clinical implication of multimodal neuroimaging

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Clinical Implication of Clinical Implication of Multimodal Neuroimaging Multimodal Neuroimaging Jungsu S. Oh, Ph.D. Assistant Professor BK21 Division of Human Life Science Seoul National University On behalf of Jun Soo Kwon, M.D., Ph.D. (Clinical Neuroscience and Computational Neuroscience Unit) Professor at BCS, Seoul National University WCU

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Clinical Implication of Multimodal Neuroimaging. Jungsu S. Oh, Ph.D. Assistant Professor BK21 Division of Human Life Science Seoul National University. On behalf of Jun Soo Kwon, M.D., Ph.D. (Clinical Neuroscience and Computational Neuroscience Unit) - PowerPoint PPT Presentation

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Page 1: Clinical Implication of Multimodal Neuroimaging

Clinical Implication of Clinical Implication of Multimodal NeuroimagingMultimodal Neuroimaging

Jungsu S. Oh, Ph.D. Assistant Professor

BK21 Division of Human Life ScienceSeoul National University

On behalf of Jun Soo Kwon, M.D., Ph.D.(Clinical Neuroscience and Computational Neuroscience Unit)

Professor at BCS, Seoul National University WCU

Page 2: Clinical Implication of Multimodal Neuroimaging

BackgroundBackground

• Interests in brain function and connectivity have much grown up in recent decades.

• Synergic effects of Multi-modal/Multi-technique Imaging, which is useful– not only for assessing chronic patients– but also for detecting subtle changes in

• Ultra-high-risk (UHR) pathological subjects• Neuro-plasticity groups

Page 3: Clinical Implication of Multimodal Neuroimaging

Example of “High-risk” groupExample of “High-risk” groupin the course of schizophreniain the course of schizophrenia

Healthy↑

↓Severity of Symptoms

Page 4: Clinical Implication of Multimodal Neuroimaging

Basic Structures of BrainBasic Structures of Brain

• Gray Matter– Functional activations– Structural imaging– Functional/molecular

imaging

• White Matter (Tracts)– Connecting distinctive

functional regions– Diffusion Tensor MRI

for reconstructing pathway information and estimating quantity/quality of anatomical connectivity

Page 5: Clinical Implication of Multimodal Neuroimaging

Basic Principle and Properties of Basic Principle and Properties of Diffusion Tensor Imaging (DTI)Diffusion Tensor Imaging (DTI)

• Mean DiffusivityMean Diffusivity (Dm)– Size of tensor– (Degree of tissue microstructure

disruption)

• Fractional AnisotropyFractional Anisotropy (FA)– Sharpness of tensor– Normalized variance of

eigenvalues:0~1– (Degree of fiber integrity)

• ModeMode (Ennis and Kindlmann, MRM, 2006)(Ennis and Kindlmann, MRM, 2006)

– Proximity of tensor shape to a disc– Degree of fiber crossing

• two principal axes – disc shape– Negative Mode

• Crossing fiber tracts: λ1 ≈ λ2 > λ3

>

>

λ1≈ λ2 > λ3

Free Water: Isotropic Diffusion

White Matter Tracts: Anisotropic Diffusion

Page 6: Clinical Implication of Multimodal Neuroimaging

Tract (Tractography)-Based Tract (Tractography)-Based DTI AnalysisDTI Analysis

• Not only diffusion properties but “connectivity”

• Not only visualization tool but “quantitative analysis tool” of fiber tracts

• Tractography Methods– Most Basic: StreamlineMost Basic: Streamline

• Using principal diffusion direction(e1) only• Euler Integration method

– Tensorline (regularized, using tensor deflection), level set-based tractography (fast marching tractography)

– High-End: Stochastic Tractography and High High-End: Stochastic Tractography and High Angular Resolution Diffusion Imaging (DSI, QBI)Angular Resolution Diffusion Imaging (DSI, QBI)

Page 7: Clinical Implication of Multimodal Neuroimaging

Quantitative DTI analysis using Brodmann ROI-Quantitative DTI analysis using Brodmann ROI-based parcellation and tract parameterization based parcellation and tract parameterization

(Oh et al., Human Brain Mapping, in press)(Oh et al., Human Brain Mapping, in press)

Shape-based parameterization

(Oh et al., NeuroImage, 2007)(Oh et al., NeuroImage, 2007)

(Oh et al., Unpublished data)

Application in Drug-naïve

OCD patients

Application in UHR Schizophrenia

patients??

