Physics of Medical Imaging

Volume estimation of multidensity nodules with thoracic computed tomography

[+] Author Affiliations
Marios A. Gavrielides, Qin Li, Rongping Zeng, Kyle J. Myers, Berkman Sahiner, Nicholas Petrick

U.S. Food and Drug Administration, Division of Imaging, Diagnostics, and Software Reliability (DIDSR), Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, 10903 New Hampshire Avenue, Building 62, Room 4126, Silver Spring, Maryland 20993, United States

J. Med. Imag. 3(1), 013504 (Jan 29, 2016). doi:10.1117/1.JMI.3.1.013504
History: Received April 14, 2015; Accepted December 18, 2015
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Abstract.  This work focuses on volume estimation of “multidensity” lung nodules in a phantom computed tomography study. Eight objects were manufactured by enclosing spherical cores within larger spheres of double the diameter but with a different density. Different combinations of outer-shell/inner-core diameters and densities were created. The nodules were placed within an anthropomorphic phantom and scanned with various acquisition and reconstruction parameters. The volumes of the entire multidensity object as well as the inner core of the object were estimated using a model-based volume estimator. Results showed percent volume bias across all nodules and imaging protocols with slice thicknesses <5  mm ranging from 5.1% to 6.6% for the entire object (standard deviation ranged from 1.5% to 7.6%), and within 12.6% to 5.7% for the inner-core measurement (standard deviation ranged from 2.0% to 17.7%). Overall, the estimation error was larger for the inner-core measurements, which was expected due to the smaller size of the core. Reconstructed slice thickness was found to substantially affect volumetric error for both tasks; exposure and reconstruction kernel were not. These findings provide information for understanding uncertainty in volumetry of nodules that include multiple densities such as ground glass opacities with a solid component.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Marios A. Gavrielides ; Qin Li ; Rongping Zeng ; Kyle J. Myers ; Berkman Sahiner, et al.
"Volume estimation of multidensity nodules with thoracic computed tomography", J. Med. Imag. 3(1), 013504 (Jan 29, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.1.013504


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