Predictive value of early MRI findings on neurocognitive and psychiatric outcomes in patients with severe traumatic brain injury

Aldossary, Nasser M.; Kotb, Mamdouh Ali; Kamal, Ahmed

doi:10.1016/j.jad.2018.09.001

Cited by 19 publications

(10 citation statements)

References 44 publications

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“…One study has been published documenting the possible impact of imaging findings on neuropsychiatric outcomes. In this study, in which a baseline MRI was obtained in 251 patients with sTBI within one month of their hospitalization, those with MRI findings consistent with diffuse axonal injury were found to be significantly more likely than those without to exhibit evidence of one or more psychiatric disorders, cognitive impairment, and a poor overall outcome (as indicated by the Glasgow Outcome Scale score) ( 73 ). The volume of diffuse axonal injury also was predictive of a poor neurocognitive outcome.…”

Section: Predictors Of Psychosocial and Neuro-psychiatric Dysfunctionmentioning

confidence: 97%

“…Longer duration of post-traumatic amnesia (PTA) has likewise been linked to decreased processing speed ( 69 ); as well as to decreased executive functioning (affecting color-word interference, verbal fluency, and letter-digit sequencing) ( 60 ); impaired verbal memory ( 71 ); and an overall poor neurocognitive outcome ( 73 ).…”

Section: Predictors Of Cognitive Recoverymentioning

confidence: 99%

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Baseline Predictors of Survival, Neurological Recovery, Cognitive Function, Neuropsychiatric Outcomes, and Return to Work in Patients after a Severe Traumatic Brain Injury: an Updated Review

Algethamy¹

2020

Mater Sociomed

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Introduction: Severe traumatic brain injury (sTBI) is a common cause of death and disability worldwide, with long-term squeal among survivors that include cognitive deficits, psychosocial and neuropsychiatric dysfunction, failure to return to pre-injury levels of work, school and inter-personal relationships, and overall reduced quality of and satisfaction with life. Aim: The aim of this work is to review the current literature on baseline predictors of outcomes in adults post sTBI. Method: Most of available literature on baseline predictors of outcomes in adults post sTBI were reviewed and summarized in this work. Results: Currently, a sizeable number of composite predictors of mortality and overall function exists; however, these instruments tend to over-estimate poor outcomes and fail to address issues like cognition, psychosocial/ neuropsychiatric dysfunction, and return to work or school. Conclusion: This article reviews currently-identified predictors of all these outcomes.

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Section: Predictors Of Psychosocial and Neuro-psychiatric Dysfunctionmentioning

confidence: 97%

Section: Predictors Of Cognitive Recoverymentioning

confidence: 99%

Baseline Predictors of Survival, Neurological Recovery, Cognitive Function, Neuropsychiatric Outcomes, and Return to Work in Patients after a Severe Traumatic Brain Injury: an Updated Review

Algethamy¹

2020

Mater Sociomed

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“…It involves the use of advanced techniques of different capabilities including microscopy, bioluminescence imaging, ultrasound, X-ray radiography, magnetic resonance imaging, positron emission tomography, and single-photon emission computed tomography. MI techniques have proven to be useful in analysis and characterization of different brain diseases ranging from infections to brain tumors and neurological disorders (Mankoff, 2007;Aldossary et al, 2019;Bocan et al, 2019). The specificity of MI is enhanced by the use of contrast beacons known as probes (Schocke et al, 2002).…”

Section: Nanotechnology In Brain Diseases and Disorders Molecular Imamentioning

confidence: 99%

The Application of Nanotechnology for the Diagnosis and Treatment of Brain Diseases and Disorders

Ngowi

Wang

Qian

et al. 2021

Front. Bioeng. Biotechnol.

