Quantitative Automated Lesion Detection of Traumatic Brain Injury

Because of their non-focal nature, TBI-related brain lesions are difficult to detect and
quantify with traditional MRI. In the current research program the investigators propose to
develop quantitative automated lesion detection (QALD) procedures to (1) clarify the nature
and distribution of tissue damage following mild, moderate and severe TBI (2) improve the
capability of detecting, quantifying, and localizing TBI brain damage in individual patients
and (3) correlate quantitative measures of brain damage in individual TBI patients with
neuropsychological deficits in attention, memory, and executive function.

QALD detects abnormal tissue parameters in the diseased brain through statistical
comparisons with a normative database. Preliminary results show that QALD is capable of
detecting highly significant abnormalities in the brains of TBI patients with normal
clinical MRI scans. QALD will be further enhanced and tested with a larger database and
including brain images acquired with four different imaging sequences (T1, T2, DTI and
fluid-attenuated inversion recovery or FLAIR) from 100 control subjects. Data analysis will
incorporate advanced cortical surface mapping techniques to quantify gray matter tissue
parameters and thickness in 34 distinct cortical regions in each hemisphere. In addition,
cortical fiber projections will be quantified with DTI and FLAIR analysis of white matter
lying below the cortical surface. Subcortical fiber tracts critical for complex cognitive
operations will be analyzed with voxel-based morphometry and with improved region of
interest algorithms to define fiber tract boundaries. Tissue properties in critical
subcortical structures (e.g., the hippocampus) will be quantified after automatic
parcellation of these brain regions. The investigators will also test the control subjects
on a battery of neuropsychological tests (NPTs) and correlate variations in the size,
myelination, and tissue properties of normal cortical and subcortical structures with
cognitive performance. Then, the investigators will gather identical imaging data in 99 TBI
patients divided into three groups (mild, moderate and severe TBI) in order to characterize
the average pattern of damage caused by TBIs of different severity. Next, the investigators
will quantify lesions in individual TBI patients and describe the variability of lesion
patterns in the different severity groups. In parallel, the investigators will develop
further multimodal analysis techniques to combine statistical information from different
imaging sequences to improve lesion-detection sensitivity to co-localized abnormalities
evident with different imaging protocols. In addition, the investigators will test patients
with NPTs and analyze the relationship between brain damage, cognitive performance and
self-assessments of outcome in order to improve the prognostic value of neuroradiological
studies of TBI.

Inclusion Criteria:

- Control subjects from 18-50.

- Patients from 18-50 who have suffered TBI.

Exclusion Criteria:

- Substance abuse.

- Irremedial sensory deficits (blindness, deafness).

- Primary psychiatric disorder.

- Neurological disease unrelated to TBI.