Volumetric analysis of structural brain changes in acute and sub-acute mild traumatic brain injury
Tianhao Zhang1, Sumit Niogi2, John A. Tsiouris2, Luca Marinelli3, and Teena Shetty4

1GE Healthcare, Waukesha, WI, United States, 2Weill Cornell Medical Center, New York, NY, United States, 3GE Global Research, Niskayuna, NY, United States, 4Hospital for Special Surgery, New York, NY, United States

Synopsis

Mild traumatic brain injury (mTBI) is a heterogeneous disease with a variety of symptoms associated with brain function alterations after the trauma. There is still limited understanding of the relationship between physiological and structural changes and recovery rate. In this work, we aim to identify structural brain changes in a mTBI population at 4 time points. The analysis is in two folds: 1) correlation analysis between brain volumes and clinical scores; and 2) longitudinal analysis across different encounters. The results revealed significant brain volume changes over time, and at 3 months post-injury, volumes demonstrated significant negative correlations with clinical scores.

Purpose

Mild traumatic brain injury (mTBI) is a heterogeneous disease with a wide variety of clinical symptomatology associated with physiological alteration of brain function after the trauma. Recovery time is also widely variable and while many mTBI subjects are symptom free in 1-2 weeks, part of the mTBI population can suffer from neurological symptoms that significantly affect quality of life for several months. There is still limited understanding of the relationship between physiological and structural change in brain structures and rate of recovery from symptoms or outcomes.1 In this work, we aim to identify structural signatures in sub-cortical gray matter and their relationship to alteration of brain physiology on the path to recovery in a mTBI population at 4 encounters (3 days to 3 months post-injury). We conduct two separate analyses: 1) correlation analysis between brain volumes and clinical symptoms at each encounter; and 2) longitudinal analysis of brain volumes across multiple encounters.

Method

T1-weighted images with 1mm isotropic resolution (MPRAGE2) were acquired using a GE 3T Signa MR750 scaner and a 32 channel brain coil (Nova Medical) on 78 uncomplicated mTBI subjects at four encounters: 3 days (32 subjects), 7 days (61 subjects), 1 month (56 subjects), and 3 months (42 subjects) post injury, and 23 controls (scanned twice, one week apart). The images were preprocessed (skull stripping using ROBEX3, bias/inhomogeneity correction using N44, registration of labeled atlas images using ANTs5) and subcortical gray matter segmented using a deformable atlas method.6,7 The segmented brain structures (illustrated in Figure 1) were further corrected for the effects of i) sex, ii) age, iii) education, and iv) handedness, using multiple linear regression model.8 Subjects were also evaluated by an experienced neurologist (TS) at each encounter and the symptom burden (22 symptoms on 0-6 scale9, total score 0-124) recorded. Based on the data, two different analyses were conducted: 1) Correlation analysis: the Pearson correlation coefficient was calculated between volume of brain structures and clinical symptoms at each encounter; 2) Longitudinal analysis: volume changes at multiple time points were studied with the one tail paired t-test.

Results

For the correlation analysis, no significant correlations were found between brain volumes and symptom scores at encounters 1-3 (E1-E3), while significant (p<0.05) negative correlations were found at encounter 4 (E4) between clinical scores and whole brain, supratentorial, and left/right thalamus volumes. Figure 2 demonstrated the significance levels for all the brain structures and Figure 3 illustrates the Pearson correlations. For the longitudinal analysis, we find significant reduction in volume of mTBI patients in the left thalamus (E2>E4, p<0.01) and left hippocampus (E2>E4, p<0.05) in the patient population. Supratentorial brain volume increased significantly between early and late encounters (E1<E4, p<0.05; E2<E4, p<0.01). Figure 4 shows the effect sizes of the paired differences between encounters, corresponding to the significant structures. There are no significant longitudinal changes between encounters 1 and 2 of controls.

Conclusions

A longitudinal MRI study based on volumetric analysis was conducted to investigate the structural brain changes in a mild TBI population. The results of this study showed significant volume changes between the acute and sub-acute time points, and, at 3 months post-injury, volumes of the thalamus and whole brain were significantly anti-correlated with clinical symptom scores.

Acknowledgements

No acknowledgement found.

References

1. Zagorchev L, Meyer C, Stehle T, et al. Differences in Regional Brain Volumes Two Months and One Year after Mild Traumatic Brain Injury. Journal of neurotrauma 2015; ahead of print. doi:10.1089/neu.2014.3831.

2. Mugler JP, Brookeman JR. Three-dimensional magnetization-prepared rapid gradient-echo imaging (3D MP RAGE). Magnetic Resonance in Medicine 1990;15(1):152-157.

3. Iglesias JE, Liu CY, Thompson PM, Tu Z. Robust brain extraction across datasets and comparison with publicly available methods. IEEE Transactions on Medical Imaging 2011;30(9):1617-1634.

4. Tustison NJ, Avants BB, Cook P, et al. N4ITK: improved N3 bias correction. IEEE Transactions on Medical Imaging 2010;29(6):1310-1320.

5. Avants B, Gee JC. Geodesic estimation for large deformation anatomical shape averaging and interpolation. NeuroImage 2004;23:S139-S150.

6. Liu X, Montillo A, Tan ET, et al. Deformable Atlas for Multi-structure Segmentation. In Medical Image Computing and Computer-Assisted Intervention 2013:743-750.

7. Worth AJ. The Internet brain segmentation repository (IBSR). 1996: http://www.cma.mgh.harvard.edu/ibsr.

8. Kiebel SJ, Holmes AP. The general linear model. Academic Press. 2003.

9. McCrory P, Meeuwisse W, Johnston K, et al. SCAT2. British Journal of Sports Medicine 2009;43(Suppl. 1): i85-i88.

Figures

Figure 1. An example of multiple brain structure segmentation. A) The original T1-weighted image; B) The segmented brain structures, indicated by different colors.

Figure 2. The significance levels of different brain structures in correlation analysis of encounter 4.

Figure 3. Correlations between brain volumes (mm3) and symptom scores at encounter 4. r indicates the Pearson correlation; red line indicated the best linear fit.

Figure 4. Effect sizes of the paired differences between encounters, corresponding to the significant structures in the longitudinal analysis. d indicates the Cohen’s d effect size. A) Brain volumes decreasing; B) Brain volume increasing.



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