Impact of a New Adaptive Statistical Iterative Reconstruction (ASIR)-V Algorithm on Image Quality in Coronary Computed Tomography Angiography

Rationale and objectives

A new postprocessing algorithm named adaptive statistical iterative reconstruction (ASIR)-V has been recently introduced. The aim of this article was to analyze the impact of ASIR-V algorithm on signal, noise, and image quality of coronary computed tomography angiography.

Materials and Methods

Fifty consecutive patients underwent clinically indicated coronary computed tomography angiography (Revolution CT; GE Healthcare, Milwaukee, WI). Images were reconstructed using filtered back projection and ASIR-V 0%, and a combination of filtered back projection and ASIR-V 20%–80% and ASIR-V 100%. Image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were calculated for left main coronary artery (LM), left anterior descending artery (LAD), left circumflex artery (LCX), and right coronary artery (RCA) and were compared between the different postprocessing algorithms used. Similarly a four-point Likert image quality score of coronary segments was graded for each dataset and compared. A cutoff value of P < .05 was considered statistically significant.

Results

Compared to ASIR-V 0%, ASIR-V 100% demonstrated a significant reduction of image noise in all coronaries ( P < .01). Compared to ASIR-V 0%, SNR was significantly higher with ASIR-V 60% in LM ( P < .01), LAD ( P < .05), LCX ( P < .05), and RCA ( P < .01). Compared to ASIR-V 0%, CNR for ASIR-V ≥60% was significantly improved in LM ( P < .01), LAD ( P < .05), and RCA ( P < .01), whereas LCX demonstrated a significant improvement with ASIR-V ≥80%. ASIR-V 60% had significantly better Likert image quality scores compared to ASIR-V 0% in segment-, vessel-, and patient-based analyses ( P < .01).

Conclusions

Reconstruction with ASIR-V 60% provides the optimal balance between image noise, SNR, CNR, and image quality.

Introduction

Coronary computed tomography angiography (CCTA) is an excellent noninvasive tool for the accurate diagnosis of patients with coronary artery disease (CAD) . Novel techniques utilizing CCTA are broadening its application for the assessment of ischemic heart disease . However, CCTA has raised concerns regarding radiation exposure to the patient . Several strategies for CCTA image acquisition and postprocessing have been adopted from different vendors to maintain diagnostic image quality while reducing radiation dose . Low–dose protocol CCTA using dose modulation, prospective electrocardiographic triggering, high-pitch acquisition, and low tube potential have been shown to be effective strategies for radiation dose reduction . However, decreasing tube potential has been associated with increased image noise and degradation of CCTA images . To overcome this issue, iterative reconstruction (IR) algorithms were developed. IR algorithms allow for an improvement in image quality and diagnostic accuracy compared to standard filtered back projection (FBP) in CCTA acquired with a low-dose protocol . Although IR represents a useful tool in clinical practice, it is important to consider some of its limitations. Compared to standard FBP, IR requires a longer time for reconstruction and may cause underestimation of coronary artery calcium .

Recently, a new generation of adaptive statistical iterative reconstruction (ASIR-V; GE Healthcare, Milwaukee, WI) was developed . This new algorithm de-emphasizes the modeling of system optics and allows a reconstruction of images with similar speed compared to FBP. System optics is the main driver for improved spatial resolution and is the most time-consuming portion of the IR reconstruction process. Furthermore, the new ASIR-V compared to older versions of ASIR enables a further reduction of low signal artifacts. Therefore, a significant improvement in image quality can be achieved without a large penalty in reconstruction speed. The aim of this article was to compare image quality metrics for FBP with varying degrees of ASIR-V in CCTA.

Materials and Methods

Patient Population

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Patient Preparation and CCTA Acquisition

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Reconstruction and Analysis of CCTA Images

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Phantom Setup and Image Acquisition

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Statistical Analysis

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Results

Patient Characteristics

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TABLE 1

Baseline Characteristics of the Overall Population

Baseline Characteristics Number, n (%) 50 Age (y), mean ± SD 64.3 ± 9.2 Male, n (%) 38 (76) Body mass index (kg/m 2 ), mean ± SD 26 ± 3.9

Risk Factors Hypertension, n (%) 18 (36) Smoker, n (%) 9 (18) Hyperlipidemia, n (%) 21 (42) Diabetes, n (%) 6 (12) Family history, n (%) 15 (30)

