Literature DB >> 21294647

Computed tomography and outcome in moderate and severe traumatic brain injury: hematoma volume and midline shift revisited.

Bram Jacobs1, Tjemme Beems, Ton M van der Vliet, Ramon R Diaz-Arrastia, George F Borm, Pieter E Vos.   

Abstract

Intracranial lesion volume and midline shift are powerful outcome predictors in moderate and severe traumatic brain injury (TBI), and therefore they are used in TBI and computed tomography (CT) classification schemes, like the Traumatic Coma Data Bank (TCDB) classification. In this study we aimed to explore the prognostic value of lesion volume and midline shift in moderate and severe TBI as measured from acute cranial CT scans. Also, we wanted to determine interrater reliability for the evaluation of these CT abnormalities. We included all consecutive moderate and severe TBI patients admitted to our hospital who were aged ≥16 years, over an 8-year period, as part of the prospective Radboud University Brain Injury Cohort Study. Six months post-trauma we assessed outcomes using the Glasgow Outcome Scale-Extended (GOS-E). We analyzed 605 patients and found an association of both lesion volume and midline shift with outcome; increases were associated with a higher frequency of patients with an unfavorable outcome or death. A cut-off value, such as that used in the TCDB CT classification (lesion volume 25 mL and midline shift 5 mm), was not found. The average interrater difference in volume measurement was 6.8 mL, and it was 0.2 mm for the determination of degree of shift. Using lesion volume and midline shift as continuous variables in prognostic models might be preferable over the use of threshold values, although an association of these variables with outcome in relation to other CT abnormalities was not tested. The data provided here will be useful for stratification of patients enrolled in clinical trials of neuroprotective therapies.

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Year:  2011        PMID: 21294647     DOI: 10.1089/neu.2010.1558

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  29 in total

1.  Quantitative CT improves outcome prediction in acute traumatic brain injury.

Authors:  Esther L Yuh; Shelly R Cooper; Adam R Ferguson; Geoffrey T Manley
Journal:  J Neurotrauma       Date:  2011-12-08       Impact factor: 5.269

Review 2.  A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury.

Authors:  Franck Amyot; David B Arciniegas; Michael P Brazaitis; Kenneth C Curley; Ramon Diaz-Arrastia; Amir Gandjbakhche; Peter Herscovitch; Sidney R Hinds; Geoffrey T Manley; Anthony Pacifico; Alexander Razumovsky; Jason Riley; Wanda Salzer; Robert Shih; James G Smirniotopoulos; Derek Stocker
Journal:  J Neurotrauma       Date:  2015-09-30       Impact factor: 5.269

3.  Midline Shift vs. Mid-Surface Shift: Correlation with Outcome of Traumatic Brain Injuries.

Authors:  Cheng Jiang; Jie Cao; Craig Williamson; Negar Farzaneh; Venkatakrishna Rajajee; Jonathan Gryak; Kayvan Najarian; S M Reza Soroushmehr
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2020-02-06

4.  Smaller but denser: postmortem changes alter the CT characteristics of subdural hematomas.

Authors:  Nicole Berger; Lars C Ebert; Garyfalia Ampanozi; Patricia M Flach; Dominic Gascho; Michael J Thali; Thomas D Ruder
Journal:  Forensic Sci Med Pathol       Date:  2015-01-08       Impact factor: 2.007

5.  Motor vehicle crash-related subdural hematoma from real-world head impact data.

Authors:  Jillian E Urban; Christopher T Whitlow; Colston A Edgerton; Alexander K Powers; Joseph A Maldjian; Joel D Stitzel
Journal:  J Neurotrauma       Date:  2012-12-10       Impact factor: 5.269

6.  Outcome prediction in moderate and severe traumatic brain injury: a focus on computed tomography variables.

Authors:  Bram Jacobs; Tjemme Beems; Ton M van der Vliet; Arie B van Vugt; Cornelia Hoedemaekers; Janneke Horn; Gaby Franschman; Ian Haitsma; Joukje van der Naalt; Teuntje M J C Andriessen; George F Borm; Pieter E Vos
Journal:  Neurocrit Care       Date:  2013-08       Impact factor: 3.210

7.  Automatic Quantification of Computed Tomography Features in Acute Traumatic Brain Injury.

Authors:  Saurabh Jain; Thijs Vande Vyvere; Vasilis Terzopoulos; Diana Maria Sima; Eloy Roura; Andrew Maas; Guido Wilms; Jan Verheyden
Journal:  J Neurotrauma       Date:  2019-02-01       Impact factor: 5.269

8.  Microstructural basis of contusion expansion in traumatic brain injury: insights from diffusion tensor imaging.

Authors:  Virginia F J Newcombe; Guy B Williams; Joanne G Outtrim; Doris Chatfield; M Gulia Abate; Thomas Geeraerts; Anne Manktelow; Hywel Room; Leela Mariappen; Peter J Hutchinson; Jonathan P Coles; David K Menon
Journal:  J Cereb Blood Flow Metab       Date:  2013-02-20       Impact factor: 6.200

9.  Traumatic intracranial hematomas: prognostic value of contrast extravasation.

Authors:  L Letourneau-Guillon; T Huynh; R Jakobovic; R Milwid; S P Symons; R I Aviv
Journal:  AJNR Am J Neuroradiol       Date:  2012-10-18       Impact factor: 3.825

10.  Identification of hematomas in mild traumatic brain injury using an index of quantitative brain electrical activity.

Authors:  Leslie S Prichep; Rosanne Naunheim; Jeffrey Bazarian; W Andrew Mould; Daniel Hanley
Journal:  J Neurotrauma       Date:  2015-01-01       Impact factor: 5.269

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