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基于深度学习图像重建的冠状动脉 CT 血管造影:评估辐射剂量降低的初步研究。

Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction.

机构信息

Medical Physics Unit, Azienda Ospedaliero-Universitaria (AOU), 07100 Sassari, Italy.

Department of Medicine, Surgery and Pharmacy, University of Sassari, 07100 Sassari, Italy.

出版信息

Tomography. 2023 May 16;9(3):1019-1028. doi: 10.3390/tomography9030083.

DOI:10.3390/tomography9030083
PMID:37218943
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10204394/
Abstract

Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R-R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings.

摘要

冠状动脉计算机断层扫描血管造影(CCTA)是一种医学成像技术,可生成冠状动脉的详细图像。我们的工作重点是优化前瞻性心电图触发扫描技术,该技术仅在 R-R 间隔的一部分时间内有效地提供辐射,从而符合在这种日益使用的放射检查中降低辐射剂量的目标。在这项工作中,我们分析了我们中心的 CCTA 的中值 DLP(剂量长度乘积)值如何在最近显著降低,主要是由于所使用的技术发生了明显变化。我们的整个检查的中值 DLP 值从 1158 mGy·cm 降至 221 mGy·cm,如果仅考虑 CCTA 扫描,则中值 DLP 值从 1140 mGy·cm 降至 204 mGy·cm。这一结果是通过在剂量成像优化过程中结合重要因素获得的:技术改进、采集技术和图像重建算法干预。这三个因素的结合使我们能够以更低的辐射剂量进行更快、更准确的前瞻性 CCTA。我们的未来目标是通过结合算法强度和自动剂量设置的基于检测能力的研究来调整图像质量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c302/10204394/fbe55bd415cf/tomography-09-00083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c302/10204394/fbe55bd415cf/tomography-09-00083-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c302/10204394/fbe55bd415cf/tomography-09-00083-g001.jpg

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本文引用的文献

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Radiol Med. 2023 Apr;128(4):434-444. doi: 10.1007/s11547-023-01607-8. Epub 2023 Feb 27.
2
Comparison of radiation dose and its correlates between coronary computed tomography angiography and invasive coronary angiography in Northeastern Thailand.泰国东北部地区冠状动脉计算机断层扫描血管造影与有创冠状动脉造影辐射剂量及其相关因素的比较。
Egypt Heart J. 2022 Jan 25;74(1):6. doi: 10.1186/s43044-022-00241-5.
3
High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.
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Eur Radiol. 2022 May;32(5):2912-2920. doi: 10.1007/s00330-021-08424-5. Epub 2022 Jan 21.
4
A deep-learning reconstruction algorithm that improves the image quality of low-tube-voltage coronary CT angiography.一种深度学习重建算法,可提高低管电压冠状动脉 CT 血管造影的图像质量。
Eur J Radiol. 2022 Jan;146:110070. doi: 10.1016/j.ejrad.2021.110070. Epub 2021 Nov 24.
5
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