. Whilst primarily developed for research, implementation of CDE templates for use in clinical practice is advocated, but this will require development of an abbreviated version. In conclusion, with this study, we provide an educational resource for clinicians and researchers to help assess, characterize, and report the vast and complex spectrum of imaging findings in patients with TBI. Our data provides a comprehensive overview of the contemporary landscape of TBI imaging pathology in Europe, and the findings can serve as empirical evidence for updating the current NINDS radiologic CDEs to version 3.0.
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Affiliation(s)
- Thijs Vande Vyvere
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
- Department of Molecular Imaging and Radiology (MIRA), Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium
| | - Dana Pisică
- Department of Neurosurgery, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Public Health, Erasmus MC - University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Guido Wilms
- Department of Radiology, University Hospitals Leuven, Leuven, Belgium
| | - Lene Claes
- icometrix, Research and Development, Leuven, Belgium
| | - Pieter Van Dyck
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
- Department of Molecular Imaging and Radiology (MIRA), Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium
| | - Annemiek Snoeckx
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
- Department of Molecular Imaging and Radiology (MIRA), Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium
| | - Luc van den Hauwe
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
| | - Pim Pullens
- Department of Imaging, University Hospital Ghent; IBITech/MEDISIP, Engineering and Architecture, Ghent University; Ghent Institute for Functional and Metabolic Imaging, Ghent University, Belgium
| | - Jan Verheyden
- icometrix, Research and Development, Leuven, Belgium
| | - Max Wintermark
- Department of Neuroradiology, University of Texas MD Anderson Center, Houston, Texas, USA
| | - Sven Dekeyzer
- Department of Radiology, Antwerp University Hospital, Antwerp, Belgium
- Department of Radiology, University Hospital Ghent, Belgium
| | - Christine L Mac Donald
- Department of Neurological Surgery, School of Medicine, Harborview Medical Center, Seattle, Washington, USA
- Department of Neurological Surgery, School of Medicine, University of Washington, Seattle, Washington, USA
| | - Andrew I R Maas
- Department of Neurosurgery, Antwerp University Hospital, Antwerp, Belgium
- Department of Translational Neuroscience, Faculty of Medicine and Health Science, University of Antwerp, Antwerp, Belgium
| | - Paul M Parizel
- Department of Radiology, Royal Perth Hospital (RPH) and University of Western Australia (UWA), Perth, Australia; Western Australia National Imaging Facility (WA NIF) node, Australia
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Joseph CR, Lim JK, Grohol BN, Zivcevska M, Lencke J, Rich ED, Arrasmith CJ, Dorman IS, Clark BW, Love K, Ferry B, Rolfs ME. Identifying delay in glymphatic clearance of labeled protons post-acute head trauma utilizing 3D ASL MRI (arterial spin labeling): a pilot study. Sci Rep 2024; 14:6188. [PMID: 38485759 PMCID: PMC10940642 DOI: 10.1038/s41598-024-56236-6] [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: 11/02/2023] [Accepted: 03/04/2024] [Indexed: 03/18/2024] Open
Abstract
This study correlated mild traumatic brain injury (mTBI) cognitive changes with ASL-MRI glymphatic clearance rates (GCRs) and recovery with GCR improvement. mTBI disrupts the blood brain barrier (BBB), reducing capillary mean transit time and GCRs. mTBI is clinically diagnosed utilizing history/examination findings with no physiologic biomarkers. 3D TGSE (turbo-gradient spin-echo) pulsed arterial spin-labeling 3T MRI with 7 long inversion times (TIs) assessed the signal clearance of labeled protons 2800-4000 ms postlabeling in bifrontal, bitemporal, and biparietal regions within 7 days of mTBI and once clinically cleared to resume activities. The Sport Concussion Assessment Tool Version 5 (SKAT5) and Brief Oculomotor/Vestibular Assessment evaluated injured athletes' cognitive function prior to MRIs. The pilot study demonstrated significant GCRs improvement (95% CI - 0.06 to - 0.03 acute phase; to CI-recovery CI 0.0772 to - 0.0497; P < 0.001 in frontal lobes; and parietal lobes (95% CI - 0.0584 to - 0.0251 acute; CI - 0.0727 to - 0.0392 recovery; P = 0.024) in 9 mTBI athletes (8 female, 1 male). Six age/activity-matched controls (4 females, 2 males) were also compared. mTBI disrupts the BBB, reducing GCR measured using the 3D ASL MRI technique. ASL MRI is a potential noninvasive biomarker of mTBI and subsequent recovery.
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Affiliation(s)
- Charles R Joseph
- Liberty University College of Osteopathic Medicine, Lynchburg, USA.
| | - Jubin Kang Lim
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | - Bryce N Grohol
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | - Marija Zivcevska
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | - Joshua Lencke
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | - Ethan Dean Rich
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | | | | | | | - Kim Love
- K. R. Love Quantitative Consulting and Collaboration, Athens, USA
| | - Ben Ferry
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
| | - Mark E Rolfs
- Liberty University College of Osteopathic Medicine, Lynchburg, USA
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15
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Zhu G, Ozkara BB, Chen H, Zhou B, Jiang B, Ding VY, Wintermark M. Enhancing hospital course and outcome prediction in patients with traumatic brain injury: A machine learning study. Neuroradiol J 2024; 37:74-83. [PMID: 37921691 PMCID: PMC10863571 DOI: 10.1177/19714009231212364] [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: 11/04/2023] Open
Abstract
PURPOSE We aimed to use machine learning (ML) algorithms with clinical, lab, and imaging data as input to predict various outcomes in traumatic brain injury (TBI) patients. METHODS In this retrospective study, blood samples were analyzed for glial fibrillary acidic protein (GFAP) and ubiquitin C-terminal hydrolase L1 (UCH-L1). The non-contrast head CTs were reviewed by two neuroradiologists for TBI common data elements (CDE). Three outcomes were designed to predict: discharged or admitted for further management (prediction 1), deceased or not deceased (prediction 2), and admission only, prolonged stay, or neurosurgery performed (prediction 3). Five ML models were trained. SHapley Additive exPlanations (SHAP) analyses were used to assess the relative significance of variables. RESULTS Four hundred forty patients were used to predict predictions 1 and 2, while 271 patients were used in prediction 3. Due to Prediction 3's hospitalization requirement, deceased and discharged patients could not be utilized. The Random Forest model achieved an average accuracy of 1.00 for prediction 1 and an accuracy of 0.99 for prediction 2. The Random Forest model achieved a mean accuracy of 0.93 for prediction 3. Key features were extracranial injury, hemorrhage, UCH-L1 for prediction 1; The Glasgow Coma Scale, age, GFAP for prediction 2; and GFAP, subdural hemorrhage volume, and pneumocephalus for prediction 3, per SHAP analysis. CONCLUSION Combining clinical and laboratory parameters with non-contrast CT CDEs allowed our ML models to accurately predict the designed outcomes of TBI patients. GFAP and UCH-L1 were among the significant predictor variables, demonstrating the importance of these biomarkers.
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Affiliation(s)
- Guangming Zhu
- Department of Neurology, The University of Arizona, USA
| | - Burak B Ozkara
- Department of Neuroradiology, MD Anderson Cancer Center, USA
| | - Hui Chen
- Department of Neuroradiology, MD Anderson Cancer Center, USA
| | - Bo Zhou
- Neuroradiology Division, Department of Radiology, Stanford University, USA
| | - Bin Jiang
- Neuroradiology Division, Department of Radiology, Stanford University, USA
| | - Victoria Y Ding
- Quantitative Sciences Unit, Department of Medicine, Stanford University, USA
| | - Max Wintermark
- Department of Neuroradiology, MD Anderson Cancer Center, USA
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Zasler ND. Medicolegal issues and disorders of consciousness. NeuroRehabilitation 2024; 54:149-165. [PMID: 38217622 DOI: 10.3233/nre-230242] [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: 01/15/2024]
Abstract
BACKGROUND The tasks and responsibilities that come with clinician involvement in medicolegal proceedings can be daunting and particularly so in challenging areas such as provision of medicolegal opinions in cases involving disorders of consciousness (DoC). OBJECTIVE The aim of this narrative review was to provide education and advice to healthcare practitioners who by choice or circumstance are asked and/or required to provide medicolegal opinions in cases involving patients with DoC. METHODS A literature search was conducted using PubMed Central and MedlinePlus for articles dealing with clinician involvement in medicolegal cases involving persons with DoC. The information provided also integrates the authors' nearly 40 years of clinical experience, brain injury medicine practice and "trials and tribulations" associated with medicolegal involvement in such cases. RESULTS The literature was found to be replete with articles on brain death and withdrawal/withholding of care (which are not the focus of this review). The extant medical literature in brain injury medicine on the other hand is currently lacking in practical information for clinicians working "in the trenches" regarding the challenges and caveats of medicolegal involvement in such cases. CONCLUSION This review provides the reader with a big picture overview of the most pertinent medicolegal topics inherent in clinical work with patients with DOC including pertinent nomenclature, caveats regarding forensic consultation including independent medical examinations, testimony tips, discussion of life expectancy/median survival concepts, prognostication in a medicolegal context, documentation and record keeping as well as some of the specific challenges pertinent to these types of brain injury cases that are not per se relevant in less severe injuries.
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Affiliation(s)
- Nathan D Zasler
- Concussion Care Centre of Virginia, Ltd., Richmond, VA, USA
- Tree of Life, Richmond, VA, USA
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA, USA
- Department of Physical Medicine and Rehabilitation, University of Virginia, Charlottesville, VA, USA
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17
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Kitagawa M, Abiko K, Sheriff S, Maudsley AA, Li X, Sawamura D, Ahn S, Tha KK. Brain Temperature as an Indicator of Cognitive Function in Traumatic Brain Injury Patients. Metabolites 2023; 14:17. [PMID: 38248820 PMCID: PMC10818445 DOI: 10.3390/metabo14010017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Revised: 11/27/2023] [Accepted: 12/20/2023] [Indexed: 01/23/2024] Open
Abstract
Whether brain temperature noninvasively extracted by magnetic resonance imaging has a role in identifying brain changes in the later phases of mild to moderate traumatic brain injury (TBI) is not known. This prospective study aimed to evaluate if TBI patients in subacute and chronic phases had altered brain temperature measured by whole-brain magnetic resonance spectroscopic imaging (WB-MRSI) and if the measurable brain temperature had any relationship with cognitive function scores. WB-MRSI was performed on eight TBI patients and fifteen age- and sex-matched control subjects. Brain temperature (T) was extracted from the brain's major metabolites and compared between the two groups. The T of the patients was tested for correlation with cognitive function test scores. The results showed significantly lower brain temperature in the TBI patients (p < 0.05). Brain temperature derived from N-acetylaspartate (TNAA) strongly correlated with the 2 s paced auditory serial addition test (PASAT-2s) score (p < 0.05). The observation of lower brain temperature in TBI patients may be due to decreased metabolic activity resulting from glucose and oxygen depletion. The correlation of brain temperature with PASAT-2s may imply that noninvasive brain temperature may become a noninvasive index reflecting cognitive performance.
