Effects of Model-Based Iterative Reconstruction on Image Quality for Low-Dose Computed Tomographic Angiography of the Thoracic Aorta in a Swine Model

Caywood, Devin; Paxton, Ben E.; Boll, Daniel T.; Nelson, Rendon C.; Kim, Charles; Lowry, Carolyn; Seaman, Danielle M.; Roos, Justus E.; Hurwitz, Lynne M.

doi:10.1097/rct.0000000000000180

Cited by 4 publications

(3 citation statements)

References 15 publications

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“…A recent study evaluated low dose CT angiography of the thoracic aorta in a live porcine model under anesthesia, comparing MBIR with FBP and ASIR50 [9]. A statistically significant improvement in subjective image quality was found with MBIR over FBP, but not with ASIR.…”

Section: Discussionmentioning

confidence: 99%

“…However, image comparisons using data from phantoms do not always approximate the clinical experience when assessing real anatomical organs and ethical limitations preclude repetitive scans to compare a wide range of techniques in a single patient. Only a few studies have utilized animal models to perform image comparisons [7]- [9]. Furthermore, many existing studies focus solely on lesion detection, which poorly approximates other clinical scenarios for which a scan may be commonly performed, such as detection of inflammatory stranding or hemorrhage surrounding a particular organ.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of CT Dose Reduction Algorithms in a Porcine Model

Khan¹,

Elbakri²,

Henderson³

et al. 2015

ACT

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The present study utilized a porcine model for qualitative and quantitative assessment of the diagnostic quality of non-contrast abdominal computed tomography (CT) images generated by Adaptive Statistical Iterative Reconstruction (ASIR, GE Healthcare, Waukesha, Wisconsin, USA), Model-Based Iterative Reconstruction (GE company name VEO), and conventional Filtered back projection (FBP) technique. Methods: Multiple CT whole-body scans of a freshly euthanized pig carcass were performed on a 64-slice GE CT scanner at varying noise indices (5, 10, 15, 20, 30, 37, 40, 45), and with three different algorithms (VEO, FBP, and ASIR at 30%, 50%, and 70% levels of ASIR-FBP blending). Abdominal CT images were reviewed and scored in a blinded and randomized manner by two board-certified abdominal radiologists. The task was to evaluate the clarity of the images according to a rubric involving edge sharpness, presence of artifact, anatomical clarity (assessed at four regions), and perceived diagnostic acceptability. This amounted to seven criteria, each of which was graded on a scale of 1 to 5. A weighted formula was used to calculate a composite score for each scan. Results: VEO outperforms ASIR and FBP by an average of 0.5 points per the scoring system used (p < 0.05). Above a threshold noise index of 30, diagnostic acceptability is lost by all algorithms, and there is no diagnostic advantage to increasing the dose beyond a noise index of 10. Between a noise index of 25-30, VEO retains diagnostic acceptability, as opposed to ASIR and FBP which lose acceptability above noise index of 25. Conclusion: Model-based iterative reconstruction provides superior image quality and anatomical clarity at reduced radiation dosages, supporting the routine use of this technology, particularly in pediatric abdominal CT scans.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of CT Dose Reduction Algorithms in a Porcine Model

Khan¹,

Elbakri²,

Henderson³

et al. 2015

ACT

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“…Iterative reconstruction algorithms should be used where deemed appropriate to allow reduced radiation dose. 57 – 59 For larger detector array or high-pitch dual-source systems, ECG synchronization may not be necessary for motion-free imaging of the aorta. A summary of all the protocols can be seen in Table 1 .…”

Section: Introductionmentioning

confidence: 99%

Recommendations for accurate CT diagnosis of suspected acute aortic syndrome (AAS)—on behalf of the British Society of Cardiovascular Imaging (BSCI)/British Society of Cardiovascular CT (BSCCT)

Vardhanabhuti¹,

Nicol²,

Morgan‐Hughes³

et al. 2016

BJR

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Accurate and timely assessment of suspected acute aortic syndrome is crucial in this life-threatening condition. Imaging with CT plays a central role in the diagnosis to allow expedited management. Diagnosis can be made using locally available expertise with optimized scanning parameters, making full use of recent advances in CT technology. Each imaging centre must optimize their protocols to allow accurate diagnosis, to optimize radiation dose and in particular to reduce the risk of false-positive diagnosis that may simulate disease. This document outlines the principles for the acquisition of motion-free imaging of the aorta in this context.

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Computed Tomographic Angiography of the Abdominal Aorta

Hansen

2016

Radiologic Clinics of North America

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Effects of Model-Based Iterative Reconstruction on Image Quality for Low-Dose Computed Tomographic Angiography of the Thoracic Aorta in a Swine Model

Abstract: Model-based iterative reconstruction reduces relative noise and improves CNR compared with ASIR and FBP at all kVp and mA settings, which were significantly greater at lower mA settings.

Cited by 4 publications

References 15 publications

Comparison of CT Dose Reduction Algorithms in a Porcine Model

Comparison of CT Dose Reduction Algorithms in a Porcine Model

Recommendations for accurate CT diagnosis of suspected acute aortic syndrome (AAS)—on behalf of the British Society of Cardiovascular Imaging (BSCI)/British Society of Cardiovascular CT (BSCCT)

Computed Tomographic Angiography of the Abdominal Aorta

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