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Contribution of CT-Scan Analysis by Artificial Intelligence to the Clinical Care of TBI Patients

Clément Brossard, Benjamin Lemasson, Arnaud Attyé, Jules-Arnaud de Busschère, Jean-François Payen, Emmanuel L. Barbier, Jules Grèze, Pierre Bouzat
2021 Frontiers in Neurology  
This short review will summarize what is ongoing with the use of AI and CT scan for patients with TBI.  ...  patients, identifying the nature and volume of lesions and estimating the patient outcome.  ...  All authors listed have made a substantial, direct and intellectual contribution to the work, approved it for publication, proofread, and corrected the final manuscript.  ... 
doi:10.3389/fneur.2021.666875 pmid:34177773 pmcid:PMC8222716 fatcat:eytn3fa7erhfxj3nuasabw6pke

Recommended Primary Outcomes for Clinical Trials Evaluating Hemostatic Agents in Patients With Intracranial Hemorrhage

Stephan A. Mayer, Jennifer A. Frontera, Brian Jankowitz, Christopher P. Kellner, Nathan Kuppermann, Bhiken I. Naik, Daniel K. Nishijima, Thorsten Steiner, Joshua N. Goldstein, Simone Glynn, Andrei Kindzelski, Christopher Loftus (+5 others)
2021 JAMA Network Open  
In patients with acute spontaneous or traumatic intracranial hemorrhage, early hemostasis is thought to be critical to minimize ongoing bleeding.  ...  A hierarchy of 3 outcome measures is recommended, with the first choice being a global patient-centered clinical outcome scale measured 30 to 180 days after the event; the second, a combined clinical and  ...  whereas either a 33% or greater or a 6 mL or greater increase was used to define expansion in the Prediction of Hematoma Growth and Outcome in Patients with ICH Using the CT-Angiography Spot Sign Study  ... 
doi:10.1001/jamanetworkopen.2021.23629 pmid:34473266 fatcat:d5fiifyqrvbarhgmcofa6zr46q

Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives

Vidhya V., Anjan Gudigar, U. Raghavendra, Ajay Hegde, Girish R. Menon, Filippo Molinari, Edward J. Ciaccio, U. Rajendra Acharya
2021 International Journal of Environmental Research and Public Health  
Traumatic brain injury (TBI) occurs due to the disruption in the normal functioning of the brain by sudden external forces.  ...  In this paper, a systematic review of prevailing CAD systems for the detection of hematoma, raised ICP, and MLS in non-contrast axial CT brain images is presented.  ...  Acknowledgments: The authors would like to thank the Manipal Academy of Higher Education (MAHE) for providing the required facility to carry out this research.  ... 
doi:10.3390/ijerph18126499 pmid:34208596 pmcid:PMC8296416 fatcat:6xikhm22rvh7vb7sberifgy6ym

Automated Segmentation and Severity Analysis of Subdural Hematoma for Patients with Traumatic Brain Injuries

Negar Farzaneh, Craig A. Williamson, Cheng Jiang, Ashok Srinivasan, Jayapalli R. Bapuraj, Jonathan Gryak, Kayvan Najarian, S. M. Reza Soroushmehr
2020 Diagnostics  
Detection and severity assessment of subdural hematoma is a major step in the evaluation of traumatic brain injuries.  ...  Such a system can aid critical care physicians in reducing time to intervention and thereby improve long-term patient outcomes.  ...  The predictive power of the SDH volumetric measurement should also be evaluated against a representative data set that covers different variations of SDH in traumatic brain injury patients.  ... 
doi:10.3390/diagnostics10100773 pmid:33007929 pmcid:PMC7600198 fatcat:2dgmv3aydzhlbgtuwlevazuwcy

Automated Prediction of Glasgow Outcome Scale for Traumatic Brain Injury

Bolan Sut, Thien Anh Dinh, Abhinit Kumar Ambastha, Tianxia Gong, Tomi Silander, Shijian Lu, C.C. Tchoyoson Lim, Boon Chuan Pang, Cheng Kiang Lee, Tze-Yun Leong, Chew Lim Tan
2014 2014 22nd International Conference on Pattern Recognition  
Clinical features found in brain CT scan images are widely used in traumatic brain injury (TBI) as indicators for Glasgow Outcome Scale (GOS) prediction.  ...  This paper introduces an automated GOS prediction system for traumatic brain CT images.  ...  In this paper, we focus on traumatic brain injury (TBI) [6] , which is a major cause of mortality.  ... 
doi:10.1109/icpr.2014.559 dblp:conf/icpr/SuDAGSLLPLLT14 fatcat:bsyezbqxqjae7hiinr62py7gem