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Affiliation(s)
- Maho Kitagawa
- Laboratory for Biomarker Imaging Science, Graduate School of Biomedical Science and Engineering, Hokkaido University, N15 W7, Kita-ku, Sapporo 060-8638, Japan; (M.K.); (X.L.)
| | - Kagari Abiko
- Department of Rehabilitation, Hokkaido University Hospital, Sapporo 060-8648, Japan;
- Department of Rehabilitation, Sapporo Azabu Neurosurgical Hospital, Sapporo 065-0022, Japan
| | - Sulaiman Sheriff
- Department of Radiology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (S.S.); (A.A.M.)
| | - Andrew A. Maudsley
- Department of Radiology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; (S.S.); (A.A.M.)
| | - Xinnan Li
- Laboratory for Biomarker Imaging Science, Graduate School of Biomedical Science and Engineering, Hokkaido University, N15 W7, Kita-ku, Sapporo 060-8638, Japan; (M.K.); (X.L.)
| | - Daisuke Sawamura
- Department of Rehabilitation Science, Hokkaido University Faculty of Health Sciences, Sapporo 060-0812, Japan;
| | - Sinyeob Ahn
- Siemens Healthineers, San Francisco, CA 94553, USA;
| | - Khin Khin Tha
- Laboratory for Biomarker Imaging Science, Graduate School of Biomedical Science and Engineering, Hokkaido University, N15 W7, Kita-ku, Sapporo 060-8638, Japan; (M.K.); (X.L.)
- Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, N15 W7, Kita-ku, Sapporo 060-8638, Japan
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18
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Jiang B, Ozkara BB, Creeden S, Zhu G, Ding VY, Chen H, Lanzman B, Wolman D, Shams S, Trinh A, Li Y, Khalaf A, Parker JJ, Halpern CH, Wintermark M. Validation of a deep learning model for traumatic brain injury detection and NIRIS grading on non-contrast CT: a multi-reader study with promising results and opportunities for improvement. Neuroradiology 2023; 65:1605-1617. [PMID: 37269414 DOI: 10.1007/s00234-023-03170-5] [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: 04/03/2023] [Accepted: 05/21/2023] [Indexed: 06/05/2023]
Abstract
PURPOSE This study aimed to assess and externally validate the performance of a deep learning (DL) model for the interpretation of non-contrast computed tomography (NCCT) scans of patients with suspicion of traumatic brain injury (TBI). METHODS This retrospective and multi-reader study included patients with TBI suspicion who were transported to the emergency department and underwent NCCT scans. Eight reviewers, with varying levels of training and experience (two neuroradiology attendings, two neuroradiology fellows, two neuroradiology residents, one neurosurgery attending, and one neurosurgery resident), independently evaluated NCCT head scans. The same scans were evaluated using the version 5.0 of the DL model icobrain tbi. The establishment of the ground truth involved a thorough assessment of all accessible clinical and laboratory data, as well as follow-up imaging studies, including NCCT and magnetic resonance imaging, as a consensus amongst the study reviewers. The outcomes of interest included neuroimaging radiological interpretation system (NIRIS) scores, the presence of midline shift, mass effect, hemorrhagic lesions, hydrocephalus, and severe hydrocephalus, as well as measurements of midline shift and volumes of hemorrhagic lesions. Comparisons using weighted Cohen's kappa coefficient were made. The McNemar test was used to compare the diagnostic performance. Bland-Altman plots were used to compare measurements. RESULTS One hundred patients were included, with the DL model successfully categorizing 77 scans. The median age for the total group was 48, with the omitted group having a median age of 44.5 and the included group having a median age of 48. The DL model demonstrated moderate agreement with the ground truth, trainees, and attendings. With the DL model's assistance, trainees' agreement with the ground truth improved. The DL model showed high specificity (0.88) and positive predictive value (0.96) in classifying NIRIS scores as 0-2 or 3-4. Trainees and attendings had the highest accuracy (0.95). The DL model's performance in classifying various TBI CT imaging common data elements was comparable to that of trainees and attendings. The average difference for the DL model in quantifying the volume of hemorrhagic lesions was 6.0 mL with a wide 95% confidence interval (CI) of - 68.32 to 80.22, and for midline shift, the average difference was 1.4 mm with a 95% CI of - 3.4 to 6.2. CONCLUSION While the DL model outperformed trainees in some aspects, attendings' assessments remained superior in most instances. Using the DL model as an assistive tool benefited trainees, improving their NIRIS score agreement with the ground truth. Although the DL model showed high potential in classifying some TBI CT imaging common data elements, further refinement and optimization are necessary to enhance its clinical utility.
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Affiliation(s)
- Bin Jiang
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
| | | | - Sean Creeden
- Deparment of Neuroradiology, University of Illinois College of Medicine Peoria, Peoria, IL, USA
| | - Guangming Zhu
- Department of Neurology, The University of Arizona, Tucson, AZ, USA
| | - Victoria Y Ding
- Department of Medicine, Stanford University, Stanford, CA, USA
| | - Hui Chen
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, TX, USA
| | - Bryan Lanzman
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Dylan Wolman
- Department of Neuroimaging and Neurointervention, Stanford University, Stanford, CA, USA
| | - Sara Shams
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
- Department of Radiology, Karolinska University Hospital, Stockholm, Sweden
- Institution for Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Austin Trinh
- Department of Neuroimaging and Neurointervention, Stanford University, Stanford, CA, USA
| | - Ying Li
- Department of Radiology, Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Alexander Khalaf
- Department of Neuroimaging and Neurointervention, Stanford University, Stanford, CA, USA
| | - Jonathon J Parker
- Device-Based Neuroelectronics Laboratory, Mayo Clinic, Phoenix, AZ, USA
- Department of Neurological Surgery, Mayo Clinic, Phoenix, AZ, USA
| | - Casey H Halpern
- Department of Neurosurgery, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
- Department of Surgery, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA
| | - Max Wintermark
- Department of Neuroradiology, MD Anderson Cancer Center, Houston, TX, USA.
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19
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Jo J, Williams KL, Jonzzon S, Yengo-Kahn AM, Terry DP, Zuckerman SL. Positive Head Computed Tomography Findings in the Setting of Sport Head Injuries: Can These Athletes Return-to-Play? Neurosurgery 2023; 93:773-781. [PMID: 37166195 DOI: 10.1227/neu.0000000000002520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/20/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND The literature on athletes with positive head computed tomography (HCT) findings in the setting of sport head injuries remains sparse. OBJECTIVE To report the proportions of athletes with a positive HCT and compare acute injury characteristics and recovery between those with and without a positive HCT. METHODS A retrospective, single-institution, cohort study was performed with all athletes aged 12 to 23 years seen at a regional concussion center from 11/2017 to 04/2022. The cohort was dichotomized into positive vs negative HCT (controls). Acute injury characteristics (ie, loss of consciousness and amnesia) and recovery, as measured by days to return-to-learn (RTL), symptom resolution, and return-to-play (RTP) were compared. χ 2 and Mann-Whitney U tests were performed. RESULTS Of 2061 athletes, 226 (11.0%) received an HCT and 9 (4.0%) had positive findings. HCT findings included 4 (44.4%) subdural hematomas, 1 (11.1%) epidural hematoma, 2 (22.2%) facial fractures, 1 (11.1%) soft tissue contusion, and 1 (11.1%) cavernous malformation. All 9 (100.0%) athletes were treated nonoperatively and successfully returned-to-play at a median (IQR) of 73.0 (55.0-82.0) days. No differences in loss of consciousness or amnesia were seen between positive HCT group and controls. The Mann-Whitney U test showed differences in RTL (17.0 vs 4.0 days; U = 45.0, P = .016) and RTP (73.0 vs 27.0 days; U = 47.5, P = .007) but not in symptom resolution. Our subanalysis showed no differences across all recovery metrics between acute hemorrhages and controls. CONCLUSION Among athletes seen at a regional concussion center who underwent an acute HCT, positive findings were seen in 4%. Although athletes with a positive HCT had longer RTL and RTP, symptom resolution was similar between those with a positive and negative HCT. All athletes with a positive HCT successfully returned to play. Despite a more conservative approach to athletes with a positive HCT, clinical outcomes are similar between those with and without a positive HCT.
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Affiliation(s)
- Jacob Jo
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Vanderbilt University School of Medicine, Nashville , Tennessee , USA
| | - Kristen L Williams
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
| | - Soren Jonzzon
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
| | - Aaron M Yengo-Kahn
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
| | - Douglas P Terry
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
| | - Scott L Zuckerman
- Department of Neurological Surgery, Vanderbilt Sports Concussion Center, Vanderbilt University Medical Center, Nashville , Tennessee , USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville , Tennessee , USA
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20
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Krawchuk LJ, Sharrock MF. Prognostic Neuroimaging Biomarkers in Acute Vascular Brain Injury and Traumatic Brain Injury. Semin Neurol 2023; 43:699-711. [PMID: 37802120 DOI: 10.1055/s-0043-1775790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
Prognostic imaging biomarkers after acute brain injury inform treatment decisions, track the progression of intracranial injury, and can be used in shared decision-making processes with families. Herein, key established biomarkers and prognostic scoring systems are surveyed in the literature, and their applications in clinical practice and clinical trials are discussed. Biomarkers in acute ischemic stroke include computed tomography (CT) hypodensity scoring, diffusion-weighted lesion volume, and core infarct size on perfusion imaging. Intracerebral hemorrhage biomarkers include hemorrhage volume, expansion, and location. Aneurysmal subarachnoid biomarkers include hemorrhage grading, presence of diffusion-restricting lesions, and acute hydrocephalus. Traumatic brain injury CT scoring systems, contusion expansion, and diffuse axonal injury grading are reviewed. Emerging biomarkers including white matter disease scoring, diffusion tensor imaging, and the automated calculation of scoring systems and volumetrics are discussed.
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Affiliation(s)
- Lindsey J Krawchuk
- Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Matthew F Sharrock
- Department of Neurology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
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21
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Rajaei F, Cheng S, Williamson CA, Wittrup E, Najarian K. AI-Based Decision Support System for Traumatic Brain Injury: A Survey. Diagnostics (Basel) 2023; 13:diagnostics13091640. [PMID: 37175031 PMCID: PMC10177859 DOI: 10.3390/diagnostics13091640] [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: 03/28/2023] [Revised: 04/22/2023] [Accepted: 04/29/2023] [Indexed: 05/15/2023] Open
Abstract
Traumatic brain injury (TBI) is one of the major causes of disability and mortality worldwide. Rapid and precise clinical assessment and decision-making are essential to improve the outcome and the resulting complications. Due to the size and complexity of the data analyzed in TBI cases, computer-aided data processing, analysis, and decision support systems could play an important role. However, developing such systems is challenging due to the heterogeneity of symptoms, varying data quality caused by different spatio-temporal resolutions, and the inherent noise associated with image and signal acquisition. The purpose of this article is to review current advances in developing artificial intelligence-based decision support systems for the diagnosis, severity assessment, and long-term prognosis of TBI complications.
