Gray Matter Alterations Using Voxel-Based Morphometry May Not Reflect Changes In Morphometry: A Study of Mild Traumatic Brain Injury
Sohae Chung1,2, Yadi Li3, Jacqueline Smith1,2, Steven R Flanagan4, and Yvonne W Lui1,2

1Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States, 2Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States, 3Department of Radiology, The Affiliated Ningbo Medical Treatment Center Lihuili Hospital of Ningbo University, Zhejiang, China, People's Republic of, 4Department of Rehabilitation Medicine, New York University Langone Medical Center, New York, NY, United States

Synopsis

Voxel-based morphometry (VBM) analysis has been used to detect morphometric changes of the GM after mild traumatic brain injury (mTBI). Spatially normalized and modulated GM density from VBM analysis is typically interpreted as GM volume. VBM is, however, sensitive not only to changes in volume but to variations in T1 relaxation. In this study, we investigated alterations in GM density using simulated images and VBM followed by an in vivo study of cortical GM morphometry using GM density and cortical thickness in mTBI patients and matched controls.

Purpose

Mild traumatic brain injury (mTBI) is a growing public health problem, which represents more than 80% of all traumatic brain injury. However, our understanding of the underlying pathophysiology associated with mTBI is limited. A few studies using voxel-based morphometry (VBM)1 show morphometric changes to the GM after mTBI2. Spatially normalized and modulated GM density from VBM analysis is typically interpreted as GM volume with a decrease in density equated with atrophy and an increase in density equated with GM thickening2,3. VBM is, however, sensitive not only to changes in volume but to variations in T1 relaxation4. In this study, we investigated alterations in GM density using simulated images and VBM followed by an in vivo study of cortical GM morphometry using GM density and cortical thickness in mTBI patients and matched controls.

Methods

Simulation: Effect of altering T1 relaxation on VBM GM density was studied by using simulated images from a representative T1 weighted image (T1WI) of a normal individual (25 year old man). 40% of voxels within a frontal opercular region of interest (ROI) (total 833 voxels through 7 slices) were selected for simulation (Fig. 2 (top)). Hyperintense voxels were simulated via increasing voxel signal intensity by 5%-20% whereas hypointense lesions were simulated via decreasing intensity by 5-20% (Fig.2 (top)). Human Subjects: We studied 17 patients with mTBI within two weeks of injury (age, 34.4±9.5; 21-52 years old) and 14 age- and sex-matched normal controls (NC) (age, 33.8±9.6; 19-50 years old). MRI Acquisition: MR imaging was performed on 3T MR scanner (Skyra; Siemens). 3D MP-RAGE acquisition was performed to obtain structural T1WI (FOV = 256 × 256 mm2, matrix = 256 × 256, resolution = 1 × 1 × 1 mm3, slices = 192, TR/TE/TI = 2100/3.19/900 ms, FA = 8°, and bandwidth = 260 Hz/pixel). Image Analyses: FSL-VBM5 carried out with FSL tools was used to assess GM density changes. All data underwent noise reduction, brain-extraction, segmentation, registration, modulation and smoothness. Regional cortical thickness was estimated using FreeSurfer6,7 and the results were visually inspected and manually corrected by an expert neuroradiologist.

Results

In Fig.1, GM/modulated GM densities were higher in the hyperintense regions, while they were lower in the hypointense regions. We found that the cortical boundaries of the simulated lesions were almost identical as shown in Fig. 2 (bottom). Fig.2 presents the VBM results showing comparisons between NC and mTBI. We found three clusters having significantly decreased modulated GM densities in mTBI (p < 0.001; shown in red-yellow; > 350 voxels): right precuneus (cluster 1), left superior temporal (cluster 2), and left precentral regions (cluster 3). The mean values of modulated GM densities for the NC and mTBI groups were 0.50 ± 0.054 and 0.40 ± 0.051 in cluster 1, 0.56 ± 0.083 and 0.45 ± 0.03 in cluster 2, and 0.54 ± 0.054 and 0.45 ± 0.048 in cluster 3, respectively. However, we found no significant differences in cortical thickness and GM volume from FreeSurfer between NC and mTBI groups.

Discussion

In this study, which used both VBM and cortical thickness analyses, we demonstrate that changes in VBM results can be sensitive to any alterations in the GM composition after mTBI, as opposed to the volume of GM. We observed: 1) decreased GM/modulated GM densities in mTBI within three regions (right precuneus, left posterior superior temporal gyrus, left precentral gyrus); and 2) no significant differences in cortical thickness in these regions. Absence of cortical thickness changes in the setting of positive VBM findings, raises the possibility that differences in GM volume may not be the cause of this finding. As our simulation results demonstrate, a measured decrease in GM density can be due to changes in signal intensity within the region. Decreases in signal intensity without concomitant changes in GM volume, may arise in a variety of situations such as gliosis, resolving edema such as in the case of subacute infarction, as well as areas of hyperacute and acute hemorrhage (oxy- and deoxyhemoglobin).

Conclusion

This study indicates that used together, VBM and cortical thickness analyses can provide greater detail regarding GM changes. Detecting and understanding GM injury after mTBI is critical for further investigating the mechanisms of tissue damage and recovery. Focal changes in GM density as detected by VBM analysis may represent areas of signal changes rather than true volume change, particularly in the setting of maintained cortical thickness.

Acknowledgements

No acknowledgement found.

References

1. Ashburner J, Friston KJ. Voxel-based morphometry--the methods. Neuroimage. 2000;11(6 Pt 1):805-21.

2. Zhou Y, Kierans A, Kenul D, et al. Mild traumatic brain injury: longitudinal regional brain volume changes. Radiology. 2013;267(3):880-90.

3. Wessels AM, Simsek S, Remijnse PL, et al. Voxel-based morphometry demonstrates reduced grey matter density on brain MRI in patients with diabetic retinopathy. Diabetologia. 2006;49(10):2474-80.

4. Kong L, Herold CJ, Zollner F, et al. Comparison of grey matter volume and thickness for analysing cortical changes in chronic schizophrenia: a matter of surface area, grey/white matter intensity contrast, and curvature. Psychiatry Res. 2015;231(2):176-83.

5. Douaud G, Smith S, Jenkinson M, et al. Anatomically related grey and white matter abnormalities in adolescent-onset schizophrenia. Brain. 2007;130(Pt 9):2375-86.

6. Dale AM, Fischl B, Sereno MI. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage. 1999;9(2):179-94.

7. Fischl B, Sereno MI, Dale AM. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage. 1999;9(2):195-207.

Figures

Figure 1. (Top) Simulated T1WI hypo/hyperintense brain lesions via increasing/decreasing image intensities by 5-20%. (Middle) Image intensity, GM density, and modulated GM density within the ROI. (Bottom) Cortical boundaries overlaid on the corresponding T1WI in FreeSurfer space.

Figure 2. VBM results showing comparisons between NC and mTBI groups: cluster 1 - right precuneus; cluster 2 - left superior temporal; cluster 3 - left precentral regions (p < 0.05 for all clusters).



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