The aim of this study was to assess interobserver variability in size determination of pulmonary nodules at spiral CT. Twenty-three patients with known pulmonary nodules (diameter 2–40 mm, mean diameter 7 mm) underwent spiral chest CT (collimation 5 mm, pitch 1). Images were reconstructed at 3- and 5-mm intervals (RI). Hard copies were analyzed by two radiologists who recorded every nodule with regard to location, diagnostic confidence (“definite,”“probable”) and nodule size in increments of 1 mm with specific attention to correct classification into one of three size classes (≤ 5 mm, 6–10 mm, > 10 mm). Interobserver variability was determined with Pearson's correlation coefficient and k measure. Of a total of 286 nodules, 103 nodules were found accordingly by both readers at 3 mm RI, and 96 at 5 mm RI. There was a good correlation of measurements (in millimeters) between both readers (Pearson's correlation coefficient: 0.89–0.95). Interobserver variability in categories was good at both reconstruction intervals (k: 0.61 at 3 mm, 0.74 at 5 mm RI) and very good (0.81) at 5 mm RI when uncertain nodules were excluded. Spiral CT allows reproducible size determination of pulmonary nodules as shown by good interobserver agreement in exact size measurement and categorization into three size classes.

OBJECTIVE:Our aim was to assess the sensitivity of helical CT for revealing pulmonary nodules. Thoracotomy with palpation of the deflated lung, resection, and histologic examination of palpable nodules was used as the gold standard.SUBJECTS AND METHODS:Thirteen patients underwent helical CT (slice thickness, 5 mm; reconstruction intervals, 3 mm and 5 mm; interpreted by two independent observers). Subsequently, patients underwent unilateral (n = 6) or bilateral (n = 7) surgical exploration, and CT-surgical correlation of 20 lungs was performed.RESULTS:Ninety nodules were resected (61 were smaller than 6 mm; 13 were 6-10 mm; 11 were larger than 10 mm; in five nodules, the size was not recorded at surgery). Sixty-nine nodules were located in the pulmonary parenchyma and 21 in the visceral pleura. Of the 90 lesions, 43 (48%) were found on histology to represent metastases. For lesions detected by at least one observer, the sensitivity of helical CT was 69% for intrapulmonary nodules smaller than 6 mm, 95% for intrapulmonary nodules larger than or equal to 6 mm, and 100% for histologically proven intrapulmonary metastases larger than or equal to 6 mm. For lesions smaller than or equal to 10 mm, sensitivity was better using a reconstruction interval of 3 mm rather than of 5 mm.CONCLUSION:In this study, the sensitivity of helical CT exceeded the sensitivity of conventional CT in previous reports. However, because of limitations in the detection of intrapulmonary nodules smaller than 6 mm and of pleural lesions, complete surgical exploration should remain the procedure of choice in patients undergoing pulmonary metastasectomy. Preoperative helical CT should be used to guide the surgeon to lesions that are difficult to palpate.

The aim of this study was to analyze whether overlapping image reconstruction increases numbers of pulmonary nodules detected at helical CT. Forty-eight helical CT scans (21 with a slice thickness of 10 mm; 27 with a slice thickness of 5 mm) of patients with known pulmonary nodules were reconstructed both with overlapping and non-overlapping image reconstruction. Two readers recorded number and size of pulmonary nodules as well as diagnostic confidence. With overlapping image reconstruction each reader diagnosed more pulmonary nodules (slice thickness 10 mm: +24.0 and +26.7%, both p < 0.01; slice thickness 5 mm: +9.5 and +11.9%, both not significant) and more "definite" nodules (slice thickness 10 mm: +20.3%, p < 0.05, and +30.8%, p < 0.005; slice thickness 5 mm: +18.0 and +17.0%, both p < 0.05). Nodules diagnosed with overlapping image reconstruction only were almost exclusively smaller than the slice thickness. The increase in number of nodules detected was not associated with a decrease in diagnostic confidence. Overlapping image reconstruction improves detection of pulmonary nodules smaller than the slice thickness at spiral CT.