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Volume Quantitation of Small Pulmonary Nodules on Low-dose Chest CT: A Phantom Study

DATE: 11/26/2001 - 11/26/2001

(C17) Chest (Nodule Detection and Analysis)
(C17-374) Detection of Calcium in Small Pulmonary Nodules Using Multi-slice CT Scanners: Implications for Lung Cancer Screening
(C17-383) Low-Dose Lung Cancer Screening Using Multidetector-row CT System: Utility of the MIP Image for Improvement of Detectability
(C17-375) Wavelet Compression of Low-dose Chest CT: Effect on Nodule Detection
(C17-376) Missed Lung Cancers in Low-dose Helical CT Screening Obtained from a General Population
(C17-377) Volumetric Growth Index (VGI) for Small Pulmonary Nodules: Development and Validation
(C17-378) Automated Segmentation and Volumetry of Small Pulmonary Nodules: Comparison of Low Dose and Standard Dose 1-mm Multidetector-Row CT Studies
(C17-379) Volume Quantitation of Small Pulmonary Nodules on Low-dose Chest CT: A Phantom Study
(C17-380) Performance of Automated CT Lung Nodule Detection on Missed Cancers
(C17-381) Patient-specific Models for Lung Nodule Detection and Surveillance in CT
(C17-382) Maximum Intensity Projection (MIP) Processing in the Detection of Small Pulmonary Nodules: Incremental Benefit Using Multi-detector Computed Tomography (CT) Data Sets

    Jane Ko MD
    Henry Rusinek PhD
    Ramesh Chandra PhD
    Georgeann McGuinness MD
    Margrit Betke PhD
    David Naidich MD


Purpose: To evaluate 3D algebraic and threshold methods for volumetric quantitation of small pulmonary nodules on low-dose multi-detector computed tomography (CT) that is used in lung-cancer screening.

Methods and Materials: 40 plastic nodules (20 ground glass and 20 soft-tissue density) were embedded in a chest phantom comprised of material with the attenuation of lung parenchyma (-790 HU). Four groups of nodules contained 5 nodules each, all <5 mm in diameter. Nodule mass and specific gravity were used to calculate the true volume (V). The phantom was imaged using a multi-detector CT scanner (0.5 sec/rotation, 140 kVp, 1.0 mm collimation) using low-dose (20 mAs) technique. Data were reconstructed in 1.25 mm sections at 1.0 mm intervals, FOV 38 cm using a high-frequency reconstruction algorithm. Imaged nodule volumes were calculated using three 3-D quantitative techniques: (a) an algebraic method that uses density in a region of interest to correct for partial volume effect, (b) a fixed threshold method (FT) that uses a threshold of -500 HU, and (c) a variable threshold method (VT) that uses a threshold calculated from the HU of pure nodule and adjacent lung. Measured volumes were correlated to Vs, and residual volume errors were calculated. Any effect of nodule attenuation, size, and location within the lung on volume error was identified.

Results: The mean Vs of the 4 nodule size categories were 63.2 +/- 4.5 mm3, 36.3+/- 2.8 mm3, 18.6 +/- 1.4 mm3, 8.0 +/- 0.6 mm3 correlating with diameters of 4.9, 4.1, 3.3, 2.5 mm. The algebraic method's mean residual volume error (3.7 mm3, r=0.97) was significantly lower (P=0.024) than the volume error of the VT (5.7 mm3, r=0.94) and FT (5.6 mm3, r=0.93) methods. The algebraic method had a significant (P<0.001) increase in residual error for ground-glass nodules (5.37 mm3) as compared to solid nodules (1.99 mm3) while VT and FT did not. The mean residual volume error for Vs of 63.2, 36.3, 18.6, 8.0 mm3 were 7.06, 5.08, 4.33, 3.48 mm3, respectively. For nodule location, mean residual volume errors for anterior, medial, central, posterior, and lateral positions were 5.39, 5.60, 4.57, 5.72, 3.26 mm3, respectively.

Conclusion: A 3-D algebraic method can improve nodule quantitation by decreasing the partial volume effect and can potentially detect changes in nodule volume in patients who undergo low-dose multi-detector screening CT.





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