Motion Range Grouping of Brain Regions Based on Displacement Measured with Displacement Encoding with Stimulated Echoes (DENSE)
Xiaodong Zhong1, Tucker Lancaster2, Zihan Ye3, Deqiang Qiu2, Brian M. Dale4, John N. Oshinski2,3, and Amit Saindane2

1MR R&D Collaborations, Siemens Healthcare, Atlanta, GA, United States, 2Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, United States, 3Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, United States, 4MR R&D Collaborations, Siemens Healthcare, Cary, NC, United States

Synopsis

In this work, we demonstrated that the DENSE technique can be used to measure and group motion of different brain regions. Preliminary results in 9 volunteers showed that the brain regions near the CSF (midbrain, pons, medulla and optic chiasm) had larger motion magnitude than regions far away (frontal lobe, occipital lobe, parietal lobe and cerebellum). DENSE enables us to investigate brain motion to a level of detail that has not been previously possible. The findings in this study may bring new insight into brain motion and provide useful information to improve potential imaging and therapy techniques.

Background and Purpose

The periodic volume changes accompanying the arterial blood entering the brain cause a periodic brain motion, which in turn creates a pulsatile component in the cerebrospinal fluid (CSF) flow1-4. As the mechanical link between blood and CSF, the degree of brain motion may serve as a biomarker for some neuropathologies. In addition, the ability to accurately characterize brain motion helps increase our understanding of the magnitude of these motion effects, and improve imaging techniques and therapies sensitive to motion such as diffusion imaging5 and stereotactic radiosurgery (SRS) treatment6.

Displacement encoding with stimulated echoes (DENSE) is a motion imaging technique that encodes pixel-wise tissue displacements into the phase of the stimulated echoes7,8. DENSE is well suited for measuring small displacements, and has been applied to measure brain motion as low as 0.01 mm9,10. Previous studies showed different motion magnitude of brain regions9,10, but to our knowledge, no motion range grouping has been attempted. In this study, we took advantage of the high motion sensitivity of DENSE to quantify the displacements of different brain regions, and hypothesized that the brain regions near the CSF had larger motion magnitude than regions far away.

Method

Approved by our IRB, after informed consent was obtained, 9 healthy volunteers (33.7 ± 11.0 years, two females) were scanned on a 3T scanner with the head and neck coils (Tim Trio, Siemens, Erlangen, Germany). Each subject was in the supine position with simple immobilization buffers around the head. A mid-sagittal slice through the cervical cord and brain stem was imaged with a customized, pulse-gated, segmented EPI, cine DENSE sequence. Image parameters included displacement encoding frequency ke = 1.5 cycle/mm, through-plane dephasing frequency kd = 0.08 cycle/mm, TE = 8.9-10.4 ms, TR = 55-59 ms, EPI factor = 8, segments = 16, pixel size = 1.2 × 1.2 mm2, slice thickness = 7 mm, averages = 4, frames = 13-16, where parameter variations depended on the pulse durations. The subjects were instructed to remain motionless during the scan.

The DENSE images were reconstructed inline to generate DICOM images with displacement encoded in two orthogonal directions11, and then these images were exported for offline processing using ImageJ (National Institute of Health, Bethesda, MD, USA). Briefly, the phase-reconstructed image in each direction was divided by 2πke to convert to displacement, and then the 2D displacement map was obtained by combining data in two directions. Regions of interest (ROIs) were placed in frontal lobe, occipital lobe, parietal lobe, cerebellum, midbrain, pons, medulla and optic chiasm, respectively. The mean 2D displacement values in the ROIs for each frame were recorded for all 9 volunteers, and fitted using a 3rd or 4th order polynomial in Matlab (The Mathworks, Natick, MA, USA) to compensate for varying temporal resolutions in the acquired data. An analysis of variance (ANOVA) was performed using R v3.2 (R Core Team, Vienna, Austria) to test and group displacement as a function of brain regions. Post-hoc comparisons were performed using Tukey’s HSD to adjust for multiple comparisons.

