1024×1024重建矩阵结合迭代重建算法在胃部CT血管成像中的应用

Application of 1024×1024 Reconstruction Matrix Combined with Iterative Reconstruction Algorithm in Gastric CT Angiography

目的 探究1 024×1 024重建矩阵结合迭代重建(Karl)算法在胃部血管及肿瘤供血动脉CT血管成像中的应用价值。资料与方法 前瞻性收集大连医科大学附属第一医院2022年3—6月行胃部CT血管成像的胃部肿瘤患者30例,对CT扫描图像原始数据进行分组重建。A组采用常规512×512矩阵结合Karl 5级重建;B组采用1 024×1 024大重建矩阵结合不同等级Karl算法重建,分为B1(Karl 5)、B2(Karl 7)及B3(Karl 9)3个亚组。在轴位图像上测量胃左动脉起始部的腹主动脉、腹腔干、脾动脉、肝动脉及同层面腹壁皮下脂肪组织的CT值和SD值,计算信噪比(SNR)、对比噪声比(CNR)。由2名观察者采用5分法评估各组图像质量。结果 2名观察者主观评价一致性较好(Kappa=0.782~0.789,P<0.05),B1~B3组图像主观评分均优于A组,B2组得分最高(二维评分:χ^(2)=27.309、24.250;三维评分:χ^(2)=21.964、21.294;P均<0.05),30例患者中25例见胃动脉系统参与肿瘤供血,B2组各血管的清晰显示率均优于A组;A与B1、B2组各血管CT值差异无统计学意义(t=-1.918~2.720,P>0.05),B2组较A组血管SD值、SNR、CNR和背景噪声值,除腹主动脉SD、肝动脉CNR外差异均无统计学意义(t=-5.909~5.768,P>0.05);B1~3组图像随着Karl算法等级提高,SD值逐渐降低(F=2.881~27.109,P<0.05),SNR、CNR逐渐升高(F=3.612~12.149,P<0.05)。结论 1 024×1 024重建矩阵结合Karl 7级算法可以改善图像质量,增强胃部微细血管及肿瘤供血动脉分支的显示效果,在临床上有很好的应用价值。

Purpose To explore the application value of 1024×1024 reconstruction matrix combined with iterative reconstruction algorithm(Karl)in computed tomography angiography(CTA)of gastric vessels and tumor-supplying arteries.Materials and Methods Thirty patients with gastric tumors who underwent clinical gastric CTA from March to June 2022 at the First Affiliated Hospital of Dalian Medical University were prospectively collected.The original data of CT scan images were grouped and reconstructed.Group A used the conventional 512×512 matrix combined with Karl-5 reconstruction;group B used 1024×1024 large reconstruction matrix combined with different levels of Karl algorithm reconstruction,obtaining three subgroups:B1(Karl 5),B2(Karl 7)and B3(Karl 9).The CT and SD values of abdominal aorta at the origin of the left gastric artery,celiac trunk,splenic artery,hepatic artery and the subcutaneous fat tissue of the abdominal wall were measured,and the signal-to-noise ratio(SNR)and contrast-to-noise ratio(CNR)were calculated.The image quality of each group was assessed by two observers using a 5-point scale.Results The two observers had good consistency in the evaluation of image quality(Kappa=0.782-0.789,P<0.05).Subjective scores for groups B1 to B3 were all better than those for group A,with the highest score in group B2(two-dimensional scores:χ^(2)=27.309,24.250;three-dimensional scores:χ^(2)=21.964,21.294;all P<0.05).The gastric artery system was involved in tumor blood supply in 25 cases of 30 gastric tumors,with the clarity rate of each vessel in group B2 being superior to group A.There were no statistically significant differences in CT values of vessels between groups A,B1 and B2(t=-1.918-2.720,P>0.05),and apart from the SD of the abdominal aorta and CNR of the hepatic artery,differences in SD values,SNR,CNR,and background noise between group B2 and group A were not significant(t=-5.909-5.768,P>0.05);images from B1 to B3 showed a gradual decrease in SD values(F=2.881-27.109,P<0.05)and a gradual increase in SNR and CNR(F=3.612-12.149,P<0.05)as the level of Karl algorithm increased.Conclusion 1024×1024 reconstruction matrix combined with Karl-7 can improve the image quality and enhance the display effect of gastric microvessels and tumor-supplying artery branches,which have good clinical application value.