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Affiliation(s)
- Flora Rajaei
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Shuyang Cheng
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Craig A Williamson
- Department of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, MI 48109, USA
| | - Emily Wittrup
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kayvan Najarian
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Max Harry Weil Institute for Critical Care Research and Innovation, University of Michigan, Ann Arbor, MI 48109, USA
- Michigan Institute for Data Science, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Emergency Medicine, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
- Center for Data-Driven Drug Development and Treatment Assessment (DATA), University of Michigan, Ann Arbor, MI 48109, USA
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22
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Diouf A, Machnowska M. Conventional MR Imaging in Trauma Management in Adults. Neuroimaging Clin N Am 2023; 33:235-249. [PMID: 36965942 DOI: 10.1016/j.nic.2022.12.001] [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: 02/11/2023]
Abstract
MR imaging has been shown to have higher sensitivity than computed tomography (CT) for traumatic intracranial soft tissue injuries as well as most cases of intracranial hemorrhage, thus making it a significant adjunct to CT in the management of traumatic brain injury, mostly in the subacute to chronic phase, but may also be of use in the acute phase, when there are persistent neurologic symptoms unexplained by prior imaging.
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Affiliation(s)
- Ange Diouf
- Department of Radiology, Radio-Oncology and Nuclear Medicine Faculty of Medicine, University of Montré al, Montré al, QC, Canada; Interventional Neuroradiology Clinical Fellow at St. Michael's Hospital, University of Toronto, Toronto, ON, Canada; Department of Radiology, Centre Hospitalier de l'Université de Montré al (CHUM), 1051 Sanguinet Street, Montré al, QC H2X 0C1, Canada
| | - Matylda Machnowska
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada.
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23
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Roche S, Crombé A, Benhamed A, Hak JF, Dabadie A, Fauconnier-Fatus C, Rega A, Pech-Gourg G, Tazarourte K, Seux M, Acquier A, Gorincour G. Risk Factors Associated with Traumatic Brain Injury and Implementation of Guidelines for Requesting Computed Tomography After Head Trauma Among Children in France. JAMA Netw Open 2023; 6:e2311092. [PMID: 37129895 PMCID: PMC10155067 DOI: 10.1001/jamanetworkopen.2023.11092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/03/2023] Open
Abstract
Importance Pediatric traumatic brain injuries (TBIs) are a leading cause of death and disability. The Pediatric Emergency Care Applied Research Network (PECARN) guidelines provide a framework for requesting head computed tomography (HCT) after pediatric head trauma (PHT); however, quantitative data are lacking regarding both TBIs found on HCT and justification of the HCT request according to the PECARN guidelines. Objectives To evaluate the types, frequencies, and risk factors for TBIs on HCT in children referred to emergency departments (EDs) who underwent HCT for PHT and to evaluate quality of HCT request. Design, Setting, and Participants This multicenter, retrospective cohort study included patients younger than 18 years who underwent HCT for PHT who were referred to 91 EDs during on-call hours between January 1, 2020, to May 31, 2022. Data were analyzed between July and August 2022. Exposure All radiological reports with pathologic findings were reviewed by 4 senior radiologists. Six hundred HCT requests filled by emergency physicians were randomly sampled to review the examination justification according to the PECARN guidelines. Main Outcomes and Measures Associations between TBIs, age, sex, and Glasgow Coma Scale (GCS) were investigated using univariable χ2 and Cochrane-Armitage tests. Multivariable stepwise binary logistic regressions were used to estimate the odds ratio (ORs) for intracranial hemorrhages (ICH), any type of fracture, facial bone fracture, and skull vault fracture. Results Overall, 5146 children with HCT for PHT were included (median [IQR] age, 11.2 [4.7-15.7] years; 3245 of 5146 [63.1%] boys). ICHs were diagnosed in 306 of 5146 patients (5.9%) and fractures in 674 of 5146 patients (13.1%). The following variables were associated with ICH in multivariable analysis: GCS score of 8 or less (OR, 5.83; 95% CI, 1.97-14.60; P < .001), extracranial hematoma (OR, 2.54; 95% CI, 1.59-4.02; P < .001), skull base fracture (OR, 9.32; 95% CI, 5.03-16.97; P < .001), upper cervical fracture (OR, 19.21; 95% CI, 1.79-143.59; P = .006), and skull vault fracture (OR, 35.64; 95% CI, 24.04-53.83; P < .001). When neither extracranial hematoma nor fracture was found on HCT, the OR for presenting ICH was 0.034 (95% CI, 0.026-0.045; P < .001). Skull vault fractures were more frequently encountered in children younger than 2 years (multivariable OR, 6.31; 95% CI, 4.16-9.66; P < .001; reference: children ≥12 years), whereas facial bone fractures were more frequently encountered in boys older than 12 years (multivariable OR, 26.60; 95% CI, 9.72-109.96; P < .001; reference: children younger than 2 years). The justification for performing HCT did not follow the PECARN guidelines for 396 of 589 evaluable children (67.2%) for requests filled by emergency physicians. Conclusion and Relevance In this cohort study of 5146 children who underwent HCT for PHT, knowing the odds of clinical and radiological features for ICHs and fractures could help emergency physicians and radiologists improve their image analysis and avoid missing significant injuries. The PECARN rules were not implemented in nearly two-thirds of patients.
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Affiliation(s)
| | - Amandine Crombé
- IMADIS, Lyon, Bordeaux, Marseille, Dijon, France
- Department of Radiology, Pellegrin University Hospital, Bordeaux, France
- Models in Oncology (MONC) Team, INRIA Bordeaux Sud-Ouest, CNRS UMR 5251 & Bordeaux University, Talence, France
| | - Axel Benhamed
- Service SAMU-Urgences, Centre Hospitalier Universitaire Édouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Jean-François Hak
- Assistance Publique-Hôpitaux de Marseille, Marseille, France
- LIIE, Aix Marseille University, Marseille, France
- CERIMED, Aix Marseille University, Marseille, France
| | - Alexia Dabadie
- IMADIS, Lyon, Bordeaux, Marseille, Dijon, France
- Assistance Publique-Hôpitaux de Marseille, Marseille, France
| | | | | | | | - Karim Tazarourte
- Service SAMU-Urgences, Centre Hospitalier Universitaire Édouard Herriot, Hospices Civils de Lyon, Lyon, France
| | - Mylène Seux
- IMADIS, Lyon, Bordeaux, Marseille, Dijon, France
| | - Adrien Acquier
- IMADIS, Lyon, Bordeaux, Marseille, Dijon, France
- CHU de Dijon, Dijon, France
| | - Guillaume Gorincour
- IMADIS, Lyon, Bordeaux, Marseille, Dijon, France
- ELSAN, Clinique Bouchard, Marseille, France
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24
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Diffusion-Weighted Imaging in Mild Traumatic Brain Injury: A Systematic Review of the Literature. Neuropsychol Rev 2023; 33:42-121. [PMID: 33721207 DOI: 10.1007/s11065-021-09485-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Accepted: 02/09/2021] [Indexed: 12/14/2022]
Abstract
There is evidence that diffusion-weighted imaging (DWI) is able to detect tissue alterations following mild traumatic brain injury (mTBI) that may not be observed on conventional neuroimaging; however, findings are often inconsistent between studies. This systematic review assesses patterns of differences in DWI metrics between those with and without a history of mTBI. A PubMed literature search was performed using relevant indexing terms for articles published prior to May 14, 2020. Findings were limited to human studies using DWI in mTBI. Articles were excluded if they were not full-length, did not contain original data, if they were case studies, pertained to military populations, had inadequate injury severity classification, or did not report post-injury interval. Findings were reported independently for four subgroups: acute/subacute pediatric mTBI, acute/subacute adult mTBI, chronic adult mTBI, and sport-related concussion, and all DWI acquisition and analysis methods used were included. Patterns of findings between studies were reported, along with strengths and weaknesses of the current state of the literature. Although heterogeneity of sample characteristics and study methods limited the consistency of findings, alterations in DWI metrics were most commonly reported in the corpus callosum, corona radiata, internal capsule, and long association pathways. Many acute/subacute pediatric studies reported higher FA and lower ADC or MD in various regions. In contrast, acute/subacute adult studies most commonly indicate lower FA within the context of higher MD and RD. In the chronic phase of recovery, FA may remain low, possibly indicating overall demyelination or Wallerian degeneration over time. Longitudinal studies, though limited, generally indicate at least a partial normalization of DWI metrics over time, which is often associated with functional improvement. We conclude that DWI is able to detect structural mTBI-related abnormalities that may persist over time, although future DWI research will benefit from larger samples, improved data analysis methods, standardized reporting, and increasing transparency.
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25
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Li Y, Ding VY, Chen H, Zhu G, Jiang B, Boothroyd D, Rezaii PG, Bet AM, Paulino AD, Weber A, Glushakova OY, Hayes RL, Wintermark M. Comparing blood biomarkers to clinical decision rules to select patients suspected of traumatic brain injury for head computed tomography. Neuroradiol J 2023; 36:68-75. [PMID: 35588232 PMCID: PMC9893157 DOI: 10.1177/19714009221101306] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
INTRODUCTION Traumatic brain injury (TBI) is a major public health concern in the U.S. Recommendations for patients admitted in the emergency department (ED) to receive head computed tomography (CT) scan are currently guided by various clinical decision rules. OBJECTIVE To compare how a blood biomarker approach compares with clinical decision rules in terms of predicting a positive head CT in adult patients suspected of TBI. METHODS We retrospectively identified patients transported to our emergency department and underwent a noncontrast head CT due to suspicion of TBI and who had blood samples available. Published thresholds for serum and plasma glial fibrillary acidic protein (GFAP), ubiquitin carboxyl-terminal hydrolase-L1 (UCH-L1), and serum S100β were used to make CT recommendations. These blood biomarker-based recommendations were compared to those achieved under widely used clinical head CT decision rules (Canadian, New Orleans, NEXUS II, and ACEP Clinical Policy). RESULTS Our study included 463 patients, of which 122 (26.3%) had one or more abnormalities presenting on head CT. Individual blood biomarkers achieved high negative predictive value (NPV) for abnormal head CT findings (88%-98%), although positive predictive value (PPV) was consistently low (25%-42%). A composite biomarker-based decision rule (GFAP+UCH-L1)'s NPV of 100% and PPV of 29% were comparable or better than those achieved under the clinical decision rules. CONCLUSION Blood biomarkers perform at least as well as clinical rules in terms of selecting TBI patients for head CT and may be easier to implement in the clinical setting. A prospective study is necessary to validate this approach.
