CEST Metrics for Assessing Early Response to Stereotactic Radiosurgery in Human Brain Metastases
Kimberly L. Desmond1,2, Hatef Mehrabian1,2, Arjun Sahgal1,3, Hany Soliman1,3, and Greg J. Stanisz1,2

1Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada, 2Medical Biophysics, University of Toronto, Toronto, ON, Canada, 3Radiation Oncology, Odette Cancer Centre, Toronto, ON, Canada

Synopsis

Chemical exchange saturation transfer (CEST) spectra were collected at three timepoints following stereotactic radiosurgery (SRS). The magnetization transfer ratio (MTR) and CEST peak properties were evaluated at the offset frequencies of the NOE, amide and amine pools in the lesion and in the surrounding tissue. Positive correlation was found between changes in NOE peak amplitude and amide MTR at 1 week post-therapy and tumour volume change at one month post-therapy, while negative correlation was found between amide peak width and NOE peak amplitude at the pre-treatment timepoint with volume change at one month post-therapy (p<0.1).

Introduction

Stereotactic radiosurgery (SRS) is common for the management of brain metastases. It is a localized treatment which has led to increased patient survival [1] and reduced side-effects, but volume changes may not manifest for months. Chemical exchange saturation transfer (CEST) shows great promise for improving the characterization of brain tumours and their response to therapy [2-10]. Our objective was to assess the utility of CEST metrics in characterizing the tumour response to SRS. To limit a priori assumptions about which feature of CEST might be sensitive to therapy, a CEST spectrum was collected at equally spaced frequency offsets. This study explores not only whether CEST changes correlate with the change in tumour volume, but whether CEST imaging at early time-points is predictive of future growth or regression of the tumour.

Methods

The CEST spectrum was approximated by five pools: "magnetization transfer" (broad lineshape at 0 ppm), "bulk water" (0 ppm), "amide" (3.5ppm), "amine" (2ppm), and "NOE" (-3.5ppm). Two groups of CEST metrics were considered for each CEST peak:

1) The magnetization transfer ratio (MTR) evaluated at the frequency of the pool:

$$MTR\left(\Delta\right)=\frac{S_{ref} -S(\Delta)}{S_{ref}}$$

2) The peak amplitude of each CEST effect (with amplitude “A”, width “w”, and offset frequency “Δ0”) from a Lorentzian decomposition of the CEST spectrum:

$$S(\Delta) = 1 - \sum_{i=1}^5A_i\left(1 + \left(\frac{\Delta-\Delta_{0i}}{0.5*w_i}\right)^2\right)^{-1}$$

20 patients with brain metastases were scanned on a 3T Philips Achieva at three time-points: pre-treatment, one week and one month post-therapy. CEST imaging was optimized to be sensitive to small changes in the CEST pool. Image acquisition: 2D, single-shot gradient echo EPI (FE-EPI), TR: 1532ms, effTE = 30ms, resolution: 2.5mm, slice thickness: 3mm. Saturation scheme: 750ms block pulse, 0.52µT, preceding EPI. Offset frequencies: -750 to 750 Hz with reference at 100,000 Hz. Averages: 5, Total Scan Time: 12 minutes. Post-Gd T1-weighted images were used as a reference to define ROIs in enhancing tumour, and ipsilateral normal-appearing white matter (iNAWM). The mean MTR was calculated over the ROI at three different offset frequencies: the amide, amine and NOE peak offsets. CEST peakfit metrics were determined for each voxel, then averaged over the ROI with a partial-volume correction [12].

Results and Discussion:

MTR metrics offered the best discrimination between tumour and adjacent white matter at the pre-treatment time-point (Fig. 1). Except for the amide and amine peak amplitude, metrics were all higher in the iNAWM.

Predictive factors were identified by comparing CEST changes between pre-treatment and one week with volume changes between pre-treatment and one month. Several significant trends were observed (Fig. 2), including a positive correlation between volume and Amide MTR (R=0.50, p=0.085) in tumour. This corroborates research that shows cell lines which are responsive to radiation have a reduced APT effect [2] after treatment, and that the APT of apoptotic/necrotic tissue is reduced [13]. Decrease in NOE peak amplitude in the iNAWM at one week was also correlated (R=0.73, p=0.0048) with volume reduction at one month. One theory is that if NOE can be considered correlated with cell proliferation rate, then this reflects radiosensitivity of the iNAWM, and possibly by extension, the tumour[14]. No significant correlation was observed between the change in T1 after one week and the volume changes at one month.

