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在不同曝光模式和棒状物体取向条件下,对锥形束CT(CBCT)中金属伪影减少情况的定量评估。

Quantitative evaluation of metal artifact reduction in CBCT under varying exposure modes and rod orientations.

作者信息

Jo Gyu-Dong, Park Chul-Wan, Jeon Kug Jin, Han Sang-Sun

机构信息

Department of Oral and Maxillofacial Radiology, Yonsei University College of Dentistry, Seoul, Republic of Korea.

Oral Science Research Center, Yonsei University College of Dentistry, Seoul, Republic of Korea.

出版信息

Sci Rep. 2025 Jul 1;15(1):20645. doi: 10.1038/s41598-025-08188-8.

DOI:10.1038/s41598-025-08188-8
PMID:40594906
Abstract

This study aimed to quantitatively evaluate the efficacy of a metal artifact reduction (MAR) algorithm in cone-beam computed tomography (CBCT) under varying exposure modes and metal rod orientations using a standardized evaluation method. A SEDENTEXCT IQ phantom was scanned with a CBCT system under three exposure modes (standard, low-dose, ultra-low-dose) and two rod orientations (horizontal, vertical), with the MAR algorithm activated and deactivated. Artifact areas were quantified from binarized images based on a thresholding method that distinguished artifact-affected regions from the background. The percentage reduction in metal artifacts was calculated by comparing scans acquired with and without MAR activation. Statistical analyses were conducted to assess differences across conditions. The MAR algorithm significantly reduced metal artifacts under all tested conditions (P < 0.05), with reductions of 61.5% in the standard mode, 73.6% in the low-dose mode, and 80.3% in the ultra-low-dose mode. By rod orientation, artifact reduction was 63.3% for the horizontal orientation and 80.7% for the vertical orientation. These results confirm the consistent effectiveness of the MAR algorithm across different acquisition settings. The proposed standardized evaluation method provides a reproducible framework for objectively assessing MAR performance and supporting its clinical integration.

摘要

本研究旨在使用标准化评估方法,定量评估金属伪影减少(MAR)算法在不同曝光模式和金属棒方向下的锥束计算机断层扫描(CBCT)中的效果。使用CBCT系统在三种曝光模式(标准、低剂量、超低剂量)和两种棒方向(水平、垂直)下对SEDENTEXCT IQ体模进行扫描,同时激活和停用MAR算法。基于区分受伪影影响区域与背景的阈值方法,从二值化图像中对伪影区域进行量化。通过比较激活和未激活MAR时获得的扫描结果,计算金属伪影减少的百分比。进行统计分析以评估不同条件之间的差异。在所有测试条件下,MAR算法均显著减少了金属伪影(P < 0.05),在标准模式下减少了61.5%,在低剂量模式下减少了73.6%,在超低剂量模式下减少了80.3%。按棒方向划分,水平方向的伪影减少率为63.3%,垂直方向为80.7%。这些结果证实了MAR算法在不同采集设置下的一致有效性。所提出的标准化评估方法为客观评估MAR性能并支持其临床应用提供了一个可重复的框架。

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本文引用的文献

1
Deep Learning Image Reconstruction for CT: Technical Principles and Clinical Prospects.深度学习在 CT 图像重建中的应用:技术原理与临床前景。
Radiology. 2023 Mar;306(3):e221257. doi: 10.1148/radiol.221257. Epub 2023 Jan 31.
2
Convolutional neural network-based metal and streak artifacts reduction in dental CT images with sparse-view sampling scheme.基于卷积神经网络的稀疏视图采样方案在牙科 CT 图像中减少金属伪影和条纹伪影。
Med Phys. 2022 Sep;49(9):6253-6277. doi: 10.1002/mp.15884. Epub 2022 Aug 10.
3
Assessment of the efficiency of a pre- versus post-acquisition metal artifact reduction algorithm in the presence of 3 different dental implant materials using multiple CBCT settings: An in vitro study.
在使用多种CBCT设置的情况下,评估在存在3种不同牙科植入材料时,采集前与采集后金属伪影减少算法的效率:一项体外研究。
Imaging Sci Dent. 2021 Mar;51(1):1-7. doi: 10.5624/isd.20200094. Epub 2021 Jan 28.
4
Metal artifact reduction using iterative CBCT reconstruction algorithm for head and neck radiation therapy: A phantom and clinical study.采用迭代 CBCT 重建算法降低头颈部放疗中的金属伪影:体模和临床研究。
Eur J Radiol. 2020 Nov;132:109293. doi: 10.1016/j.ejrad.2020.109293. Epub 2020 Sep 21.
5
Quantitative analysis of metal artifact reduction using the auto-edge counting method in cone-beam computed tomography.使用锥形束计算机断层扫描中的自动边缘计数法进行金属伪影减少的定量分析。
Sci Rep. 2020 Jun 1;10(1):8872. doi: 10.1038/s41598-020-65644-3.
6
The efficacy of metal artifact reduction (MAR) algorithm in cone-beam computed tomography on the diagnostic accuracy of fenestration and dehiscence around dental implants.锥形束计算机断层扫描中金属伪影降低算法对种植体周围开窗和崩裂诊断准确性的影响。
J Periodontol. 2020 Feb;91(2):209-214. doi: 10.1002/JPER.18-0433. Epub 2019 Aug 28.
7
The performance of metal artifact reduction algorithms in cone beam computed tomography images considering the effects of materials, metal positions, and fields of view.考虑材料、金属位置和视野影响的锥形束计算机断层摄影图像中金属伪影减少算法的性能。
Oral Surg Oral Med Oral Pathol Oral Radiol. 2019 Jan;127(1):71-76. doi: 10.1016/j.oooo.2018.09.004. Epub 2018 Sep 26.
8
Current and Novel Techniques for Metal Artifact Reduction at CT: Practical Guide for Radiologists.CT 金属伪影降低的当前和新方法:放射科医师实用指南。
Radiographics. 2018 Mar-Apr;38(2):450-461. doi: 10.1148/rg.2018170102.
9
Evaluation of the efficacy of a metal artifact reduction algorithm in different cone beam computed tomography scanning parameters.在不同锥形束计算机断层扫描参数下评估金属伪影减少算法的功效。
Oral Surg Oral Med Oral Pathol Oral Radiol. 2017 Jun;123(6):729-734. doi: 10.1016/j.oooo.2017.02.015. Epub 2017 Mar 9.
10
Observer Evaluation of a Metal Artifact Reduction Algorithm Applied to Head and Neck Cone Beam Computed Tomographic Images.应用于头颈部锥形束计算机断层扫描图像的金属伪影减少算法的观察者评估
Int J Radiat Oncol Biol Phys. 2016 Nov 15;96(4):897-904. doi: 10.1016/j.ijrobp.2016.07.028. Epub 2016 Jul 30.