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Affiliation(s)
- Ying Li
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Victoria Y Ding
- Quantitative Sciences Unit,
Department of Medicine, Stanford University, Stanford, CA, USA
| | - Hui Chen
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Guangming Zhu
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Bin Jiang
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Derek Boothroyd
- Quantitative Sciences Unit,
Department of Medicine, Stanford University, Stanford, CA, USA
| | - Paymon G Rezaii
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | - Anthony M Bet
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
| | | | - Art Weber
- Banyan Biomarkers Inc., San Diego, CA, USA
| | - Olena Y Glushakova
- Department of Neurosurgery, Virginia Commonwealth
University, Richmond, VA, USA
| | - Ronald L Hayes
- Department of Neurosurgery, Virginia Commonwealth
University, Richmond, VA, USA
| | - Max Wintermark
- Department of Radiology,
Neuroradiology Division, Stanford University, Stanford, CA, USA
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Jeong TS, Yee GT, Kim KG, Kim YJ, Lee SG, Kim WK. Automatically Diagnosing Skull Fractures Using an Object Detection Method and Deep Learning Algorithm in Plain Radiography Images. J Korean Neurosurg Soc 2023; 66:53-62. [PMID: 35650677 PMCID: PMC9837484 DOI: 10.3340/jkns.2022.0062] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Revised: 05/05/2022] [Accepted: 05/18/2022] [Indexed: 01/25/2023] Open
Abstract
OBJECTIVE Deep learning is a machine learning approach based on artificial neural network training, and object detection algorithm using deep learning is used as the most powerful tool in image analysis. We analyzed and evaluated the diagnostic performance of a deep learning algorithm to identify skull fractures in plain radiographic images and investigated its clinical applicability. METHODS A total of 2026 plain radiographic images of the skull (fracture, 991; normal, 1035) were obtained from 741 patients. The RetinaNet architecture was used as a deep learning model. Precision, recall, and average precision were measured to evaluate the deep learning algorithm's diagnostic performance. RESULTS In ResNet-152, the average precision for intersection over union (IOU) 0.1, 0.3, and 0.5, were 0.7240, 0.6698, and 0.3687, respectively. When the intersection over union (IOU) and confidence threshold were 0.1, the precision was 0.7292, and the recall was 0.7650. When the IOU threshold was 0.1, and the confidence threshold was 0.6, the true and false rates were 82.9% and 17.1%, respectively. There were significant differences in the true/false and false-positive/false-negative ratios between the anteriorposterior, towne, and both lateral views (p=0.032 and p=0.003). Objects detected in false positives had vascular grooves and suture lines. In false negatives, the detection performance of the diastatic fractures, fractures crossing the suture line, and fractures around the vascular grooves and orbit was poor. CONCLUSION The object detection algorithm applied with deep learning is expected to be a valuable tool in diagnosing skull fractures.
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Affiliation(s)
- Tae Seok Jeong
- Department of Traumatology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Gi Taek Yee
- Department of Neurosurgery, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Kwang Gi Kim
- Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Young Jae Kim
- Department of Biomedical Engineering, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Sang Gu Lee
- Department of Neurosurgery, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
| | - Woo Kyung Kim
- Department of Traumatology, Gil Medical Center, Gachon University College of Medicine, Incheon, Korea
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Wang H, Chen H, Liu C, Yuan L, Bao Y, Zhao G, Wang D, Song G. Successful resuscitation and multidisciplinary management of penetrating brain injury caused by tire explosion: A case report. Medicine (Baltimore) 2022; 101:e32048. [PMID: 36451440 PMCID: PMC9704937 DOI: 10.1097/md.0000000000032048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
RATIONALE Penetrating brain injury (PBI) is a rare trauma that presents as a difficult and serious surgical emergency for neurosurgeons in clinical practice. Our patient was admitted with a PBI caused by a tire explosion, which is an extremely rare cause of injury. PATIENT CONCERNS We report a case of a 28-year-old male patient who suffered a PBI when a tire exploded while it was being inflated with a high-pressure air pump. DIAGNOSES The patient was diagnosed with PBI presenting with multiple comminuted skull fractures, massive bone fragments with foreign bodies penetrating the underlying brain tissue of the top right frontal bone, multiple cerebral contusions, and intracranial hematoma. INTERVENTIONS Emergency combined multidisciplinary surgery was performed for the removal of the fragmented bone pieces, hematoma, and foreign bodies; decompression of the debridement flap; reconstruction of the anterior skull base; and repair of the dura mater. OUTCOMES The patient was successfully resuscitated and discharged 1 month later and is now recovering well. LESSONS Patients with PBI are critically ill. Therefore, timely, targeted examinations and appropriate multidisciplinary interventions through a green channel play a key role in assessing the condition, developing protocols, and preventing complications.
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Affiliation(s)
- Haozhan Wang
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
| | - Hao Chen
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - Changtong Liu
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
| | - Long Yuan
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
| | - Yonggang Bao
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
| | - Guodong Zhao
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
| | - Dengqin Wang
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
| | - Guohong Song
- Department of Clinical Medicine, Jining Medical University, Jining, Shandong Province, China
- Department of Neurosurgery, Affiliated Hospital of Jining Medical University, Jining, Shandong, China
- * Correspondence: Guohong Song, The Affiliated Hospital of Jining Medical University, No. 89 Guhuai Street, Jining 272000, Shandong Province, China (e-mail: )
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Anto-Ocrah M, Aboagye RG, Hasman L, Ghanem A, Owusu-Agyei S, Buranosky R. The elephant in the room: Intimate partner violence, women, and traumatic brain injury in sub-Saharan Africa. Front Neurol 2022; 13:917967. [PMID: 36147046 PMCID: PMC9485886 DOI: 10.3389/fneur.2022.917967] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 08/08/2022] [Indexed: 12/04/2022] Open
Abstract
Background Intimate partner violence (IPV) is a gendered form of violence that has been linked with traumatic brain injury (TBI). The prevalence of IPV in sub-Saharan Africa (SSA) is estimated to be one of the highest globally. Yet, little is known about the association between IPV and TBI in the SSA context. In this scoping review, we examine the intersection between IPV and TBI in SSA to identify gaps, as well as intervention opportunities. Methods Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses—Extension for Scoping Review (PRISMA-ScR) guidelines to guide our analyses and reporting, we searched for published articles indexed in the four largest and most comprehensive library databases: Pubmed, Embase, Web of Science and PsychInfo. Given the increasing attention that has been placed on gender disparities and health in recent years, we focused on studies published between 2010 and 2021. Results Our search yielded 5,947 articles and 1,258 were IPV and SSA related. Out of this, only ten examined the intersection between IPV and TBI. All focused on outcomes in female populations from South Africa (n = 5), Ghana (n = 3), Uganda (n = 1), and Cameroon (n = 1). They were a mix of qualitative studies (n = 3), neuro-imaging/biomarker studies (n = 3), case studies/reports (n = 2), quantitative surveys (n = 1) and mixed qualitative/quantitative study (n = 1). Six studies evaluated subjective reporting of IPV-induced TBI symptoms such as headaches, sleep disruptions, and ophthalmic injuries. Three examined objective assessments and included Hypothalamic-Pituitary-Adrenal (HPA) dysregulation detected by salivary cortisol levels, magnetic resonance imaging (MRI) including diffusion tensor imaging (DTI) to evaluate brain connectivity and white matter changes. One final study took a forensic anthropology lens to document an autopsy case report of IPV-induced mortality due to physical head and face trauma. Conclusion Our findings demonstrate that both subjective and objective assessments of IPV and TBI are possible in “resource-limited” settings. The combination of these outcomes will be critical for viewing IPV through a clinical rather than a cultural lens, and for substantiating the assertion that gender, is indeed, a social determinant of brain health.
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Affiliation(s)
- Martina Anto-Ocrah
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- *Correspondence: Martina Anto-Ocrah
| | - Richard Gyan Aboagye
- Department of Family and Community Health, Fred N. Binka School of Public Health, University of Health and Allied Sciences, Hohoe, Ghana
| | - Linda Hasman
- Institute for Innovative Education: Miner Libraries, University of Rochester Medical Center, Rochester, NY, United States
| | - Ali Ghanem
- Institute for Global Health, University College London, London, United Kingdom
| | - Seth Owusu-Agyei
- Institute of Health Research, University of Health and Allied Sciences, Hohoe, Ghana
| | - Raquel Buranosky
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States
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Park S, Yu IK, Kim H. MRI Findings of Acute Hippocampal Disorders: Pictorial Essay. JOURNAL OF THE KOREAN SOCIETY OF RADIOLOGY 2022; 83:1046-1058. [PMID: 36276220 PMCID: PMC9574276 DOI: 10.3348/jksr.2021.0101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/29/2021] [Accepted: 09/23/2021] [Indexed: 12/05/2022]
Abstract
The hippocampus is one of the most metabolically active regions of the brain; therefore, it may be affected by various acute disorders. This study aimed to introduce and categorize various acute conditions that can involve the hippocampus and explain the findings of MRI, especially diffusion-weighted imaging (DWI). Acute hippocampal disorders are divided into six categories: infection, inflammation, metabolic, ischemic, traumatic, and miscellaneous. In this study, patients were retrospectively reviewed based on clinical findings and MRI, especially DWI. All diseases had been confirmed clinically or pathologically. Many acute hippocampal disorders overlap with the clinical manifestations. Thus, it is necessary to categorize acute hippocampal lesions and understand their specific imaging findings for differential diagnosis.
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Jumah F, Chotai S, Hilden P, Raju B, Nagaraj A, Agarwalla P, Johnson S, Gupta G, Sun H, Nanda A. Characteristics and Outcomes of Discharge Against Medical Advice and 30-Day Readmissions After Concussion: Analysis of the Nationwide Readmissions Database. Neurosurgery 2022; 91:373-380. [PMID: 35593720 DOI: 10.1227/neu.0000000000002040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/24/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Little is known about the impact of discharge against medical advice (DAMA) in patients admitted with concussion. OBJECTIVE To explore the prevalence of DAMA and its effect on 30-day readmissions and cost in concussion using a nationally representative sample. METHODS The Nationwide Readmissions Database was queried for concussion admissions and their disposition at discharge between 2010 and 2014. Included patients were ≥18 years old who were admitted with concussion and had <1 hour loss of consciousness. We excluded in-hospital deaths or discharge dispositions other than home or against medical advice. Univariate and multivariate analyses were performed to determine characteristics associated with DAMA and 30-day readmissions. RESULTS A total of 38 919 index admissions were identified, which resulted in 998 (2.6%) DAMA. In multivariate analysis, characteristics associated with DAMA included younger age (odds ratio [OR] = 0.84, 95% CI 0.80-0.88), male sex (1.47, 1.22-1.76), an Elixhauser comorbidity index >3 (1.67, 1.15-1.60), and assault (2.02, 1.48-2.75) and fall injuries (1.28, 1.03-1.60). The highest-income quartile was negatively associated with DAMA (0.91, 0.73-1.13). In multivariate analysis, DAMA (1.63, 1.29-2.06), higher comorbidity index (2.61, 2.22-3.06), and self-inflicted mode of injury (2.28, 1.30-4.02) were independently associated with 30-day readmission. The most common indication for readmission in both routine and DAMA groups was traumatic injury (21.1% and 24.5%, respectively). CONCLUSION DAMA is an independent risk factor for readmission in patients admitted for concussion. The variables associated with DAMA identified in this study can be used to design patient-centered interventions that can be implemented to reduce DAMA and its impact on clinical outcomes in patients with traumatic brain injury.
