Automated continuous quantitative measurement of proximal airways on dynamic ventilation CT: initial experience using an ex vivo porcine lung phantom
Authors Yamashiro T, Tsubakimoto M, Nagatani Y, Moriya H, Sakuma K, Tsukagoshi S, Inokawa H, Kimoto T, Teramoto R, Murayama S
Received 29 April 2015
Accepted for publication 16 June 2015
Published 25 September 2015 Volume 2015:10(1) Pages 2045—2054
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Charles Downs
Peer reviewer comments 3
Editor who approved publication: Dr Richard Russell
Tsuneo Yamashiro,1 Maho Tsubakimoto,1 Yukihiro Nagatani,2 Hiroshi Moriya,3 Kotaro Sakuma,3 Shinsuke Tsukagoshi,4 Hiroyasu Inokawa,5 Tatsuya Kimoto,5 Ryuichi Teramoto,6 Sadayuki Murayama1
1Department of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa; 2Department of Radiology, Shiga University of Medical Science, Otsu; 3Department of Radiology, Ohara General Hospital, Fukushima; 4CT Systems Division, 5Center for Medical Research and Development, Toshiba Medical Systems Corporation, Otawara; 6Corporate Manufacturing Engineering Center, Toshiba Corporation, Yokohama, Japan
Background: The purpose of this study was to evaluate the feasibility of continuous quantitative measurement of the proximal airways, using dynamic ventilation computed tomography (CT) and our research software.
Methods: A porcine lung that was removed during meat processing was ventilated inside a chest phantom by a negative pressure cylinder (eight times per minute). This chest phantom with imitated respiratory movement was scanned by a 320-row area-detector CT scanner for approximately 9 seconds as dynamic ventilatory scanning. Obtained volume data were reconstructed every 0.35 seconds (total 8.4 seconds with 24 frames) as three-dimensional images and stored in our research software. The software automatically traced a designated airway point in all frames and measured the cross-sectional luminal area and wall area percent (WA%). The cross-sectional luminal area and WA% of the trachea and right main bronchus (RMB) were measured for this study. Two radiologists evaluated the traceability of all measurable airway points of the trachea and RMB using a three-point scale.
Results: It was judged that the software satisfactorily traced airway points throughout the dynamic ventilation CT (mean score, 2.64 at the trachea and 2.84 at the RMB). From the maximum inspiratory frame to the maximum expiratory frame, the cross-sectional luminal area of the trachea decreased 17.7% and that of the RMB 29.0%, whereas the WA% of the trachea increased 6.6% and that of the RMB 11.1%.
Conclusion: It is feasible to measure airway dimensions automatically at designated points on dynamic ventilation CT using research software. This technique can be applied to various airway and obstructive diseases.
Keywords: computed tomography, dynamic ventilation CT, airway, luminal area, wall area percent, COPD
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