Clinical History Chest pain, n (%) 14 (28) Positive stress test, n (%) 12 (24) Follow-up of known CAD, n (%) 8 (16) Valvular disease, n (%) 5 (10) Arrhythmias, n (%) 5 (10) Dilated cardiomyopathy, n (%) 6 (12)

Intravenous β-blocker Number of patients, n (%) 31 (62) Dose (mg), mean ± SD 9.1 ± 4.2

Heart rate during the scan Minimum heart rate (bpm), mean ± SD 59.3 ± 13.5 Mean heart rate (bpm), mean ± SD 63.2 ± 13.8 Maximum heart rate (bpm), mean ± SD 73.9 ± 20.3

CAD, coronary artery disease; SD, standard deviation.

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Objective Image Quality

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TABLE 2

Comparison of SNR, CNR, and Image Noise Between ASIR-V 20%, 40%, 60%, 80%, 100%, and 0%

ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% LM SNR, mean ± SD 14.6 ± 5.7 16.0 ± 6.7 17.1 ± 7.1 \* 19.9 ± 8.4 \* 21.8 ± 12.1 \* 23.0 ± 10.2 \* CNR, mean ± SD 17.3 ± 6.8 19.2 ± 8.0 † 20.3 ± 8.4 \* 23.7 ± 10.2 \* 26.0 ± 14.5 \* 27.5 ± 12.3 \* Noise (HU), mean ± SD 38.8 ± 12.7 35.6 ± 12.5 \* 34.3 ± 13.8 \* 30.4 ± 14.0 \* 30.3 ± 17.5 \* 27.0 ± 14.8 \* LAD SNR, mean ± SD 12.0 ± 4.7 12.6 ± 5.5 13.2 ± 6.7 13.8 ± 8.0 † 15.7 ± 8.6 \* 17.2 ± 9.5 \* CNR, mean ± SD) 14.6 ± 5.9 13.3 ± 6.9 16. 0 ± 8.0 16.8 ± 9.8 † 19.2 ± 10.1 \* 21.1 ± 12.5 \* Noise (HU), mean ± SD 44.8 ± 16.5 45.0 ± 20.0 43. 9 ± 22.3 45.0 ± 25.7 41.8 ± 26 .3 38.2 ± 23.3 \* LCX SNR, mean ± SD 9.0 ± 4.0 9.3 ± 3.9 9.9 ± 7.9 10.1 ± 5.3 † 11.4 ± 7.1 \* 13.0 ± 9.5 \* CNR, mean ± SD 11.0 ± 4.9 11.4 ± 4.6 12.2 ± 10.3 12.4 ± 6.5 14.0 ± 8.8 \* 15.9 ± 11.6 \* Noise (HU), mean ± SD 58.4 ± 27 54.5 ± 24.5 † 56.6 ± 28.6 56.5 ± 28.7 † 52.3 ± 26.0 \* 45.7 ± 23.9 \* RCA SNR, mean ± SD 9.8 ± 4.8 11.5 ± 5.8 \* 11.2 ± 5.8 † 12.8 ± 7.3 \* 13.4 ± 7.9 \* 14.6 ± 8.9 \* CNR, mean ± SD 11.8 ± 5.8 13.9 ± 6.6 \* 13.4 ± 6.6 \* 15.3 ± 8.2 \* 16.2 ± 9.3 \* 17.7 ± 10.8 \* Noise (HU), mean ± SD 54.3 ± 25.2 47.2 ± 22.9 \* 48.5 ± 25.1 \* 44.3 ± 22.3 \* 44.2 ± 25.6 \* 42.1 ± 25.8 \*

ASIR, adaptive statistical iterative reconstruction; CNR, contrast-to-noise ratio; LAD, left anterior descending artery; LCX, left circumflex coronary artery; LM, left main coronary artery; RCA, right coronary artery; SD, standard deviation; SNR, signal-to-noise ratio.

Statistical analysis compared different combinations of ASIR-V ≥20% with ASIR-V 0%.

