Objective To investigate the value of MRI artificial intelligence-assisted compressed sensing(ACS)cardiac cine(cine)sequence in cardiac function assessment.Methods Sixty-three subjects who underwent cardiac MRI in our hospital from May to December 2022 were consecutively included in this study.All subjects were scanned with both conventional cine and ACS-cine sequences,and image quality was evaluated using a 5-point scale.The Wilcoxon signed rank test was applied to compare the scan time,image quality scores and ventricular function results of the 2 cardiac cine sequences.Spearman correlation analysis and Bland-Altman analysis were used to evaluate the correlation and consistency of the two sequences for measuring cardiac function.Results The difference in scan time between the conventional cine and ACS-cine sequences was statistically significant(Z=-6.904,P<0.001),with the latter significantly reducing scan time by approximately 92.82%.The difference in image quality scores between conventional cine and ACS-cine sequences was not statistically significant(Z=-0.816,P>0.05).There was no statistically significant difference in LVEF,LVESV,RVEF,RVEDV,and RVESV parameters between conventional cine and ACS-cine sequences(all P>0.05),but there was a statistically significant difference in the LVEDV parameter(Z=-2.958,P<0.05).Quantitative cardiac function parameters(LVEF,LVEDV,LVESV,RVEF,RVEDV,RVESV)were all well correlated between conventional cine and ACS-cine sequences(r=0.865-0.963,all P<0.01).Bland-Altman analysis showed that the mean differences in quantitative parameters of LV and RV function(LVEF,LVEDV,LVESV,RVEF,RVEDV,RVESV)obtained from conventional cine and ACS-cine sequence images were all close to zero with a small range of variation and high agreement.Conclusion Compared with conventional cine,ACS-cine can significantly shorten the imaging time while guaranteeing the image quality,and can accurately analyze the LV and RV functions,which has high clinical application value.
Magnetic Resonance ImagingArtificial IntelligenceCompressed SensingCardiac Cine ImagingCardiac Function Analysis