首页|头颈联合3D-TOF-MRA人工智能辅助压缩感知序列的优化

头颈联合3D-TOF-MRA人工智能辅助压缩感知序列的优化

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目的 通过比较施加不同加速因子(acceleration factors,AF)的并行采集(parallel imaging,PI)、压缩感知(compressed sensing,CS)、人工智能-压缩感知(artificial intelligence compressed sensing,ACS)技术的头颈联合三维时间飞跃法磁共振血管成像(three-dimensional time-of-fight magnetic resonance angiography,3D-TOF-MRA)的图像质量,选取优化序列.材料与方法 前瞻性招募24例健康志愿者,以PI的AF为3(PI 3)、CS的AF分别为4和6(CS 4、CS 6)以及ACS的AF分别为4、6、8、10(ACS 4、ACS 6、ACS 8、ACS 10)进行头颈联合3D-TOF-MRA扫描.扫描时间:PI 3=8 min 40 s;CS 4= 6 min 38 s;CS 6=4 min 9 s;ACS 4=5 min 24 s;ACS 6=4 min 30 s;ACS 8=4 min 13 s;ACS 10=3 min 24 s.分别在双侧大脑中动脉(middle cerebral artery,MCA)M1段、双侧颈内动脉(internal carotid artery,ICA)C4段、颈动脉分叉处下5个层面的双侧颈总动脉(common carotid artery,CCA)以及MCA及ICA同一层面的颞叶白质,CCA同一层面的胸锁乳突肌作为背景区域勾画感兴趣区(regions of interest,ROI),记录信号强度(signal intensity,SI)及标准差(standard deviation,SD),从而计算信噪比(signal-to-noise ratio,SNR)与对比噪声比(contrast-to-noise ratio,CNR).采用四分法和五分法分别对整体图像质量以及颅内动脉、颈部大动脉进行评分.以组内相关系数(intra-class correlation coefficient,ICC)比较两名放射医师之间及同一名放射医师内客观评价结果的一致性,Kappa检验比较两名放射医师之间及同一名放射医师内主观评价结果的一致性,若一致性良好,则选取其中一位医师的客观评分及主观评分进行后续统计分析.采用单因素方差分析或Kruskal-Wallis检验对客观评分以及主观评分进行总体差异比较,若差异具有统计学意义则进行两两比较.结果 与PI技术比较显示,ACS 4~ACS 8的SNRL-MCA,ACS 8、ACS 10的CNRL-MCA,ACS 4、ACS 6、ACS 10的CNRR-MCA,ACS 4~ACS 10的SNRR-MCA、SNRL-CCA、CNRL-CCA,ACS 6~ACS 10的SNRR-CCA、CNRR-CCA均高于PI 3,差异具有统计学意义(P<0.05).与CS技术比较显示,ACS 4~ACS 10的SNRR-MCA、CNRL-MCA及CNRR-MCA,ACS 4~ACS 8的SNRL-MCA、SNRL-CCA、SNRR-CCA、CNRL-CCA、CNRR-CCA与CS 4差异具有统计学意义(P<0.05),ACS 4~ACS 10的SNRL-MCA、SNRR-MCA、CNRL-MCA、CNRR-MCA、SNRL-ICA、SNRR-ICA、CNRL-ICA、SNRL-CCA、SNRR-CCA、CNRL-CCA、CNRR-CCA与CS 6差异具有统计学意义(P<0.05),均优于CS 4、CS 6.ACS技术之间两两比较,ACS 8的SNRL-MCA高于ACS 10(P<0.05),ACS 8、ACS 10的SNRR-CCA、CNRR-CCA均高于ACS 4(P<0.05),其余差异均无统计学意义(P>0.05).除颈部大动脉图像外,主观评分统计结果均为ACS 4~ACS 10与CS 6差异具有统计学意义(P<0.05),优于CS 6.结论 与PI及CS技术相比,ACS技术拥有更短的扫描时间,更好的图像质量.ACS 8为最优序列,扫描时间比PI 3缩短51%.
Optimization of artificial intelligence-assisted compressed sensing sequences for cerebral and carotid 3D-TOF-MRA
Objective:By comparing the application of different acceleration factors(AF)in parallel imaging(PI),compressed sensing(CS),and artificial intelligence-compressed sensing(ACS)techniques for three-dimensional time-of-flight magnetic resonance angiography(3D-TOF-MRA)in the cerebral and carotid region,to select an optimized acceleration factor for ACS.Materials and Methods:Twenty-four healthy volunteers were prospectively recruited and underwent cerebral and carotid 3D-TOF-MRA scanning with AF of 3 in PI(PI 3),4 and 6 in CS(CS 4 and CS 6),and 4,6,8 and 10 in ACS(ACS 4,ACS 6,ACS 8 and ACS 10).Scan durations were:PI 3=8 min 40 s;CS 4=6 min 38 s;CS 6=4 min 9 s;ACS 4=5 min 24 s;ACS 6=4 min 30 s;ACS 8=4 min 13 s;ACS 10=3 min 24 s.Regions of interest(ROIs)were delineated in bilateral middle cerebral artery(MCA)at M1 segment,bilateral internal carotid artery(ICA)at