Artificial Intelligence Iterative Reconstruction in Multiphase Abdominopelvic CT: Added Value for Anatomic Evaluation of Uterine Artery.

IF 1.4 4区 医学 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Qianqian Qu, Haiyang Geng, Ting Meng, Qingshi Zeng, Kai Deng
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引用次数: 0

Abstract

Objective: To assess the anatomic evaluation performance of the uterine artery (UA) on routine multiphase abdominopelvic CT images, and to investigate whether artificial intelligence iterative reconstruction (AIIR) can improve this performance to a level comparable to that on CTA images.

Methods: This retrospective study included 50 patients who underwent multiphase abdominopelvic CT. Aarterial phase (AP) images were reconstructed with AIIR (group B) in addition to the routine hybrid iterative reconstruction (HIR) (group A). Another 50 patients who underwent routine abdominal aorta CTA were retrospectively identified, and their images were reconstructed with HIR (group C). The anatomic evaluation performance of UA in terms of the interpretability of origins, branching pattern, and lumen diameter was compared across the 3 image sets. The objective image quality was also compared.

Results: A total of 100 patients (age 18 to 65 y) were investigated, and 300 UAs were evaluated (150 images × 2 UAs). Both group B and group C outperformed group A in terms of the proportion of UAs with identifiable origins (90% and 88% vs. 68%), classifiable branching pattern (89% and 87% vs. 71%), and totally measurable diameter (63% and 67% vs. 33%) (all P<0.017). No significant differences were found between groups B and C for any of these proportions (all P>0.017). The measured diameters exhibited excellent intraobserver agreement with ICC values of 0.90, 0.93, and 0.98 for groups A, B, and C, respectively. The UA attenuation was highest in group C, followed by group B and group A (all P<0.017). Group B exhibited the lowest noise in all scenarios (all P<0.017). No significant difference was found in the CNR of UA between group B and group C (all P>0.017). Sensitivity analysis excluding hypertensive patients confirmed the stability of the results.

Conclusions: Anatomic evaluation performance of UA on routine multiphase abdominopelvic CT images is suboptimal. However, when AIIR is applied, both the interpretability of anatomic features and the image quality of UA are comparable to those obtained with dedicated CTA.

人工智能迭代重建多期腹部骨盆CT对子宫动脉解剖评价的价值。
目的:评价子宫动脉(UA)在常规骨盆多相CT图像上的解剖评价性能,探讨人工智能迭代重建(AIIR)能否将子宫动脉(UA)的解剖评价提高到与CTA图像相当的水平。方法:回顾性研究50例经腹部骨盆多期CT检查的患者。在常规混合迭代重建(HIR)的基础上,采用AIIR重建非物质相(AP)图像(B组)。另外50例行常规腹主动脉CTA的患者进行回顾性鉴定,并用HIR重建其图像(C组)。在起源、分支模式和管腔直径的可解释性方面,UA的解剖学评估性能在3个图像集之间进行了比较。对客观图像质量进行了比较。结果:共调查100例患者(18 ~ 65岁),评估300个UAs(150张图像× 2个UAs)。B组和C组在起源可识别的UAs比例(90%和88%比68%),可分类的分支模式(89%和87%比71%)和完全可测量的直径(63%和67%比33%)方面优于A组(均P0.017)。A、B和C组的测量直径与ICC值的一致性非常好,分别为0.90、0.93和0.98。UA衰减以C组最高,其次为B组和A组(p均为0.017)。排除高血压患者的敏感性分析证实了结果的稳定性。结论:UA在常规多期腹部骨盆CT图像上的解剖评价效果不理想。然而,当应用AIIR时,UA的解剖特征的可解释性和图像质量与专用CTA获得的图像质量相当。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
230
审稿时长
4-8 weeks
期刊介绍: The mission of Journal of Computer Assisted Tomography is to showcase the latest clinical and research developments in CT, MR, and closely related diagnostic techniques. We encourage submission of both original research and review articles that have immediate or promissory clinical applications. Topics of special interest include: 1) functional MR and CT of the brain and body; 2) advanced/innovative MRI techniques (diffusion, perfusion, rapid scanning); and 3) advanced/innovative CT techniques (perfusion, multi-energy, dose-reduction, and processing).
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