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Brain is by far the most complex organ in the body. It is involved in the regulation of cognitive, behavioral, and emotional activities. The organ is also a target for many diseases and disorders ranging from injuries to cancers and neurodegenerative diseases. Brain diseases are the main causes of disability and one of the leading causes of deaths. Several drugs that have shown potential in improving brain structure and functioning in animal models face many challenges including the delivery, specificity, and toxicity. For many years, researchers have been facing challenge of developing drugs that can cross the physical (blood–brain barrier), electrical, and chemical barriers of the brain and target the desired region with few adverse events. In recent years, nanotechnology emerged as an important technique for modifying and manipulating different objects at the molecular level to obtain desired features. The technique has proven to be useful in diagnosis as well as treatments of brain diseases and disorders by facilitating the delivery of drugs and improving their efficacy. As the subject is still hot, and new research findings are emerging, it is clear that nanotechnology could upgrade health care systems by providing easy and highly efficient diagnostic and treatment methods. In this review, we will focus on the application of nanotechnology in the diagnosis and treatment of brain diseases and disorders by illuminating the potential of nanoparticles.

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“…TAI, also referred to as diffuse axonal injuries (DAI), occur as a consequence of angular acceleration-deceleration forces that are exerted on the brain at the time of injury [9]. TAI have been linked to loss of consciousness, disability and poor outcomes following TBI [10][11][12][13]. Magnetic resonance imaging (MRI), which exhibits greater sensitivity to TAI than CT, has emerged as the main imaging modality for diagnosing TAI [14].…”

Section: Introductionmentioning

confidence: 99%

Extended analysis of axonal injuries detected using magnetic resonance imaging and their relation to outcome in critically ill traumatic brain injury patients

Tjerkaski

Nyström

Raj

et al. 2021

Preprint

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Background: Studies suggest that the detection of traumatic axonal injuries (TAI) using magnetic resonance imaging (MRI) in traumatic brain injury (TBI) may benefit outcome prediction. However, the association between existing TAI grading systems and outcomes following TBI remains uncertain. Therefore, we documented the presence of TAI in several brain regions, using different MRI sequences, and examined their association to patient outcomes. Furthermore, we created a novel MRI-based TAI grading system, with the goal of improving outcome prediction in TBI. We subsequently assessed the performance of several TAI grading systems with regard to outcome prediction.Methods: This was a retrospective study including TBI patients admitted to the intensive care unit between 2005 and 2019. MRI was performed at a median of 7 days post-trauma. We used a genetic algorithm to identify TAI that distinguish favourable from unfavourable outcomes, laying the groundwork for the novel Stockholm MRI grading system. We assessed the discriminatory performance (AUC) and goodness-of-fit (Nagelkerke’s pseudo-R2) of the Stockholm MRI grading system and the TAI grading systems of Adams et al, Firsching et al. and Abu Hamdeh et al., using both univariate and multivariate logistic regression. The dichotomised Glasgow outcome scale was considered the primary outcome.Results: We assessed the MRI scans of 351 TBI patients. TAI that were found to be associated with unfavourable outcomes include TAI in the midbrain tegmentum and TAI in the posterior limb of the internal capsule. The Stockholm MRI grading system exhibited the highest AUC (0.72 vs. 0.68–0.69) and Nagelkerke’s pseudo-R2 (0.21 vs. 0.14–0.15) values of all the studied TAI grading systems. These differences in model performance were, however, not statistically significant (De long’s test p>0.05). Furthermore, all included TAI grading systems improved outcome prediction relative to established outcome predictors of TBI, such as age and computed tomography-based scoring systems (likelihood-ratio test, p < 0.001).Conclusions: Our findings suggest that the detection of TAI using MRI is a valuable addition to prognostication in TBI patients. Additionally, we present the Stockholm MRI grading system, which could potentially improve outcome prediction in TBI. Although, an external validation is required to confirm these results.

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Predictive value of early MRI findings on neurocognitive and psychiatric outcomes in patients with severe traumatic brain injury

Cited by 19 publications

References 44 publications

Baseline Predictors of Survival, Neurological Recovery, Cognitive Function, Neuropsychiatric Outcomes, and Return to Work in Patients after a Severe Traumatic Brain Injury: an Updated Review

Baseline Predictors of Survival, Neurological Recovery, Cognitive Function, Neuropsychiatric Outcomes, and Return to Work in Patients after a Severe Traumatic Brain Injury: an Updated Review

The Application of Nanotechnology for the Diagnosis and Treatment of Brain Diseases and Disorders

Extended analysis of axonal injuries detected using magnetic resonance imaging and their relation to outcome in critically ill traumatic brain injury patients

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