Browsing by Subject "TBI"

Traumatic brain injuries (TBIs) are a major public health concern and socioeconomic burden worldwide. In recent years, brain injuries in US service personnel have focused attention on TBI affecting the military population (Bass et al., 2012). Blast injuries have become the most common cause of mortality and morbidity in soldiers returning from Iraq and Afghanistan (Owens et al., 2008, Warden, 2006). The frequency of blast-related sequelae found in allied forces has led some to call it the ‘signature wound’ of the wars abroad.

The growing incidence of TBI has spurred an increase in research efforts within the neurotrauma community to define TBI etiology. Identification of the critical injury mechanisms underlying TBI is an area of greatest need. Our understanding of TBI etiology, physical damaging mechanisms, and pathophysiology remains inadequate. The ability to design specific countermeasures and targeted prevention strategies is restricted by an incomplete understanding of the underlying damaging mechanisms.

Cavitation, the formation of vapor filled cavities in a liquid medium, has been proposed as a damaging mechanism of TBI in both blunt impacts (Ward et al., 1948, Gross, 1958) and blast-induced neurotrauma (Moore et al., 2008, Panzer et al., 2012c). The cavitation hypothesis of TBI centers on observation that high energy events such as high-explosive blast impingement onto the head generate large pressure transients in and around the brain. Localized areas of low pressure may surpass the tensile limits of the cerebrospinal fluid vaporizing the fluid and forming cavitation bubbles. These voids grow, potentially displacing surrounding tissue. When the bubbles collapse, perhaps violently, jets of liquid with potentially large localized pressures and temperatures may be created, damaging surrounding tissue.

The main objective of this dissertation was to develop an experimental foundation and provide empirical evidence for cavitation as a damaging mechanism of blast-induced TBI. This dissertation uses biofidelic surrogate head models of blast and in vivo animal models of blast injury to address the unanswered questions surrounding cavitation and blast neurotrauma. Foremost, cavitation response was observed in the surrogate head form exposed to blast conditions associated with injury. The 50% risk of cavitation occurs at a blast level of 262 kPa incident overpressure and 1.96 ms duration. This blast dosage represents a 62% chance of mild intracranial bleeding from scaled ferret experiments (Rafaels et al., 2012). Cavitation onsert, growth, and collapse were confirmed through high-speed imaging of the fluid layers of the contrecoup, while strong acoustic emission signatures associated with cavity collapse were captured and time matched with the video. Near-harmonic frequencies at 64 kHz, 126 kHz, and 267 kHz were associated with the energetic collapse of the bubbles. Our results provide compelling evidence that primary blast alone may induce cavitation that leads to TBI.

Evidence of cavitation was recorded in live porcine specimen exposed to blast. Acoustic sensors mounted to the skull of each specimen recorded acoustic emissions during blast exposure. Scaled spectral analysis revealed acoustic energy in higher frequencies bands with peaks at 64 kHz, 139 kHz, and 251 kHz, closely matching the spectral peaks associated with void collapse in surrogate experiments. To our knowledge, this study is the first to present evidence of blast-induced cavitation in a live animal model in the field of cavitation TBI research.

The results presented in this dissertation also greatly improve our understanding of how mechanical loads are imparted onto the head during a blast exposure and how this loading leads to cavitation onset. Strain analysis of the surrogate head indicates wall compliance from skull deformation and shear wave propagation through the skull as significant physical factors driving the tensile fluid responses in the head. Future design considerations for preventative measures should account for these physical mechanisms.

This dissertation also makes important contributions to blast injury research by presenting a clinically relevant murine model of blast TBI. Murine blast lethality risk and functional behavior outcomes before and after blast injury are presented. We provide guidelines for small animal blast testing, along with methodological recommendations for benchtop shock tube design and specimen placement in relation to the shock tube.

The contributions of this dissertation further serve as an important methodological guide to the neurotrauma and biomechanics community studying blast-related TBI and cavitation as a damaging mechanism. The developed surrogate head system and cavitation detection techniques provide a research template and are a springboard to future research efforts elucidating the damaging effects of cavitation during TBI.

Background:

Traumatic Brain Injury (TBI) is a leading cause of death and disability. TBI patients in low and middle- income countries (LMIC) have twice the odds of death than in high-income countries. There is limited data describing the epidemiology and mortality predictors for TBI in LMIC.

Objective:

Determine epidemiology and predictors of mortality in TBI patients at Kigali University Teaching Hospital Accident and Emergency Department (KUTH A&E).

Methods:

Consecutive, injured KUTH A&E patients were prospectively screened for inclusion by reported head trauma, alteration in consciousness, headache, or visible head trauma. Exclusion criteria were <10 years old, presenting >48 hours after injury, or repeat visits. Data were assessed for association with death using logistic regression. Significant variables were included in an adjusted multivariable logistic regression model then refined via backwards elimination until all variables were significant at P <0.05.

Results:

684 patients enrolled between October 7, 2013 and April 6, 2014. 12 (2%) were excluded due to incomplete data. 81% were male with mean age of 31.5 years (range 10 - 89). Most patients (75%) had mild TBI (Glasgow Coma Score (GCS) 14-15), while 15% had moderate (GCS 9-13), and 10% had severe TBI (GCS 3-8). Multivariable logistic regression and refinement by backwards elimination determined that GCS <14, hypoxia, tachycardia and age >50 years predicted mortality.

Conclusion:

GCS <14, hypoxia, tachycardia and age >50 years were associated with mortality among TBI patients at KUTH A&E. These findings can guide clinicians in prioritizing care for patients at highest risk of mortality.

Background: Globally, many low-income settings lack diagnostic tools to handle prognosis of TBI patients. In such settings, development of generalizable predictive models which indicate likelihood of patient outcomes may help improve decision-making for physicians and health care providers.

Methods: An analysis of a Rwanda TBI registry (n=682) was conducted to determine key predictors of TBI mortality. A previously developed prognostic model of a Tanzania TBI registry (n=3209) was subsequently implemented in the Rwanda TBI registry for external validation. 8 different machine learning models were implemented in the Rwanda dataset. Subsequently, 6 Tanzania models and a combined model aggregating the Tanzania model predictions were used to compare and predict Rwanda patient outcomes.

Results: The predictive models developed in Rwanda had satisfactory predictive ability, with the best performing model, Ridge Regression having an AUC of 90% (CI: 89.3%-90.7%). The models developed in Tanzania and used to predict outcomes within the Rwanda dataset showed similar predictive ability, the AUC of the best performing Random Forest model, 91.3% (CI: 88.0%-94.6%) and the combined Tanzania machine learning model, AUC 91.9% (CI: 88.7%-95.1%).

Conclusions: The results from the Tanzania and combined models indicate satisfactory predictive ability and generalizability. The ability of the models to hold similar predictive power in an external dataset, with the use of indicators collectable at triage suggests potential applicability in other low-resource settings.