Diffusion tensor imaging (DTI) is a promising method for characterizing microstructural changes in the brain. It measures the magnitude, anisotropy, and orientation of water diffusion, providing insights into white matter (WM) pathology and treatment effects. DTI is highly sensitive to changes at the cellular and microstructural level, making it valuable for diagnosing and monitoring neurological conditions. The diffusion tensor describes the covariance of diffusion displacements in three dimensions, with eigenvalues and eigenvectors representing the principal diffusion directions and apparent diffusivities. DTI measures such as mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (Dr), and axial diffusivity (Da) are used to assess tissue microstructure. FA is sensitive to microstructural changes but not specific to their type. To improve specificity, multiple DTI measures should be used together. DTI has applications in tissue characterization, white matter tractography, and neurotherapeutic monitoring. It is particularly useful for detecting changes in diseases like ischemic stroke, demyelination, inflammation, edema, and neoplasia. DTI can also aid in surgical planning by mapping critical WM pathways. However, its interpretation is complex due to factors like noise, partial volume averaging, and crossing fibers. Despite these challenges, DTI remains a powerful tool for understanding brain microstructure and its changes in disease and treatment.Diffusion tensor imaging (DTI) is a promising method for characterizing microstructural changes in the brain. It measures the magnitude, anisotropy, and orientation of water diffusion, providing insights into white matter (WM) pathology and treatment effects. DTI is highly sensitive to changes at the cellular and microstructural level, making it valuable for diagnosing and monitoring neurological conditions. The diffusion tensor describes the covariance of diffusion displacements in three dimensions, with eigenvalues and eigenvectors representing the principal diffusion directions and apparent diffusivities. DTI measures such as mean diffusivity (MD), fractional anisotropy (FA), radial diffusivity (Dr), and axial diffusivity (Da) are used to assess tissue microstructure. FA is sensitive to microstructural changes but not specific to their type. To improve specificity, multiple DTI measures should be used together. DTI has applications in tissue characterization, white matter tractography, and neurotherapeutic monitoring. It is particularly useful for detecting changes in diseases like ischemic stroke, demyelination, inflammation, edema, and neoplasia. DTI can also aid in surgical planning by mapping critical WM pathways. However, its interpretation is complex due to factors like noise, partial volume averaging, and crossing fibers. Despite these challenges, DTI remains a powerful tool for understanding brain microstructure and its changes in disease and treatment.