Predicting obsessive-compulsive disorder severity combining neuroimaging and machine learning methods

Journal of Affective Disorders

Volumn 150, Issue 3, 2013, Pages 1213-1216

  Hoexter, Marcelo Q ^a   Miguel, Euripedes C ^a   Diniz, Juliana B ^a   Shavitt, Roseli G ^a   Busatto, Geraldo F ^a   Sato, João R ^b  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b UNIVERSIDADE FEDERAL DO ABC   (Brazil)

Author keywords

Machine learning; Magnetic resonance imaging; Neuroimaging; Obsessive compulsive disorder; Support vector regression; Symptom severity

Indexed keywords

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; DISEASE SEVERITY; GRAY MATTER; HUMAN; MACHINE LEARNING; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; OBSESSIVE COMPULSIVE DISORDER; ORBITAL CORTEX; PREDICTIVE VALUE; PRIORITY JOURNAL; PUTAMEN; SCORING SYSTEM; SUPPORT VECTOR MACHINE;

MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; NEUROIMAGING; OBSESSIVE-COMPULSIVE DISORDER; SUPPORT VECTOR REGRESSION; SYMPTOM SEVERITY;

ADOLESCENT; ADULT; ARTIFICIAL INTELLIGENCE; CEREBRAL CORTEX; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NEUROIMAGING; OBSESSIVE-COMPULSIVE DISORDER; PROGNOSIS; PUTAMEN; SEVERITY OF ILLNESS INDEX; YOUNG ADULT;

EID: 84888352564     PISSN: 01650327     EISSN: 15732517     Source Type: Journal    
DOI: 10.1016/j.jad.2013.05.041     Document Type: Article

References (24)

