# Presentation: 049885

## Multimodal MRI Analysis of White Matter Degeneration

- Wang Zhan, Ph.D.
- Tel: 415-221-4810x2454, Email: _[Wang.Zhan@ucsf.edu](mailto:Wang.Zhan@ucsf.edu)_
- Center for Imaging of Neurodegenerative Diseases
- UCSF / Radiology / VA Medical Center
- 01/08/2007

- Medical Imaging Informatics, 2008  --- W. Zhan

## 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

## MRI Modalities on WM Degeneration 

*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

- Medical Imaging Informatics, 2008  --- W. Zhan

## Fluid Attenuated Inversion Recovery (FLAIR)

- Parameters at 4T: TR = 6000 (ms) TE = 355 (ms) TI = 2030 (ms)

- Medical Imaging Informatics, 2008  --- W. Zhan

- Ref: http://www.mr-tip.com/serv1.php

- 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

## Traditional MRI Contrasts

- Krishnan et al., 2005, Duke Silvio Conte Center

- Medical Imaging Informatics, 2008  --- W. Zhan

## Diffusion in 3-D: Homogeneous Medium

**Diffusion in 3-D: Homogeneous Medium**

**Water in a **
**Homogeneous Medium**

**Water Motion**

## Diffusion in 3-D: White Matter

**Diffusion in 3-D: White Matter**

**Water in an Oriented Tissue**

**Water Motion**

## Diffusion Tensor Imaging

- Medical Imaging Informatics, 2008  --- W. Zhan

- WMH

## Group Analysis of Correlations (DTI ↔ FLAIR)

- FLAIR

- Group Analysis of Correlations (DTI ↔ FLAIR)

- Medical Imaging Informatics, 2008  --- W. Zhan

- Mean DTI

- Mean WML

- DTI

## Correlations (DTI ↔WML Volume)

- Medical Imaging Informatics, 2008  --- W. Zhan

- Subjects: N=47 (F=26), Age=77±6, MMSE=27.3±3.3, WML=11±16 (ml)

## Effects of Image Misregistration?

- Correlation / WML

- DTI / T1 Template

- Medical Imaging Informatics, 2008  --- W. Zhan

## Modeling for WM Degeneration

- Medical Imaging Informatics, 2008  --- W. Zhan

## Two-Compartment Model of Relaxation

- Relaxation Times:

- Lesion Progression: *f* = 0 ~ 1

- Medical Imaging Informatics, 2008  --- W. Zhan

- (T1/T2)

- (T1/T2)

## Fluid Attenuated Inversion Recovery (FLAIR)

- Parameters at 4T: TR = 6000 (ms) TE = 355 (ms) TI = 2030 (ms)

- WMH

- Medical Imaging Informatics, 2008  --- W. Zhan

## Multimodal Contrasts for WML Progression

**Noise-Free**

**Noise-Contaminated**

- Medical Imaging Informatics, 2008  --- W. Zhan

## Two-Compartment Model of Diffusion

- Lesion Progression: *f* = 0 ~ 1

- Medical Imaging Informatics, 2008  --- W. Zhan

- (DWM)

- Slow exchange:

- (DCSF)

- Fast exchange:

## Diffusion Tensor Imaging (Slow-Exchange)

- SNR = 80

- Noise free

- Medical Imaging Informatics, 2008  --- W. Zhan

## Diffusion Tensor Imaging (Fast-Exchange)

- SNR = 80

- Noise free

- Medical Imaging Informatics, 2008  --- W. Zhan

## DTI (FA) ↔ WML (FLAIR) Correlations

- DTI (FA) ↔ WML (FLAIR) Correlations

- SNR= 80,  b = 1000 s/mm2

- Medical Imaging Informatics, 2008  --- W. Zhan

## DTI (MD) ↔ WML (FLAIR) Correlations

- SNR= 80,  b = 1000 s/mm2

- Medical Imaging Informatics, 2008  --- W. Zhan

## DTI (FA) ↔ T1 Dark (MPARGE) Correlations

- SNR= 80,  b = 1000 s/mm2

- Medical Imaging Informatics, 2008  --- W. Zhan

## FLAIR Phantom Simulations (N=20)

- Medical Imaging Informatics, 2008  --- W. Zhan

## Correlations (DTI ↔WML Volume)

- Medical Imaging Informatics, 2008  --- W. Zhan

- Subjects: N=47 (F=26), Age=77±6, MMSE=27.3±3.3, WML=11±16 (ml)

