European researchers test TBIcare prototype that could help improve treatment outcomes for patients with traumatic brain injuries.
Eight European universities from Finland, France, Lithuania, and the UK have teamed together to test the feasibility and efficacy of harnessing patient data to build a predictive care model for use in traumatic brain injury (TBI) care.
Researchers proposed a multi-template approach for the registration of CT data. They intend to harness the insight of shared data across geographical boundaries in order to improve the speed and accuracy of TBI diagnosis.
Low tissue contrast and significant pathologies make registration of TBI patient CT images incrementally challenging. Other variables, such as a patient’s demographics and clinical history, further complicate outcomes.
To provide accurate computer-assisted clinical decision support, the TBIcare tool should take these factors into account. Once the model is complete, it could become a diagnostic tool for emergency department physicians. Doctors would enter a TBI patient’s CT results into the tool, which would use data analysis to predict the most effective treatment course.
Concussions, contusions, fractured skulls, and hematomas are all classified as traumatic brain injuries. TBI is the most common cause of permanent disability in people under the age of 40. Transportation accidents (those involving cars, motorcycles, bicycles, and walking) are the major cause of TBIs for individuals under the age of 75. Other causes include firearm injuries, violence, and falls.
Diagnosis of brain injuries involves three steps: an initial trauma assessment, a neurological examination, and neuroimaging via CT scan. In 80% of TBI patients, the injury is mild, and they are discharged provided that friends or family can watch them closely for 24 hours. In moderate or severe TBIs, patients are admitted for close monitoring, and may require ventilation, drainage, or a craniotomy, among other treatments.
In Europe, approximately 1 million patients are admitted to the hospital each year with TBI. Of them, approximately 75,000 die. TBIs are responsible for more lost working years than cancer, stroke, and HIV combined. TBIs are devastating in part due to the natural complexities of the brain and the seemingly unique nature of individual injuries.
Better Care from Shared Knowledge
The initial TBIcare study used retrospective data from participating hospitals and cooperating research initiatives to develop the first trial. Although data from some 6,000 cases were used, there were enough limitations that researchers felt the use of a prospective dataset was warranted.
The prospective dataset was composed of information from 201 TBI cases and 40 control cases from Turku University Central Hospital in Finland, and 193 TBI cases and 42 control cases from the UK’s Cambridge University. Clinicians at both sites were able to use and provide feedback on a TBIcare prototype.
“Clinicians were very enthusiastic about the application’s potential,” TBIcare’s Scientific Coordinator Dr. Mark van Gils told nuviun. “Things like integrated data visualization, image processing tools and the promising aspects of metabolomics and proteomics in the data were considered especially useful.”
Dr. van Gils feels that TBIcare is still in the research phase, and that it will take several years before the product is ready for market. The current prototype has been tested, and requires further development with more patient data. Ongoing projects, such as CENTER-TBI, should provide additional patient data.
CENTER-TBI is a focused, European effort involving data collection from approximately 5,400 TBI patients. Originating in 60 different centers, data will be collected from patients examined and discharged from emergency departments, patients admitted to the hospital but not seen in the intensive care unit (ICU), and patients admitted to the ICU. A wide range of data will be collected throughout the course of treatment, including demographics, injury details, treatment, outcome and health costs.
TBIcare is also applying for new funding via various instruments. In time, TBIcare partners are hopeful that the TBIcare tool will predict which tests will give the best outcome indicators, and help prioritize emergency procedures.
Jenn Lonzer has a B.A. in English from Cleveland State University and an M.A. in Health Communication from Johns Hopkins University. Passionate about access to care and social justice issues, Jenn writes on global digital health developments, research, and trends. Follow Jenn on Twitter @jnnprater3.