A comparative study of 2D image segmentation algorithms for traumatic brain lesions using CT data from the ProTECTIII multicenter clinical trial [article]

Shruti Jadon, Owen P. Leary, Ian Pan, Tyler J. Harder, David W. Wright, Lisa H. Merck, Derek L. Merck
2020 arXiv   pre-print
In this research, we have experimented with multiple available deep learning architectures to segment different phenotypes of hemorrhagic lesions found after moderate to severe traumatic brain injury (  ...  These include: intraparenchymal hemorrhage (IPH), subdural hematoma (SDH), epidural hematoma (EDH), and traumatic contusions.  ...  While rapid diagnosis and treatment of TBI is directly related to patient outcomes, attempts to automate identification, 7 classification, and segmentation 89 of traumatic brain lesions on non-contrast  ... 
arXiv:2006.01263v1 fatcat:3qyge2i25bfcdomylci4gmhrey

Detection of Midline Shift from CT Scans to Predict Outcome in Patients with Head Injuries

Ikhlas Abdelaziz, Rowa Aljondi, Ali B Alhailiy, Mustafa Z. Mahmoud
2021 International Journal of Biomedicine  
The worst outcome was seen in patients with midline shift and subdural hematoma, when compared with other lesions in patients with brain injuries.  ...  The inclusion criteria were patients with traumatic brain injury (TBI) or patients evaluated for level of consciousness by a neurosurgeon.  ...  to predict outcomes in patients with head injuries.  ... 
doi:10.21103/article11(1)_oa3 doaj:985ebf942d8c41a5916200e0f968e7d3 fatcat:icolsbfghnav5ci3cxw5aedaiu

Automatic quantification of brain lesion volume from post-trauma MR Images [article]

Thomas Mistal, Pauline Roca, Christophe Maggia, Alan Tucholka, Florence Forbes, Senan Doyle, Alexandre Krainik, Damien Galanaud, Emmanuelle Schmitt, Stephane Kremer, Irene Tropres, Emmanuel Louis Barbier (+2 others)
2021 medRxiv   pre-print
Similar findings were obtained when comparing AQP and manual annotations for TBI patients.  ...  images according to the intensity, form and location of lesion observed in real TBI cases; ii) severe TBI patients (n=12 patients) who underwent MR imaging within 10 days after injury.  ...  with severe traumatic brain injury.  ... 
doi:10.1101/2021.04.24.21255599 fatcat:7avws22bjbbrbm3vjv3yoi4z2m

Brain Midline Shift Measurement and Its Automation: A Review of Techniques and Algorithms

Chun-Chih Liao, Ya-Fang Chen, Furen Xiao
2018 International Journal of Biomedical Imaging  
We review studies that used the MLS to predict outcomes of patients with intracranial mass. In some studies, the MLS was also correlated to clinical features.  ...  Shift of midline intracranial structures helps diagnosing intracranial lesions, especially traumatic brain injury, stroke, brain tumor, and abscess.  ...  Acknowledgments This work was supported by Taiwan Ministry of Science and Technology (Grant 106-2314-B-002-082) .  ... 
doi:10.1155/2018/4303161 pmid:29849536 pmcid:PMC5925103 fatcat:kvyxrjvbqrf2rhgtdprxla3zlu

Deep Learning to Predict TBI Outcomes in the Low Resource Setting

Syed M Adil, Cyrus Elahi, Anthony Fuller, Michael M Haglund, Timothy Dunn
2020 Neurosurgery  
INTRODUCTION Traumatic brain injury (TBI) disproportionately affects low- and middle-income countries (LMICs).  ...  RESULTS Ultimately, 2164 patients were included for model training and a subset of 1677 for model testing, of which 12% had poor outcomes. The mean age was 28 -± 15 years and 85% were male.  ...  Experience with prior traumatic incidents also increased comfort levels with assessing and managing injuries, P = .026.  ... 
doi:10.1093/neuros/nyaa447_488 fatcat:qgqrgdfbwbdb5enfvojcqazfbm

