Impact of Advanced Modeled Iterative Reconstruction on Coronary Artery Calcium Quantification

Messerli, Michael; Rengier, Fabian; Desbiolles, Lotus; Ehl, Niklas F.; Bauer, Ralf W.; Leschka, Sebastian; Alkadhi, Hatem; Wildermuth, Simon; Nähle, C.

doi:10.1016/j.acra.2016.08.008

Cited by 23 publications

(15 citation statements)

References 30 publications

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“…In another hand, the ADMIRE technique is an iterative method and an available option to reduce radiation doses and optimize image quality mainly in cardiac imaging. [13,34–36] Its capacity to reduce metal artifacts is, however, nonsignificant with inconsistent clinical impact, as demonstrated in our study.…”

Section: Discussionsupporting

confidence: 43%

Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging

et al. 2019

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To evaluate iterative metal artifact reduction (iMAR) technique in images data of hip prosthesis on computed tomography (CT) and the added value of advanced modeled iterative reconstruction (ADMIRE) compared with standard filtered back projection (FBP). Twenty-eight patients addressed to CT examinations for hip prosthesis were included prospectively. Images were reconstructed with iMAR algorithm in addition to FBP and ADMIRE techniques. Measuring image noise assessed objective image quality and attenuation values with standardized region of interest (ROI) in 4 predefined anatomical structures (gluteus medius and rectus femoris muscles, inferior and anterior abdominal fat, and femoral vessels when contrast media was present). Subjective image quality was graded on a 5-point Likert scale, taking into account the size of artifacts, the metal–bone interface and the conspicuity of pelvic organs, and the diagnostic confidence. Improvement in overall image quality was statistically significant using iMAR ( P <.001) compared with ADMIRE and FBP. ADMIRE did not show any impact in image noise, attenuation value, or global quality image. iMAR showed a significant decrease in image noise in all ROIs (Hounsfield Unit) as compared with FBP and ADMIRE. Interobserver agreement was high in all reconstructions (FBP, FBP+iMAR, ADMIRE, and ADMIRE + iMAR) more than 0.8. iMAR reconstructions showed emergence of new artifacts in bone–metal interface. iMAR algorithm allows a significant reduction of metal artifacts on CT images with unilateral or bilateral prostheses without additional value of ADMIRE. It improves the analysis of surrounding tissue but potentially generates new artifacts in bone–metal interface.

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Section: Discussionsupporting

confidence: 43%

Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging

et al. 2019

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“…It is reported that [21][22][23][24] the improvement of image quality (such as the reduction of image noise) usually leads to the reduction in the CAC score. however, the widespread existence of image noise may hinder the dependable quantification on CAC.…”

Section: Discussionmentioning

confidence: 99%

Influence of Deep Learning Image Reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on Coronary Artery Calcium Quantification

Zhan

Liu

et al. 2021

Preprint

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Deep learning image reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) has been used for cardiac computed tomography imaging. However, DLIR and ASIR-V may influence the quantification of coronary artery calcification. This study aimed to investigate the effects of DLIR and ASIR-V on coronary calcium quantification compared to traditional filtered back projection (FBP). CT images of 96 patients were reconstructed by FBP, ASIR-V 50%, and three levels of DLIR (low [L], medium [M], and high [H], respectively). Image noise decreased significantly with ASIR-V 50% and increasing DLIR levels from L to H in comparison with FBP (all P < 0.001). There is a significantly decline with ASIR-V 50% and incremental DLIR levels in Agatston calcium score, volume score and mass score as compared to FBP (all P < 0.001). For all CAC score risk categories, Severity classification shows no significant differences among five reconstructions (all P > 0.05). DLIR-L has the minimal effect on coronary calcium quantification as compared to ASIR-V and DLIR at medium and high levels. it may be considered as an alternative to FBP for routine clinical use.

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“…While most CT scanners still employ the analytical FBP reconstruction method, commercial SIR engines have become available in the clinic recently. Several clinical applications of these SIR engines have been reported, which demonstrate the potential to substantially reduce radiation dose without compromising the image quality for clinical tasks . SIR appears to represent a promising direction for developing reconstruction algorithms for low‐dose CT, although more clinical reports are needed to fully demonstrate its advantages.…”

Section: Discussionmentioning

confidence: 99%

Regularization strategies in statistical image reconstruction of low‐dose x‐ray CT: A review

et al. 2018

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Statistical image reconstruction (SIR) methods have shown potential to substantially improve the image quality of low-dose x-ray computed tomography (CT) as compared to the conventional filtered back-projection (FBP) method. According to the maximum a posteriori (MAP) estimation, the SIR methods are typically formulated by an objective function consisting of two terms: (a) a data-fidelity term that models imaging geometry and physical detection processes in projection data acquisition, and (b) a regularization term that reflects prior knowledge or expectations of the characteristics of the to-be-reconstructed image. SIR desires accurate system modeling of data acquisition, while the regularization term also has a strong influence on the quality of reconstructed images. A variety of regularization strategies have been proposed for SIR in the past decades, based on different assumptions, models, and prior knowledge. In this paper, we review the conceptual and mathematical bases of these regularization strategies and briefly illustrate their efficacies in SIR of low-dose CT.

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Impact of Advanced Modeled Iterative Reconstruction on Coronary Artery Calcium Quantification

Cited by 23 publications

References 30 publications

Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging

Metallic artifact reduction by evaluation of the additional value of iterative reconstruction algorithms in hip prosthesis computed tomography imaging

Influence of Deep Learning Image Reconstruction (DLIR) and Adaptive Statistical Iterative Reconstruction-V (ASIR-V) on Coronary Artery Calcium Quantification

Regularization strategies in statistical image reconstruction of low‐dose x‐ray CT: A review

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