Marios A Gavrielides1, Rongping Zeng, Kyle J Myers, Berkman Sahiner, Nicholas Petrick. 1. Division of Imaging and Applied Mathematics, Office of Science and Engineering Laboratories, Center for Devices and Radiological Health, US Food and Drug Administration, 10903 New Hampshire Avenue, Building 62, Room 4114, Silver Spring, MD 20993, USA. marios.gavrielides@fda.hhs.gov
Abstract
RATIONALE AND OBJECTIVES: The aim of this study was to quantify the effect of overlapping reconstruction on the precision and accuracy of lung nodule volume estimates in a phantom computed tomographic (CT) study. MATERIALS AND METHODS: An anthropomorphic phantom was used with a vasculature insert on which synthetic lung nodules were attached. Repeated scans of the phantom were acquired using a 64-slice CT scanner. Overlapping and contiguous reconstructions were performed for a range of CT imaging parameters (exposure, slice thickness, pitch, reconstruction kernel) and a range of nodule characteristics (size, density). Nodule volume was estimated with a previously developed matched-filter algorithm. RESULTS: Absolute percentage bias across all nodule sizes (n = 2880) was significantly lower when overlapping reconstruction was used, with an absolute percentage bias of 6.6% (95% confidence interval [CI], 6.4-6.9), compared to 13.2% (95% CI, 12.7-13.8) for contiguous reconstruction. Overlapping reconstruction also showed a precision benefit, with a lower standard percentage error of 7.1% (95% CI, 6.9-7.2) compared with 15.3% (95% CI, 14.9-15.7) for contiguous reconstructions across all nodules. Both effects were more pronounced for the smaller, subcentimeter nodules. CONCLUSIONS: These results support the use of overlapping reconstruction to improve the quantitative assessment of nodule size with CT imaging. Published by Elsevier Inc.
RATIONALE AND OBJECTIVES: The aim of this study was to quantify the effect of overlapping reconstruction on the precision and accuracy of lung nodule volume estimates in a phantom computed tomographic (CT) study. MATERIALS AND METHODS: An anthropomorphic phantom was used with a vasculature insert on which synthetic lung nodules were attached. Repeated scans of the phantom were acquired using a 64-slice CT scanner. Overlapping and contiguous reconstructions were performed for a range of CT imaging parameters (exposure, slice thickness, pitch, reconstruction kernel) and a range of nodule characteristics (size, density). Nodule volume was estimated with a previously developed matched-filter algorithm. RESULTS: Absolute percentage bias across all nodule sizes (n = 2880) was significantly lower when overlapping reconstruction was used, with an absolute percentage bias of 6.6% (95% confidence interval [CI], 6.4-6.9), compared to 13.2% (95% CI, 12.7-13.8) for contiguous reconstruction. Overlapping reconstruction also showed a precision benefit, with a lower standard percentage error of 7.1% (95% CI, 6.9-7.2) compared with 15.3% (95% CI, 14.9-15.7) for contiguous reconstructions across all nodules. Both effects were more pronounced for the smaller, subcentimeter nodules. CONCLUSIONS: These results support the use of overlapping reconstruction to improve the quantitative assessment of nodule size with CT imaging. Published by Elsevier Inc.
Authors: Stefano Young; Hyun J Grace Kim; Moe Moe Ko; War War Ko; Carlos Flores; Michael F McNitt-Gray Journal: Med Phys Date: 2015-05 Impact factor: 4.071
Authors: Andrew J Buckler; Jovanna Danagoulian; Kjell Johnson; Adele Peskin; Marios A Gavrielides; Nicholas Petrick; Nancy A Obuchowski; Hubert Beaumont; Lubomir Hadjiiski; Rudresh Jarecha; Jan-Martin Kuhnigk; Ninad Mantri; Michael McNitt-Gray; Jan H Moltz; Gergely Nyiri; Sam Peterson; Pierre Tervé; Christian Tietjen; Etienne von Lavante; Xiaonan Ma; Samantha St Pierre; Maria Athelogou Journal: Acad Radiol Date: 2015-09-14 Impact factor: 3.173