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Classification of first-episode psychosis: a multi-modal multi-feature approach integrating structural and diffusion imaging

  • Psychiatry and Preclinical Psychiatric Studies - Original Article
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Abstract

Currently, most of the classification studies of psychosis focused on chronic patients and employed single machine learning approaches. To overcome these limitations, we here compare, to our best knowledge for the first time, different classification methods of first-episode psychosis (FEP) using multi-modal imaging data exploited on several cortical and subcortical structures and white matter fiber bundles. 23 FEP patients and 23 age-, gender-, and race-matched healthy participants were included in the study. An innovative multivariate approach based on multiple kernel learning (MKL) methods was implemented on structural MRI and diffusion tensor imaging. MKL provides the best classification performances in comparison with the more widely used support vector machine, enabling the definition of a reliable automatic decisional system based on the integration of multi-modal imaging information. Our results show a discrimination accuracy greater than 90 % between healthy subjects and patients with FEP. Regions with an accuracy greater than 70 % on different imaging sources and measures were middle and superior frontal gyrus, parahippocampal gyrus, uncinate fascicles, and cingulum. This study shows that multivariate machine learning approaches integrating multi-modal and multisource imaging data can classify FEP patients with high accuracy. Interestingly, specific grey matter structures and white matter bundles reach high classification reliability when using different imaging modalities and indices, potentially outlining a prefronto-limbic network impaired in FEP with particular regard to the right hemisphere.

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References

  • Arnone D, McIntosh A, Tan GM, Ebmeier KP (2008a) Meta-analysis of magnetic resonance imaging studies of the corpus callosum in schizophrenia. Schizophr Res 101(1–3):124–132

    Article  CAS  PubMed  Google Scholar 

  • Arnone D, McIntosh A, Chandra P, Ebmeier KP (2008b) Meta-analysis of magnetic resonance imaging studies of the corpus callosum in bipolar disorder. Acta Psychiatr Scand 118(5):357–362

    Article  CAS  PubMed  Google Scholar 

  • Bach FR, Lanckriet GRG, Jordan MI (2004) Multiple kernel learning, conic duality, and the SMO algorithm. In: Proceedings of international conference on machine learning, ICML, pp 41–48

  • Bagary MS, Symms MR, Barker GJ, Mutsatsa SH, Joyce EM, Ron MA (2003) Gray and white matter brain abnormalities in first-episode schizophrenia inferred from magnetization transfer imaging. Arch Gen Psychiatry 60:779–788

    Article  PubMed  Google Scholar 

  • Bartholomeusz CF, Whittle SL, Montague A, Ansell B, McGorry PD, Velakoulis D, Pantelis C, Wood SJ (2013) Sulcogyral patterns and morphological abnormalities of the orbitofrontal cortex in psychosis. Progress Neuro-Psychopharmacol Biol Psychiatry 44:168–177

    Article  Google Scholar 

  • Bellani M, Cerruti S, Brambilla P (2010a) Orbitofrontal cortex abnormalities in schizophrenia. Epidemiol Psychiatr Sci 19(1):23–25

    Google Scholar 

  • Bellani M, Marzi CA, Savazzi S, Perlini C, Cerruti S, Ferro A, Marinelli V, Sponda S, Rambaldelli G, Tansella M, Brambilla P (2010b) Laterality effects in schizophrenia and bipolar disorder. Exp Brain Res 201(1):339–344

    Article  PubMed  Google Scholar 

  • Bourne VJ, Watling D (2014) Individual differences in emotion lateralisation and the processing of emotional information arising from social interactions. Laterality 12:1–17

    Google Scholar 

  • Brambilla P, Nicoletti M, Sassi RB, Mallinger AG, Frank E, Keshavan MS, Soares JC (2004) Corpus callosum signal intensity in bipolar and unipolar disorder patients. J Neurol Neurosurg Psychiatry 75:221–225

    PubMed Central  CAS  PubMed  Google Scholar 

  • Brambilla P, Cerini R, Gasparini A, Versace A, Andreone N, Vittorini E, Barbui C, Pelizza L, Nosè M, Barlocco L, Marrella G, Gregis M, Tournikioti K, David AS, Keshavan KS, Tansella M (2005) Investigation of corpus callosum in schizophrenia with diffusion imaging. Schizophr Res 79:201–210

