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Comparison of the effect of iterative reconstruction versus filtered back projection on cardiac CT postprocessing.
- Source :
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Academic radiology [Acad Radiol] 2014 Mar; Vol. 21 (3), pp. 318-24. Date of Electronic Publication: 2013 Dec 18. - Publication Year :
- 2014
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Abstract
- Rationale and Objectives: To investigate the impact of iterative reconstruction in image space (IRIS) on image noise, image quality (IQ), and postprocessing at coronary computed tomography angiography (cCTA) compared to traditional filtered back-projection (FBP).<br />Materials and Methods: The cCTA results of 50 patients (26 men; 58 ± 15 years, body mass index 31.5 ± 6.7 kg/m²) were investigated using a second-generation dual-source computed tomography system. Scan data were reconstructed with the use of IRIS and FBP algorithms. Two radiologists independently evaluated the reconstructions using automated coronary tree analysis software. Image noise was measured and IQ was rated on a 5-point Likert scale. The number of manual corrections after automated vessel segmentation, the time required to complete segmentation, and the number of missed segments were assessed in both IRIS and FBP reconstructions. Results were compared using paired t-test.<br />Results: IRIS significantly reduced image noise compared to FBP (23.3 ± 8.8 vs. 33.5 ± 13.5 Hounsfield units, P < .001). Subjective IQ improved with IRIS (IRIS 3.2 ± 1.0 vs. FBP 3.0 ± 1.0, P < .05). IRIS decreased the time needed for coronary segmentation from 111.9 ± 40.5 seconds to 95.2 ± 38.2 seconds with FBP (P < .01) and required fewer manual corrections (5.7 ± 3.0 vs. 6.8 ± 3.6, P < .01). The number of missed vessel segments was not significantly different (3.6 ± 1.8 vs. 3.8 ± 1.9, P > .05) between IRIS and FBP, respectively.<br />Conclusions: During cCTA postprocessing, IRIS significantly decreases the time and the number of manual corrections for a complete coronary segmentation compared to FBP. This effect is likely attributable to suppression of image noise by IRIS, which improves the performance of automated vessel segmentation and positively impacts cCTA analysis.<br /> (Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.)
- Subjects :
- Female
Humans
Male
Middle Aged
Reproducibility of Results
Sensitivity and Specificity
Algorithms
Coronary Angiography methods
Coronary Artery Disease diagnostic imaging
Radiographic Image Enhancement methods
Radiographic Image Interpretation, Computer-Assisted methods
Tomography, X-Ray Computed methods
Subjects
Details
- Language :
- English
- ISSN :
- 1878-4046
- Volume :
- 21
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Academic radiology
- Publication Type :
- Academic Journal
- Accession number :
- 24360635
- Full Text :
- https://doi.org/10.1016/j.acra.2013.11.008