1. Alvarenga, P.G, do Rosário, M.C., Batistuzzo, M.C., Diniz, J.B., Shavitt, R.G., Duran, F.L., Dougherty, D.D., Bressan, R.A., Miguel, E.C., Hoexter, M.Q., 2012. Obsessive-compulsive symptom dimensions correlate to specific gray matter volumes in treatment-naive patients. Journal of Psychiatric Research 46, 1635-1642.
2. Delucchi, K.L., Bostrom, A., 2004. Methods for analysis of skewed data distributions in psychiatric clinical studies: working with many zero values. American Journal of Psychiatry 161, 1159-1168.
3. Denys, D., Burger, H., van Megen, H., de Geus, F., Westenberg, H., 2003. A score for predicting response to pharmacotherapy in obsessive-compulsive disorder. International Clinical Psychopharmacology 18, 315-322.
4. Ferrao, Y.A., Shavitt, R.G., Bedin, N.R., de Mathis, M.E., Carlos Lopes, A., Fontenelle, L. F., Torres, A.R., Miguel, E.C., 2006. Clinical features associated to refractory obsessive-compulsive disorder. Journal of Affective Disorders 94, 199-209.
5. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B., 1997. Structured Clinical Interview for DSM-IV Axis I Disorders: Clinical Version (SCID CV). American Psychiatric Press, Washington, DC.
6. Fischl, B., Sereno, M.I., Dale, A.M., 1999. Cortical surface-based analysis.II: inflation, flattening, and a surface-based coordinate system. Neurolmage 9, 195-207.
7. Goodman, W.K., Price, L.H., Rasmussen, S.A., Mazure, C., Fleischmann, R.L., Hill, C.L., Heninger, G.R., Charney, D.S., 1989. The Yale-Brown obsessive compulsive scale. I. Development, use, and reliability. Archives of General Psychiatry 46, 1006-1011.
8. Guyon, I., Weston, J., Barnhill, S., Vapnik, V., 2002. Gene selection for cancer classification using support vector machines. Machine Learning 46, 389-122.
9. Hoexter, M.Q., Shavitt, R.G., D'Alcante, C.C., Cecconi, J.P., Diniz, J.B., Belotto-Silva, C., Hounie, A.G., Borcato, S., Moraes, I., Joaquim, M.A., Cappi, C., Sampaio, A.S., Mathis, M.A., Batistuzzo, M.C., Lopes, A.C., Rosa, A.C., Muniz, R.K., Marques, A.H., Santos, L.C., Taub, A., Duran, F.L., Dougherty, D.D., Busatto, G.F., Bressan, R.A., Miguel, E.C., 2009. The drug-naive OCD patients imaging genetics, cognitive and treatment response study: methods and sample description. Revista Brasileira de Psiquiatria 31, 349-353.
10. Hoexter, M.Q., de Souza Duran, F.L., D'Alcante, C.C., Dougherty, D.D., Shavitt, R.G., Lopes, A.C., Diniz, J.B., Deckersbach, T., Batistuzzo, M.C., Bressan, R.A., Miguel, E. C., Busatto, G.F., 2012. Gray matter volumes in obsessive-compulsive disorder before and after fluoxetine or cognitive-behavior therapy: a randomized clinical trial. Neuropsychopharmacology 37, 734-745.
11. Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D.S., Quinn, K., Sanislow, C., Wang, P., 2010. Research domain criteria (RDoC): toward a new classification framework for research on mental disorders. American Journal of Psychiatry 167, 748-751.
12. Mataix-Cols, D., Rauch, S.L., Manzo, P.A., Jenike, M.A., Baer, L., 1999. Use of factor-analyzed symptom dimensions to predict outcome with serotonin reuptake inhibitors and placebo in the treatment of obsessive-compulsive disorder. American Journal of Psychiatry 156, 1409-1416.
13. Miguel, E.C., Leckman, J.F., Rauch, S., do Rosario-Campos, M.C., Hounie, A.G., Mercadante, M.T., Chacon, P., Pauls, D.L., 2005. Obsessive-compulsive disorder phenotypes: implications for genetic studies. Molecular Psychiatry 10, 258-275.
14. Pereira, F., Mitchell, T., Botvinick, M., 2009. Machine learning classifiers and fMRI: a tutorial overview. NeuroImage 45, S199-S209.
15. Radua, J., Mataix-Cols, D., 2009. Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. British Journal of Psychiatry 195, 393-402.
16. Rosario-Campos, M.C., Miguel, E.C., Quatrano, S., Chacon, P., Ferrao, Y., Findley, D., Katsovich, L., Scahill, L., King, R.A., Woody, S.R., Tolin, D., Hollander, E., Kano, Y., Leckman, J.F., 2006. The dimensional Yale-Brown obsessive-compulsive Scale (DY-BOCS): an instrument for assessing obsessive-compulsive symptom dimensions. Molecular Psychiatry 11, 495-504.
17. Rotge, J.Y., Langbour, N., Guehl, D., Bioulac, B., Jaafari, N., Allard, M., Aouizerate, B., Burbaud, P., 2010. Gray matter alterations in obsessive-compulsive disorder: an anatomic likelihood estimation meta-analysis. Neuropsychopharmacology 35, 686-691.
18. Sato, J.R., de Araujo Filho, G.M., de Araujo, T.B., Bressan, R.A, de Oliveira, P.P., Jackowski, A.P., 2012a. Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuro-anatomy and machine learning. Journal of Psychiatric Research 46, 1126-1132.
19. Sato, J.R., Kozasa, E.H., Russell, T.A., Radvany, J., Mello, L.E., Lacerda, S.S., Amaro Jr., E, 2012b. Brain imaging analysis can identify participants under regular mental training. PLoS One 7, e39832.
20. Saxena, S., Rauch, S.L., 2000. Functional neuroimaging and the neuroanatomy of obsessive-compulsive disorder. Psychiatric Clinics of North America 23, 563-586.
21. Smola, A.J., Scholkopf, B., 1998. On a kernel-based method for pattern recognition, regression, approximation and operator inversion. Algorithmica 22, 211-231.
22. Soriano-Mas, C., Pujol, J., Alonso, P., Cardoner, N., Menchön, J.M., Harrison, B.J., Deus, J., Vallejo, J., Gaser, C., 2007. Identifying patients with obsessive-compulsive disorder using whole-brain anatomy. NeuroImage 35, 1028-1037.
23. Weygandt, M., Blecker, C.R., Schafer, A., Hackmack, K., Haynes, J.D., Vaitl, D., Stark, R., Schienle, A., 2012. fMRI pattern recognition in obsessive-compulsive disorder. NeuroImage 60, 1186-1193.
24. de Almeida, J.R., Phillips, M.L., 2013. Distinguishing between unipolar depression and bipolar depression: current and future clinical and neuroimaging perspectives. Biological Psychiatry 73, 111-118.