Prognostic factors were also identified by comparing the pre-treatment CEST metrics to the volume changes at one month, including MT amplitude in tumour (R=-0.5, p=0.094), and NOE amplitude (R=-0.64, p=0.0180), amide width (R=-0.57, p=0.042) and NOE MTR (R=-0.51, p=0.080) in iNAWM (Fig. 3). Interestingly, the correlation was greater in the iNAWM than within the tumour. This is likely a consequence of the iNAWM ROIs being larger and more homogeneous, forming a much more consistent baseline upon which to assess altered metabolism [15]. Conclusion: Early CEST metric increases in either tumour or the surrounding iNAWM following SRS correlated with future tumour expansion. At the pre-treatment stage, low MT amplitude in tumour, or low NOE amplitude or MTR in iNAWM correlated with worse outcome at one month, which could be investigated as a biomarker for poor response to SRS or vulnerability to future metastases.

Conclusions

Early CEST metric increases in either tumour or the surrounding iNAWM following SRS correlated with future tumour expansion. At the pre-treatment stage, low MT amplitude in tumour, or low NOE amplitude or MTR in iNAWM correlated with worse outcome at one month, which could be investigated as a biomarker for poor response to SRS or vulnerability to future metastases.

Acknowledgements

This research was supported by grants from the Terry Fox Research Institute, the Canadian Cancer Society Research Innovation and Canadian Institute of Health Research.

References

1. Linskey, M.E., et al., The role of stereotactic radiosurgery in the management of patients with newly diagnosed brain metastases: a systematic review and evidence-based clinical practice guideline. Journal of Neuro-Oncology, 2010. 96(1): p. 45-68.
2. Sagiyama, K., et al., In vivo chemical exchange saturation transfer imaging allows early detection of a therapeutic response in glioblastoma. Proceedings of the National Academy of Sciences, 2014. 111(12): p. 4542-4547.
3. Dula, A.N., et al., Amide proton transfer imaging of the breast at 3 T: establishing reproducibility and possible feasibility assessing chemotherapy response. Magnetic Resonance in Medicine, 2013. 70(1): p. 216-224.
4. Paech, D., et al., Nuclear Overhauser Enhancement Imaging of Glioblastoma at 7 Tesla: Region Specific Correlation with Apparent Diffusion Coefficient and Histology. PLoS ONE, 2014. 10(3): p. e0121220-e0121220.
5. Sun, P.Z. and A.G. Sorensen, Imaging pH using the chemical exchange saturation transfer (CEST) MRI: correction of concomitant RF irradiation effects to quantify CEST MRI for chemical exchange rate and pH. Magnetic Resonance in Medicine, 2008. 60(2): p. 390-397.
6. Zhou, J., et al., Using the amide proton signals of intracellular proteins and peptides to detect pH effects in MRI. Nat Med, 2003. 9(8): p. 1085-90.
7. Togao, O., et al., Amide proton transfer imaging of adult diffuse gliomas: correlation with histopathological grades. Neuro-oncology, 2014. 16(3): p. 441-448.
8. Wen, Z., et al., MR imaging of high-grade brain tumors using endogenous protein and peptide-based contrast. NeuroImage, 2010. 51(2): p. 616-622.
9. Jia, G., et al., Amide proton transfer MR imaging of prostate cancer: a preliminary study. Journal of Magnetic Resonance Imaging, 2011. 33(3): p. 647-654.
10. Salhotra, A., et al., Amide proton transfer imaging of 9L gliosarcoma and human glioblastoma xenografts. Nmr in Biomedicine, 2008. 21(5): p. 489-497.
11. Heinrich, M.P., et al., MIND: Modality independent neighbourhood descriptor for multi-modal deformable registration. Medical Image Analysis, 2012. 16(7): p. 1423-1435.
12. Hofheinz, F., et al., A method for model-free partial volume correction in oncological PET. EJNMMI research, 2012. 2(1): p. 1-12.
13. Desmond, K.L., F. Moosvi, and G.J. Stanisz, Mapping of amide, amine, and aliphatic peaks in the CEST spectra of murine xenografts at 7 T. Magnetic Resonance in Medicine, 2014. 71(5): p. 1841-1853.
14. Tucker, S.L., et al., How much could the radiotherapy dose be altered for individual patients based on a predictive assay of normal-tissue radiosensitivity? Radiotherapy and Oncology, 1996. 38(2): p. 103-113.
15. Steeg, P.S., K.A. Camphausen, and Q.R. Smith, Brain metastases as preventive and therapeutic targets. Nature Reviews Cancer, 2011. 11(5): p. 352-363.

Figures

Figure 1. Average ROI values at pre-treatment expressed as percent of the reference signal. All pairs are significantly different by the Wilcoxon rank sum test at p < 0.001 except for the amide peak amp. (p = 0.01) and amine peak amp. (p = 0.08)

Figure 2. Scatter plots detailing significant correlations uncovered between changes in CEST metrics between pre-treatment and the 1 week time-point and volume changes at 1 month time-point. Patient ID is in square brackets, blue triangle for responder and stable disease, red square for non-responder.

Figure 3. Scatter plots detailing significant correlations between CEST metrics at the pre-treatment time-point, and volume changes at one month post-treatment. Patient ID is in square brackets, blue triangle for responder and stable disease, red square for non-responder.



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