Increased slow diffusion in cortical gray matter is related with cognitive decline in severe white matter hyperintensity
Yerfan Jiaerken1, Xinfeng Yu1, and Minming Zhang1

1Radiology, The second affiliated hospital of Zhejiang university school of medicine, Hangzhou, China, People's Republic of

Synopsis

We used MRI IVIM technique to investigate how is microstructure in cortical gray matter (CGM) affected by white matter hyperintensity (WMH), and how does it affect cognitive function. We found that diffusion in WMH is correlated with diffusion in CGM. And diffusion in CGM is connected with cognitive state, while diffusion in WMH isn’t. This may suggest that CGM damage is secondary to microstructural damage in WMH. And CGM damage may lead to cognitive dysfunction, while WMH can only affect cognitive state by damaging gray matter.

Purpose

White matter hyperintensity (WMH) is highly prevalent in the elderly and is a risk factor of cognitive decline. Recent report have shown that WMH volume is not correlated with cognitive function.1 But gray matter is correlated with cognitive decline. And previous studies have found that cortical thickness is affected by WMH.2 Therefore in the present study, we utilized the IVIM technique to examine the microstrucatural and microcircular changes in cortical gray matter (CGM) and to test the hypothesis that increased CGM damage is associated with severe WMH, and is correlated with cognitive decline.

Methods

40 subjects with different degrees of WMH were enrolled in our study. MMSE data was obtained from 21 of the patients by trained neurologist. We gathered 3DT1, T2FLAIR and IVIM image data from each subject. 3DT1 and T2FLAIR image were used to automatically create WMH ROI and CGM ROI. (Fig. 1) Automatically created ROIs were further corrected by trained neuro-radiologist. IVIM images were processed and D maps and f maps were obtained. We used WMH ROI and CGM ROI to extract average diffusion parameter D and perfusion parameter f from corresponding regions. Visual ranking of WMH severity based on T2FLAIR image was performed by a trained radiologist. A modified Fazekas ranking was used, and we combined periventricular score and deep white matter score, resulting a total score ranging from 0~6. Subjects were further grouped based on their ranking (≤3:mild WMH group;>3: severe WMH group). Student-t test was performed to test the differences of D or f parameter in CGM. Pearson correlation was performed to determine the correlation between parameters in CGM and WMH region, as well as correlation between MMSE ranking and MRI parameters.

Results

No significant difference of D or f in CGM area between mild and severe group was found, but there was a trend of increased D in CGM of severe WMH group over mild group. Significant correlation was found between the diffusion parameters D in CGM and D in WMH area in the severe WMH group (R=0.640, P=0.001, Fig 2A). While in the mild WMH group, no correlation between D in CGM and WMH area was found. And the perfusion fraction parameter f in CGM was not correlated with f parameters in WMH area in any group. We also found that MMSE ranking was significantly correlated with D parameter in CGM only in severe WMH group(R=-0.656, P=0.011, Fig 2B), While D in WMH was not correlated with MMSE ranking in any group.

Discussions and Conclusions

In the present study, we found that microstructural disruption in CGM is associated with microstructural damage in white matter, and this correlation was significant only in the severe WMH group. It has been reported that axonal damage in white matter can causes degeneration in the proximal neuron (dying-back), and may lead to neuron body damage and gray matter atrophy.3 No correlation found between the diffusion in CGM and WMH in the mild WMH group may further strengthen the point that damage in gray matter may be secondary only to severe white matter damage. We also found that microstructural disruption in CGM is correlated with cognitive state in severe WMH group. Cellular architecture and connection between cerebral cortex regions established a network, neuron activity in this network may have created cognition.4 Therefore it is no surprise that disruption in cortical microstructure would affect cognitive state. On the other hand, WMH diffusion is not correlated with cognitive state. This may suggest that white matter doesn’t directly affect cognitive state. But WMH may affect cognitive ability by first affecting CGM. Through this study, we confirmed that microstructural damage in CGM is connected with damage in severe WMH, and cognitive dysfunction is directly connected with damage in CGM rather than WMH.

Acknowledgements

No acknowledgement found.

References

1. Tuladhar AM, Reid AT, Shumskaya E, de Laat KF, van Norden AG, van Dijk EJ, Norris DG, de Leeuw FE. Relationship between white matter hyperintensities, cortical thickness, and cognition. Stroke. 2015 Feb;46(2):425-32.

2. Seo SW, Lee JM, Im K, Park JS, Kim SH, Kim ST, Ahn HJ, Chin J, Cheong HK, Weiner MW, Na DL. Cortical thinning related to periventricular and deep white matter hyperintensities. Neurobiol Aging. 2012 Jul;33(7):1156-67.

3. Siffrin V, Vogt J, Radbruch H, Nitsch R, Zipp F. Multiple sclerosis - candidate mechanisms underlying CNS atrophy. Trends Neurosci. 2010 Apr;33(4):202-10. 4 Young VG, Halliday GM, Kril JJ. Neuropathologic correlates of white matter hyperintensities. Neurology. 2008 Sep 9;71(11):804-11.

4. Bota M, Sporns O, Swanson LW. Architecture of the cerebral cortical association connectome underlying cognition. Proc Natl Acad Sci U S A. 2015 Apr 21;112(16):E2093-101.

Figures

Fig.1 Showing 3DT1 and T2FLAIR imagine of a subject. WMH is visible on T2FLAIR imagine. 3 ROIs were created automatically based on 3DT1 and T2FLAIR image: cortical gray matter (red area), normal white matter (green area) and white matter hyperintensity (Blue area).

Fig 2.Dotted graph of A), correlation of D in white matter hyperintensity and D in cortical gray matter; B), correlation of D in cortical gray matter and MMSE.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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