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Original Research: LUNG CANCER |

Imprecision in Automated Volume Measurements of Pulmonary Nodules and Its Effect on the Level of Uncertainty in Volume Doubling Time Estimation

Paul J. Nietert, PhD; James G. Ravenel, MD; William M. Leue, BA; James V. Miller, PhD; Katherine K. Taylor, MS; Elizabeth S. Garrett-Mayer, PhD; Gerard A. Silvestri, MD, FCCP
Author and Funding Information

*From the Departments of Biostatistics, Bioinformatics, and Epidemiology (Drs. Nietert and Garrett-Mayer), Radiology (Dr. Ravenel), and Medicine (Ms. Taylor and Dr. Silvestri), Division of Pulmonary and Critical Care, Medical University of South Carolina, Charleston, SC; and General Electric Global Research (Mr. Leue and Dr. Miller), Niskayuna, NY.

Correspondence to: Paul J. Nietert, PhD, Medical University of South Carolina, Biostatistics and Bioinformatics, 135 Cannon St, Suite 303, Charleston, SC 29425; e-mail: nieterpj@musc.edu


Mr. Leue and Dr. Miller are employees of General Electric Global Research (Niskayuna, NY). GE Global Research supplied the GE Lightspeed 16-slice CT scan system. Part of the salaries of Drs. Nietert, Ravenel, and Silvestri, and Ms. Taylor at the Medical University of South Carolina (MUSC) were funded by a contract (No. W81XWH-05-1-0378) from the Department of Defense. No financial support was received by the MUSC from General Electric. Dr. Garrett-Mayer has no conflicts to disclose.

Reproduction of this article is prohibited without written permission from the American College of Chest Physicians (www.chestjournal.org/site/misc/reprints.xhtml).


© 2009 American College of Chest Physicians


Chest. 2009;135(6):1580-1587. doi:10.1378/chest.08-2040
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Background:  Detection of small indeterminate pulmonary nodules (4 to 10 mm in diameter) in clinical practice is increasing, largely because of increased utilization and improved imaging technology. Although there currently exists software for CT scan machines that automate nodule volume estimation, the imprecision associated with volume estimates is particularly poor for nodules ≤ 6 mm in diameter, with greater imprecision associated with increasing CT scan slice thickness. This study examined the effects of the volume estimation error associated with four CT scan slice thicknesses (0.625, 1.25, 2.50, and 5.00 mm) on estimates of volume doubling time (VDT) for solid nodules of various sizes.

Methods:  Data reflecting the accuracy of 1,624 automated volume estimations were obtained from experiments incorporating volume estimation software, performed on a commercially available lung phantom. These data informed mathematical simulations that were used to estimate imprecision around VDT estimates for hypothetical pairs of volume estimates for a given solid pulmonary nodule observed at different time points.

Results:  The confidence intervals around the VDT estimates were extremely wide for 2.50- and 5.00-mm slice thicknesses, often encompassing values traditionally associated with both benignity and malignity for simulated 1- and 2-mm growths in diameter.

Conclusions:  Because of the inaccuracy in automated volume estimation, the confidence a clinician should have in estimating VDT should be highly dependent on the degree of observed growth and on the CT scan slice thickness. The performance of CT scanners with slice thicknesses of ≥ 2.5 mm for assessing growth in pulmonary nodules is essentially inadequate for 1-mm changes in nodule diameter.

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