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Affiliation(s)
- Fareed Jumah
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Silky Chotai
- Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Patrick Hilden
- Rutgers Neurosurgery Health Outcomes, Policy, and Economics (HOPE) Center, New Brunswick, New Jersey, USA
| | - Bharath Raju
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Anmol Nagaraj
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Pankaj Agarwalla
- Department of Neurosurgery, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
| | - Stephen Johnson
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Gaurav Gupta
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Hai Sun
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA
| | - Anil Nanda
- Department of Neurosurgery, Rutgers-Robert Wood Johnson Medical School and University Hospital, New Brunswick, New Jersey, USA.,Department of Neurosurgery, Rutgers-New Jersey Medical School, Newark, New Jersey, USA
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31
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Singh S, Hearps S, Nishijima DK, Cheek JA, Borland M, Dalziel S, Holmes J, Kuppermann N, Babl FE, Hoch JS. Cost-effectiveness of patient observation on cranial CT use with minor head trauma. Arch Dis Child 2022; 107:712-718. [PMID: 35193874 DOI: 10.1136/archdischild-2021-323701] [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] [Received: 12/10/2021] [Accepted: 02/04/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVE To evaluate the cost-effectiveness of planned observation on cranial CT use in children with minor head trauma. DESIGN Planned secondary analysis of a multicentre prospective observation study. SETTING Australia and New Zealand. PATIENTS An analytic cohort of 18 471 children aged <18 years with Glasgow Coma Scale scores 14-15 presenting <24 hours after blunt head trauma stratified by the Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury (TBI) risk categories. INTERVENTION A plan for observation and immediate CT scan were documented after the initial assessment. The planned observation group included those with planned observation and no immediate plan for CT. MAIN OUTCOME MEASURES Taking an Australian public-funded healthcare perspective, we estimated the cost-effectiveness of planned observation on the adjusted mean costs per child and CT use reduction by net benefit regression analysis using ordinary least squares with robust SEs and bootstrapping. All costs presented in 2018 euros. RESULTS Planned observation in 4945 (27%) children was cost-saving of €85 (95% CI -120 to -51) with 10.4% lower CT use (95% CI 9.6 to 11.2). This strategy was cost-saving for the PECARN high-risk (-€757 (95% CI -961 to -554)) and intermediate-risk (-€52 (95% CI -99 to -4.3)) categories, with 43% (95% CI 39 to 47) and 11% (95% CI 9.6 to 12.4) lower CT use, respectively. The very low-risk category incurred more cost of €86 (95% CI 67 to 104) with planned observation and 0.05% lower CT use (95% CI -0.61 to 0.71). CONCLUSION Planned ED observation in selected children with minor head trauma is cost-effective for reducing CT use for the PECARN intermediate-risk and high-risk categories. TRIAL REGISTRATION NUMBER ACTRN12614000463673.
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Affiliation(s)
- Sonia Singh
- Department of Paediatrics, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia .,Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Department of Emergency Medicine, University of California Davis School of Medicine, Sacramento, California, USA
| | - Stephen Hearps
- Child Neuropsychology, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Daniel K Nishijima
- Department of Emergency Medicine, University of California Davis School of Medicine, Sacramento, California, USA
| | - John Alexander Cheek
- Department of Paediatrics, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia.,Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Emergency Department, Royal Children's Hospital Melbourne, Parkville, Victoria, Australia
| | - Meredith Borland
- Emergency Medicine, Perth Children's Hospital, Nedlands, Western Australia, Australia.,Divisions of Paediatrics and Emergency Medicine, University of Western Australia, Crawley, Western Australia, Australia
| | - Stuart Dalziel
- Emergency Department, Starship Children's Health, Auckland, New Zealand.,Departments of Surgery and Paediatrics: Child and Youth Health, The University of Auckland, Auckland, New Zealand
| | - James Holmes
- Department of Emergency Medicine, University of California Davis School of Medicine, Sacramento, California, USA.,Center for Healthcare Policy and Research, University of California Davis Health System, Sacramento, California, USA
| | - Nathan Kuppermann
- Department of Emergency Medicine, University of California Davis School of Medicine, Sacramento, California, USA.,Department of Pediatrics, University of California Davis School of Medicine, Sacramento, California, USA
| | - Franz E Babl
- Department of Paediatrics, The University of Melbourne Faculty of Medicine Dentistry and Health Sciences, Melbourne, Victoria, Australia.,Clinical Sciences, Murdoch Children's Research Institute, Parkville, Victoria, Australia.,Emergency Department, Royal Children's Hospital Melbourne, Parkville, Victoria, Australia
| | - Jeffrey S Hoch
- Center for Healthcare Policy and Research, University of California Davis Health System, Sacramento, California, USA.,Department of Public Health Sciences, University of California Davis, Davis, California, USA
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Abstract
Headache is a common presenting symptom in the ambulatory setting that often prompts imaging. The increased use and associated health care money spent in the setting of headache have raised questions about the cost-effectiveness of neuroimaging in this setting. Neuroimaging for headache in most cases is unlikely to reveal significant abnormality or impact patient management. In this article, reasons behind an observed increase in neuroimaging and its impact on health care expenditures are discussed. The typical imaging modalities available and various imaging guidelines for common clinical headache scenarios are presented, including recommendations from the American College of Radiology.
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Lui A, Kumar KK, Grant GA. Management of Severe Traumatic Brain Injury in Pediatric Patients. FRONTIERS IN TOXICOLOGY 2022; 4:910972. [PMID: 35812167 PMCID: PMC9263560 DOI: 10.3389/ftox.2022.910972] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
The optimal management of severe traumatic brain injury (TBI) in the pediatric population has not been well studied. There are a limited number of research articles studying the management of TBI in children. Given the prevalence of severe TBI in the pediatric population, it is crucial to develop a reference TBI management plan for this vulnerable population. In this review, we seek to delineate the differences between severe TBI management in adults and children. Additionally, we also discuss the known molecular pathogenesis of TBI. A better understanding of the pathophysiology of TBI will inform clinical management and development of therapeutics. Finally, we propose a clinical algorithm for the management and treatment of severe TBI in children using published data.
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Affiliation(s)
- Austin Lui
- Touro University College of Osteopathic Medicine, Vallejo, CA, United States
| | - Kevin K. Kumar
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
- Division of Pediatric Neurosurgery, Lucile Packard Children’s Hospital, Palo Alto, CA, United States
| | - Gerald A. Grant
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
- Division of Pediatric Neurosurgery, Lucile Packard Children’s Hospital, Palo Alto, CA, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
- *Correspondence: Gerald A. Grant,
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Nwafor DC, Brichacek AL, Foster CH, Lucke-Wold BP, Ali A, Colantonio MA, Brown CM, Qaiser R. Pediatric Traumatic Brain Injury: An Update on Preclinical Models, Clinical Biomarkers, and the Implications of Cerebrovascular Dysfunction. J Cent Nerv Syst Dis 2022; 14:11795735221098125. [PMID: 35620529 PMCID: PMC9127876 DOI: 10.1177/11795735221098125] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 04/14/2022] [Indexed: 11/15/2022] Open
Abstract
Traumatic brain injury (TBI) is a leading cause of pediatric morbidity and mortality. Recent studies suggest that children and adolescents have worse post-TBI outcomes and take longer to recover than adults. However, the pathophysiology and progression of TBI in the pediatric population are studied to a far lesser extent compared to the adult population. Common causes of TBI in children are falls, sports/recreation-related injuries, non-accidental trauma, and motor vehicle-related injuries. A fundamental understanding of TBI pathophysiology is crucial in preventing long-term brain injury sequelae. Animal models of TBI have played an essential role in addressing the knowledge gaps relating to pTBI pathophysiology. Moreover, a better understanding of clinical biomarkers is crucial to diagnose pTBI and accurately predict long-term outcomes. This review examines the current preclinical models of pTBI, the implications of pTBI on the brain’s vasculature, and clinical pTBI biomarkers. Finally, we conclude the review by speculating on the emerging role of the gut-brain axis in pTBI pathophysiology.
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Affiliation(s)
- Divine C. Nwafor
- Department of Neuroscience, West Virginia University School of Medicine, Morgantown, WV, USA
- West Virginia University School of Medicine, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
| | - Allison L. Brichacek
- Department of Microbiology, Immunology, and Cell Biology, West Virginia University School of Medicine, Morgantown, WV, USA
| | - Chase H. Foster
- Department of Neurosurgery, George Washington University Hospital, Washington D.C., USA
| | | | - Ahsan Ali
- Department of Neuroscience, West Virginia University School of Medicine, Morgantown, WV, USA
| | | | - Candice M. Brown
- Department of Neuroscience, West Virginia University School of Medicine, Morgantown, WV, USA
- Rockefeller Neuroscience Institute, West Virginia University, Morgantown, WV, USA
- Department of Microbiology, Immunology, and Cell Biology, West Virginia University School of Medicine, Morgantown, WV, USA
| | - Rabia Qaiser
- Department of Neurosurgery, Baylor Scott and White, Temple, TX, USA
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Minchew HM, Ferren SL, Christian SK, Hu J, Keselman P, Brooks WM, Andrews BT, Harris JL. Comparing Imaging Biomarkers of Cerebral Edema after TBI in Young Adult Male and Female Rats. Brain Res 2022; 1789:147945. [PMID: 35595066 DOI: 10.1016/j.brainres.2022.147945] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/16/2022] [Accepted: 05/13/2022] [Indexed: 11/02/2022]
Abstract
Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. Cerebral edema following TBI is known to play a critical role in injury severity and prognosis. In the current study we used multimodal magnetic resonance imaging (MRI) to assess cerebral edema 24 hours after unilateral contusive TBI in male and female rats. We then directly quantified brain water content in the same subjectsex vivo.We found that both males and females had similarly elevated T2 values after TBI compared with sham controls. Apparent diffusion coefficient (ADC) was more variable than T2 and did not show significant injury effects in males or females. Brain water was elevated in male TBI rats compared with sham controls, but there was no difference between female TBI and sham groups. Notably, MRI biomarkers of edema were more closely correlated with brain water in male rats; female rats did not show any relationship between brain water and T2 or ADC. These observations raise questions about the interpretation of radiological findings traditionally interpreted as edema in female TBI patients. A better understanding of sex differences and similarities in the pathophysiology of post-traumatic edema is needed to help improve patient management and the development of effective treatment strategies for men and women.
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Affiliation(s)
- Heather M Minchew
- University of Kansas School of Medicine, Kansas City, KS, United States
| | - Sadie L Ferren
- Department of Anatomy and Cell Biology, KUMC, Kansas City, KS, United States
| | - Sarah K Christian
- Department of Anatomy and Cell Biology, KUMC, Kansas City, KS, United States
| | - Jinxiang Hu
- Department of Biostatistics, KUMC, Kansas City, KS, United States
| | - Paul Keselman
- Hoglund Biomedical Imaging Center, KUMC, Kansas City, KS, United States
| | - William M Brooks
- Hoglund Biomedical Imaging Center, KUMC, Kansas City, KS, United States; Depatment of Neurology, KUMC, Kansas City, KS, United States
| | - Brian T Andrews
- Department of Otolaryngology, University of Iowa Carver College of Medicine, Iowa City, IA, United States
| | - Janna L Harris
- Department of Anatomy and Cell Biology, KUMC, Kansas City, KS, United States; Hoglund Biomedical Imaging Center, KUMC, Kansas City, KS, United States.
