Estimation of non-solid lung nodule volume with low-dose CT protocols:  effect of reconstruction algorithm and measurement method

Marios A. Gavrielides; Gino DeFilippo; Benjamin P. Berman; Qin Li; Nicholas Petrick; Kurt Schultz; Jenifer Siegelman

doi:10.1117/12.2255982

9 March 2017 Estimation of non-solid lung nodule volume with low-dose CT protocols: effect of reconstruction algorithm and measurement method

Marios A. Gavrielides, Gino DeFilippo, Benjamin P. Berman, Qin Li, Nicholas Petrick, Kurt Schultz, Jenifer Siegelman

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Proceedings Volume 10132, Medical Imaging 2017: Physics of Medical Imaging; 101322P (2017) https://doi.org/10.1117/12.2255982
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Computed tomography is primarily the modality of choice to assess stability of nonsolid pulmonary nodules (sometimes referred to as ground-glass opacity) for three or more years, with change in size being the primary factor to monitor. Since volume extracted from CT is being examined as a quantitative biomarker of lung nodule size, it is important to examine factors affecting the performance of volumetric CT for this task. More specifically, the effect of reconstruction algorithms and measurement method in the context of low-dose CT protocols has been an under-examined area of research. In this phantom study we assessed volumetric CT with two different measurement methods (model-based and segmentation-based) for nodules with radiodensities of both nonsolid (-800HU and -630HU) and solid (-10HU) nodules, sizes of 5mm and 10mm, and two different shapes (spherical and spiculated). Imaging protocols included CTDI_vol typical of screening (1.7mGy) and sub-screening (0.6mGy) scans and different types of reconstruction algorithms across three scanners. Results showed that radio-density was the factor contributing most to overall error based on ANOVA. The choice of reconstruction algorithm or measurement method did not affect substantially the accuracy of measurements; however, measurement method affected repeatability with repeatability coefficients ranging from around 3-5% for the model-based estimator to around 20-30% across reconstruction algorithms for the segmentation–based method. The findings of the study can be valuable toward developing standardized protocols and performance claims for nonsolid nodules.

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Marios A. Gavrielides, Gino DeFilippo, Benjamin P. Berman, Qin Li, Nicholas Petrick, Kurt Schultz, and Jenifer Siegelman "Estimation of non-solid lung nodule volume with low-dose CT protocols: effect of reconstruction algorithm and measurement method", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101322P (9 March 2017); https://doi.org/10.1117/12.2255982

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KEYWORDS

Reconstruction algorithms

Image segmentation

3D modeling

Computed tomography

Lung

Error analysis

Statistical analysis

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