Volume 81, Issue 1 pp. 208-219

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Toward more reliable measurements of NOE effects in CEST spectra at around −1.6 ppm (NOE (−1.6)) in rat brain

Zhongliang Zu,

Corresponding Author

Zhongliang Zu

[email protected]

orcid.org/0000-0001-7361-7480

Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee

Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee

Correspondence

Zhongliang Zu, Vanderbilt University Institute of Imaging Science, 1161 21st Ave. S, Medical Center North, AAA-3112, Nashville, TN 37232-2310.

Email: [email protected]

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Zhongliang Zu,

Corresponding Author

Zhongliang Zu

[email protected]

orcid.org/0000-0001-7361-7480

Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee

Department of Radiology and Radiological Sciences, Vanderbilt University, Nashville, Tennessee

Correspondence

Zhongliang Zu, Vanderbilt University Institute of Imaging Science, 1161 21st Ave. S, Medical Center North, AAA-3112, Nashville, TN 37232-2310.

Email: [email protected]

Search for more papers by this author

First published: 29 July 2018

https://doi.org/10.1002/mrm.27370

Citations: 26

Funding information: National Institutes of Health, Grant/Award number: EB017873

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Abstract

Purpose

Recently, a new relayed nuclear Overhauser enhancement (NOE) saturation transfer effect at around −1.6 parts per million, termed NOE(−1.6), and its potential applications in tumor and stroke were reported by several institutes. However, there is a concern of the reproducibility of NOE(−1.6) measurements because it is not reported by many other publications. This paper aims to study the influence of typically overlooked experimental settings on the NOE(−1.6) signal and to build a framework for more reliable measurements of NOE(−1.6) at 9.4T.

Methods

Z-spectra were obtained in rat brains. A fitting approach was performed to quantify all known saturation transfer effects except NOE(−1.6). Residual signals were obtained by removing these confounding effects from Z-spectra and were then used to quantify NOE(−1.6). Multislice imaging was performed to study the NOE(−1.6) dependence on brain regions. The influences of euthanasia, anesthesia, breathing gases, and RF irradiation power were also evaluated.

Results

Results demonstrate that the NOE(−1.6) signal contributions are often not clearly observable in raw Z-spectra at relatively high irradiation powers due to, for example, the direct water saturation effect, but they can be visualized after removing other nonspecific effects. In addition, the NOE(−1.6) effect depends on brain region, decreases postmortem, shifts after long-duration anesthesia, and may be enhanced by increasing O₂ and N₂O breathing air concentrations.

Conclusion

Because the NOE(−1.6) effect is more susceptible to the direct water saturation effect and more sensitive to physiological conditions than are other CEST effects, incorporating known sensitivities into the experimental design and data analysis is necessary to ensure more reliable NOE(−1.6) results.

Supporting Information

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Description

mrm27370-sup-0001-SupInfo.pdfPDF document, 309.9 KB

FIGURE S1. Axial images of anatomy (a), R_1obs (b), f_m (c), amide (d), amine (e), NOE(-1.6) (f), and NOE(-3.5) (g) from different slices of a representative rat brain. Images from left to right are from slice #1, #2, #3, and #4, respectively.

FIGURE S2. Simulated Z-spectra and corresponding fitted NOE(-1.6) spectra (dotted line) and NOE(-3.5) spectra (dashed line) from the simulated Z-spectra with a series of solute concentration f_s (a and b), exchanging/coupling rate k_sw (c and d), solute resonance frequency offset (D) (e and f), and water transverse relaxation time (T_2w) (g and h), respectively. Note that the fitted NOE(-1.6) peak depends on f_s, k_sw, D, but not on T_2w. The shift of D changes the magnitude of the fitted NOE(-1.6) peak, but the change is very small. Simulated Z-spectra were created using a seven-pool (amide at 3.5 ppm, fast exchanging amine at 3 ppm, intermediate exchanging amine at 2 ppm, NOE at -1.6 ppm, NOE at -3.5 ppm, semi-solid MT centered at -2.3 ppm, and water at 0 ppm) model mimicking complex biological tissues at 9.4 T. The seven-pool model contains nineteen coupled Bloch equations and can be written as $urn:x-wiley:07403194:media:mrm27370:mrm27370-math-0001$ , where A is a 19 × 19 matrix. The water and solute pools each has three coupled equations representing their x, y, and z components. The semi-solid MT pool has a single coupled equation representing the z component, with a Lorentzian absorption lineshape. f_s, k_sw, Δ, and T_2w were varied individually with all other parameters remaining at the value listed in the following table. T₁ and T₂ represent the longitudinal and transverse relaxation time of each pool.

TABLE S1. Starting points and boundaries of the amplitude (A), width (W), and offset (D) of the exchanging pools in the two-pool model (water and semi-solid MT) Lorentzian fit. The unit of peak width and offset is ppm.

TABLE S2. Starting points and boundaries of the amplitude (A) and width (W) of the exchanging pool in the one-pool model (aliphatic NOE pool centered at -3.5 ppm) Lorentzian fit. Offset (D) of this pool was fixed at -3.5 ppm. The unit of peak width and offset is ppm.

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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Volume81, Issue1

January 2019

Pages 208-219

Toward more reliable measurements of NOE effects in CEST spectra at around −1.6 ppm (NOE (−1.6)) in rat brain

Abstract

Purpose

Methods

Results

Conclusion

Supporting Information

REFERENCES

Citing Literature

References

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Toward more reliable measurements of NOE effects in CEST spectra at around −1.6 ppm (NOE (−1.6)) in rat brain

Abstract

Purpose

Methods

Results

Conclusion

Supporting Information

REFERENCES

Citing Literature

References

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