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Technical Article
Impact of AI-assisted compressed sensing on quality and phase value of nuclei of brain susceptibility weighted imaging
ZHONG Meimeng  CAO Jiajun  AN Qi  YANG Chao  SONG Qingwei 

Cite this article as: ZHONG M M, CAO J J, AN Q, et al. Impact of AI-assisted compressed sensing on quality and phase value of nuclei of brain susceptibility weighted imaging[J]. Chin J Magn Reson Imaging, 2023, 14(12): 91-97. DOI:10.12015/issn.1674-8034.2023.12.015.

[Abstract] Objective To examine the influence of artificial intelligence assisted compressed sensing (ACS) with different acceleration factors (AF) on the quality and phase value (PV) of gray matter nuclei in brain susceptibility weighted imaging (SWI), and to screen the optimal ACS acceleration factor.Materials and Methods A total of 24 healthy volunteers were prospectively enrolled. They underwent axial SWI scans combined with parallel imaging (PI) and ACS, respectively, with acceleration factors PI AF=2.2 and ACS AF=3, 4 and 5. Two radiologists subjectively assessed images at the aspects of sharpness of nuclei's anatomic structure and boundary using a three-point scoring method (1-3, 3=best), and also objectively evaluated signal-to-noise ratio (SNR) and contrast-to-noiseratio (CNR). The PV of the head of caudate nucleus, putamen, globus pallidus, red nucleus, substantia nigra and dentate nucleis were measured and compared on the SWI phase images, and the SNR and CNR of the four images at different layers were calculated. The Cohen's Kappa test was used to test Inter-observer score consistency. In the following analysis, the Fisher's precision probability test exact was used to test the differences of the subjective scores of the same observer.Results There were statistical differences of SNR, CNR and subjective scores among four groups of images (all P<0.05). Paired comparison showed that the subjective scores of ACS 4 and ACS 5 were lower than PI 2.2 (all P<0.001), while SNR and CNR were higher than PI 2.2 (all P<0.05). There was no significant different in SNR, CNR and subjective scores between ACS 3 and PI 2.2 (all P>0.05). Compared with PI 2.2, PV of the left PUT, bilateral RN and bilateral SN varied at ACS 4 (all P<0.001), while PV of the right PUT became different when ACS 5 (P<0.001). There was no significant difference in PV among the rest nuclei measured under all AF conditions (all P>0.05). The inter-observer consistency of subjective scoring was good (Kappa: 0.704-0.864, all P<0.001).Conclusions ACS can shorten the scan time of SWI without affecting imaging quality and PV results, and ACS 3 is the optimal acceleration factor.
[Keywords] susceptibility weighted imaging;artificial intelligence;compressed sensing;parallel imaging;magnetic resonance imaging

ZHONG Meimeng   CAO Jiajun   AN Qi   YANG Chao   SONG Qingwei*  

Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian 116011, China

Corresponding author: SONG Q W, E-mail:

Conflicts of interest   None.

Received  2023-06-30
Accepted  2023-11-27
DOI: 10.12015/issn.1674-8034.2023.12.015
Cite this article as: ZHONG M M, CAO J J, AN Q, et al. Impact of AI-assisted compressed sensing on quality and phase value of nuclei of brain susceptibility weighted imaging[J]. Chin J Magn Reson Imaging, 2023, 14(12): 91-97. DOI:10.12015/issn.1674-8034.2023.12.015.

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