## 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.

## [1] Le Bihan D, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161:401-407.
[2] Pfefferbaum A, Sullivan EV, Hedehus M, et al., Age-related decline in brain white matter  nisotropy measured with spatially corrected echo-planar diffusion tensor imaging.  agn Reson Med 2000;44(2):259-8.
[3] Lansberg MG, Albers GW, Beaulieu C, Marks MP. Comparison of diffusion-weighted MRI and CT in acute stroke. Neurology 2000;54(8):1557-61.
[4] Meier-Ruge W, Ulrich J, Bruhlmann M, Meier E. Age-related white matter atrophy in the human brain. Ann N Y Acad Sci 1992;673:260-9.
[5] Awad IA, Johnson PC, Spetzler RF, Hodak JA. Incidental subcortical lesions identified on magnetic resonance imaging in the elderly. II. Postmortem pathological correlations. Stroke 1986;17(6):1090-7.
[6] Breteler MM, van Swieten JC, Bots ML, et al. Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology 1994;44(7):1246-52.
[7] Yoshita M, Fletcher E, Harvey D, et al., Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology 2006;67(12):2192-8.
[8] DeCarli et al, Neurobiology of Aging, 1007 (In Press). 
[9] Smith SM, Jenkinson M, Woolrich MW, et al., Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 2004, 23(S1):208-219.
[10] Smith SM, Jenkinson M, Johansen-Berg H, et al., Tract-based spatial statistics: Voxelwise analysis multi-subject diffusion data. NeuroImage 2006, 31:1487. 
[11] Hadjidemetriou S, Studholme C, Mueller S, et al., Restoration of MRI data for field nonuniformities using high order neighborhood statistics. Proc. Of SPIE Medical Image Processing, 6512, 2007.
[12] Boykov Y, Veksler O, and Zabih R, Fast approximate energy minimization via graph cuts. IEEE Trans. on AMI, 23(11):1222–1239, 2001.
[13] Christensen GE, Rabbitt RD, and Miller MI. Deformable templates using large deformation kinematics. Image Processing, IEEE Transactions on, 5(10):1435-1447, 1996.
[14] Joshi S, Lorenzen P, Gerig G, and Bullitt E, Structural and radiometric asymmetry in brain images. Med Image Anal, 7(2):155-170, 2003.
[15] Neter, J, Wasserman, W, Kutner, MH. Applied Linear Statistical Models: Regression, Analysis of Variance, and Experimental Designs,  3rd edition. Richard d Irwin Publishing. 1990.
[16] Kamman RL, Go KG, Brouwer WH, Berendsen JC. Nuclear magnetic resonance relaxation in experimental brain edema: Effects of water concentration, protein concentration, and temperature. Med. Reson. Med. 6 (3): 265-274, 1988. 

- [2] Pfefferbaum A, Sullivan EV, Hedehus M, et al., Age-related decline in brain white matter  nisotropy measured with spatially corrected echo-planar diffusion tensor imaging.  agn Reson Med 2000;44(2):259-8.
- [3] Lansberg MG, Albers GW, Beaulieu C, Marks MP. Comparison of diffusion-weighted MRI and CT in acute stroke. Neurology 2000;54(8):1557-61.
- [4] Meier-Ruge W, Ulrich J, Bruhlmann M, Meier E. Age-related white matter atrophy in the human brain. Ann N Y Acad Sci 1992;673:260-9.
- [5] Awad IA, Johnson PC, Spetzler RF, Hodak JA. Incidental subcortical lesions identified on magnetic resonance imaging in the elderly. II. Postmortem pathological correlations. Stroke 1986;17(6):1090-7.
- [6] Breteler MM, van Swieten JC, Bots ML, et al. Cerebral white matter lesions, vascular risk factors, and cognitive function in a population-based study: the Rotterdam Study. Neurology 1994;44(7):1246-52.
- [7] Yoshita M, Fletcher E, Harvey D, et al., Extent and distribution of white matter hyperintensities in normal aging, MCI, and AD. Neurology 2006;67(12):2192-8.
- [8] DeCarli et al, Neurobiology of Aging, 1007 (In Press).
- [9] Smith SM, Jenkinson M, Woolrich MW, et al., Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage 2004, 23(S1):208-219.
- [10] Smith SM, Jenkinson M, Johansen-Berg H, et al., Tract-based spatial statistics: Voxelwise analysis multi-subject diffusion data. NeuroImage 2006, 31:1487.
- [11] Hadjidemetriou S, Studholme C, Mueller S, et al., Restoration of MRI data for field nonuniformities using high order neighborhood statistics. *Proc. Of SPIE Medical Image Processing*, 6512, 2007.
- [12] Boykov Y, Veksler O, and Zabih R, Fast approximate energy minimization via graph cuts. *IEEE Trans. on AMI*, 23(11):1222–1239, 2001.
- [13] Christensen GE, Rabbitt RD, and Miller MI. Deformable templates using large deformation kinematics. Image Processing, IEEE Transactions on, 5(10):1435-1447, 1996.
- [14] Joshi S, Lorenzen P, Gerig G, and Bullitt E, Structural and radiometric asymmetry in brain images. *Med Image Anal*, 7(2):155-170, 2003.
- [15] Neter, J, Wasserman, W, Kutner, MH. Applied Linear Statistical Models: Regression, Analysis of Variance, and Experimental Designs,  3rd edition. Richard d Irwin Publishing. 1990.
- [16] Kamman RL, Go KG, Brouwer WH, Berendsen JC. Nuclear magnetic resonance relaxation in experimental brain edema: Effects of water concentration, protein concentration, and temperature. *Med. Reson. Med.* 6 (3): 265-274, 1988.

- Literatures