Comparison of the effects of model-based iterative reconstruction and filtered back projection algorithms on software measurements in pulmonary subsolid nodules
- 391 Downloads
To evaluate the differences between filtered back projection (FBP) and model-based iterative reconstruction (MBIR) algorithms on semi-automatic measurements in subsolid nodules (SSNs).
Unenhanced CT scans of 73 SSNs obtained using the same protocol and reconstructed with both FBP and MBIR algorithms were evaluated by two radiologists. Diameter, mean attenuation, mass and volume of whole nodules and their solid components were measured. Intra- and interobserver variability and differences between FBP and MBIR were then evaluated using Bland–Altman method and Wilcoxon tests.
Longest diameter, volume and mass of nodules and those of their solid components were significantly higher using MBIR (p < 0.05) with mean differences of 1.1% (limits of agreement, −6.4 to 8.5%), 3.2% (−20.9 to 27.3%) and 2.9% (−16.9 to 22.7%) and 3.2% (−20.5 to 27%), 6.3% (−51.9 to 64.6%), 6.6% (−50.1 to 63.3%), respectively. The limits of agreement between FBP and MBIR were within the range of intra- and interobserver variability for both algorithms with respect to the diameter, volume and mass of nodules and their solid components. There were no significant differences in intra- or interobserver variability between FBP and MBIR (p > 0.05).
Semi-automatic measurements of SSNs significantly differed between FBP and MBIR; however, the differences were within the range of measurement variability.
• Intra- and interobserver reproducibility of measurements did not differ between FBP and MBIR.
• Differences in SSNs’ semi-automatic measurement induced by reconstruction algorithms were not clinically significant.
• Semi-automatic measurement may be conducted regardless of reconstruction algorithm.
• SSNs’ semi-automated classification agreement (pure vs. part-solid) did not significantly differ between algorithms.
KeywordsLung neoplasms Multidetector computed tomography Iterative reconstruction Subsolid nodule Measurement variability
The scientific guarantor of this publication is Chang Min Park, MD, Ph.D. The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article. This study has received funding by the Korean Foundation for Cancer Research (grant number: CB-2011-02-01). Julien G. Cohen acknowledges support from the Société Francaise de Radiologie (SFR) and Collège des Enseignants de Radiologie de France (CERF). Ms. Su Bin Park is an expert in statistics and she provided statistical advice in this study. Institutional review board approval was obtained. Written informed consent was waived by the institutional review board. Study subjects have not been previously reported or published before. Methodology: retrospective, observational, performed at one institution.
- 11.Vardhanabhuti V, Loader RJ, Mitchell GR, Riordan RD, Roobottom CA (2013) Image quality assessment of standard- and low-dose chest CT using filtered back projection, adaptive statistical iterative reconstruction, and novel model-based iterative reconstruction algorithms. AJR Am J Roentgenol 200:545–552CrossRefPubMedGoogle Scholar
- 14.Vardhanabhuti V, Ilyas S, Gutteridge C, Freeman SJ, Roobottom CA (2013) Comparison of image quality between filtered back-projection and the adaptive statistical and novel model-based iterative reconstruction techniques in abdominal CT for renal calculi. Insights Imaging 4:661–669CrossRefPubMedPubMedCentralGoogle Scholar
- 20.de Hoop B, Gietema H, van Ginneken B, Zanen P, Groenewegen G, Prokop M (2009) A comparison of six software packages for evaluation of solid lung nodules using semi-automated volumetry: what is the minimum increase in size to detect growth in repeated CT examinations. Eur Radiol 19:800–808CrossRefPubMedGoogle Scholar