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TABLE 3

Comparison of SNR, CNR, and Image Noise Between ASIR-V 20%, 40%, 60%, 80%, 100%, and 0% in phantom

400 mg/mL ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% Syringe of 20 mL SNR, mean ± SD 213.3 ± 19.9 233.7 ± 15.6 258.2 ± 26.2 † 289. 2 ± 28.8 † 310.0 ± 24.4 † 355.2 ± 54.0 † CNR, mean ± SD 196.9 ± 6.7 204.6 ± 40.3 212.2 ± 52.2 244.0 ± 70.4 262.3 ± 71.9 273.4 ± 87.2 Noise (HU), mean ± SD 14.4 ± 1.2 13.1 ± 0.9 11.9 ± 1.1 \* 10.7 ± 1.2 † 9.9 ± 0.8 † 8.7 ± 1.2 \*

320 mg/mL ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% Syringe of 20 mL SNR, mean ± SD 228.7 ± 39.9 251.6 ± 14.9 282.5 ± 18.8 291.0 ± 13.9 350.6 ± 13.1 † 407.8 ± 11.4 † CNR, mean ± SD 228.1 ± 39.4 251.1 ± 14.4 281.8 ± 17.2 290.4 ± 12.8 349.9 ± 13.9 † 407.0 ± 12.4 † Noise (HU), mean ± SD 13.7 ± 2.6 12.2 ± 0.7 10.9 ± 0.7 10.5 ± 0.4 8.7 ± 0.3 7.5 ± 0.2

ASIR, adaptive statistical iterative reconstruction; CNR, contrast-to-noise ratio; SD, standard deviation; SNR, signal-to-noise ratio.

Statistical analysis compared different combinations of ASIR-V ≥20% with ASIR-V 0%.

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Subjective Image Quality

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TABLE 4

Comparison of Likert Image Quality Score Between ASIR-V 20%, 40%, 60%, 80%, 100%, and 0% in a Segment-based Analysis

N ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% LM 50 2.6 ± 0.5 3.2 ± 0.6 \* 3.7 ± 0.4 \* 3.8 ± 0.4 \* 2.9 ± 0.6 \* 2.5 ± 0.5 Proximal LAD 50 2.4 ± 0.6 3.0 ± 0.6 \* 3.6 ± 0.7 \* 3.6 ± 0.8 \* 2.7 ± 0.6 \* 2.2 ± 0.5 Mid LAD 50 2.3 ± 0.6 2.7 ± 0.8 \* 3.3 ± 0.9 \* 3.4 ± 0.8 \* 2.5 ± 0.6 † 2.1 ± 0.6 \* Distal LAD 50 2.3 ± 0.6 2.7 ± 0.7 \* 3.2 ± 0.8 \* 3.3 ± 0.9 \* 2.5 ± 0.6 † 2.1 ± 0.5 \* D1 50 2.2 ± 0.6 2.5 ± 0.8 \* 3.1 ± 1.0 \* 3.2 ± 1.0 \* 2.4 ± 0.7 1.9 ± 0.5 \* Proximal LCX 50 2.4 ± 0.5 3.0 ± 0.6 \* 3.5 ± 0.6 \* 3.6 ± 0.6 \* 2.8 ± 0.6 \* 2.3 ± 0.5 Mid LCX 50 2.3 ± 0.5 2.7 ± 0.7 \* 3.3 ± 0.8 \* 3.3 ± 0.8 \* 2.5 ± 0.6 † 2.1 ± 0.5 † Distal LCX 50 2.2 ± 0.5 2.3 ± 0.7 3.0 ± 1.0 \* 3.0 ± 1.1 \* 2.4 ± 0.7 † 2.0 ± 0.5 † M1 50 2.3 ± 0.7 2.6 ± 0.8 \* 3.2 ± 0.9 \* 3.3 ± 0.9 \* 2.2 ± 0.7 \* 2.0 ± 0.6 \* Proximal RCA 50 2.4 ± 0.7 2.7 ± 0.8 \* 3.3 ± 0.9 \* 3.3 ± 0.9 \* 2.4 ± 0.7 2.1 ± 0.6 \* Mid RCA 50 2.1 ± 0.8 2.3 ± 0.9 † 2.9 ± 1.0 \* 2.9 ± 1.1 \* 2.3 ± 0.8 1.9 ± 0.6 \* Distal RCA 50 2.2 ± 0.7 2.5 ± 0.8 \* 3.0 ± 1.0 \* 3.1 ± 1.0 \* 2.3 ± 0.8 1.9 ± 0.5 \* PLA 50 2.1 ± 0.7 2.3 ± 0.8 3.0 ± 1.0 \* 3.0 ± 1.0 \* 2.4 ± 0.7 † 1.9 ± 0.6 \* PDA 50 2.1 ± 0.7 2.3 ± 0.8 \* 2.9 ± 1.0 \* 2.9 ± 1.1 \* 2.3 ± 0.8 † 1.9 ± 0.6 \*