A hybrid method for traumatic brain injury lesion segmentation

Ahmad Yahya Dawod, Aniwat Phaphuangwittayakul, Salita Angkurawaranon
2022 International Journal of Power Electronics and Drive Systems (IJPEDS)  
<span>Traumatic brain injuries are significant effects of disability and loss of life.  ...  We propose a novel technique free-form object model for brain injury CT image segmentation based on superpixel image processing that uses CT to analyzing brain injuries, quite challenging to create a high  ...  ACKNOWLEDGMENTS The researchers thank the international college of digital innovation Chiang Mai University for giving to us the opportunity and the Faculty of Medicine's support through the research fund  ... 
doi:10.11591/ijece.v12i2.pp1437-1448 fatcat:kjfgy6usnjgkvjh5wgavptk2kq

Automated Quantification of Brain Lesion Volume From Post-trauma MR Diffusion-Weighted Images

Thomas Mistral, Pauline Roca, Christophe Maggia, Alan Tucholka, Florence Forbes, Senan Doyle, Alexandre Krainik, Damien Galanaud, Emmanuelle Schmitt, Stéphane Kremer, Adrian Kastler, Irène Troprès (+3 others)
2022 Frontiers in Neurology  
Similar findings were obtained when comparing AQP and manual annotations for TBI patients.  ...  , with similar accuracy to manual delineation, the volume of low and high MD brain lesions after trauma, and thus allow the determination of the type and volume of edematous brain lesions.  ...  the 10 patients with severe traumatic brain injury.  ... 
doi:10.3389/fneur.2021.740603 pmid:35281992 pmcid:PMC8905597 fatcat:sdk7ihdqrba4joeg74hvyvc4vq

Cerebral Atrophy after Traumatic White Matter Injury: Correlation with Acute Neuroimaging and Outcome

Kan Ding, Carlos Marquez de la Plata, Jun Yi Wang, Marysa Mumphrey, Carol Moore, Caryn Harper, Christopher J. Madden, Roderick McColl, Anthony Whittemore, Michael D. Devous, Ramon Diaz-Arrastia
2008 Journal of Neurotrauma  
Traumatic brain injury (TBI) is a pathologically heterogeneous disease, including injury to both neuronal cell bodies and axonal processes.  ...  Acute axonal lesions measured by FLAIR imaging are strongly predictive of post-traumatic cerebral atrophy.  ...  Department of Education (grant NIDRR H133 A020526) and the National Institutes of Health (grants NIH R01 HD48179 and NIH U01 HD42652).  ... 
doi:10.1089/neu.2008.0683 pmid:19072588 pmcid:PMC2858299 fatcat:mrgvrxkk35bpfizrrpsjydkqti

Prediction of Recovery from Traumatic Brain Injury with EEG Power Spectrum in Combination of Independent Component Analysis and RUSBoost Model

Nor Safira Elaina Mohd Noor, Haidi Ibrahim, Muhammad Hanif Che Lah, Jafri Malin Abdullah
2022 BioMedInformatics  
in moderate traumatic brain injury (TBI).  ...  As a result, it is crucial to devise a strategy for meticulously flagging and extracting clean EEG data to retrieve high-quality discriminative features for successful model development.  ...  and Lai Chi Qin for discussion on algorithm development.  ... 
doi:10.3390/biomedinformatics2010007 fatcat:vflmguuarjea5kj3yk7nuqcf7y

Quantification of Iodine Leakage on Dual-Energy CT as a Marker of Blood-Brain Barrier Permeability in Traumatic Hemorrhagic Contusions: Prediction of Surgical Intervention for Intracranial Pressure Management

U.K. Bodanapally, K. Shanmuganathan, Y.P. Gunjan, G. Schwartzbauer, R. Kondaveti, T.R. Feiter
2019 American Journal of Neuroradiology  
Quantitative iodine-based parameters derived from follow-up dual-energy CT may predict the intensity of intracranial pressure management in patients with hemorrhagic contusions.  ...  Consecutive patients with contusions from May 2016 through January 2017 were retrospectively analyzed.  ...  ACKNOWLEDGMENT The authors thank Brigitte Pocta for editing the manuscript.  ... 
doi:10.3174/ajnr.a6316 pmid:31727752 pmcid:PMC6975368 fatcat:dpawrfcn7ffufb6mnfrj7zj3ty
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