Review of the Evidence Supporting the Medical and Legal Use of NeuroQuant® in Patients with Traumatic Brain Injury
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Decades of research have shown that the brain atrophies after traumatic brain injury (TBI). However, multiple practical issues made it difficult to detect brain atrophy in individual patients with mild to moderate TBI. This situation improved by 2007 with the FDA approval of NeuroQuant®, a commercially available, computer-automated software program for measuring MRI brain volume in human subjects. Several peer-reviewed scientific studies have supported the reliability and validity of NeuroQuant®. This review addresses whether NeuroQuant® meets the Daubert standard for admissibility in court cases involving persons with TBI. The review finds that NeuroQuant® is an objective, reliable, and practical means of measuring brain volume and therefore can be an important tool for measuring the effects of TBI on brain volume in clinical or medicolegal settings.
KeywordsTraumatic brain injury Magnetic resonance imaging Daubert NeuroQuant Atrophy
The authors would like to thank Matthew W. Broughton, Esq., for his helpful comments on this article.
Conflict of Interest
The authors report no financial conflicts of interest or financial relationships with respect to any of the companies or products discussed in this manuscript.
- Bigler, E. D. (2005). Structural imaging. In J. M. Silver, T. W. McAllister & S. C. Yudofsky (Eds.), Textbook of traumatic brain injury (pp. 79–105). Washington: American Psychiatric Publishing, Inc.Google Scholar
- Bigler, E. D. (2011). Structural imaging. In J. M. Silver, T. W. McAllister & S. C. Yudofsky (Eds.), Textbook of traumatic brain injury (pp. 73–90). Washington: American Psychiatric Publishing, Inc.Google Scholar
- Bigler, E. D., T. J. Abildskov, E. A. Wilde, S. R. McCauley, X. Li, T. L. Merkley, … H. S. Levin (2010). Diffuse damage in pediatric traumatic brain injury: A comparison of automated versus operator-controlled quantification methods. Neuroimage, 50, 1017–1026.Google Scholar
- Birk, S. (2009). Hippocampal atrophy: Biomarker for early AD?: Hippocampal volume in patients with AD is typically two standard deviations below normal. http://www.internalmedicinenews.com/index.php?id=2049&type=98&tx_ttnews%5Btt_news%5D=10034&cHash=da03e20e36 Accessed 25 February 2012
- Ding, K., C. Marquez de la Plata, J. Y. Wang, M. Mumphrey, C. Moore, C. Harper, … R. Diaz_Arrastia (2008). Cerebral atrophy after traumatic white matter injury: Correlation with acute neuroimaging and outcome. Journal of Neurotrauma, 25, 1433–1440.Google Scholar
- Fischl, B. (2011). [Freesurfer] general info about FS. https://mail.nmr.mgh.harvard.edu/pipermail//freesurfer/2011-March/017501.html Accessed 25 February 2012
- Gronenschild, E. H., Habets, P., Jacobs, H. I., Mengelers, R., Rozendaal, N., van Os, J. & Marcelis, M. (2012). The effects of FreeSurfer version, workstation type, and Macintosh operating system version on anatomical volume and cortical thickness measurements. PloS One, 7, e38234.PubMedCrossRefGoogle Scholar
- Jack Jr, C. R., M. A. Bernstein, N. C. Fox, P. Thompson, G. Alexander, D. Harvey, … M. W. Weiner (2008). The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods. Journal Magnetic Resonance Imaging, 27, 685–691.Google Scholar
- Jovicich, J., S. Czanner, X. Han, D. Salat, A. v. d. Kouwe, B. Quinn, … B. Fischl (2009). MRI-derived measurements of human subcortical, ventricular and intracranial brain volumes: Reliability effects of scan sessions, acquisition sequences, data analyses, scanner upgrade, scanner vendors and field strengths. Neuroimage, 46, 177–192.Google Scholar
- McCauley, S. R., E. A. Wilde, T. L. Merkley, K. P. Schnelle, E. D. Bigler, J. V. Hunter, … H. S. Levin (2010). Patterns of cortical thinning in relation to event-based prospective memory performance 3 months after moderate to severe traumatic brain injury in children. Developmental Neuropsychology, 35, 318–332.Google Scholar
- Ross, D. E., Ochs, A. L., Seabaugh, J. M., DeMark, M. F., Shrader, C. R., Marwitz, J. H. & Havranek, M. D. (2012b). Progressive brain atrophy in patients with chronic neuropsychiatric symptoms after mild traumatic brain injury: A preliminary study. Brain Injury, 26(12), 1500–1509.PubMedCrossRefGoogle Scholar
- Ross, D. E., A. L. Ochs, J. M. Seabaugh & C. R. Shrader (2012). Man vs. Machine: Comparison of radiologists’ interpretations and Neuroquant® volumetric analyses of brain MRIs in patients with traumatic brain injury. Journal of Neuropsychiatry and Clinical Neurosciences. (in press)Google Scholar
- Simpson, J. R. (Ed.). (2012). Neuroimaging in forensic psychaitry: From the clinic to the courtroom. West Sussex: Wiley-Blackwell.Google Scholar
- Warner, M. A., T. S. Youn, T. Davis, A. Chandra, d. l. P. C. Marquez, C. Moore, … R. Diaz-Arrastia (2010). Regionally selective atrophy after traumatic axonal injury. Archives Neurology, 67, 1336–1344.Google Scholar
- Xu, Y., D. L. McArthur, J. R. Alger, M. Etchepare, D. A. Hovda, T. C. Glenn, … P. M. Vespa (2010). Early nonischemic oxidative metabolic dysfunction leads to chronic brain atrophy in traumatic brain injury. Journal of Cerebral Blood Flow Metabolism, 30, 883–894.Google Scholar