Anatomical Imaging: Volumetric Analysis
The introduction of neuroimaging methodologies revolutionised clinical diagnosis of Central Nervous System (CNS) diseases by enabling for the first time the in vivo visualisation of disease processes that were previously accessible only post-mortem. Non-invasive imaging methods have provided insight into progressive pathological processes and offer the potential to identify early markers of disease onset associated with or even preceding clinical symptom onset. Unsurprisingly, therefore, the development of these putative imaging biomarkers to identify novel therapeutic targets and provide earlier read-outs of novel drug action and efficacy has attracted great interest from both the scientific community and pharmaceutical companies. This chapter outlines applications of anatomic imaging measures, with a particular emphasis on those derived from volumetric analyses, to understanding CNS disease and therapy.
KeywordsTemporal Lobe Epilepsy Grey Matter Volume Central Nervous System Disease Cortical Change Cortical Density
The author would like to thank Morgan Hough for the VBM-SBM images and Paul Matthews and Tom Nichols for references and advice.
NLV is a full-time employee of GlaxoSmithKline.
- Ballmaier M, O’Brien JT, Burton EJ, Thompson PM, Rex DE, Narr KL, McKeith IG, DeLuca H, Toga AW (2004) Comparing gray matter loss profiles between dementia with Lewy bodies and Alzheimer’s disease using cortical pattern matching: diagnosis and gender effects. Neuroimage 23(1):325–335PubMedCrossRefGoogle Scholar
- Bendfeldt K, Kuster P, Traud S, Egger H, Winklhofer S, Mueller-Lenke N, Naegelin Y, Gass A, Kappos L, Matthews PM, Nichols TE, Radue E-W, Borgwardt SJ (2009) Association of regional gray matter volume loss and progression of white matter lesions in multiple sclerosis–a longitudinal voxel-based morphometry study. Neuroimage 45:60–67PubMedCrossRefGoogle Scholar
- Bodini B, Khaleeli Z, Cercignani M, Miller DH, Thompson AJ, Ciccarelli O (2009). Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: An in vivo study with TBSS and VBM. Hum Brain Map (in press)Google Scholar
- Cachia A, Paillère-Martinot ML, Galinowski A, Januel D, de Beaurepaire R, Bellivier F, Artiges E, Andoh J, Bartrés-Faz D, Duchesnay E, Rivière D, Plaze M, Mangin JF, Martinot JL (2008) Cortical folding abnormalities in schizophrenia patients with resistant auditory hallucinations. Neuroimage 39(9):927–935PubMedCrossRefGoogle Scholar
- Douaud G, Gaura V, Ribeiro MJ, Lethimonnier F, Maroy R, Verny C, Krystkowiak P, Damier P, Bachoud-Levi AC, Hantraye P, Remy P (2006) Distribution of grey matter atrophy in Huntington’s disease patients: a combined ROI-based and voxel-based morphometric study. Neuroimage 32(4):1562–1575PubMedCrossRefGoogle Scholar
- Dubois C, Hertz-Pannier L, Dehaene-Lambertz G, Cointepas Y, Le Bihan D (2006) Assessment of the early organization and maturation of infants’ cerebral white matter fiber bundles: a feasibility study using quantitative diffusion tensor imaging and tractography. Neuroimage 30(4):1121–1132PubMedCrossRefGoogle Scholar
- Filippini N, Rao A, Wetten S, Gibson RA, Borrie M, Guzman D, Kertesz A, Loy-English I, Williams J, Nichols T, Whitcher B, Matthews PM (2009) Anatomically-distinct genetic associations of APOE epsilon 4 allele load with regional cortical atrophy in Alzheimer’s disease. Neuroimage 44(3):724–728PubMedCrossRefGoogle Scholar
- Harris JM, Moorhead TW, Miller P, McIntosh AM, Bonnici HM, Owens DG, Johnstone EC, Lawrie SM (2007) Increased prefrontal gyrification in a large high-risk cohort characterizes those who develop schizophrenia and reflects abnormal prefrontal development. Biol Psychiatry 63(1):722–729CrossRefGoogle Scholar
- Jezzard P, Matthews PM, Smith SM (2001) Functional magnetic resonance imaging: an introduction to methods. Oxford University Press, OxfordGoogle Scholar
- Roffman JL, Gollub RL, Calhoun VD, Wassink TH, Weiss AP, Ho BC, White T, Clark VP, Fries J, Andreasen NC, Goff DC, Manoach DS (2008) MTHFR 677C –T genotype disrupts prefrontal function in schizophrenia through an interaction with COMT 158Val-Met. Proc Natl Acad Sci USA 105(45):17573–17578PubMedCrossRefGoogle Scholar
- Sheperd TM, Ozarslan E, Yachnis AT, King MA, Blackband SJ (2007) Diffusion tensor microscopy indicates the cytoarchitectural basis for diffusion anisotropy in the human hippocampus. Am J Neuroradiol 28(5):958–964Google Scholar
- Sormani MP, Rovaris M, Valsasina P, Wilinsky JS, Comi G, Filippi M (2004) Measurement error of two different techniques for brain atrophy assessment in multiple sclerosis. Neurology 62(8):1432–1434Google Scholar