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Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders.

O'Halloran R, Kopell BH, Sprooten E, Goodman WK, Frangou S - Front Psychiatry (2016)

Bottom Line: Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits.We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain.However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment.

View Article: PubMed Central - PubMed

Affiliation: Brain Imaging Center, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai , New York, NY , USA.

ABSTRACT
Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment. We demonstrate how this approach can be validated in the treatment of Parkinson's disease by identifying connectivity patterns that can be used as biomarkers for treatment planning and thus refine the traditional approach of DBS planning that uses only gray matter landmarks. Finally, we describe how this approach could be used in planning DBS treatment of psychiatric disorders.

No MeSH data available.


Related in: MedlinePlus

Tractography at 3-T compared to 7-T. Tracts connecting the nucleus accumbens (shown in green) to the ventral prefrontal cortex from diffusion-weighted imaging at 3-T (A) and 7-T (B). Tract probability map >1% of streamlines (red) corrected for distance; primary diffusion direction overlaid on T1-weighted image.
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Figure 3: Tractography at 3-T compared to 7-T. Tracts connecting the nucleus accumbens (shown in green) to the ventral prefrontal cortex from diffusion-weighted imaging at 3-T (A) and 7-T (B). Tract probability map >1% of streamlines (red) corrected for distance; primary diffusion direction overlaid on T1-weighted image.

Mentions: The increasing availability of high-field MRI scanners, improvements in susceptibility correction methods, and advances in sequence developments enable the in vivo investigation of the human brain at higher resolution and higher signal-to-noise ratio than ever before. We illustrate the benefits of high-field imaging using data obtained with DWI/DTI (50), a technique that yields measures of water diffusion within the brain. One DTI-derived measure is fractional anisotropy (FA) that reflects the relative degree to which water diffusion is not evenly restricted in all directions; FA is elevated in areas with high density of white matter tracts due to diffusion being more restricted perpendicular to tracts than along the tracts. Figure 3 provides a visual comparison of FA maps (Figure 3, gray scale images) with the preferred direction of diffusion (Figure 3, colored lines) derived from a 7-T compared to a 3-T diffusion-weighted scan. This demonstrates the improvement in the characterization of the anterior limb of the internal capsule (ALIC) and of the boundary between white matter and cortical gray matter with 7-T compared to 3-T.


Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders.

O'Halloran R, Kopell BH, Sprooten E, Goodman WK, Frangou S - Front Psychiatry (2016)

Tractography at 3-T compared to 7-T. Tracts connecting the nucleus accumbens (shown in green) to the ventral prefrontal cortex from diffusion-weighted imaging at 3-T (A) and 7-T (B). Tract probability map >1% of streamlines (red) corrected for distance; primary diffusion direction overlaid on T1-weighted image.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4835492&req=5

Figure 3: Tractography at 3-T compared to 7-T. Tracts connecting the nucleus accumbens (shown in green) to the ventral prefrontal cortex from diffusion-weighted imaging at 3-T (A) and 7-T (B). Tract probability map >1% of streamlines (red) corrected for distance; primary diffusion direction overlaid on T1-weighted image.
Mentions: The increasing availability of high-field MRI scanners, improvements in susceptibility correction methods, and advances in sequence developments enable the in vivo investigation of the human brain at higher resolution and higher signal-to-noise ratio than ever before. We illustrate the benefits of high-field imaging using data obtained with DWI/DTI (50), a technique that yields measures of water diffusion within the brain. One DTI-derived measure is fractional anisotropy (FA) that reflects the relative degree to which water diffusion is not evenly restricted in all directions; FA is elevated in areas with high density of white matter tracts due to diffusion being more restricted perpendicular to tracts than along the tracts. Figure 3 provides a visual comparison of FA maps (Figure 3, gray scale images) with the preferred direction of diffusion (Figure 3, colored lines) derived from a 7-T compared to a 3-T diffusion-weighted scan. This demonstrates the improvement in the characterization of the anterior limb of the internal capsule (ALIC) and of the boundary between white matter and cortical gray matter with 7-T compared to 3-T.

Bottom Line: Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits.We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain.However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment.

View Article: PubMed Central - PubMed

Affiliation: Brain Imaging Center, Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai , New York, NY , USA.

ABSTRACT
Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment. We demonstrate how this approach can be validated in the treatment of Parkinson's disease by identifying connectivity patterns that can be used as biomarkers for treatment planning and thus refine the traditional approach of DBS planning that uses only gray matter landmarks. Finally, we describe how this approach could be used in planning DBS treatment of psychiatric disorders.

No MeSH data available.


Related in: MedlinePlus