Abstract
The purpose of this study is to elucidate if it is possible to discriminate between cocaine dependent patients and healthy controls applying computer aided diagnosis tools to brain magnetic resonance imaging. Feature extraction was done computing Pearson’s correlation using subjects class as indicative variable. Linear support vector machines classifiers were trained and tested on the most significative voxels using leave one out cross-validation process. Results show that classifier achieve on average almost perfect accuracy, sensitivity and specificity in a group of 30 cocaine-dependent and 35 controls, supporting the usefulness of this process to discriminate between these subjects.
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References
Graña, M., Termenon, M., Savio, A., Gonzalez-Pinto, A., Echeveste, J., Pérez, J.M., Besga, A.: Computer aided diagnosis system for alzheimer disease using brain diffusion tensor imaging features selected by pearson’s correlation. Neuroscience Letters 502(3), 225–229 (2011) PMID: 21839143
Savio, A., García-Sebastián, M., Chyzyk, D., Hernandez, C., Graña, M., Sistiaga, A., de Munain, A.L., Villanúa, J.: Neurocognitive disorder detection based on feature vectors extracted from VBM analysis of structural MRI. Computers in Biology and Medicine (2011)
Savio, A., Charpentier, J., Termenon, M., Shinn, A.K., Graña, M.: Neural classifiers for schizophrenia diagnostic support on diffusion imaging data. Neural Network World 20, 935–949 (2010)
Frangou, S.: CS02-02 - risk and resilience markers: Use of whole-brain structural MR scans to predict familial risk and disease expression in bipolar disorder. European Psychiatry 26(suppl.1) (2011)
Ernst, T., Chang, L., Oropilla, G., Gustavson, A., Speck, O.: Cerebral perfusion abnormalities in abstinent cocaine abusers: a perfusion MRI and SPECT study. Psychiatry Research: Neuroimaging 99(2), 63–74 (2000)
Franklin, T.R., Acton, P.D., Maldjian, J.A., Gray, J.D., Croft, J.R., Dackis, C.A., O’Brien, C.P., Childress, A.R.: Decreased gray matter concentration in the insular, orbitofrontal, cingulate, and temporal cortices of cocaine patients. Biological Psychiatry 51(2), 134–142 (2002) PMID: 11822992
Barrós-Loscertales, A., Garavan, H., Bustamante, J.C., Ventura-Campos, N., Llopis, J.J., Belloch, V., Parcet, M.A., Ávila, C.: Reduced striatal volume in cocaine-dependent patients. NeuroImage 56(3), 1021–1026 (2011)
Bustamante, J.C., Barrós-Loscertales, A., Ventura-Campos, N., Sanjún, A., Llopis, J.J., Parcet, M.A., Ávila, C.: Right parietal hypoactivation in a cocaine-dependent group during a verbal working memory task. Brain Research 1375, 111–119 (2011)
Li, S., Biswal, B., Li, Z., Risinger, R., Rainey, C., Cho, J., Salmeron, B.J., Stein, E.A.: Cocaine administration decreases functional connectivity in human primary visual and motor cortex as detected by functional MRI. Magnetic Resonance in Medicine 43(1), 45–51 (2000)
Moeller, F.G., Hasan, K.M., Steinberg, J.L., Kramer, L.A., Dougherty, D.M., Santos, R.M., Valdes, I., Swann, A.C., Barratt, E.S., Narayana, P.A.: Reduced anterior corpus callosum white matter integrity is related to increased impulsivity and reduced discriminability in Cocaine-Dependent subjects: Diffusion tensor imaging. Neuropsychopharmacology 30(3), 610–617 (2004)
Lane, S.D., Steinberg, J.L., Ma, L., Hasan, K.M., Kramer, L.A., Zuniga, E.A., Narayana, P.A., Moeller, F.G.: Diffusion tensor imaging and decision making in cocaine dependence. PloS One 5(7), e11591 (2010) PMID: 20661285
Lim, K.O., Wozniak, J.R., Mueller, B.A., Franc, D.T., Specker, S.M., Rodriguez, C.P., Silverman, A.B., Rotrosen, J.P.: Brain macrostructural and microstructural abnormalities in cocaine dependence. Drug and Alcohol Dependence 92(1-3), 164–172 (2008), PMID: 17904770 PMCID: 2693223
Fan, Y., Rao, H., Hurt, H., Giannetta, J., Korczykowski, M., Shera, D., Avants, B.B., Gee, J.C., Wang, J., Shen, D.: Multivariate examination of brain abnormality using both structural and functional MRI. NeuroImage 36(4), 1189–1199 (2007) PMID: 17512218
Honorio, J., Samaras, D., Tomasi, D., Goldstein, R.: Simple fully automated group classification on brain fMRI, pp. 1145–1148 (April 2010)
Avants, B., Epstein, C., Grossman, M., Gee, J.: Symmetric diffeomorphic image registration with cross-correlation: Evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis 12(1), 26–41 (2008)
Vapnik, V.N.: Statistical Learning Theory. Wiley-Interscience (September 1998)
Noble, W.S.: What is a support vector machine? Nat. Biotech. 24(12), 1565–1567 (2006)
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Termenon, M., Graña, M., Barrós-Loscertales, A., Bustamante, J.C., Ávila, C. (2012). Cocaine Dependent Classification Using Brain Magnetic Resonance Imaging. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7209. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28931-6_43
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DOI: https://doi.org/10.1007/978-3-642-28931-6_43
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