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Alagic Z, Diaz Cardenas J, Halldorsson K, Grozman V, Wallgren S, Suzuki C, Helmenkamp J, Koskinen SK. Deep learning versus iterative image reconstruction algorithm for head CT in trauma. Emerg Radiol 2022; 29:339-352. [PMID: 34984574 PMCID: PMC8917108 DOI: 10.1007/s10140-021-02012-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 12/19/2021] [Indexed: 10/27/2022]
Abstract
PURPOSE To compare the image quality between a deep learning-based image reconstruction algorithm (DLIR) and an adaptive statistical iterative reconstruction algorithm (ASiR-V) in noncontrast trauma head CT. METHODS Head CT scans from 94 consecutive trauma patients were included. Images were reconstructed with ASiR-V 50% and the DLIR strengths: low (DLIR-L), medium (DLIR-M), and high (DLIR-H). The image quality was assessed quantitatively and qualitatively and compared between the different reconstruction algorithms. Inter-reader agreement was assessed by weighted kappa. RESULTS DLIR-M and DLIR-H demonstrated lower image noise (p < 0.001 for all pairwise comparisons), higher SNR of up to 82.9% (p < 0.001), and higher CNR of up to 53.3% (p < 0.001) compared to ASiR-V. DLIR-H outperformed other DLIR strengths (p ranging from < 0.001 to 0.016). DLIR-M outperformed DLIR-L (p < 0.001) and ASiR-V (p < 0.001). The distribution of reader scores for DLIR-M and DLIR-H shifted towards higher scores compared to DLIR-L and ASiR-V. There was a tendency towards higher scores with increasing DLIR strengths. There were fewer non-diagnostic CT series for DLIR-M and DLIR-H compared to ASiR-V and DLIR-L. No images were graded as non-diagnostic for DLIR-H regarding intracranial hemorrhage. The inter-reader agreement was fair-good between the second most and the less experienced reader, poor-moderate between the most and the less experienced reader, and poor-fair between the most and the second most experienced reader. CONCLUSION The image quality of trauma head CT series reconstructed with DLIR outperformed those reconstructed with ASiR-V. In particular, DLIR-M and DLIR-H demonstrated significantly improved image quality and fewer non-diagnostic images. The improvement in qualitative image quality was greater for the second most and the less experienced readers compared to the most experienced reader.
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Affiliation(s)
- Zlatan Alagic
- Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden.
- Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, 17177, Stockholm, Sweden.
| | | | - Kolbeinn Halldorsson
- Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden
| | - Vitali Grozman
- Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 17177, Stockholm, Sweden
| | - Stig Wallgren
- Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden
| | - Chikako Suzuki
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 17177, Stockholm, Sweden
| | - Johan Helmenkamp
- Department of Medical Physics and Nuclear Medicine, Karolinska University Hospital, 17176, Stockholm, Sweden
| | - Seppo K Koskinen
- Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden
- Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institutet, 17177, Stockholm, Sweden
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Medeiros GC, Twose C, Weller A, Dougherty JW, Goes FS, Sair HI, Smith GS, Roy D. Neuroimaging correlates of depression after traumatic brain injury: A systematic review. J Neurotrauma 2022; 39:755-772. [PMID: 35229629 DOI: 10.1089/neu.2021.0374] [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: 11/12/2022] Open
Abstract
Depression is the most frequent neuropsychiatric complication after traumatic brain injury (TBI) and is associated with poorer outcomes. Neuroimaging has the potential to improve our understanding of the neural correlates of depression after TBI and may improve our capacity to accurately predict and effectively treat this condition. We conducted a systematic review of structural and functional neuroimaging studies that examined the association between depression after TBI, and neuroimaging measures. Electronic searches were conducted in four databases and were complemented by manual searches. In total, 2,035 citations were identified and, ultimately, 38 articles were included totaling 1,793 individuals (median [25%-75%] sample size of 38.5 (21.8-54.3) individuals). The most frequently used modality was structural magnetic resonance imaging (MRI) (n=17, 45%), followed by diffusion tensor imaging (n=11, 29%), resting-state functional MRI (n=10, 26%), task-based functional MRI (n=4, 8%), and positron emission tomography (n=2, 4%). Most studies (n=27, 71%) were cross-sectional. Overall, depression after TBI was associated with lower grey matter measures (volume, thickness, and/or density) and greater white matter damage. However, identification of specific brain areas was somewhat inconsistent. Findings that were replicated in more than one study included reduced grey matter in the rostral anterior cingulate cortex, prefrontal cortex and hippocampus, and damage in five white matter tracts (cingulum, internal capsule, superior longitudinal fasciculi, anterior, and posterior corona radiata). This systematic review found that the available data did not converge on a clear neuroimaging biomarker for depression after TBI. However, there are promising targets that warrant further study.
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Affiliation(s)
- Gustavo C Medeiros
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Claire Twose
- Welch Medical Library, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Alexandra Weller
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - John W Dougherty
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Fernando S Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Haris I Sair
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Gwenn S Smith
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Durga Roy
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Diaz-Pacheco V, Vargas-Medrano J, Tran E, Nicolas M, Price D, Patel R, Tonarelli S, Gadad BS. Prognosis and Diagnostic Biomarkers of Mild Traumatic Brain Injury: Current Status and Future Prospects. J Alzheimers Dis 2022; 86:943-959. [PMID: 35147534 DOI: 10.3233/jad-215158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Mild traumatic brain injury (mTBI) is the most prevalent type of TBI (80-90%). It is characterized by a loss consciousness for less than 30 minutes, post-traumatic amnesia for less than 24 hours, and Glasgow Coma Score of 13-15. Accurately diagnosing mTBIs can be a challenge because the majority of these injuries do not show noticeable or visible changes on neuroimaging studies. Appropriate determination of mTBI is tremendously important because it might lead in some cases to post-concussion syndrome, cognitive impairments including attention, memory, and speed of information processing problems. The scientists have studied different methods to improve mTBI diagnosis and enhanced approaches that would accurately determine the severity of the trauma. The present review focuses on discussing the role of biomarkers as potential key factors in diagnosing mTBI. The present review focuses on 1) protein based peripheral and CNS markers, 2) genetic biomarkers, 3) imaging biomarkers, 4) neurophysiological biomarkers, and 5) the studies and clinical trials in mTBI. Each section provides information and characteristics on different biomarkers for mTBI.
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Affiliation(s)
- Valeria Diaz-Pacheco
- Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA.,Southwest Brain Bank, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Javier Vargas-Medrano
- Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA.,Southwest Brain Bank, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Eric Tran
- Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Meza Nicolas
- Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Diamond Price
- The Chicago School of Professional Psychology, Irvine, CA, USA
| | - Richa Patel
- Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Silvina Tonarelli
- Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA
| | - Bharathi S Gadad
- Department of Psychiatry, Paul L. Foster School of Medicine, Texas Tech University Health Science Center, El Paso, TX, USA.,Southwest Brain Bank, Texas Tech University Health Science Center, El Paso, TX, USA
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Wilde EA, Wanner I, Kenney K, Gill J, Stone JR, Disner S, Schnakers C, Meyer R, Prager EM, Haas M, Jeromin A. A Framework to Advance Biomarker Development in the Diagnosis, Outcome Prediction, and Treatment of Traumatic Brain Injury. J Neurotrauma 2022; 39:436-457. [PMID: 35057637 PMCID: PMC8978568 DOI: 10.1089/neu.2021.0099] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Elisabeth A. Wilde
- University of Utah, Neurology, 383 Colorow, Salt Lake City, Utah, United States, 84108
- VA Salt Lake City Health Care System, 20122, 500 Foothill Dr., Salt Lake City, Utah, United States, 84148-0002
| | - Ina Wanner
- UCLA, Semel Institute, NRB 260J, 635 Charles E. Young Drive South, Los Angeles, United States, 90095-7332, ,
| | - Kimbra Kenney
- Uniformed Services University of the Health Sciences, Neurology, Center for Neuroscience and Regenerative Medicine, 4301 Jones Bridge Road, Bethesda, Maryland, United States, 20814
| | - Jessica Gill
- National Institutes of Health, National Institute of Nursing Research, 1 cloister, Bethesda, Maryland, United States, 20892
| | - James R. Stone
- University of Virginia, Radiology and Medical Imaging, Box 801339, 480 Ray C. Hunt Dr. Rm. 185, Charlottesville, Virginia, United States, 22903, ,
| | - Seth Disner
- Minneapolis VA Health Care System, 20040, Minneapolis, Minnesota, United States
- University of Minnesota Medical School Twin Cities, 12269, 10Department of Psychiatry and Behavioral Sciences, Minneapolis, Minnesota, United States
| | - Caroline Schnakers
- Casa Colina Hospital and Centers for Healthcare, 6643, Pomona, California, United States
- Ronald Reagan UCLA Medical Center, 21767, Los Angeles, California, United States
| | - Restina Meyer
- Cohen Veterans Bioscience, 476204, New York, New York, United States
| | - Eric M Prager
- Cohen Veterans Bioscience, 476204, External Affairs, 535 8th Ave, New York, New York, United States, 10018
| | - Magali Haas
- Cohen Veterans Bioscience, 476204, 535 8th Avenue, 12th Floor, New York City, New York, United States, 10018,
| | - Andreas Jeromin
- Cohen Veterans Bioscience, 476204, Translational Sciences, Cambridge, Massachusetts, United States
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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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Wong KK, Cummock JS, He Y, Ghosh R, Volpi JJ, Wong STC. Retrospective study of deep learning to reduce noise in non-contrast head CT images. Comput Med Imaging Graph 2021; 94:101996. [PMID: 34637998 DOI: 10.1016/j.compmedimag.2021.101996] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Revised: 08/30/2021] [Accepted: 09/06/2021] [Indexed: 10/20/2022]
Abstract
PURPOSE Presented herein is a novel CT denoising method uses a skip residual encoder-decoder framework with group convolutions and a novel loss function to improve the subjective and objective image quality for improved disease detection in patients with acute ischemic stroke (AIS). MATERIALS AND METHODS In this retrospective study, confirmed AIS patients with full-dose NCCT head scans were randomly selected from a stroke registry between 2016 and 2020. 325 patients (67 ± 15 years, 176 men) were included. 18 patients each with 4-7 NCCTs performed within 5-day timeframe (83 total scans) were used for model training; 307 patients each with 1-4 NCCTs performed within 5-day timeframe (380 total scans) were used for hold-out testing. In the training group, a mean CT was created from the patient's co-registered scans for each input CT to train a rotation-reflection equivariant U-Net with skip and residual connections, as well as a group convolutional neural network (SRED-GCNN) using a custom loss function to remove image noise. Denoising performance was compared to the standard Block-matching and 3D filtering (BM3D) method and RED-CNN quantitatively and visually. Signal-to-noise ratio (SNR) and contrast-to-noise (CNR) were measured in manually drawn regions-of-interest in grey matter (GM), white matter (WM) and deep grey matter (DG). Visual comparison and impact on spatial resolution were assessed through phantom images. RESULTS SRED-GCNN reduced the original CT image noise significantly better than BM3D, with SNR improvements in GM, WM, and DG by 2.47x, 2.83x, and 2.64x respectively and CNR improvements in DG/WM and GM/WM by 2.30x and 2.16x respectively. Compared to the proposed SRED-GCNN, RED-CNN reduces noise effectively though the results are visibly blurred. Scans denoised by the SRED-GCNN are shown to be visually clearer with preserved anatomy. CONCLUSION The proposed SRED-GCNN model significantly reduces image noise and improves signal-to-noise and contrast-to-noise ratios in 380 unseen head NCCT cases.
