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基于图像质量信息的 CT 特征分析框架。

An Image Quality-informed Framework for CT Characterization.

机构信息

From the Department of Radiology and Biomedical Imaging (R.S.B., S.Y., Y.W., M.D.K., P.C., R.C., J.L., C.S.), Department of Epidemiology and Biostatistics (R.S.B., A.B.), Philip R. Lee Institute for Health Policy Studies (R.S.B., A.B.), and Department of Medicine (A.B.), University of California San Francisco (UCSF), UCSF Mission Bay Campus, Mission Hall: Global Health and Clinical Sciences Building, 550 16th St, 2nd Floor, Box 0560, San Francisco, CA 94158; Department of Demography, University of California Berkeley, Berkeley, Calif (R.C.); Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany (D.B.); Department of Radiology and Biomedical Imaging, University of California Irvine, Irvine, Calif (B.B.); UCSF Medical School, San Francisco, Calif (A.A.C.); Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY (B.D.); Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, and Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY (A.J.E.); Department of Radiology and Public Health Sciences, Henry Ford Health System, Detroit, Mich (M.F.); Department of Nuclear Engineering and Radiological Science, University of Michigan, Ann Arbor, Mich (M.F.); Department of Medicine and Pediatrics (P.R.) and Department of Radiology (J.A.S.), University of California Davis Health, Sacramento, Calif; and Department of Radiology, University of Washington, Seattle, WA (A.C.W.).

出版信息

Radiology. 2022 Feb;302(2):380-389. doi: 10.1148/radiol.2021210591. Epub 2021 Nov 9.

DOI:10.1148/radiol.2021210591
PMID:34751618
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8805663/
Abstract

Background Lack of standardization in CT protocol choice contributes to radiation dose variation. Purpose To create a framework to assess radiation doses within broad CT categories defined according to body region and clinical imaging indication and to cluster indications according to the dose required for sufficient image quality. Materials and Methods This was a retrospective study using Digital Imaging and Communications in Medicine metadata. CT examinations in adults from January 1, 2016 to December 31, 2019 from the University of California San Francisco International CT Dose Registry were grouped into 19 categories according to body region and required radiation dose levels. Five body regions had a single dose range (ie, extremities, neck, thoracolumbar spine, combined chest and abdomen, and combined thoracolumbar spine). Five additional regions were subdivided according to dose. Head, chest, cardiac, and abdomen each had low, routine, and high dose categories; combined head and neck had routine and high dose categories. For each category, the median and 75th percentile (ie, diagnostic reference level [DRL]) were determined for dose-length product, and the variation in dose within categories versus across categories was calculated and compared using an analysis of variance. Relative median and DRL (95% CI) doses comparing high dose versus low dose categories were calculated. Results Among 4.5 million examinations, the median and DRL doses varied approximately 10 times between categories compared with between indications within categories. For head, chest, abdomen, and cardiac (3 266 546 examinations [72%]), the relative median doses were higher in examinations assigned to the high dose categories than in examinations assigned to the low dose categories, suggesting the assignment of indications to the broad categories is valid (head, 3.4-fold higher [95% CI: 3.4, 3.5]; chest, 9.6 [95% CI: 9.3, 10.0]; abdomen, 2.4 [95% CI: 2.4, 2.5]; and cardiac, 18.1 [95% CI: 17.7, 18.6]). Results were similar for DRL doses (all < .001). Conclusion Broad categories based on image quality requirements are a suitable framework for simplifying radiation dose assessment, according to expected variation between and within categories. © RSNA, 2021 See also the editorial by Mahesh in this issue.

摘要

背景

CT 协议选择缺乏标准化会导致辐射剂量的差异。目的:创建一个框架,根据身体部位和临床成像适应证来评估广泛的 CT 类别内的辐射剂量,并根据获得足够图像质量所需的剂量对适应证进行聚类。材料与方法:这是一项回顾性研究,使用了数字成像和通信中的医学元数据。2016 年 1 月 1 日至 2019 年 12 月 31 日期间,来自加利福尼亚大学旧金山分校国际 CT 剂量登记处的成人 CT 检查根据身体部位和所需的辐射剂量水平分为 19 个类别。5 个身体部位的剂量范围是单一的(即四肢、颈部、胸腰椎、胸部和腹部联合以及胸腰椎联合)。另外 5 个部位根据剂量进一步细分。头部、胸部、心脏和腹部各有低剂量、常规剂量和高剂量类别;头部和颈部联合则有常规剂量和高剂量类别。对于每个类别,确定剂量长度产品的中位数和 75 百分位数(即诊断参考水平 [DRL]),并使用方差分析计算和比较类别内和类别间的剂量变化。计算并比较高剂量与低剂量类别之间的相对中位数和 DRL(95%CI)剂量。结果:在 450 万次检查中,与类别内的适应证相比,类别间的中位数和 DRL 剂量差异约为 10 倍。对于头部、胸部、腹部和心脏(3266546 次检查[72%]),分配到高剂量类别的检查的相对中位数剂量高于分配到低剂量类别的检查,这表明将适应证分配到广泛的类别是合理的(头部,高 3.4 倍[95%CI:3.4,3.5];胸部,高 9.6 倍[95%CI:9.3,10.0];腹部,高 2.4 倍[95%CI:2.4,2.5];心脏,高 18.1 倍[95%CI:17.7,18.6])。DRL 剂量的结果也相似(均<0.001)。结论:根据类别间和类别内的预期变化,基于图像质量要求的广泛类别是简化辐射剂量评估的合适框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/8805663/4773f741e2d9/radiol.2021210591.va.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/8805663/4773f741e2d9/radiol.2021210591.va.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e9ad/8805663/4773f741e2d9/radiol.2021210591.va.jpg

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