Common computed tomography artifact: source and avoidance
Tóm tắt
Artifacts have significantly degraded the quality of computed tomography (CT) images, to the extent of making them unusable for diagnosis. The types of artifact that could be used are as follows: (a) streaking, which is commonly due to a discrepancy in a single measurement, (b) shading, which is due to a group of channels deviating gradually from the true measurement, (c) rings, which are due to errors in individual detector calibration and (d) distortion, which is due to helical reconstruction. It is occasionally possible to avoid scanning of a bony area, by means of changing the postion of the patient. Thus, this study aimed to evaluate the common artifacts that affect image quality and the method of correction to improve image quality. The data were collected by distributing a questionnaire to the CT technologist at different hospitals about the most common type of artifacts in the CT images, source of artifacts and methods of correction. A total of 95 CT technologists responded to the questionnaire, which included 67% males and 33% females. Most of the participants (70%) were experienced CT technologists, and 61% of the participants had not done any subspecialty CT scan courses. The most common artifact used in the CT departments was motion artifact in brain CT (73%), and the best method to reduce motion artifact was patient preparation (87%). The most common shown artifact in this study was motion artifact, and the common cause was the patient-based artifact. It is important to understand why objects occur and how they could be prevented or suppressed to improve image quality.
Tài liệu tham khảo
Chen GT, Kung JH, Beaudette KP (2004) Artifacts in computed tomography scanning of moving objects. Semin Radiat Oncol 14(1):19–26. https://doi.org/10.1053/j.semradonc.2003.10.004
Wang Y, Gao X, Lu A, Zhou Z, Li B, Sun X, Zhu B (2012) Residual aneurysm after metal coils treatment detected by spectral CT. Quant Imaging Med Surg 2(2):137–138. https://doi.org/10.3978/j.issn.2223-4292.2012.06.04
Lehmann G (2018) An introduction to CT scan image artifacts. North Star Imaging Blog https://4nsi.com/blog/2018/01/09/an-introduction-to-ct-scan-image-artifacts/. Accessed 25 Jul 2020
Zhou C, Zhao YE, Luo S, Shi H, Zheng L, Zhang LJ et al (2011) Monoenergetic imaging of dual-energy CT reduces artifacts from implanted metal orthopedic devices in patients with factures. Acad Radiol 18(10):1252–1257. https://doi.org/10.1016/j.acra.2011.05.009
Pua R, Wi S, Park M, Lee JR, Cho S (2016) An image-based reduction of metal artifacts in computed tomography. J Comput Assist Tomogr 40(1):131–141. https://doi.org/10.1097/RCT.0000000000000316
Kim JH, Nuyts J, Kuncic Z, Fulton R (2013) The feasibility of head motion tracking in helical CT: a step toward motion correction. Med Phys 40(4):041903–041904. https://doi.org/10.1118/1.4794481
Boas FE, Fleischmann D (2012) CT artifacts: causes and reduction techniques. J Med Imaging 4(2):229–240. https://doi.org/10.1053/j.semradonc.2003.10.004
Yan Z, Hu X, Zhang L, Serikawa S (2014) Analysis and solutions of artifacts on multi-slice spiral CT images. https://doi.org/10.12792/iciae2014.009
Barrett JF (2004) Artifacts in CT: recognition and avoidance. Radiographics 24(6):1679–1691. https://doi.org/10.1148/rg.246045065
Veikutis V, Budrys T, Basevicius A, Lukosevicius S, Gleizniene R, Unikas R et al (2015) Artifacts in computer tomography imaging: how it can really affect diagnostic image quality and confuse clinical diagnosis? J Vibroengineering 17(2):995–1003 https://www.jvejournals.com/article/15949
Kim JH, Nuyts J, Kyme A, Kuncic Z, Fulton R (2015) A rigid motion correction method for helical computed tomography (CT). Phys Med Biol 60(5):2047. https://iopscience.iop.org/article/10.1088/0031-9155/60/5/2047/meta–2073
Zhou P, Zhang C, Gao Z, Cai W, Yan D, Wei Z (2018) Evaluation of the quality of CT images acquired with smart metal artifact reduction software. Open Life Sci 13(1):155–162. https://doi.org/10.1515/biol-2018-0021
Wei Y, Jia F, Hou P, Zha K, Pu S, Gao J (2020) Clinical application of multi-material artifact reduction (MMAR) technique in Revolution CT to reduce metallic dental artifacts. Insights Imaging 11(1):32. https://doi.org/10.1186/s13244-020-0836-1