C4 segment,five levels below the bifurcation of the carotid artery in bilateral common carotid artery(CCA),and temporal white matter at the same level as MCA and ICA,with the sternocleidomastoid muscle at the same level as CCA serving as the background region.Signal intensity(SI)and standard deviation(SD)were recorded to calculate signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR).Image quality was assessed using four-point and five-point scales for overall image quality,intracranial arteries,and major neck arteries.Intra-class correlation coefficient(ICC)was used to compare the consistency of objective evaluations between two radiologists and within the same radiologist,while Kappa test was employed to compare the consistency of subjective evaluations.If consistency was satisfactory,objective and subjective ratings from one radiologist were selected for subsequent analysis.One-way ANOVA or Kruskal-Wallis test was used to compare overall differences in objective and subjective ratings,with post hoc tests conducted for statistically significant differences.Results:Compared with PI,there were statistically significant differences(P<0.05)in SNRL-MCA of ACS 4-ACS 8,CNRL-MCA of ACS 8 and ACS 10,CNRR-MCA of ACS 4,ACS 6,and ACS 10,SNRR-MCA,SNRL-CCA,CNRL-CCA of ACS 4-ACS 10,SNRR-CCA,CNRR-CCA,compared with PI 3,all of which were higher than PI 3.Compared with CS,statistically significant differences(P<0.05)were observed in SNRR-MCA,CNRL-MCA,and CNRR-MCA of ACS 4-ACS 10,SNRL-MCA,SNRL-CCA,SNRR-CCA,CNRL-CCA,CNRR-CCA of ACS 4-ACS 8,compared with CS 4,as well as SNRL-MCA,SNRR-MCA,CNRL-MCA,CNRR-MCA,SNRL-ICA,SNRR-ICA,CNRL-ICA,SNRL-CCA,SNRR-CCA,CNRL-CCA,CNRR-CCA of ACS 4-ACS 10,compared with CS 6,all of which were superior to CS 4 and CS 6.In pairwise comparisons among ACS,SNRL-MCA of ACS 8 was higher than ACS 10(P<0.05),SNRR-CCA and CNRR-CCA of ACS 8 and ACS 10 were both higher than ACS4(P<0.05),while other differences were not statistically significant(P>0.05).Except for the images of the carotid arteries,subjective scoring results showed statistically significant differences(P<0.05)between ACS 4-ACS 10 and CS 6,all of which were superior to CS 6.Conclusions:Compared with PI and CS,ACS has shorter scanning time and better image quality.ACS 8 is the optimal sequence,with a 51%reduction in scanning time compared with PI 3.

parallel imagingcompressed sensingartificial intelligence-compressed sensingcerebral and carotid combined time-of-flight magnetic resonance angiographymagnetic resonance imaging

袁畅、张煜堃、曹家骏、宋清伟、苗延巍

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大连医科大学附属第一医院放射科,大连 116011

并行采集 压缩感知 人工智能-压缩感知 头颈联合三维时间飞跃法磁共振血管成像 磁共振成像

辽宁省教育厅科学研究经费项目

LJKZ0856

2024

磁共振成像
中国医院协会 首都医科大学附属北京天坛医院

磁共振成像

CSTPCD北大核心
影响因子:1.38
ISSN:1674-8034
年,卷(期):2024.15(4)
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