No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS)
1.J. P. Sieren, J. D. Newell, P. F. Judy, D. A. Lynch, K. S. Chan, J. Guo, and E. A. Hoffman, “Reference standard and statistical model for intersite and temporal comparisons of CT attenuation in a multicenter quantitative lung study,” Med. Phys. 39, 5757–5767 (2012).
2.D. Couper, L. M. LaVange, M. Han, R. G. Barr, E. Bleecker, E. A. Hoffman, R. Kanner, E. Kleerup, F. J. Martinez, P. G. Woodruff, and S. Rennard, “Design of the subpopulations and intermediate outcomes in COPD study (SPIROMICS),” Thorax 69, 491–494 (2014).
4.D. Jin, K. Iyer, E. Hoffman, and P. Saha, “Automated assessment of pulmonary arterial morphology in multi-row detector CT imaging using correspondence with anatomic airway branches,” in Advances in Visual Computing, edited by G. Bebis et al. (Springer International, Cham, Switzerland, 2014), Vol. 8887, pp. 521–530.
5.D. Jin, J. Guo, T. M. Dougherty, K. S. Iyer, E. A. Hoffman, and P. K. Saha, “A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging,” Proc. SPIE 9788, 978816 (2016).
6.N. D. D’Souza, J. M. Reinhardt, and E. A. Hoffman, “ASAP: Interactive quantification of 2D airway geometry,” Proc. SPIE 2709, 180–196 (1996).
7.S. N. Friedman, G. S. Fung, J. H. Siewerdsen, and B. M. Tsui, “A simple approach to measure computed tomography (CT) modulation transfer function (MTF) and noise-power spectrum (NPS) using the American College of Radiology (ACR) accreditation phantom,” Med. Phys. 40, 051907 (9pp.) (2013).
8.S. Richard, D. B. Husarik, G. Yadava, S. N. Murphy, and E. Samei, “Towards task-based assessment of CT performance: System and object MTF across different reconstruction algorithms,” Med. Phys. 39, 4115–4122 (2012).
9.M. E. Pique, “Rotation tools,” in Graphics Gems, edited by A. S. Glassner (Academic Inc., Cambridge, MA, 1990), pp. 465–469.
10.D. Gruber, “The mathematics of the 3D rotation matrix,” in Xtreme Game Developers Conference, Santa Clara, CA (2000).
11.S. N. Wood, Generalized Additive Models: An Introduction with r (Chapman & Hall/CRC, Boca Raton, FL, 2006).
12.J. C. Pinheiro and D. M. Bates, Mixed-Effects Models in S and S-PLUS (Springer, New York, NY, 2000).
13.A. W. Van der Vaart, Asymptotic Statistics (Cambridge University Press, Cambridge, England, 2000).
Article metrics loading...
A test object (phantom) is an important tool to evaluate comparability and stability of CTscanners used in multicenter and longitudinal studies. However, there are many sources of error that can interfere with the test object-derived quantitative measurements. Here the authors investigated three major possible sources of operator error in the use of a test object employed to assess pulmonary density-related as well as airway-related metrics.
Two kinds of experiments were carried out to assess measurement variability caused by imperfect scanning status. The first one consisted of three experiments. A COPDGene test object was scanned using a dual source multidetector computed tomographic scanner (Siemens Somatom Flash) with the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) inspiration protocol (120 kV, 110 mAs, pitch = 1, slice thickness = 0.75 mm, slice spacing = 0.5 mm) to evaluate the effects of tilt angle, water bottle offset, and air bubble size. After analysis of these results, a guideline was reached in order to achieve more reliable results for this test object. Next the authors applied the above findings to 2272 test object scans collected over 4 years as part of the SPIROMICS study. The authors compared changes of the data consistency before and after excluding the scans that failed to pass the guideline.
This study established the following limits for the test object: tilt index ≤0.3, water bottle offset limits of [−6.6 mm, 7.4 mm], and no air bubble within the water bottle, where tilt index is a measure incorporating two tilt angles around x- and y-axis. With 95% confidence, the density measurement variation for all five interested materials in the test object (acrylic, water,lung, inside air, and outside air) resulting from all three error sources can be limited to ±0.9 HU (summed in quadrature), when all the requirements are satisfied. The authors applied these criteria to 2272 SPIROMICS scans and demonstrated a significant reduction in measurement variation associated with the test object.
Three operator errors were identified which significantly affected the usability of the acquired scan images of the test object used for monitoring scanner stability in a multicenter study. The authors’ results demonstrated that at the time of test object scan receipt at a radiology core laboratory, quality control procedures should include an assessment of tilt index, water bottle offset, and air bubble size within the water bottle. Application of this methodology to 2272 SPIROMICS scans indicated that their findings were not limited to the scanner make and model used for the initial test but was generalizable to both Siemens and GE scanners which comprise the scanner types used within the SPIROMICS study.
Full text loading...
Most read this month