Volumetric measurement of synthetic lung nodules with multi-detector row CT: effect of various image reconstruction parameters and segmentation thresholds on measurement accuracy.

Abstract

To evaluate the effect of various multi-detector row computed tomographic (CT) reconstruction parameters and nodule segmentation thresholds on the accuracy of volumetric measurement of synthetic lung nodules. Synthetic lung nodules of four different diameters (3.2, 4.8, 6.4, and 12.7 mm) were scanned with multi-detector row CT. Images were reconstructed at various section thicknesses (0.75, 1.0, 2.0, 3.0, and 5.0 mm), fields of view (30, 20, and 10 cm), and reconstruction intervals (0.5, 1.0, and 2.0 mm). The nodules were segmented from the simulated background lung region by using four segmentation thresholds (-300, -400, -500, and -600 HU), and their volumes were estimated and compared with a reference standard (measurements according to fluid displacement) by computing the absolute percentage error (APE). APE was regressed against nodule size, and multivariate analysis of variance (MANOVA) was performed with APE as the dependent variable and with four within-subject factors (field of view, reconstruction interval, threshold, and section thickness). The MANOVA demonstrated statistically significant effects for threshold (P = .02), section thickness (P < .01), and interaction of threshold and section thickness (P = .04). The regression of mean APE values on nodule size indicates that APE progressively increases with decreasing synthetic nodule size (R2 = 0.99, P < .01). For accurate measurement of lung nodule volume, it is critical to select a section thickness and/or segmentation threshold appropriate for the size of a nodule.