Making an accurate diagnosis of schizophrenia and related psychoses early in the course of the disease is important for initiating treatment and counseling patients and families. In this study, we developed classification models for early disease diagnosis using structural MRI (Structural Magnetic Resonance ImagingStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project.) and neuropsychological (NP) testing. We used sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. measurements and NP test results from 28 patients with recent-onset schizophrenia and 47 healthy subjects, drawn from the larger sample of the Mind Clinical Imaging Consortium. We developed diagnostic models based on Linear Discriminant Analysis (LDA) following two approaches; namely, (a) stepwise (STP) LDA on the original measurements, and (b) LDA on variables created through Principal Component Analysis (PCA) and selected using the Humphrey-Ilgen parallel analysis. Error estimation of the modeling algorithms was evaluated by leave-one-out external cross-validation. These analyses were performed on sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. and NP variables separately and in combination. The following classification accuracy was obtained for different variables and modeling algorithms. sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. only: (a) STP-LDA: 64.3% sensitivity and 76.6% specificity, (b) PCA-LDA: 67.9% sensitivity and 72.3% specificity. NP only: (a) STP-LDA: 71.4% sensitivity and 80.9% specificity, (b) PCA-LDA: 78.5% sensitivity and 91.5% specificity. Combined sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project.-NP: (a) STP-LDA: 64.3% sensitivity and 83.0% specificity, (b) PCA-LDA: 89.3% sensitivity and 93.6% specificity. (i) Maximal diagnostic accuracy was achieved by combining sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. and NP variables. (ii) NP variables were more informative than sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project., indicating that cognitive deficits can be detected earlier than volumetric structural abnormalities. (iii) PCA-LDA yielded more accurate classification than STP-LDA. As these sMRIStructural Magnetic Resonance Imaging (sMRI)Performed to assess gray-matter volume. The data are acquired using a Philips 3T Achieva XL magnet with a SENSE 8 channel head coil. Approximately 500,000 voxels per brain are analyzed. In the first analysis, the volume of about 100 separate brain regions is calculated using FreeSurfer software (www.surfer.nmr.mgh.harvard. edu). This provides a coarse-grain, volumetric analysis of areas of the brain. In the second analysis, called voxel-based morphometry, the density of each voxel is assessed for a fine-grain analysis of each area.5 Typically, gray-matter volume decreases with age but at rates that are different for different people, for different areas of the brain, and for men and women. In that sense, one can talk about "gray-matter age" versus chronological age. A person may be 68 years old but have the gray-matter volume of a 50-year-old. Defining brain age based on measurements (as contrasted with chronological age) is a pervasive theme in this project. and NP tests are widely available, they can increase accuracy of early intervention strategies and possibly be used in evaluating treatment response.