人工智能-压缩感知技术在颅脑3D T2-FLAIR序列采集及脑白质高信号评价中的应用

Application of artificial intelligence-assisted compressed sensing technology in brain 3D T2-FLAIR sequence acquisition and evaluation of white matter hyperintensity

目的探究不同的基于人工智能压缩感知(artificial intelligence-assisted compressed sensing,ACS)加速因子对颅脑3D T2WI液体衰减反转恢复(3D T2WI fluid-attenuated inversion-recovery,3D T2-FLAIR)序列图像质量的影响,并获取最优化的扫描方案。材料与方法前瞻性纳入健康青年志愿者(healthy control,HC)25例、脑白质高信号(white matter hyperintensity,WMH)患者15例,HC组分别以并行采集(parallel imaging,PI)技术(加速因子为3,F3)和不同加速因子(3、4、5、6、7、8)ACS技术采集颅脑3D T2-FLAIR图像,测量双侧半卵圆中心、双侧尾状核、胼胝体压部、双侧红核、双侧黑质、脑桥、双侧小脑的信号强度以及标准差,并计算图像的信噪比(signal to noise ratio,SNR)和对比噪声比(contrast to noise ratio,CNR)。采用五分法对图像质量进行主观评分。采用组内相关系数(intra-class correlation coefficient,ICC)、Kappa检验比较前后两次测量及观察者间主观评分的一致性。对不同加速因子的图像的SNR、CNR及主观评分采用Friedman秩和检验进行对照分析,综合评判后得出最佳的ACS加速因子;WMH组分别以F3及最佳ACS加速因子采集颅脑3D T2-FLAIR图像,并由两名经验丰富的诊断医师对脑白质病灶数目、Fazekas分级进行评估,采用独立样本t检验、Mann-Whitney U检验进行对照分析。结果HC组中,不同3D T2-FLAIR的SNR、CNR及主观评分差异具有统计学意义(P均<0.05);两两比较结果显示,3D T2-FLAIRACS3、3D T2-FLAIRACS4与3D T2-FLAIRF3的SNR、CNR,3D T2-FLAIRACS3、3D T2-FLAIRACS4、3D T2-FLAIRACS5与3D T2-FLAIRF3的主观评分差异无统计学意义(P均>0.05),其余图像SNR、CNR及主观评分差异均具有统计学意义(P均<0.05)。WMH组中,3D T2-FLAIRF3与3D T2-FLAIRACS4在病灶数目和Fazekas分级方面差异无统计学意义(P均>0.05)。结论以ACS技术采集颅脑3D T2-FLAIR可在保证图像质量和序列诊断效能的前提下缩短扫描时间,选取的最优加速因子为ACS4。

Objective:To investigate the effects of different acceleration factors based on artificial intelligence-assisted compressed sensing(ACS)on the image quality of 3D T2WI fluid-attenuated inversion-recovery(3D T2-FLAIR)sequence.Materials and Methods:Twenty-five healthy volunteers(HC)and fifteen patients with white matter hyperintensity(WMH)were prospectively included in the study.In HC group,the brain 3D T2-FLAIR images were collected by parallel imaging(PI)technique(parallel acquisition acceleration factor was 3)and ACS technique with different acceleration factors(3,4,5,6,7,8).The signal intensity(SI)and standard deviation(SD)of all 3D T2-FLAIR images were measured in bilateral centrum semiovale,bilateral caudate nucleus,splenium of corpus callosum,bilateral red nucleus,bilateral substantia nigra,pons and bilateral cerebellum.The signal to noise ratio(SNR)and contrast to noise ratio(CNR)were further calculated.The subjective score of image quality was analyzed according to five grades standard.The intra-class correlation coefficient(ICC)and Kappa test were used to compare the consistency between the measured data and the subjective scores of the two observers.The SNR,CNR and subjective scores of images with different acceleration factors were compared by Friedman test.After comprehensive evaluation,the best ACS acceleration factor is obtained.In the WMH group,3D T2-FLAIR images of the brain were collected with F3 and the best ACS acceleration factor,and the number of WMH and Fazekas grades were evaluated by two experienced diagnostic physicians.Independent sample t test and Mann-Whitney U test were used for comparative analysis.Results:In HC group,The SNR,CNR and subjective scores of different 3D T2-FLAIR sequences were statistically significant(all P<0.05).The results of pairwise comparison showed that the SNR and CNR of 3D T2-FLAIRACS3,3D T2-FLAIRACS4 and 3D T2-FLAIRF3,and the subjective scores of 3D T2-FLAIRACS3,3D T2-FLAIRACS4,3D T2-FLAIRACS5 and 3D T2-FLAIRF3 were not statistically significant(all P>0.05).The SNR,CNR and subjective scores of the remaining images were statistically significant(all P<0.05).In the WMH group,there was no significant difference in the number of WMH and Fazekas grades between 3D T2-FLAIR F3 and 3D T2-FLAIR ACS4(P>0.05).Conclusions:The acquisition of brain 3D T2-FLAIR with ACS technology can shorten the scanning time under the premise of ensuring image quality and diagnostic efficiency,and ACS4 can be considered as the best acceleration factor.