Effect of Computed Tomography Dose on Quantitative Measurement and Automated Segmentation of Airway Tree

被引:6
作者
Yu Nan [1 ]
Xin Xiao-Min [1 ]
Li Yan [1 ]
Ma Jun-Chao [1 ]
Gao Jun-Gang [1 ]
Jin Chen-Wang [2 ]
Guo You-Min [1 ]
机构
[1] Xi An Jiao Tong Univ, Affiliated Hosp 1, Pet CT Ctr, Xian 710061, Peoples R China
[2] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Radiol, Xian 710061, Peoples R China
关键词
Airway Diseases; Low-Dose CT; Quantitative Measurement; Lung; LUNG-CANCER; CT; MORTALITY; NODULES; DISEASE; SCANS; COPD;
D O I
10.1166/jmihi.2015.1558
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
A fully automated computerized scheme that can segment an airway depicted on computed tomography (CT) images has certain advantages, particularly its simplicity and reliability. However, the CT scanning dose may affect the obtained measurement. In this study, we investigate whether the low-dose CT can be used to quantitative analysis of airway dimensions, which were measured by a computerized scheme. The study comprises twelve lung chest CT examinations acquired from three dogs with different beam currents of 30, 50, 100, and 200 mAs. At each dose, the lumen diameters, wall area, and lumen area of the matched airways (n = 82) were measured by this scheme. The bronchial segmentation ability and the measurement variability at individual dose were compared to that obtained at 200 mAs. Finally, we found that the CT dose impacts the measurement variability of the airway diameter (P < 0.01) and of the percentage of wall area (WA%) (P < 0.05). To obtain the same image quality, a CT dose of no less than 50 mAs should be selected since the percentage of leakage and/or obstruction bronchus at 30 mAs was significantly different from that at 200 mAs (P < 0.00). In conclusion, the airway tree segmentation algorithms by the fully automated computerized scheme are feasible on low-dose CT at doses as low as 50 mAs. However, the scanning dose does affect the obtained measurements.
引用
收藏
页码:1519 / 1523
页数:5
相关论文
共 50 条
[41]   Automated method for structural segmentation of nasal airways based on cone beam computed tomography [J].
Tymkovych, Maksym Yu. ;
Avrunin, Oleg G. ;
Paliy, Victor G. ;
Filzow, Maksim ;
Gryshkov, Oleksandr ;
Glasmacher, Birgit ;
Omiotek, Zbigniew ;
Dzierzak, Roza ;
Smailova, Saule ;
Kozbekova, Ainur .
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH ENERGY PHYSICS EXPERIMENTS 2017, 2017, 10445
[42]   Automated Segmentation of Left Ventricular Myocardium on Cardiac Computed Tomography Using Deep Learning [J].
Koo, Hyun Jung ;
Lee, June-Goo ;
Ko, Ji Yeon ;
Lee, Gaeun ;
Kang, Joon-Won ;
Kim, Young-Hak ;
Yang, Dong Hyun .
KOREAN JOURNAL OF RADIOLOGY, 2020, 21 (06) :660-669
[44]   Computed Tomography Assessment of Airways Throughout Bronchial Tree Demonstrates Airway Narrowing in Severe Asthma [J].
Brillet, Pierre-Yves ;
Debray, Marie-Pierre ;
Golmard, Jean-Louis ;
Hmeidi, Yahya Ould ;
Fetita, Catalin ;
Taille, Camille ;
Aubier, Michel ;
Grenier, Philippe A. .
ACADEMIC RADIOLOGY, 2015, 22 (06) :734-742
[45]   Effect of Segmental Bronchoalveolar Lavage on Quantitative Computed Tomography of the Lung [J].
Gabe, Luke M. ;
Baker, Kimberly M. ;
van Beek, Edwin J. R. ;
Hunninghake, Gary W. ;
Reinhardt, Joseph M. ;
Hoffman, Eric A. .
ACADEMIC RADIOLOGY, 2011, 18 (07) :876-884
[46]   Automated Lung Segmentation on Chest Computed Tomography Images with Extensive Lung Parenchymal Abnormalities Using a Deep Neural Network [J].
Yoo, Seung-Jin ;
Yoon, Soon Ho ;
Lee, Jong Hyuk ;
Kim, Ki Hwan ;
Choi, Hyoung In ;
Park, Sang Joon ;
Goo, Jin Mo .
KOREAN JOURNAL OF RADIOLOGY, 2021, 22 (03) :476-488
[47]   Computed tomography mucus plugs and airway tree structure in patients with chronic obstructive pulmonary disease: Associations with airflow limitation, health-related independence and mortality [J].
Tanabe, Naoya ;
Shimizu, Kaoruko ;
Shima, Hiroshi ;
Wakazono, Nobuyasu ;
Shiraishi, Yusuke ;
Terada, Kunihiko ;
Terada, Satoru ;
Oguma, Tsuyoshi ;
Sakamoto, Ryo ;
Suzuki, Masaru ;
Makita, Hironi ;
Sato, Atsuyasu ;
Sato, Susumu ;
Nishimura, Masaharu ;
Konno, Satoshi ;
Hirai, Toyohiro .
RESPIROLOGY, 2024, 29 (11) :951-961
[48]   The use of contrast for automated pulmonary nodule detection in low-dose computed tomography [J].
Narayan, TK ;
Herman, GT .
MEDICAL PHYSICS, 1999, 26 (03) :427-437
[49]   A robust and semi-automatic quantitative measurement of patellofemoral instability based on four dimensional computed tomography [J].
Chen, Hao ;
Kluijtmans, Leo ;
Bakker, Max ;
Dunning, Hans ;
Kang, Yan ;
van de Groes, Sebastiaan ;
Sprengers, Andre M. J. ;
Verdonschot, Nico .
MEDICAL ENGINEERING & PHYSICS, 2020, 78 :29-38
[50]   Three-Dimensional Reconstruction of the Bony Nasolacrimal Canal by Automated Segmentation of Computed Tomography Images [J].
Janez-Garcia, Lucia ;
Saenz-Frances, Federico ;
Ramirez-Sebastian, Jose M. ;
Toledano-Fernandez, Nicolas ;
Urbasos-Pascual, Maria ;
Janez-Escalada, Luis .
PLOS ONE, 2016, 11 (05)