    Article  PubMed  Google Scholar 

  • Brambilla P, Perlini C, Bellani M, Tomelleri L, Ferro A, Cerruti S, Marinelli V, Rambaldelli G, Christodoulou T, Jogia J, Dima D, Tansella M, Balestrieri M, Frangou S (2012) Increased salience of gains versus decreased associative learning differentiate bipolar disorder from schizophrenia during decision-making. Psychol Med 12(1–10):2012

    Google Scholar 

  • Brambilla P, Perlini C, Rajagopalan P, Saharan P, Rambaldelli G, Bellani M, Dusi N, Cerini R, Pozzi Mucelli R, Tansella M, Thompson PM (2013) Illness severity and poor social functioning relate to hippocampal shape deflation in schizophrenia: a three-dimensional mapping study. Br J Psychiatry 202:50–55

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Castellani U, Perina P, Murino V, Bellani M, Rambaldelli G, Tansella M, Brambilla P (2010) Brain morphometry by probabilistic latent semantic analysis. In: Proceedings of the international conference on medical image computing and computer-assisted intervention, MICCAI'10, LNCS, vol 6362, pp 177–184

  • Castellani U, Mirtuono P, Murino V, Bellani M, Rambaldelli G, Tansella M, Brambilla P (2011) A new shape diffusion descriptor for brain classification. In: Proceedings of the international conference on medical image computing and computer assisted intervention, MICCAI’11, LNCS, vol 6892, Issue PART 2, pp 426–433

  • Castellani U, Rossato E, Murino V, Bellani M, Rambaldelli G, Perlini C, Tomelleri M, Tansella M, Brambilla P (2012) Classification of schizophrenia using feature-based morphometry. J Neural Transm 119:395–404

    Article  CAS  PubMed  Google Scholar 

  • Castro E, Martínez-Ramón M, Pearlson G, Sui J, Calhoun VD (2011) Characterization of groups using composite kernels and multi-source FMRI analysis data: application to schizophrenia. Neuroimage 58:526–536

    Article  PubMed Central  PubMed  Google Scholar 

  • Choum PH, Koike S, Nishimura Y, Kawasaki S, Satomura Y, Kinoshita A, Takizawa R, Kasai K (2014) Distinct effects of duration of untreated psychosis on brain cortical activities in different treatment phases of schizophrenia: a multi-channel near-infrared spectroscopy study. Prog Neuropsychopharmacol Biol Psychiatry 49:63–69

    Article  Google Scholar 

  • Corradi-Dell’Acqua C, Tomelleri L, Bellani M, Rambaldelli G, Cerini R, Pozzi-Mucelli R, Balestrieri M, Tansella M, Brambilla P (2012) Thalamic-insular dysconnectivity in schizophrenia: evidence from structural equation modeling. Hum Brain Mapp 33(3):740–752

    Article  PubMed  Google Scholar 

  • Crossley NA, Mechell A, Fusar-Poli P, Broome MR, Matthiasson P, Johns LC, Bramon E, Valmaggia L, Williams SC, McGuire PK (2009) Superior temporal lobe dysfunction and frontotemporal dysconnectivity in subjects at risk of psychosis and in first-episode psychosis. Hum Brain Mapp 30(12):4129–4137

    Article  PubMed  Google Scholar 

  • Crow TJ, Paez P, Chance S (2007) Callosal misconnectivity and the sex difference in psychosis. Int Rev Psychiatry 19(4):449–457

    Article  CAS  PubMed  Google Scholar 

  • Desikan RS, Sgonne F, Fischl B, Quinn BT, Dickerson BC, Blacker D, Buckner RLea (2006) An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31:968–980

    Article  PubMed  Google Scholar 

  • Duda RO, Hart PE, Stork DG (2000) Pattern classification, 2nd edn. Wiley-Intersciences, New York

    Google Scholar 

  • Ecker C, Rocha-Rego V, Johnston P, Mourao-Miranda J, Marquand A, Daly EM, Brammer MJ, Murphy C, Murphy DG, Consortium MA (2010) Investigating the predictive value of whole-brain structural mr scans in autism: a pattern classification approach. Neuroimage 49:44–56

    Article  PubMed  Google Scholar 

  • Ellison-Wright I, Glahn DC, Laird AR, Thelen SM, Bullmore E (2008) The anatomy of first-episode and chronic schizophrenia: an anatomical likelihood estimation meta-analysis. Am J Psychiatry 165(8):1015–1023

    Article  PubMed Central  PubMed  Google Scholar 

  • Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neurotechnique 33:341–355

    CAS  Google Scholar 

  • Friston KJ, Ashburner J (2004) Generative and recognition models for neuroanatomy. Neuroimage 23:21–24

