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Updated: Mar 26, 2026

Author Spotlight: A 3D Digital Model for the Diagnosis and Treatment of Pulmonary Nodules
Published on: May 19, 2023
Volume estimation of multidensity nodules with thoracic computed tomography
Marios A Gavrielides1, Qin Li1, Rongping Zeng1
1U.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.
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 [Formula: see text] ranging from [Formula: see text] to 6.6% for the entire object (standard deviation ranged from 1.5% to 7.6%), and within [Formula: see text] 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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