When used correctly, DTI exams can reliably identify Traumatic Brain Injuries in cases where CT and MRI exam results have been described as normal. But some DTI providers are still using methods that have proven problematic in court. Below are four common methods some DTI providers are using that can actually harm your case instead of advancing it.
The Concussion Group strongly believes the proprietary Quantify database provides the most scientifically valid normative database for individual comparison. Other databases lack volume and integrity. Our large dataset allows individual exam results to be matched to a subset of age and sex-matched control subjects.
QuantifyTM analyses were developed by MINDSET Consulting Group in collaboration with attorneys who are experts in the admissibility of scientific evidence and neuroscientists who are experts in neuroimaging data analysis and neurobiology. Quantitative analysis of Fractional Anisotropy and comparison to large normative databases is now considered the gold standard in clinical and experimental research studies funded by the National Institutes of Health.
Our qDTI exams rely on 1,200+ control datasets across 107 brain regions and 48 fiber tracts. We incorporate imaging sequences that collect high-resolution MRI data across the entire brain. The qDTI algorithms then extract detailed measurements of your client’s brain. QuantifyTM organizes the gray matter data measurements into 107 recognized brain regions and measures the integrity of 48 major white matter fiber tracts interconnecting different regions. A Volumetric Analysis studies the gray matter made up of cell bodies that act as the brain’s processing motors. A qDTI analysis studies the white matter fiber tracts that connect cell bodies and enable communication across brain regions.
Our qDTI analysis relies on control datasets from calibrated scanners.
Each of the 1,200+ sets of brain measurements in the control group were collected on the same MRI scanner and with the same protocols. A unique scaling method calibrates the machine used for your client to the one that obtained the control dataset, thus eliminating the contentious issues of variability between individual scanners, manufacturers, and generic normative datasets.