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Affiliation(s)
- Kelvin K Wong
- Systems Medicine and Bioengineering, Houston Methodist Cancer Center, Houston Methodist Hospital and Department of Radiology, Weill Cornell Medicine, 6670 Bertner Ave, Houston, TX 77030, USA; The Ting Tsung and Wei Fong Chao Center for BRAIN, Houston Methodist Hospital, 6670 Bertner Ave, Houston, TX 77030, USA; Department of Radiology, Houston Methodist Institute for Academic Medicine, 6670 Bertner Ave, Houston, TX 77030, USA.
| | - Jonathon S Cummock
- Systems Medicine and Bioengineering, Houston Methodist Cancer Center, Houston Methodist Hospital and Department of Radiology, Weill Cornell Medicine, 6670 Bertner Ave, Houston, TX 77030, USA; MD/PhD Program, Texas A&M University College of Medicine, 8447 Riverside Parkway, Suite 1002, Bryan, TX 77807, USA
| | - Yunjie He
- Systems Medicine and Bioengineering, Houston Methodist Cancer Center, Houston Methodist Hospital and Department of Radiology, Weill Cornell Medicine, 6670 Bertner Ave, Houston, TX 77030, USA
| | - Rahul Ghosh
- Systems Medicine and Bioengineering, Houston Methodist Cancer Center, Houston Methodist Hospital and Department of Radiology, Weill Cornell Medicine, 6670 Bertner Ave, Houston, TX 77030, USA; MD/PhD Program, Texas A&M University College of Medicine, 8447 Riverside Parkway, Suite 1002, Bryan, TX 77807, USA
| | - John J Volpi
- Department of Neurology, Houston Methodist Institute for Academic Medicine, 6670 Bertner Ave, Houston, TX 77030, USA
| | - Stephen T C Wong
- Systems Medicine and Bioengineering, Houston Methodist Cancer Center, Houston Methodist Hospital and Department of Radiology, Weill Cornell Medicine, 6670 Bertner Ave, Houston, TX 77030, USA; The Ting Tsung and Wei Fong Chao Center for BRAIN, Houston Methodist Hospital, 6670 Bertner Ave, Houston, TX 77030, USA; Department of Radiology, Houston Methodist Institute for Academic Medicine, 6670 Bertner Ave, Houston, TX 77030, USA; Department of Neuroscience and Experimental Therapeutics, Texas A&M University College of Medicine, 8447 Riverside Parkway, Suite 1005, Bryan, TX 77807, USA.
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Edlmann E, Whitfield PC, Kolias A, Hutchinson PJ. Pathogenesis of Chronic Subdural Hematoma: A Cohort Evidencing De Novo and Transformational Origins. J Neurotrauma 2021; 38:2580-2589. [PMID: 33787358 DOI: 10.1089/neu.2020.7574] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
Chronic subdural hematoma (CSDH) is a common neurosurgical pathology, yet conflicting opinions exist concerning the pathophysiological processes involved. Many consider CSDH a product of an aged acute subdural hematoma (ASDH) secondary to trauma. Serial imaging, however, has demonstrated CSDH formation in patients without any initial ASDH. To understand the relevance of acute hemorrhage in a cohort of patients with CSDH, transformation from an ASDH were categorized as CSDH-acute transformed (CSDH-AT) and those without any acute hemorrhage at the outset as CSDH-de-novo (CSDH-DN). A cohort of 41 eligible patients with CSDH were included, with baseline imaging after trauma (or spontaneous ASDH) available for assessment of acute hemorrhage. Volumetric analysis of all subdural collections and measurements of baseline atrophy were performed. In 37% of cases, there was an ASDH present on baseline imaging (CSDH-AT), whereas 63% had no acute hemorrhage at baseline (CSDH-DN). The CSDH-ATs developed more rapidly (mean 16 days from baseline to diagnosis) and were smaller in volume than the CSDH-DNs, which developed at a mean delay of 57 days. In 54% of the CSDH-DNs, a subdural hygroma was present on baseline imaging, and there was a wide range of baseline cerebral atrophy. This study provides radiological evidence for two distinct pathways in the formation of CSDH, with CSDH-DN occurring more commonly and often involving subdural hygroma. Further work is needed to understand whether the pathological origin has implications for patient outcome.
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Affiliation(s)
- Ellie Edlmann
- South West Neurosurgical Centre, University Hospitals Plymouth NHS t\Trust, Plymouth, United Kingdom
- Faculty of Health: Medicine, Dentistry and Human Sciences, University of Plymouth, Plymouth, United Kingdom
| | - Peter C Whitfield
- South West Neurosurgical Centre, University Hospitals Plymouth NHS t\Trust, Plymouth, United Kingdom
| | - Angelos Kolias
- Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge, United Kingdom
| | - Peter J Hutchinson
- Department of Clinical Neurosciences, Cambridge Biomedical Campus, Cambridge, United Kingdom
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Nishii T, Okuyama S, Horinouchi H, Chikuda R, Kamei E, Higuchi S, Ohta Y, Fukuda T. A Real-World Clinical Implementation of Automated Processing Using Intelligent Work Aid for Rapid Reformation at the Orbitomeatal Line in Head Computed Tomography. Invest Radiol 2021; 56:599-604. [PMID: 33813578 DOI: 10.1097/rli.0000000000000779] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
MATERIALS AND METHODS We retrospectively reviewed 781 head CTs (median, 70 years; 441 men) collected by CT systems from 3 vendors. In addition to the orbitomeatal line image reformatted by a CT specialist as a reference, we obtained the fully automated orbitomeatal line image using the intelligent work aid. We calculated the offset angle from the reference of the automatically reformatted image. We defined the large offset angle groups as those with an offset angle greater than 3 degrees. Multivariate logistic regression was used to determine the independent factors for the large offset angle groups. We compared the postprocessing times measured using the intelligent work aid or by a CT specialist. RESULTS With the intelligent work aid, 99.7% of CTs were automatically reformatted to the orbitomeatal line without error. Furthermore, 88.1% of CTs were within the 3 degrees' offset angle when compared with the reference produced by a CT specialist. The median offset angle from the reference was 1.41 degrees. Multivariate analysis showed that the offset angle of the positioning plane was an independent factor (odds ratio, 1.045; P = 0.005) for predicting the large offset angle group. Furthermore, this technique was 4 times faster (6.4 ± 0.7 seconds) than a CT specialist (25.6 ± 6.4 seconds). CONCLUSIONS The intelligent work aid can generate a fast and precise head CT image aligned at the orbitomeatal line, even in real-world clinical CTs. However, precise positioning remains essential.
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Affiliation(s)
- Tatsuya Nishii
- From the Department of Radiology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
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Bigler ED, Allder S. Improved neuropathological identification of traumatic brain injury through quantitative neuroimaging and neural network analyses: Some practical approaches for the neurorehabilitation clinician. NeuroRehabilitation 2021; 49:235-253. [PMID: 34397432 DOI: 10.3233/nre-218023] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
BACKGROUND Quantitative neuroimaging analyses have the potential to provide additional information about the neuropathology of traumatic brain injury (TBI) that more thoroughly informs the neurorehabilitation clinician. OBJECTIVE Quantitative neuroimaging is typically not covered in the standard radiological report, but often can be extracted via post-processing of clinical neuroimaging studies, provided that the proper volume acquisition sequences were originally obtained. METHODS Research and commercially available quantitative neuroimaging methods provide region of interest (ROI) quantification metrics, lesion burden volumetrics and cortical thickness measures, degree of focal encephalomalacia, white matter (WM) abnormalities and residual hemorrhagic pathology. If present, diffusion tensor imaging (DTI) provides a variety of techniques that aid in evaluating WM integrity. Using quantitatively identified structural and ROI neuropathological changes are most informative when done from a neural network approach. RESULTS Viewing quantitatively identifiable damage from a neural network perspective provides the neurorehabilitation clinician with an additional tool for linking brain pathology to understand symptoms, problems and deficits as well as aid neuropsychological test interpretation. All of these analyses can be displayed in graphic form, including3-D image analysis. A case study approach is used to demonstrate the utility of quantitative neuroimaging and network analyses in TBI. CONCLUSIONS Quantitative neuroimaging may provide additional useful information for the neurorehabilitation clinician.
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Affiliation(s)
- Erin D Bigler
- Department of Neurology and Psychiatry, University of Utah, Salt Lake City, UT, USA.,Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, USA.,Department of Neurology, University of California-Davis, Sacramento, CA, USA
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Pradhan P, Pradhan A, Shrestha AP, Shrestha A, Paudel RC, Shrestha R. Impact of implementation of the national institute for health and clinical excellence (NICE) head injury guideline in a tertiary care center emergency department: A pre and post-intervention study. PLoS One 2021; 16:e0254754. [PMID: 34264993 PMCID: PMC8282013 DOI: 10.1371/journal.pone.0254754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 07/04/2021] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION Head injury, a common presentation to the emergency department (ED), is a substantial problem in developing countries like Nepal. The current national institute for health and clinical excellence (NICE) guideline revised in January 2014 focuses on effective clinical assessment and early management of head injuries according to their severity in all age groups. This study assessed the impact of implementing this guideline on the proportions of computed tomography (CT) head scans, guideline adherence, and confidence level of the attending physicians. METHODS We consecutively recruited 139 traumatic head injury (THI) patients in this prospective pre-post interventional study conducted in the ED of a tertiary care center. We implemented the NICE guideline into routine practice using multimodal intervention through physicians' education sessions, information sheets and guideline-dissemination. The pre and post-implementation CT head scan rates were compared. The post-implementation guideline adherence was assessed. Online Google form-questionnaires including 12 validated case scenarios were distributed to the attending physicians at the end of both phases to assess their confidence levels. RESULTS The implementation resulted in a statistically significant decrease in the proportion of CT head scan rates from 92.0% to 70.0% (p-value = 0.005). Following educational interventions, improved guideline adherence of 20.3 percentage points (p-value = 0.001) was observed. Nine ED attending physicians were enrolled in the study who showed statistically significant improvement in their confidence level following the intervention. The NICE guideline showed a sensitivity and specificity of 93.6% and 76.4% with 82.6% accuracy compared to that of clinical judgment (100%, 34.6%, and 58.1% respectively) in detecting intracranial lesions. CONCLUSION The implementation was successful in satisfying the aim of the NICE guideline by decreasing the proportion of CT head scans, improving guideline adherence and increasing the confidence of the attending physicians.
