TY - JOUR
T1 - Neuroanatomical pattern classification in a population-based sample of first-episode schizophrenia
AU - Zanetti, Marcus V.
AU - Schaufelberger, Maristela S.
AU - Doshi, Jimit
AU - Ou, Yangming
AU - Ferreira, Luiz K.
AU - Menezes, Paulo R.
AU - Scazufca, Marcia
AU - Davatzikos, Christos
AU - Busatto, Geraldo F.
N1 - Funding Information:
This study was supported with funding from the Wellcome Trust , UK, and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP), Brazil (no. 2003/13627-0). Marcus V. Zanetti is funded by CAPES (Brazil). Geraldo F. Busatto, Paulo R. Menezes and Marcia Scazufca are partially funded by CNPq-Brazil .
PY - 2013/6/3
Y1 - 2013/6/3
N2 - Recent neuroanatomical pattern classification studies have attempted to individually classify cases with psychotic disorders using morphometric MRI data in an automated fashion. However, this approach has not been tested in population-based samples, in which variable patterns of comorbidity and disease course are typically found. We aimed to evaluate the diagnostic accuracy (DA) of the above technique to discriminate between incident cases of first-episode schizophrenia identified in a circumscribed geographical region over a limited period of time, in comparison with next-door healthy controls. Sixty-two cases of first-episode schizophrenia or schizophreniform disorder and 62 age, gender and educationally-matched controls underwent 1.5. T MRI scanning at baseline, and were naturalistically followed-up over 1. year. T1-weighted images were used to train a high-dimensional multivariate classifier, and to generate both spatial maps of the discriminative morphological patterns between groups and ROC curves. The spatial map discriminating first-episode schizophrenia patients from healthy controls revealed a complex pattern of regional volumetric abnormalities in the former group, affecting fronto-temporal-occipital gray and white matter regions bilaterally, including the inferior fronto-occipital fasciculus, as well as the third and lateral ventricles. However, an overall modest DA (73.4%) was observed for the individual discrimination between first-episode schizophrenia patients and controls, and the classifier failed to predict 1-year prognosis (remitting versus non-remitting course) of first-episode schizophrenia (DA = 58.3%). In conclusion, using a "real world" sample recruited with epidemiological methods, the application of a neuroanatomical pattern classifier afforded only modest DA to classify first-episode schizophrenia subjects and next-door healthy controls, and poor discriminative power to predict the 1-year prognosis of first-episode schizophrenia.
AB - Recent neuroanatomical pattern classification studies have attempted to individually classify cases with psychotic disorders using morphometric MRI data in an automated fashion. However, this approach has not been tested in population-based samples, in which variable patterns of comorbidity and disease course are typically found. We aimed to evaluate the diagnostic accuracy (DA) of the above technique to discriminate between incident cases of first-episode schizophrenia identified in a circumscribed geographical region over a limited period of time, in comparison with next-door healthy controls. Sixty-two cases of first-episode schizophrenia or schizophreniform disorder and 62 age, gender and educationally-matched controls underwent 1.5. T MRI scanning at baseline, and were naturalistically followed-up over 1. year. T1-weighted images were used to train a high-dimensional multivariate classifier, and to generate both spatial maps of the discriminative morphological patterns between groups and ROC curves. The spatial map discriminating first-episode schizophrenia patients from healthy controls revealed a complex pattern of regional volumetric abnormalities in the former group, affecting fronto-temporal-occipital gray and white matter regions bilaterally, including the inferior fronto-occipital fasciculus, as well as the third and lateral ventricles. However, an overall modest DA (73.4%) was observed for the individual discrimination between first-episode schizophrenia patients and controls, and the classifier failed to predict 1-year prognosis (remitting versus non-remitting course) of first-episode schizophrenia (DA = 58.3%). In conclusion, using a "real world" sample recruited with epidemiological methods, the application of a neuroanatomical pattern classifier afforded only modest DA to classify first-episode schizophrenia subjects and next-door healthy controls, and poor discriminative power to predict the 1-year prognosis of first-episode schizophrenia.
KW - First-episode psychosis
KW - Magnetic resonance imaging
KW - Pattern classification
KW - Prognosis
KW - Schizophrenia
UR - http://www.scopus.com/inward/record.url?scp=84872514168&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84872514168&partnerID=8YFLogxK
U2 - 10.1016/j.pnpbp.2012.12.005
DO - 10.1016/j.pnpbp.2012.12.005
M3 - Article
C2 - 23261522
AN - SCOPUS:84872514168
SN - 0278-5846
VL - 43
SP - 116
EP - 125
JO - Progress in Neuro-Psychopharmacology and Biological Psychiatry
JF - Progress in Neuro-Psychopharmacology and Biological Psychiatry
ER -