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Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Neuroradiological features across major psychiatric disorders and behavioral variant of Alzheimer's disease: a
Sina Dindarian1, Joga Chaganti2, Nazanin Rafiei3
1Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Abstract:
Psychiatric disorders are complex, disabling conditions that continue to rely on subjective diagnostic criteria due to the absence of objective biological markers. Neuroradiology has become a critical discipline for examining the structural, functional, and biochemical underpinnings of these disorders through advanced brain imaging. This review synthesizes findings from five major psychiatric conditions including major depressive disorder, schizophrenia, autism spectrum disorder, obsessive-compulsive disorder, and generalized anxiety disorder, and briefly discusses the behavioral variant of Alzheimer's disease, a variant with neuropsychological overlay, across multiple imaging modalities, including structural magnetic resonance imaging (MRI), diffusion tensor imaging, functional MRI, magnetic resonance spectroscopy, functional near-infrared spectroscopy, and positron emission tomography. We present a comparative overview of cross-condition and modality-specific findings, highlighting converging disruptions in frontolimbic and temporoparietal circuits, alongside unique neurobiological features in each disorder. We also acknowledge key confounds such as medication effects, comorbidities, and methodological variability that limit direct transdiagnostic inference. We further discuss methodological limitations, emerging trends such as multimodal integration and machine learning, and future directions for translating imaging data into clinically meaningful biomarkers.
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