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Abstract: Purpose: To retrospectively evaluate whether baseline nodule density or changes in density or nodule features could be used to discriminate between benign and malignant solid indeterminate nodules. Materials and methods: Solid indeterminate nodules between 50 and 500mm3 (4.6–9.8mm) were assessed at 3 and 12 months after baseline lung cancer screening (NELSON study). Nodules were classified based on morphology (spherical or non-spherical), shape (round, polygonal or irregular) and margin (smooth, lobulated, spiculated or irregular). The mean CT density of the nodule was automatically generated in Hounsfield units (HU) by the Lungcare© software. Results: From April 2004 to July 2006, 7310 participants underwent baseline screening. In 312 participants 372 solid purely intra-parenchymal nodules were found. Of them, 16 (4%) were malignant. Benign nodules were 82.8mm3 (5.4mm) and malignant nodules 274.5mm3 (8.1mm) (p =0.000). Baseline CT density for benign nodules was 42.7HU and for malignant nodules −2.2HU (p =ns). The median change in density for benign nodules was −0.1HU and for malignant nodules 12.8HU (p <0.05). Compared to benign nodules, malignant nodules were more often non-spherical, irregular, lobulated or spiculated at baseline, 3-month and 1-year follow-up (p <0.0001). In the majority of the benign and malignant nodules there was no change in morphology, shape and margin during 1 year of follow-up (p =ns). Conclusion: Baseline nodule density and changes in nodule features cannot be used to discriminate between benign and malignant solid indeterminate pulmonary nodules, but an increase in density is suggestive for malignancy and requires a shorter follow-up or a biopsy. [Copyright &y& Elsevier]

Purpose: To evaluate prospectively the value of size, shape, margin and density in discriminating between benign and malignant CT screen detected solid non-calcified pulmonary nodules. Material and Methods: This study was institutional review board approved. For this study 405 participants of the NELSON lung cancer screening trial with 469 indeterminate or potentially malignant solid pulmonary nodules (>50mm3) were selected. The nodules were classified based on size, shape (round, polygonal, irregular) and margin (smooth, lobulated, spiculated). Mean nodule density and nodule volume were automatically generated by software. Analyses were performed by univariate and multivariate logistic regression. Results were presented as likelihood ratios (LR) with 95% confidence intervals (CI). Receiver operating characteristic analysis was performed for mean density as predictor for lung cancer. Results: Of the 469 nodules, 387 (83%) were between 50 and 500mm3, 82 (17%) >500mm3, 59 (13%) malignant, 410 (87%) benign. The median size of the nodules was 103mm3 (range 50-5486mm3). In multivariate analysis lobulated nodules had LR of 11 compared to smooth; spiculated nodules a LR of 7 compared to smooth; irregular nodules a LR of 6 compared to round and polygonal; volume a LR of 3. The mean nodule CT density did not predict the presence of lung cancer (AUC 0.37, 95% CI 0.32-0.43). Conclusion: In solid non-calcified nodules larger than 50mm3, size and to a lesser extent a lobulated or spiculated margin and irregular shape increased the likelihood that a nodule was malignant. Nodule density had no discriminative power. [ABSTRACT FROM AUTHOR]

Purpose: To retrospectively evaluate the performance of consensus double reading compared with single reading at baseline screening of a lung cancer computed tomography (CT) screening trial., Materials and Methods: The study was approved by the Dutch Minister of Health and ethical committees. Written informed consent was obtained from all participants. The benefit of consensus double reading was expressed by the percentage change in cancer detection rate, recall rate, number of additional nodules detected, and change in sensitivity and specificity in 7557 participants. The reference standard was a retrospective analysis of the serial CT scans performed in participants diagnosed with lung cancer during a 2-year period after baseline. Semiautomated volumetric software was used for nodule evaluation. McNemar tests were performed to test statistical significance. In addition, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated and 95% confidence intervals (CIs) constructed., Results: Seventy-four cases of lung cancer were qualified as detectable at baseline. Compared with single reading, consensus double reading did not increase the cancer detection rate (2.7%; 95% CI: -1.0%, 6.4%; P = .50) or change the recall rate (20.6% vs 20.8%, P = .28), but led to the detection of 19.0% (1635 of 8623; 95% CI: 18.0%, 19.9%, P < .01) more nodules. The sensitivity, specificity, PPV, and NPV were 95.9% (71 of 74), 80.2% (6001 of 7483), 4.6% (71 of 1553) and 99.9% (6001 of 6004) for single reading and 98.6% (73 of 74), 80.0% (1497 of 7483), 4.6% (73 of 1570), and 99.9% (5986 of 5987) for consensus double reading, respectively., Conclusion: There is no statistically significant benefit for consensus double reading at baseline screening for lung cancer with the use of a nodule management strategy based solely on semiautomated volumetry., (© RSNA, 2011.)

Purpose: To retrospectively assess volume measurement variability in solid pulmonary nodules (volume, 15-500 mm(3)) detected at lung cancer screening and to quantify the independent effects of nodule morphology, size, and location., Materials and Methods: This retrospective study was a substudy of the screening program that was approved by the Dutch Ministry of Health, and all participants provided written informed consent. Two independent readers used semiautomated software to measure the volume of pulmonary nodules detected in 6774 participants aged 50-75 years (5917 men). Nodules were classified according to their location (purely intraparenchymal, pleural based, juxtavascular, or fissure attached), morphology (smooth, polylobulated, spiculated, or irregular), and size (50 mm(3)). The level of agreement was expressed by using the absolute values of the relative volume differences (RVDs). Multivariate logistic regression analysis was performed, and odds ratios (ORs) were computed to quantify the independent effects of morphology, location, and size on RVD categories., Results: Altogether, 4225 nodules in 2239 participants were included. Complete agreement in volume was obtained for 3646 (86%) of the nodules. Disagreement was small (absolute value of RVD < 5%) for 173 (4%) nodules, moderate (absolute value of RVD >or= 5% but < 15%) for 232 (6%), and large (absolute value of RVD >or= 15%) for 174 (4%). Multivariate analysis showed that the ORs of volume disagreement were 15.7, 3.1, and 1.9 for irregular, spiculated, and polylobulated nodules, respectively; 3.5, 2.6, and 2.1 for juxtavascular, pleural-based, and fissure-attached nodules, respectively; and 1.3 for large nodules compared with smooth, purely intraparenchymal, and small reference nodules., Conclusion: Nodule morphology, location, and size influence volume measurement variability, particularly for juxtavascular and irregular nodules.