Paper
4 May 2004 Calcification classifications of small nodules identified during CT lung cancer screening
Philip F. Judy, Roberto Riva, Yoshiko Kadota, Francine L. Jacobson
Author Affiliations +
Abstract
The aim of this study was to determine whether radiologists are more likely to report as calcified the small nodules detected during CT lung-cancer screening, if sharper reconstruction filters are utilized. Images were reconstructed with the 2 filters used at our institution for the lung (B50f) and for the mediastinum (B30f). The 4 lung-cancer screening cases were reconstructed with 1.25-mm section thickness at 0.6-mm section increments. Using a lax criterion, 2 radiologists identified the locations of nodular features and rated the likelihood that the features were calcified. There were 302 nodules reports. More of these (57%) were reported on images reconstructed using the smooth filter. Sixty (60) reports were definitely or possibly calcified. Seventy-three percent (73%) calcification reports were from images reconstructed using B50f. There were 27 calcification reports of one of the radiologist that were classified as non-calcified by the other radiologist. Most of calcification reports (81%) of 27 reports on which radiologists disagree regarding the likelihood of calcification were from images reconstructed using B50f. Radiologists are more likely to report small nodules detected during lung-cancer screening as calcified using the sharper reconstruction filter. Whether these nodules are actually calcified or not remains a question.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philip F. Judy, Roberto Riva, Yoshiko Kadota, and Francine L. Jacobson "Calcification classifications of small nodules identified during CT lung cancer screening", Proc. SPIE 5372, Medical Imaging 2004: Image Perception, Observer Performance, and Technology Assessment, (4 May 2004); https://doi.org/10.1117/12.534414
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KEYWORDS
Image filtering

Lung cancer

Computed tomography

Lung

Optical filters

Image enhancement

Data acquisition

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