ASIR, adaptive statistical iterative reconstruction; LAD, left anterior descending artery; LCX, left circumflex artery; LM, left main coronary artery; PDA, posterior descending artery; PLA, posterolateral artery.; RCA, right coronary artery.

Statistical analysis compared different combinations of ASIR-V ≥20% with ASIR-V 0%.

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TABLE 5

Comparison of Likert Image Quality Score Between ASIR-V 20%, 40%, 60%, 80%, 100%, and 0% in Vessel- and Patient-based Analyses †

N ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% LAD 50 2.3 ± 0.5 2.8 ± 0.6 \* 3.4 ± 0.7 \* 3.4 ± 0.7 \* 2.6 ± 0.5 \* 2.1 ± 0.4 \* LCX 50 2.3 ± 0.4 2.7 ± 0.6 \* 3.3 ± 0.8 \* 3.3 ± 0.7 \* 2.6 ± 0.5 \* 2.1 ± 0.4 RCA 50 2.3 ± 0.4 2.5 ± 0.7 3.1 ± 0.8 \* 3.1 ± 0.9 \* 2.3 ± 0.6 2.0 ± 0.4 \* Patient-based analysis 50 2.3 ± 0.4 2.6 ± 0.5 \* 3.2 ± 0.7 \* 3.3 ± 0.7 \* 2.5 ± 0.5 \* 2.1 ± 0.4 \*

ASIR, adaptive statistical iterative reconstruction; LAD, left anterior descending artery; LCX, left circumflex artery; RCA, right coronary artery.

Statistical analysis compared different combinations of ASIR-V ≥20% with ASIR-V 0%.

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TABLE 6

Comparison of Likert Image Quality Score Between ASIR-V 20%, 40%, 60%, 80%, 100%, and 0% in Phantom \*

400 mg/mL ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% Syringe 1 mL 1.6 ± 0.5 2.3 ± 0.6 3.3 ± 0.6 † 4.0 ± 0.0 † 3.3 ± 0.5 † 2.6 ± 0.6 Syringe 10 mL 2.0 ± 0 2.6 ± 0.5 † 3.6 ± 0.6 † 3.8 ± 0.4 † 3.3 ± 0.6 † 3.0 ± 0 † Syringe 20 mL 2.6 ± 0.5 3.0 ± 0.0 3.6 ± 0.5 † 3.7 ± 0.5 † 3.3 ± 0.5 3.3 ± 0.5

320 mg/mL ASIR-V 0% ASIR-V 20% ASIR-V 40% ASIR-V 60% ASIR-V 80% ASIR-V 100% Syringe 1 mL 1.6 ± 0.5 2.3 ± 0.5 3.6 ± 0.6 † 3.7 ± 0.6 † 3.3 ± 0.5 † 3.3 ± 0.5 † Syringe 10 mL 1.7 ± 0.6 2.7 ± 0.6 3.7 ± 0.6 4.0 ± 0.0 † 3.3 ± 0.6 3.0 ± 0.0 Syringe 20 mL 2.3 ± 0.7 3.0 ± 0.0 3.7 ± 0.5 † 3.7 ± 0.6 † 3.6 ± 0.6 † 3.2 ± 0.6

ASIR, adaptive statistical iterative reconstruction.

Statistical analysis compared different combinations of ASIR-V ≥20% with ASIR-V 0%.

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Discussion

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References

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Impact of a New Adaptive Statistical Iterative Reconstruction (ASIR)-V Algorithm on Image Quality in Coronary Computed Tomography Angiography

Rationale and objectives

Materials and Methods

Results

Conclusions

Introduction

Materials and Methods

Patient Population

Patient Preparation and CCTA Acquisition

Reconstruction and Analysis of CCTA Images

Phantom Setup and Image Acquisition

Statistical Analysis

Results

Patient Characteristics

Objective Image Quality

Subjective Image Quality

Discussion

References

Further Reading

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