Document Detail

Benefit of Overlapping Reconstruction for Improving the Quantitative Assessment of CT Lung Nodule Volume.
MedLine Citation:
PMID:  23085408     Owner:  NLM     Status:  Publisher    
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.
Marios A Gavrielides; Rongping Zeng; Kyle J Myers; Berkman Sahiner; Nicholas Petrick
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-18
Journal Detail:
Title:  Academic radiology     Volume:  -     ISSN:  1878-4046     ISO Abbreviation:  Acad Radiol     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-22     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9440159     Medline TA:  Acad Radiol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2012 AUR. Published by Elsevier Inc. All rights reserved.
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. Electronic address:
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