Artificial intelligence iterative reconstruction in abdominal CT of patients with irregular arm positioning: a case-by-case evaluation.

IF 1.1 4区 医学 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Acta radiologica Pub Date : 2024-08-01 Epub Date: 2024-06-14 DOI:10.1177/02841851241258845
Jin Li, Ting Meng, Guozhi Zhang, Xiang Yu, Zhihua Lu, Weiguo Zhang
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引用次数: 0

Abstract

Background: Streak artifacts induced by irregular arm positioning have been an issue in diagnosing the abdomen.

Purpose: To illustrate the risk of misdiagnosis in abdominal computed tomography (CT) of patients with irregular arm positioning through a case-by-case evaluation and to test if it can be solved by the artificial intelligence iterative reconstruction (AIIR) algorithm.

Material and methods: By reviewing 5220 cases of chest and thoracoabdominal CT, 64 patients with irregular arm positioning were enrolled, whose image data were reconstructed using AIIR in addition to routine hybrid iterative reconstruction (HIR). Lesion detection for livers, spleens, kidneys, gallbladders, and pancreas on AIIR images, performed by two radiologists, was compared with those on HIR images. Discrepancies arising from AIIR images included both cases with additional abnormalities and those with corrections made on previous detections. For cases with discrepancies, artifact scores for organs where discrepancies were found, and contrast-to-noise ratios (CNRs) of cysts with discrepancies were compared between two image sets.

Results: Additional abnormalities were detected for 15 cases: additional liver cirrhosis (n=2); additional gallbladder stone (n=1); additional cholecystitis (n=1), additional spleen nodule (n=1); additional kidney cysts (n=8); additional liver cysts (3); and additional spleen cyst (n=1). A spleen contusion was corrected for one case. All involved artifact scores were improved on AIIR images. CNRs of involved liver, kidney, and spleen cysts were improved by up to 539.7%, 538.5%, and 245.5%, respectively.

Conclusion: Irregular arm positioning may induce a variety of misdiagnoses in abdominal CT, which is almost totally avoidable by the AIIR algorithm.

人工智能迭代重建腹部 CT:对不规则手臂定位患者的个案评估。
背景:目的:通过逐例评估说明手臂不规则定位患者腹部计算机断层扫描(CT)的误诊风险,并检验人工智能迭代重建(AIIR)算法能否解决这一问题:通过对5220例胸部和胸腹部CT病例进行回顾性分析,共纳入64例手臂位置不规则的患者,在常规混合迭代重建(HIR)的基础上,使用人工智能迭代重建(AIIR)对其图像数据进行重建。由两名放射科医生对 AIIR 图像上的肝脏、脾脏、肾脏、胆囊和胰腺病变检测结果与 HIR 图像上的检测结果进行了比较。AIIR 图像上出现的差异既包括额外异常的病例,也包括对之前检测结果进行修正的病例。对于存在差异的病例,对发现差异的器官的伪影评分以及存在差异的囊肿的对比噪声比(CNR)在两套图像之间进行比较:结果:15 个病例发现了额外的异常:额外的肝硬化(2 例)、额外的胆囊结石(1 例)、额外的胆囊炎(1 例)、额外的脾脏结节(1 例)、额外的肾囊肿(8 例)、额外的肝囊肿(3 例)和额外的脾囊肿(1 例)。纠正了一例脾挫伤。所有受累假体在 AIIR 图像上的评分均有所提高。受累肝脏、肾脏和脾脏囊肿的 CNR 分别提高了 539.7%、538.5% 和 245.5%:结论:不规则的手臂定位可能会在腹部 CT 中引起各种误诊,而 AIIR 算法几乎可以完全避免误诊。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Acta radiologica
Acta radiologica 医学-核医学
CiteScore
2.70
自引率
0.00%
发文量
170
审稿时长
3-8 weeks
期刊介绍: Acta Radiologica publishes articles on all aspects of radiology, from clinical radiology to experimental work. It is known for articles based on experimental work and contrast media research, giving priority to scientific original papers. The distinguished international editorial board also invite review articles, short communications and technical and instrumental notes.
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