((Oh et al., in preparation)Oh et al., in preparation)

Page 8: Clinical Implication of Multimodal Neuroimaging

Functional imaging-based estimation Functional imaging-based estimation of functional activation and of functional activation and

connectivityconnectivity

(Oh et al., Annual Meeting of (Oh et al., Annual Meeting of Biol Psychiatry 2008)Biol Psychiatry 2008)

Magnetoencephalogram Magnetoencephalogram (MEG)(MEG)

Deficits of early stage of auditory processing in UHRN1m and MMNm dipole moments may represent a vulnerability marker in evaluating the risk of transition to psychotic stage in UHR group.

Decreased desynchronization of alpha rhythm in UHR

Deficits of top-down inhibitory control

N1m MMNm

((Koh et al., Koh et al., Unpublished dataUnpublished data))

Resting-state fMRIResting-state fMRI

(Shin et al., Biol Psychiatry, in press)(Shin et al., Biol Psychiatry, in press)

Page 9: Clinical Implication of Multimodal Neuroimaging

Synergic Effects of Synergic Effects of Multi-modal/Multi-technique Multi-modal/Multi-technique

ImagingImaging

ITBT

BT NT

*Abbreviations: SZ: Schizophrenia; OCD: Obsessive-Compulsive Disorder

To Better Understand the

Etiology of SZ/ OCD/ …

To Better Detect High-Risk Groups

for SZ/ OCD/ …

Brain Imaging

GeneticsStudy

“Biomarker”

Structure Function

Connectivity

Page 10: Clinical Implication of Multimodal Neuroimaging

Future Directions of Future Directions of “High Risk” Study“High Risk” Study

Large sample size and longitudinal study

Combinational approach of structural and functional imaging

Effective strategies for the recruitment of high-risk groupsContinuous efforts for the “follow-up” studies

Genetics-neuroimaging integration

Functional imaging-based connectivityFunctional imaging-based connectivity

Structural imaging-based connectivityStructural imaging-based connectivity

PrerequisitesPrerequisites

Temporal activation in fMRI/MEGIntersubject variability of FDG PET

Mostly, DTI tractography-based approachStructural ShapeStructural Shape

Cortical thickness, CC shape, Basal ganglia shape

Page 11: Clinical Implication of Multimodal Neuroimaging

An exemplary study of neuro-plasticity An exemplary study of neuro-plasticity groups: the Baduk (Go) game expertsgroups: the Baduk (Go) game experts

Working memory task-related fMRIWorking memory task-related fMRI

(Park et al., (Park et al., Unpublished dataUnpublished data))

Voxel-based DTI analysisVoxel-based DTI analysis

(Lee et al., (Lee et al., Unpublished dataUnpublished data))

Integrated Anatomo-Functional Connectivity

Page 12: Clinical Implication of Multimodal Neuroimaging

ConclusionConclusion• Multimodal neuroimaging including

structural, functional and genetic imaging will add to – finding biomarkers to detect subtle changes in

“high risk” groups– facilliating the development of treatment and

precaution strategies of psychiatric disorders.

• Its application for assessing neuro-plasticity groups (e.g., extraordinary IQ, meditation, Baduk experts) looks promising as well.

Page 13: Clinical Implication of Multimodal Neuroimaging

Seoul Youth Clinic (SYC)Seoul Youth Clinic (SYC)Brief history of SYCBrief history of SYC Procedures in SYCProcedures in SYC

• Started SYC in 16 June, 2004 • Recruited 103 subjects of CHR/GHR SZ

- 12 subjects : conversion to psychosis

(CHR only) - 18 subjects : drop-up - 73 subjects : follow-up• Mediation: Among the CHR groups, 36

subjects have been taken for antipsychotics.

• Related publications - Potential vulnerability markers within the affective

domain in subjects at genetic and clinical high risk for schizophrenia. Psychopathology. 2008, Apr

- Deficit of theory of mind in individuals at ultra-high-risk for schizophrenia. Schizophr Res. 2008, Feb

- Pre-attentive auditory processing in ultra-high-risk for schizophrenia with magnetoencephalography. Biol Psychiatry, in press