Included in this study were outpatients consecutively admitted to the Virginia Institute of Neuropsychiatry who met the selection criteria. Selection criteria required that each patient 1) was diagnosed with traumatic brain injury by a board-certified neuropsychiatrist (DER) according to the criteria of Menon et al;8 2) had a mild-or-moderate level of brain injury according to the criteria of Rao and Lyketsos;9 3) agreed to be in the study and signed the informed consent form; 4) had no contraindications to obtaining an MRI, such as having magnetic metal in the head or being pregnant; 5) had an MRI without artifacts (such as motion artifacts) which would preclude accurate identification of brain structures by the NeuroQuant software. Also, each patient was matched with a normal-control to have a similar level of education (within 3 years), in order to minimize the potentially confounding effect of education on brain volume; three patients were excluded using this method because they had very low levels of education. This study was approved by the New England Institutional Review Board and satisfied the requirements of the Code of Ethics of the World Medical Association (Declaration of Helsinki) for human research.
Twenty patients met the selection criteria; 19 had mild TBI, and 1 had moderate TBI. Demographic characteristics were as follows: 8 men and 12 women; mean age (years): 46.2 (SD: 13.9; range: 19.9–66.2); mean number of years of education was 14.6 (SD: 2.6; range: 11–19).
The NeuroQuant computer-automated analysis routinely provides volume data on 11 brain regions, left and right sides, for a total of 22 volume measurements (http://www.cortechs.net/products/neuroquant.php).4 However, it provides comparisons to a normal-control group for only three brain regions (averaged across left and right sides). In order to assess NeuroQuant’s ability to detect atrophy in all 22 brain regions, this study used a group of normal-controls different from the NeuroQuant normal-controls. For these extended analyses, normal-control data were obtained from a larger group previously studied as part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI).10–12 The ADNI normal-control data were made publicly available (http://adni.loni.ucla.edu).
The ADNI was launched in 2003 by the National Institute on Aging (NIA), the National Institute of Biomedical Imaging and Bioengineering (NIBIB), the Food and Drug Administration (FDA), private pharmaceutical companies, and nonprofit organizations, as a $60 million, 5-year public/private partnership. The primary goal of ADNI has been to test whether serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment can be combined to measure the progression of mild cognitive impairment (MCI) and early Alzheimer's disease (AD). The Principal Investigator of this initiative is Michael W. Weiner, M.D., VA Medical Center and University of California–San Francisco. ADNI is the result of efforts of many co-investigators from a broad range of academic institutions and private corporations, and subjects have been recruited from over 50 sites across the United States and Canada.
For the NeuroQuant extended analyses reported herein, a subgroup of 20 normal-control subjects (10 men, 10 women) were chosen from the ADNI database. The mean age was 68.3 years (SD: 3.6 years; range: 60.0–71.5), and the mean number of years of education was 16.0 (SD 3.1; range: 9–20).
The groups of patients and ADNI normal-controls did not differ significantly with respect to sex (chi square likelihood ratio: 0.19, df=1,35; NS). In order to compare the two groups with respect to age, a nonparametric test (Wilcoxon rank-sum test) was chosen because the normal-control group’s data were not normally distributed. The two groups differed significantly with respect to age (χ2=25.7; p <0.01), with ADNI normal-controls older than the patient group. The two groups did not differ significantly with respect to years of education (independent t-test, t=1.55, df=1,38; NS).
Magnetic resonance imaging
Each patient had a 3.0-tesla MRI of the brain performed at one of three local radiology centers, using the scanning protocol recommended for allowing later NeuroQuant analysis; this protocol is described in detail on the NeuroQuant website (http://www.cortechs.net/products/neuroquant.php) and was the same protocol used for the ADNI subjects. In addition to the general requirements for having an MRI (e.g., having no magnetic metal in the head), the NeuroQuant protocol required, at a minimum, the following:
Supported MRI scanner (GE, Siemens or Phillips)
MRI scanning protocol based on the ADNI scanning protocol
T1 timing sequence
3D inverse Fourier-transform scanning protocol
Scan included nose, ears, and vertex without wraparound
As part of the standard clinical procedure at the Virginia Institute of Neuropsychiatry and nearby radiology centers, several other MRI sequences were obtained on each patient in order to allow a thorough evaluation of the effects of traumatic brain injury on brain structure. Accordingly, in addition to the above “NeuroQuantable” MRI, each MRI evaluated by the radiologists included the following sequences: 1) T1, 3D, saggital, noncontrast (which also was used for the NeuroQuant-based volumetric analyses); 2) coronal T2 sequence; 3) axial FLAIR sequence; 4) susceptibility-weighted imaging (SWI, preferably) or gradient-recall echo (if SWI unavailable); and 4) diffusion tensor imaging.
NeuroQuant automated brain MRI segmentation
The brain MRI data for each patient or ADNI normal-control was uploaded to the NeuroQuant server, which processed and analyzed the brain-imaging data. This computer-automated analysis involved several steps, including stripping the brain of scalp, skull, and meninges; inflating the brain to a spherical shape; mapping the spherical brain to a common spherical space shared with the Talairach Atlas brain;13 identification of brain segments (that is, regions); and deflation of the patient’s brain back to its original shape while retaining the identifying information for brain segments. The output of the NeuroQuant computer-automated analysis included a report containing volumetric information, and a set of DICOM-formatted brain images that were segmented, with each region identified by a distinctive color.
The NeuroQuant segmented DICOM images were inspected for errors, a step recommended by the makers of NeuroQuant in order to ensure accurate identification of brain regions by the software. The left and right counterparts for each of the 11 brain regions were segmented. Therefore, for each subject, there were 22 brain regions segmented. The segmentation results for each region were visually inspected by two of the authors (DER and ALO). The table shows the results of inspection for errors. For determining rates of errors, there were 20 patients, with each brain region measured on right and left sides, for a total of 40 measurements per brain region. The mean rate of inaccurate identification across regions was 10.2% (SD: 11.1%; range: 0.0%–32.5%). Examples of segmentation errors are shown in Figure 1.
FIGURE 1.Example of Segmentation Errors by NeuroQuant®
This segmented MRI image created by NeuroQuant shows three examples of brain regions being misidentified as adjacent brain regions.
Each brain region volume was corrected for interindividual differences in head size by dividing by intracranial volume, with the result being expressed as a percentage. The result was compared with the normal-control data, and the patient’s brain region was classified as abnormally small if it fell below the 5th normative percentile.
For the ADNI normal-controls, the results from the NeuroQuant standard analysis were used to determine means and standard deviations (SDs) for each of the 11 brain regions (left and right sides analyzed separately). Each patient’s data were compared with the data from the normal-controls in order to calculate z-scores, which were converted to normative percentile ranks. Results were considered to be consistent with (although not probative of) parenchymal atrophy if they met one of the following criteria: 1) a parenchymal region ≤5th normative percentile; or 2) a ventricular region ≥95th normative percentile, consistent with atrophy of the surrounding parenchyma.
Radiologist’s Traditional Interpretation
For each patient, the MRI was interpreted by one of five local, board-certified radiologists on the basis of simple visual inspection, per the usual clinical practice. The radiologists were blind to the NeuroQuant results. The attending radiologist’s interpretation was examined to determine whether atrophy or ventricular enlargement had been noted.
A two-tailed paired sign test was used to test the hypothesis that the NeuroQuant findings differed from the radiologist’s interpretations. JMP software was used to perform the statistical analysis.