    Article  CAS  PubMed  Google Scholar 

  • Gonen M, Alpayden E (2011) Multiple kernel learning algorithms. J Mach Learn Res 12:2181–2238

    Google Scholar 

  • Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182

    Google Scholar 

  • Hill SY, Tessner K, Wang S, Carter H, McDermott M (2010) Temperament at 5 years of age predicts amygdala and orbitofrontal volume in the right hemisphere in adolescence. Psychiatry Res 182(1):14–21

    Article  PubMed Central  PubMed  Google Scholar 

  • Hinrichs C, Singh V, Xu G, Johnson SC, Initiative TADN (2011) Predictive markers for ad in a multi-modality framework: an analysis of MCI progression in the ADNI population. Neuroimage 55:574–589

    Article  PubMed Central  PubMed  Google Scholar 

  • Hoy K, Barrett S, Shannon C, Campbell C, Watson D, Rushe T, Shevlin M, Bai F, Cooper S, Mulholland C (2012) Childhood trauma and hippocampal and amygdalar volumes in first-episode psychosis. Schizophr Bull 38(6):1162–1169

    Article  PubMed Central  PubMed  Google Scholar 

  • Hsu C, Chang C, Lin C (2010) A practical guide to support vector classification. Technical Report 2010. http://www.csie.ntu.edu.tw/~cjlin/libsvm/

  • Iwashiro N, Suga M, Takano Y, Inoue H, Natsubori T, Satomura Y, Koike S, Yahata N, Murakami M, Katsura M, Gonoi W, Sasaki H, Takao H, Abe O, Kasai K, Yamasue H (2012) Localized gray matter volume reductions in the pars triangularis of the inferior frontal gyrus in individuals at clinical high-risk for psychosis and first episode for schizophrenia. Schizophr Res 137(1–3):124–131

    Article  PubMed  Google Scholar 

  • Jenkinson M, Beckmann CF, Behrens TEJ, Woolrich MW, Smith SM (2012) FSL. NeuroImage 62:782–790

    Article  PubMed  Google Scholar 

  • Kim JH, Budde MD, Liang HF, Klein RS, Russell JH, Cross AH (2006) Detecting axon damage in spinal cord from a mouse model of multiple sclerosis. Neurobiol Dis 21:626–632

    Article  CAS  PubMed  Google Scholar 

  • Klöppel S, Abdulkadir A, Jack CJ, Koutsouleris N, Mouro-Miranda J, Vemuri P (2012) Diagnostic neuroimaging across diseases. Neuroimage 61:457–463

    Article  PubMed Central  PubMed  Google Scholar 

  • Koo MS, Levitt JJ, Salisbury DF, Nakamura M, Shenton ME, McCarley RW (2008) A cross-sectional and longitudinal magnetic resonance imaging study of cingulate gyrus gray matter volume abnormalities in first-episode schizophrenia and first-episode affective psychosis. Arch Gen Psychiatry 65:746–760

    Article  PubMed Central  PubMed  Google Scholar 

  • Kuswanto CN, Teh I, Lee TS, Sim K (2012) Diffusion tensor imaging findings of white matter changes in first episode schizophrenia: a systematic review. Clin Psychopharmacol Neurosci 10:13–24

    Article  PubMed Central  PubMed  Google Scholar 

  • Lanckriet GRG, Cristianini N, Bartlett P, Ghaoui LE, Jordan MI (2004) Learning the kernel matrix with semidefinite programming. J Mach Learn Res 5:27–72

    Google Scholar 

  • Lasalvia A, Tosato S, Brambilla P, Bertani M, Bonetto C, Cristofalo D, Bissoli S, De Santi K, Lazzarotto L, Zanatta G, Marrella G, Mazzoncini R, Zanoni M, Garzotto N, Dolce C, Nicolau S, Ramon L, Perlini C, Rambaldelli G, Bellani M, Tansella M, Ruggeri M (2012) Psychosis incident cohort outcome study (picos). a multisite study of clinical, social and biological characteristics, patterns of care and predictors of outcome in first-episode psychosis. background, methodology and overview of the patient sample. Epidemiol Psychiatr Sci 21:281–303

    Article  CAS  PubMed  Google Scholar 

  • Lavoie S, Bartholomeuz CF, Nelson B, Lin A, McGorry PD, Velakoulis D, Whittle SL, Yung AR, Pantelis C, Wood SJ (2014) Sulcogyral pattern and sulcal count of the orbitofrontal cortex in individuals at ultra high risk for psychosis. Schizophr Res 154(1–3):93–99

