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Erschienen in: European Radiology 6/2014

01.06.2014 | Chest

Optimal image reconstruction for detection and characterization of small pulmonary nodules during low-dose CT

verfasst von: SayedMasoud Hashemi, Hatem Mehrez, Richard S. C. Cobbold, Narinder S. Paul

Erschienen in: European Radiology | Ausgabe 6/2014

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Abstract

Objectives

To optimize the slice thickness/overlap parameters for image reconstruction and to study the effect of iterative reconstruction (IR) on detectability and characterization of small non-calcified pulmonary nodules during low-dose thoracic CT.

Materials and methods

Data was obtained from computer simulations, phantom, and patient CTs. Simulations and phantom CTs were performed with 9 nodules (5, 8, and 10 mm with 100, −630, and −800 HU). Patient data were based on 11 ground glass opacities (GGO) and 9 solid nodules. For each analysis the nodules were reconstructed with filtered back projection and IR algorithms using 10 different combinations of slice thickness/overlap (0.5–5 mm). The attenuation (CT#) and the contrast to noise ratio (CNR) were measured. Spearman’s coefficient was used to correlate the error in CT# measurements and slice thickness. Paired Student’s t test was used to measure the significance of the errors.

Results

CNR measurements: CNR increases with increasing slice thickness/overlap for large nodules and peaks at 4.0/2.0 mm for smaller ones. Use of IR increases the CNR of GGOs by 60 %.
CT# measurements: Increasing slice thickness/overlap above 3.0/1.5 mm results in decreased CT# measurement accuracy.

Conclusion

Optimal detection of small pulmonary nodules requires slice thickness/overlap of 4.0/2.0 mm. Slice thickness/overlap of 2.0/2.0 mm is required for optimal nodule characterization. IR improves conspicuity of small ground glass nodules through a significant increase in nodule CNR.

Key Points

• Slice thickness/overlap affects the accuracy of pulmonary nodule detection and characterization.
• Slice thickness ≥3 mm increases the risk of misclassifying small nodules.
• Optimal nodule detection during low-dose CT requires 4.0/2.0-mm reconstructions.
• Optimal nodule characterization during low-dose CT requires 2.0/2.0-mm reconstructions.
• Iterative reconstruction improves the CNR of ground glass nodules by 60 %.
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Metadaten
Titel
Optimal image reconstruction for detection and characterization of small pulmonary nodules during low-dose CT
verfasst von
SayedMasoud Hashemi
Hatem Mehrez
Richard S. C. Cobbold
Narinder S. Paul
Publikationsdatum
01.06.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
European Radiology / Ausgabe 6/2014
Print ISSN: 0938-7994
Elektronische ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-014-3142-9

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