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Affiliation(s)
- Pratisha Pradhan
- Department of General Practice and Emergency Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
| | - Alok Pradhan
- Department of General Practice and Emergency Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
| | - Anmol Purna Shrestha
- Department of General Practice and Emergency Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
| | - Abha Shrestha
- Department of Community Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
| | - Ram Chandra Paudel
- Department of Radiodiagnosis and Imaging, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
| | - Roshana Shrestha
- Department of General Practice and Emergency Medicine, Kathmandu University School of Medical Sciences, Dhulikhel, Kavrepalanchok, Bagmati Province, Nepal
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Ahorsu DK, Adjaottor ES, Lam BYH. Intervention Effect of Non-Invasive Brain Stimulation on Cognitive Functions among People with Traumatic Brain Injury: A Systematic Review and Meta-Analysis. Brain Sci 2021; 11:brainsci11070840. [PMID: 34202739 PMCID: PMC8301762 DOI: 10.3390/brainsci11070840] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 06/14/2021] [Accepted: 06/19/2021] [Indexed: 11/30/2022] Open
Abstract
This systematic review and meta-analysis aggregated and examined the treatment effect of non-invasive brain stimulation (NIBS) (transcranial direct current stimulation and transcranial magnetic stimulation) on cognitive functions in people with traumatic brain injury (TBI). A systematic search was conducted using databases (PubMed, Web of Science, Scopus, PsycINFO, EMBASE) for studies with keywords related to non-randomized and randomized control trials of NIBS among people with TBI. Nine out of 1790 NIBS studies with 197 TBI participants (103 active vs. 94 sham) that met the inclusion and exclusion criteria of the present study were finally selected for meta-analysis using Comprehensive Meta-Analysis software (version 3). Results showed that the overall effect of NIBS on cognition in people with TBI was moderately significant (g = 0.304, 95% CI = 0.055 to 0.553) with very low heterogeneity across studies (I2 = 0.000, Tau = 0.000). Specifically, significant and marginally significant moderate effect sizes were found for cognitive sub-domains including attention, memory, and executive function. The present findings suggest that NIBS is moderately effective in improving cognitive functions among people with TBI. In particular, NIBS may be used as an alternative and/or an adjunct treatment to the traditional approach in rehabilitating cognitive functions in people with TBI.
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Affiliation(s)
- Daniel Kwasi Ahorsu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China;
| | - Emma Sethina Adjaottor
- Department of Behavioural Sciences, Kwame Nkrumah University of Science and Technology, Ashanti, Ghana;
| | - Bess Yin Hung Lam
- Department of Psychiatry, The University of Hong Kong, Hong Kong, China
- Correspondence:
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Asim M, El-Menyar A, Parchani A, Nabir S, Ahmed MN, Ahmed Z, Ramzee AF, Al-Thani A, Al-Abdulmalek A, Al-Thani H. Rotterdam and Marshall Scores for Prediction of in-hospital Mortality in Patients with Traumatic Brain Injury: An observational study. Brain Inj 2021; 35:803-811. [PMID: 34076543 DOI: 10.1080/02699052.2021.1927181] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Background: We aimed to assess the prognostic value of Rotterdam and Marshall scoring systems to predict in-hospital mortality in patients with traumatic brain injury (TBI).Methods: A retrospective analysis was conducted for patients with TBI who underwent head computerized tomography (CT) scan at a Level I trauma center between 2011 and 2018. Receiver operating characteristic (ROC) curves were used to determine the cutoff values for predicting in-hospital mortality.Results: A total of 1035 patients with TBI were included with a mean age of 30 years. The mean Rotterdam and Marshall scores were higher among non-survivors (p = .001). Patients with higher Rotterdam (>3) or Marshall (>2) CT scores were older, had higher injury severity scores and in-hospital mortality and had lower GCS and blood ethanol levels than those with lower scores. The cutoff point of Rotterdam score was 3.5 (sensitivity, 61.2%; specificity, 85.6%) and Marshall score was 2.5 (74.3% sensitivity and 76.3% specificity). Multivariable logistic regression analyses showed that Marshall and Rotterdam scoring systems were independent predictors of mortality (odds ratio 8.4; 95% confidence interval 4.95-14.17 and odds ratio 4.4; 95% confidence interval 2.36-9.39, respectively).Conclusion: Rotterdam and Marshall CT scores have independent prognostic values in patients with TBI even in alcoholic patients.
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Affiliation(s)
- Mohammad Asim
- Trauma and Vascular Surgery Section, Clinical Research, Hamad General Hospital (HGH), Doha, Qatar
| | - Ayman El-Menyar
- Trauma and Vascular Surgery Section, Clinical Research, Hamad General Hospital (HGH), Doha, Qatar.,Clinical Medicine, Weill Cornell Medical College, Doha, Qatar
| | - Ashok Parchani
- Department of Surgery, Trauma Surgery Section, Hamad General Hospital (HGH), Doha, Qatar
| | - Syed Nabir
- Department of Radiology, Hamad General Hospital (HGH), Doha, Qatar
| | | | - Zahoor Ahmed
- Department of Radiology, Hamad General Hospital (HGH), Doha, Qatar
| | | | | | | | - Hassan Al-Thani
- Department of Surgery, Trauma Surgery Section, Hamad General Hospital (HGH), Doha, Qatar
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Shih RY, Burns J, Ajam AA, Broder JS, Chakraborty S, Kendi AT, Lacy ME, Ledbetter LN, Lee RK, Liebeskind DS, Pollock JM, Prall JA, Ptak T, Raksin PB, Shaines MD, Tsiouris AJ, Utukuri PS, Wang LL, Corey AS. ACR Appropriateness Criteria® Head Trauma: 2021 Update. J Am Coll Radiol 2021; 18:S13-S36. [PMID: 33958108 DOI: 10.1016/j.jacr.2021.01.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 01/14/2021] [Indexed: 12/13/2022]
Abstract
Head trauma (ie, head injury) is a significant public health concern and is a leading cause of morbidity and mortality in children and young adults. Neuroimaging plays an important role in the management of head and brain injury, which can be separated into acute (0-7 days), subacute (<3 months), then chronic (>3 months) phases. Over 75% of acute head trauma is classified as mild, of which over 75% have a normal Glasgow Coma Scale score of 15, therefore clinical practice guidelines universally recommend selective CT scanning in this patient population, which is often based on clinical decision rules. While CT is considered the first-line imaging modality for suspected intracranial injury, MRI is useful when there are persistent neurologic deficits that remain unexplained after CT, especially in the subacute or chronic phase. Regardless of time frame, head trauma with suspected vascular injury or suspected cerebrospinal fluid leak should also be evaluated with CT angiography or thin-section CT imaging of the skull base, respectively. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.
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Affiliation(s)
| | - Judah Burns
- Panel Chair, Montefiore Medical Center, Bronx, New York
| | | | - Joshua S Broder
- Duke University School of Medicine, Durham, North Carolina, American College of Emergency Physicians, Residency Program Director for Emergency Medicine, Vice Chief for Education, Division of Emergency Medicine, Department of Surgery, Duke University School of Medicine
| | - Santanu Chakraborty
- Ottawa Hospital Research Institute and the Department of Radiology, The University of Ottawa, Ottawa, Ontario, Canada, Canadian Association of Radiologists, CAR representative in ACR Quality Commission
| | - A Tuba Kendi
- Mayo Clinic, Rochester, Minnesota, Head of Nuclear Medicine Therapies at Mayo Clinic
| | - Mary E Lacy
- University of New Mexico, Albuquerque, New Mexico, American College of Physicians
| | | | - Ryan K Lee
- Einstein Healthcare Network, Philadelphia, Pennsylvania
| | - David S Liebeskind
- University of California Los Angeles, Los Angeles, California, American Academy of Neurology, President of SVIN
| | - Jeffrey M Pollock
- Oregon Health and Science University, Portland, Oregon, Editor, ACR Case in Point; Functional MRI Director, Oregon Health and Science University
| | - J Adair Prall
- Littleton Adventist Hospital, Littleton, Colorado, Neurosurgery expert, Chair, Guidelines Committee, Joint Section for Trauma and Critical Care
| | - Thomas Ptak
- R. Adams Cowley Shock Trauma Center, University of Maryland Medical Center, Baltimore, Maryland, Vice Chair of Community Radiology, University of Maryland Medical Center, Chief of Emergency and Trauma Imaging, R Adams Cowley Shock Trauma Center
| | - P B Raksin
- John H. Stroger Jr Hospital of Cook County, Chicago, Illinois, Neurosurgery expert, Chair Elect, American Association of Neurological Surgeons/Congress of Neurological Surgeons Section on Neurotrauma & Neurocritical Care; Vice Chair, American Association of Neurological Surgeons/Congress of Neurological Surgeons Joint Guidelines Review Committee; Director, Neurosurgery ICU
| | - Matthew D Shaines
- Albert Einstein College of Medicine Montefiore Medical Center, Bronx, New York, Internal Medicine Physician, Associate Program Director for the Moses-Weiler Internal Medicine Residency Program, Albert Einstein College of Medicine; Associate Chief, Division of Hospital Medicine
| | | | | | - Lily L Wang
- University of Cincinnati Medical Center, Cincinnati, Ohio, Neuroradiology Fellowship Program Director
| | - Amanda S Corey
- Specialty Chair, Atlanta VA Health Care System and Emory University, Atlanta, Georgia
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How do we identify the crashing traumatic brain injury patient - the neurosurgeon's view. Curr Opin Crit Care 2021; 27:87-94. [PMID: 33395087 DOI: 10.1097/mcc.0000000000000799] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
PURPOSE OF REVIEW To provide an overview on recent advances in the field of assessment and monitoring of patients with severe traumatic brain injury (sTBI) in neurocritical care from a neurosurgical point of view. RECENT FINDINGS In high-income countries, monitoring of patients with sTBI heavily relies on multimodal neurocritical parameters, nonetheless clinical assessment still has a solid role in decision-making. There are guidelines and consensus-based treatment algorithms that can be employed in both absence and presence of multimodal monitoring in the management of patients with sTBI. Additionally, novel dynamic monitoring options and machine learning-based prognostic models are introduced. Currently, the acute management and treatment of secondary injury/insults is focused on dealing with the objective evident pathology. An ongoing paradigm shift is emerging towards more proactive treatment of neuroworsening as soon as premonitory signs of deterioration are detected. SUMMARY Based on the current evidence, serial clinical assessment, neuroimaging, intracranial and cerebral perfusion pressure and brain tissue oxygen monitoring are key components of sTBI care. Clinical assessment has a crucial role in identifying the crashing patient with sTBI, especially from a neurosurgical standpoint. Multimodal monitoring and clinical assessment should be seen as complementary evaluation methods that support one another.
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