    Article  PubMed  Google Scholar 

  • Lee DY, Smith GN, Su W, Honer WG, Macewan GW, Lapointe JS, Vertinsky AT, Vila-Rodriguez F, Kopala LC, Lang DJ (2012) White matter tract abnormalities in first-episode psychosis. Schizophr Res 141:29–34

    Article  CAS  PubMed  Google Scholar 

  • Liu JJ, Norman RM, Manchanda R, De Luca V (2013) Admixture analysis of age at onset in schizophrenia: evidence of three subgroups in a first-episode sample. Gen Hosp Psychiatry 35(6):664–667

    Article  PubMed  Google Scholar 

  • Manchanda R, Norman R, Malla A, Harricharan R, Northcott S, Richard J (2014) Electroencephalographic abnormalities and 5-year outcome in first-episode psychosis. Can J Psychiatry 59(5):285–288

    PubMed Central  PubMed  Google Scholar 

  • Mechelli A, Riecher-Rossler A, Meisenzahl EM, Tognin S, Wood SJ, Borgwardt SJ, Koutsouleris N, Yung AR, Stone JM, Phillips LJ, McGorry PD, Valli I, Velakoulis D, Woolley J, Pantelis C, McGuire P (2011) Neuroanatomical abnormalities that predate the onset of psychosis. Arch Gen Psychiatry 68:489–495

    Article  PubMed  Google Scholar 

  • Molnar-Szakacs I, Iacoboni M, Koski L, Mazziotta JC (2005) Functional segregation within pars opercularis of the inferior frontal gyrus: evidence from FMRI studies of imitation and action observation. Cereb Cortex 15:986–994

    Article  PubMed  Google Scholar 

  • Mori S, Wakana S, van Zijl P, Nagae-Poetscher LM (2005) MRI atlas of human white matter. Elsevier, Amsterdam

    Google Scholar 

  • Palaniyappan L, Marques TR, Taylor H, Handley R, Mondelli V, Bonaccorso S, Giordano A, McQueen G, Di Forti M, Simmons A, David AS, Pariante CM, Murray Rm, Dazzan P (2013) Cortical folding defects as marker of poor treatment response in first-episode psychosis. JAMA Psychiatry 70(10):1031–1040

    Article  PubMed  Google Scholar 

  • Perlini C, Bellani M,    Brambilla P (2012) Structural imaging techniques in schizophrenia. Acta Psychiatr Scand 126(4):235–242

    Article  CAS  PubMed  Google Scholar 

  • Perina A, Peruzzo D, Kesa M, Jojic N, Murino V, Bellani M, Brambilla P, Castellani U (2014) Mapping brains on grids of features for Schizophrenia analysis. In: Proceedings of international conference on medical image computing and computer-assisted intervention, MICCAI '14, LNCS, vol 8673, pp 807–814

  • Peters B, Blaas J, de Haan L (2010) Diffusion tensor imaging in the early phase of schizophrenia: what have we learned? J Psychiatr Res 44(15):993–1004

    Article  PubMed  Google Scholar 

  • Pettersson-Yeo W, Allen P, Benetti S, McGuire P, Mechelli A (2011) Dysconnectivity in schizophrenia: where are we now? Neurosci Biobehav Rev 35:1110–1124

    Article  PubMed  Google Scholar 

  • Smieskova R, Allen P, Simon A, Aston J, Bendfeldt K, Drewe J, Gruber K, Gschwandtner U, Klarhoefer M, Lenz C, Scheffler K, Stieglitz RD, Radue EW, McGuire P, Riecher-Rössler A, Borgwardt SJ (2012) Different duration of at-risk mental state associated with neurofunctional abnormalities. A multimodal imaging study. Hum Brain Mapp 33(10):2281–2294

    Article  PubMed  Google Scholar 

  • Song SK, Yoshino J, Le TQ, Lin SJ, Sun SW, Cross AH et al (2005) Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 26:132–140

    Article  PubMed  Google Scholar 

  • Stephens MA (1970) Use of the Kolmogorov–Smirnov, Cramer-von Mises and related statistics without extensive tables. J R Stat Soc Ser B 32:115–122

    Google Scholar 

  • Sun D, Stuart GW, Jenkinson M, Wood SJ, McGorry PD, Velakoulis D, van Erp TGM, Thompson PM, Toga AW, Smith DJ, Cannon TD, Pantelis C (2009) Brain surface contraction mapped in first-episode schizophrenia: a longitudinal magnetic resonance imaging study. Mol Psychiatry 14:976–986