Results

Example DENSE magnitude-reconstructed image with the ROIs and their grouping letters (explained later) are shown in Fig 1. Example 2D displacement maps at several time points after the pulse triggering are shown in Fig. 2. Fig. 3 shows the fitted displacement-time curves from 9 volunteers. And Fig. 4 summarizes and groups the peak displacement averaged across the 9 volunteers. ANOVA found that the model was highly significant (p < 0.0001). The post-hoc comparisons identified 3 overlapping groups of locations with respect to peak displacement with group “a” having the least displacement and group “c” having the most. In general, the brain regions near the CSF (midbrain, pons, medulla and optic chiasm) had larger motion magnitude than regions far away (frontal lobe, occipital lobe, parietal lobe and cerebellum). These were consistent with our observations in both Fig. 2 and Fig. 3.

Conclusion

In this work, we have demonstrated that the DENSE technique can be used to measure and group motion of different brain regions. Preliminary results in 9 volunteers showed that the brain regions near the CSF (midbrain, pons, medulla and optic chiasm) had larger motion magnitude than regions far away (frontal lobe, occipital lobe, parietal lobe and cerebellum). DENSE enables us to investigate brain motion to a level of detail that has not been previously possible. The findings in this study may bring new insight into brain motion and provide useful information to improve potential imaging and therapy techniques.

Acknowledgements

No acknowledgement found.

References

1. Alperin N, Vikingstad EM, Gomez-Anson B, Levin DN. Hemodynamically independent analysis of cerebrospinal fluid and brain motion observed with dynamic phase contrast MRI. Magn Reson Med 1996;35:741-754.

2. Chu D, Levin DN, Alperin N. Assessment of the biomechanical state of intracranial tissues by dynamic MRI of cerebrospinal fluid pulsations: a phantom study. Magn Reson Imaging 1998;16:1043-1048.

3. Feinberg DA, Mark AS. Human brain motion and cerebrospinal fluid circulation demonstrated with MR velocity imaging. Radiology 1987;163:793-799.

4. Figley CR, Stroman PW. Investigation of human cervical and upper thoracic spinal cord motion: implications for imaging spinal cord structure and function. Magn Reson Med 2007;58:185-189.

5. Kharbanda HS, Alsop DC, Anderson AW, Filardo G, Hackney DB. Effects of cord motion on diffusion imaging of the spinal cord. Magn Reson Med 2006;56:334-339.

6. Lawrence SC, William FR. Principles and practice of stereotactic radiosurgery. Springer. 2008.

7. Aletras AH, Ding S, Balaban RS, Wen H. DENSE: displacement encoding with stimulated echoes in cardiac functional MRI. J Magn Reson 1999;137:247-252.

8. Kim D, Gilson WD, Kramer CM, Epstein FH. Myocardial tissue tracking with two-dimensional cine displacement-encoded MR imaging: development and initial evaluation. Radiology 2004;230:862-871.

9. Zhong X, Meyer CH, David JS, Sheehan JP, Epstein FH, Larner JM, Benedict SH, Read PW, Sheng K, Cai J. Tracking brain motion during the cardiac cycle using spiral cine-DENSE MRI. Med Phys 2009;36:3413-3419.

10. Soellinger M, Rutz AK, Kozerke S, Boesiger P. 3D cine displacement-encoded MRI of pulsatile brain motion. Magn Reson Med 2009;61:153-162.

11. Spottiswoode BS, Zhong X, Hess AT, Kramer CM, Meintjes EM, Mayosi BM, Epstein FH. Tracking myocardial motion from cine DENSE images using spatiotemporal phase unwrapping and temporal fitting. IEEE Trans Med Imaging 2007;26:15-30.

Figures

Fig. 1 Example DENSE magnitude-reconstructed images with the ROIs of different brain regions and the corresponding grouping letters (see Fig. 4).

Fig. 2 Example 2D displacement maps at several time points after the pulse triggering.

Fig. 3 The fitted displacement-time curves using the data from 9 volunteers.

Fig. 4 Peak displacement of all ROIs averaged across the 9 volunteers and the corresponding grouping letters.



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