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Multimodal MRI Analysis of White Matter Degeneration

Explore techniques for analyzing white matter degeneration using FLAIR, DTI modalities with considerations for different signals, noise, and resolutions. Understanding correlations between different imaging mechanisms in neurological disorders such as MS, dementia, and stroke.

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Multimodal MRI Analysis of White Matter Degeneration

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  1. Multimodal MRI Analysis of White Matter Degeneration Wang Zhan, Ph.D. Tel: 415-221-4810x2454, Email: Wang.Zhan@ucsf.edu Center for Imaging of Neurodegenerative Diseases UCSF / Radiology / VA Medical Center 01/08/2007 Medical Imaging Informatics, 2008 --- W. Zhan

  2. Technical Issues for Multimodal Analysis • Different image resolutions • Different geometric distortions • Different imaging mechanisms (contrasts) • Different signal variations • Different signal linearity • Different noise levels • Different noise distributions

  3. Traditional Imaging: (FLAIR, T2W, T1W, PD) Aging Multiple sclerosis Dementia (AD/MCI/FTD/SIVD) Depression Schizophrenia Bipolar disorder Celiac disease Hypertension Diabetes Stroke AIDS Cancer Brain injury Diffusion Tensor Imaging: (FA, MD,Tractography) Aging Multiple sclerosis Dementia (AD/MCI/FTD/SIVD) Depression Schizophrenia Bipolar disorder Celiac disease Stroke AIDS Cancer Brain injury MRI Modalities on WM Degeneration Medical Imaging Informatics, 2008 --- W. Zhan

  4. Fluid Attenuated Inversion Recovery (FLAIR) Parameters at 4T: TR = 6000 (ms) TE = 355 (ms) TI = 2030 (ms) E. Mark Haacke, et al., “Magnetic Resonance Imaging: Physical Principles and Sequence Design”, 1999, Springer Verlag Zhi-Pei Liang, Paul C. Lauterbur, “Principles of Magnetic Resonance Imaging: A Signal Processing Perspective”, 2004, IEEE Ref: http://www.mr-tip.com/serv1.php Medical Imaging Informatics, 2008 --- W. Zhan

  5. FLAIR T1W PD T2W CSF Gray Matter White Matter WM Lesion Traditional MRI Contrasts Krishnan et al., 2005, Duke Silvio Conte Center Medical Imaging Informatics, 2008 --- W. Zhan

  6. X Z Y Diffusion ‘Sphere’ Diffusion in 3-D: Homogeneous Medium Water in a Homogeneous Medium Water Motion

  7. X Z Y Diffusion ‘Ellipse’ Diffusion in 3-D: White Matter Water in an Oriented Tissue Water Motion

  8. MD FA FA B0 Diffusion Tensor Imaging WMH Medical Imaging Informatics, 2008 --- W. Zhan

  9. S1 S2 S3 Sn Group Analysis of Correlations (DTI ↔ FLAIR) DTI FLAIR Mean DTI Mean WML Medical Imaging Informatics, 2008 --- W. Zhan

  10. FA↔WML MD↔WML MD↔WML a c b WMH Mean FA Mean FA Correlations (DTI ↔WML Volume) Subjects: N=47 (F=26), Age=77±6, MMSE=27.3±3.3, WML=11±16 (ml) Medical Imaging Informatics, 2008 --- W. Zhan

  11. EPI Read Out Phase Encoding ? Effects of Image Misregistration? DTI / T1 Template Correlation / WML Medical Imaging Informatics, 2008 --- W. Zhan

  12. Pure CSF Normal WM Lesion Progression MPRAGE (T1 Dark) 1H Dens (WMH) T2W (WMH) DTI (FA/MD) FLAIR (WMH) Modeling for WM Degeneration Medical Imaging Informatics, 2008 --- W. Zhan

  13. CSF WM Two-Compartment Model of Relaxation (T1/T2) (T1/T2) Lesion Progression: f = 0 ~ 1 Relaxation Times: Medical Imaging Informatics, 2008 --- W. Zhan

  14. Fluid Attenuated Inversion Recovery (FLAIR) Parameters at 4T:TR = 6000 (ms) TE = 355 (ms) TI = 2030 (ms) WMH Medical Imaging Informatics, 2008 --- W. Zhan

  15. Multimodal Contrasts for WML Progression Noise-Contaminated Noise-Free Medical Imaging Informatics, 2008 --- W. Zhan

  16. CSF WM Two-Compartment Model of Diffusion (DCSF) (DWM) Lesion Progression: f = 0 ~ 1 Slow exchange: Fast exchange: Medical Imaging Informatics, 2008 --- W. Zhan

  17. Diffusion Tensor Imaging (Slow-Exchange) Noise free SNR = 80 Medical Imaging Informatics, 2008 --- W. Zhan

  18. Diffusion Tensor Imaging (Fast-Exchange) Noise free SNR = 80 Medical Imaging Informatics, 2008 --- W. Zhan

  19. DTI (FA) ↔ WML (FLAIR) Correlations SNR= 80, b = 1000 s/mm2 Medical Imaging Informatics, 2008 --- W. Zhan

  20. DTI (MD) ↔ WML (FLAIR) Correlations SNR= 80, b = 1000 s/mm2 Medical Imaging Informatics, 2008 --- W. Zhan

  21. DTI (FA) ↔ T1 Dark (MPARGE) Correlations SNR= 80, b = 1000 s/mm2 Medical Imaging Informatics, 2008 --- W. Zhan

  22. FLAIR Phantom Simulations (N=20) Medical Imaging Informatics, 2008 --- W. Zhan

  23. FA↔WML MD↔WML MD↔WML a c b WMH Mean FA Mean FA Correlations (DTI ↔WML Volume) Subjects: N=47 (F=26), Age=77±6, MMSE=27.3±3.3, WML=11±16 (ml) Medical Imaging Informatics, 2008 --- W. Zhan

  24. Summaries • Multimodal MRI analysis with both FLAIR and DTI may provide extra information for characterizing WM degeneration process, which may not be captured by using either of them of alone. • Special technical issues should addressed properly for multimodal analysis, including image registration, signal nonlinearity, and noise effects, etc. • In traditional modalities, FLAIR shows a significant signal nonlinearity to the WM degeneration. FLAIR signal reaches its maximum around lesion severity of 0.7. • In DTI modalities, signal sensitivity and nonlinearity depend on the b value of diffusion weighting and the water exchange rate of issue compartments. Moreover, image noises may have heterogeneous effects on different DTI indices and lesion severities. • The correlations between FLAIR and DTI may change signs when come across the minimum magnitude of correlation at the maximum WML intensity.

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