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • Tomasino B, Bellani M, Perlini C, Rambaldelli G, Cerini R, Isola M, Balestrieri M, Calì S, Versace A, Pozzi Mucelli R, Gasparini A, Tansella M, Brambilla P (2011) Altered microstructure integrity of the amygdala in schizophrenia: a bimodal MRI and DWI study. Psychol Med 41(2):301–311

    Article  CAS  PubMed  Google Scholar 

  • Ulas A, Duin RPW, Castellani U, Loog M, Mirtuono P, Bicego M, Murino V, Bellani M, Cerruti S, Tansella M, Brambilla P (2011) Dissimilarity-based detection of schizophrenia. Int J Imaging Syst Technol 21:179–192

    Article  Google Scholar 

  • Vapnik VN (1998) Statistical learning theory. Wiley, New York

    Google Scholar 

  • Xu Z, Jin R, Yang H, King I, Lyu MR (2010) Simple and efficient multiple kernel learning by group lasso. In: Proceedings of international conference on machine learning ICML, pp 1175–1182

  • Zhang J, Zhou R (2014) Individual differences in automatic emotion regulation affect the asymmetry of the LPP component. PLoS ONE 9(2):e88261

    Article  PubMed Central  PubMed  Google Scholar 

  • Zhang D, Wang Y, Zhou L, Yuan H, Shen D, Initiative, T.A.D.N. (2011) Multimodal classification of Alzheimer’s disease and mild cognitive impairment. Neuroimage 55:856–867

    Article  PubMed Central  PubMed  Google Scholar 

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Acknowledgments

Dr. Brambilla is partly supported by grants from the Ministry of Health (GR-2010-2316745) and by the BIAL Foundation (Fellowship #262/12).

Conflict of interest

All authors have no conflict of interest to declare.

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Authors and Affiliations

  1. Department of Computer Science, University of Verona, Strada le Grazie 15, 37134, Verona, Italy

    Denis Peruzzo, Umberto Castellani & Vittorio Murino

  2. Neuroimaging Department, Scientific Institute, IRCCS “Eugenio Medea”, Bosisio Parini, Lecco, Italy

    Denis Peruzzo

  3. Section of Clinical Psychology, Department of Public Health and Community Medicine, Inter-University Centre for Behavioral Neurosciences, University of Verona, Verona, Italy

    Cinzia Perlini

  4. Section of Psychiatry, Department of Public Health and Community Medicine, Inter-University Centre for Behavioral Neurosciences, University of Verona, Verona, Italy

    Marcella Bellani, Veronica Marinelli, Gianluca Rambaldelli & Mirella Ruggeri

  5. Section of Psychiatry, Department of Public Health and Community Medicine, University of Verona, Verona, Italy

    Antonio Lasalvia, Sarah Tosato & Katia De Santi

  6. Pattern Analysis and Computer Vision, Istituto Italiano di Tecnologia, Genoa, Italy

    Vittorio Murino

  7. Department of Experimental and Clinical Medicine (DISM), Inter-University Center for Behavioral Neurosciences (ICBN), University of Udine, P.le Kolbe 3, 33100, Udine, Italy

    Paolo Brambilla

  8. Department of Psychiatry and Behavioral Sciences, University of Texas Medical School at Houston, Houston, TX, USA

    Paolo Brambilla

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  1. Denis Peruzzo
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  2. Umberto Castellani
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  3. Cinzia Perlini
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  4. Marcella Bellani
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  6. Gianluca Rambaldelli
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  7. Antonio Lasalvia
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  9. Katia De Santi
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  11. Mirella Ruggeri
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  12. Paolo Brambilla
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PICOS-Veneto Group

Corresponding authors

Correspondence to Umberto Castellani or Paolo Brambilla.

Appendix: The PICOS-VENETO Group

Appendix: The PICOS-VENETO Group

Coordinating staff: M. Tansella M. Ruggeri, A. Lasalvia, M. Bertani, C. Bonetto, P. Brambilla, S. Tosato, D. Cristofalo, G. Marrella, S. Bissoli, M. Zanoni, C. Perlini, A. Ferro, S. Cerruti, M. Bellani, V. Marinelli, G. Rambaldelli.

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Peruzzo, D., Castellani, U., Perlini, C. et al. Classification of first-episode psychosis: a multi-modal multi-feature approach integrating structural and diffusion imaging. J Neural Transm 122, 897–905 (2015). https://doi.org/10.1007/s00702-014-1324-x

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