Prospective acceleration of whole‐brain CEST imaging by golden‐angle view ordering in Cartesian coordinates and joint k‐space and image‐space parallel imaging (KIPI).
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| Title: | Prospective acceleration of whole‐brain CEST imaging by golden‐angle view ordering in Cartesian coordinates and joint k‐space and image‐space parallel imaging (KIPI). |
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| Authors: | Zu, Tao1 (AUTHOR), Yong, Xingwang1 (AUTHOR), Dai, Zhechuan1 (AUTHOR), Jiang, Tongling1 (AUTHOR), Hsu, Yi‐Cheng2 (AUTHOR), Lu, Shanshan3 (AUTHOR), Zhang, Yi1 (AUTHOR) yizhangzju@zju.edu.cn |
| Source: | Magnetic Resonance in Medicine. Apr2025, Vol. 93 Issue 4, p1585-1601. 17p. |
| Subjects: | Cartesian coordinates, Magnetization transfer, In vivo studies, Scanning systems, Protons |
| Abstract: | Purpose: To prospectively accelerate whole‐brain CEST acquisition by joint k‐space and image‐space parallel imaging (KIPI) with a proposed golden‐angle view ordering technique (GAVOT) in Cartesian coordinates. Theory and Methods: The T2‐decay effect will vary across frames with variable acceleration factors (AF) in the prospective acquisition using sequences with long echo trains. The GAVOT method uses a subset strategy to eliminate the T2‐decay inconsistency, where all frames use a subset of shots from the calibration frame to form their k‐space view ordering. The golden‐angle rule is adapted to ensure uniform k‐space coverage for arbitrary AFs in Cartesian coordinates. Phantom and in vivo studies were conducted on a 3 T scanner. Results: The GAVOT view ordering yielded a higher g‐factor than conventional uniformly centric ordering, whereas the noise propagation in amide proton transfer (APT) weighted images was similar between different view ordering. Compared to centric ordering, GAVOT successfully eliminated the T2‐decay inconsistency across all frames, resulting in fewer image artifacts for both KIPI and conventional parallel imaging methods. The synergy of GAVOT and KIPI mitigated strong aliasing artifacts and achieved high‐quality reconstruction of prospective variable‐AF datasets. GAVOT‐KIPI reduced the scan time to 2.1 min for whole‐brain APT weighted imaging and 4.7 min for quantitative APT signal (APT#) mapping. Conclusion: GAVOT makes the prospective variable AF strategy flexible and practical, and, in conjunction with KIPI, ensures high‐quality reconstruction from highly undersampled data, facilitating the clinical translation of whole‐brain CEST imaging. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Purpose: To prospectively accelerate whole‐brain CEST acquisition by joint k‐space and image‐space parallel imaging (KIPI) with a proposed golden‐angle view ordering technique (GAVOT) in Cartesian coordinates. Theory and Methods: The T2‐decay effect will vary across frames with variable acceleration factors (AF) in the prospective acquisition using sequences with long echo trains. The GAVOT method uses a subset strategy to eliminate the T2‐decay inconsistency, where all frames use a subset of shots from the calibration frame to form their k‐space view ordering. The golden‐angle rule is adapted to ensure uniform k‐space coverage for arbitrary AFs in Cartesian coordinates. Phantom and in vivo studies were conducted on a 3 T scanner. Results: The GAVOT view ordering yielded a higher g‐factor than conventional uniformly centric ordering, whereas the noise propagation in amide proton transfer (APT) weighted images was similar between different view ordering. Compared to centric ordering, GAVOT successfully eliminated the T2‐decay inconsistency across all frames, resulting in fewer image artifacts for both KIPI and conventional parallel imaging methods. The synergy of GAVOT and KIPI mitigated strong aliasing artifacts and achieved high‐quality reconstruction of prospective variable‐AF datasets. GAVOT‐KIPI reduced the scan time to 2.1 min for whole‐brain APT weighted imaging and 4.7 min for quantitative APT signal (APT#) mapping. Conclusion: GAVOT makes the prospective variable AF strategy flexible and practical, and, in conjunction with KIPI, ensures high‐quality reconstruction from highly undersampled data, facilitating the clinical translation of whole‐brain CEST imaging. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 07403194 |
| DOI: | 10.1002/mrm.30375 |
