Trial reportEuropean radiology2022
High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.
Trial report in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 65 citations in OpenAlex.
- The added value of coronary CTA in chronic total occlusion percutaneous coronary intervention: a systematic review and meta-analysis.European radiology · 2024Pooled it
- Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography.European radiology · 2025Trial
- Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.The international journal of cardiovascular imaging · 2024Trial
- Refining the radiation and contrast medium dose in weight-grouped scanning protocols for coronary CT angiography.Journal of applied clinical medical physics · 2023Trial
- Impact of artificial intelligence on cardiovascular workflow, engagement, and outcomes: a systematic review.NPJ digital medicine · 2026Article
- Clinical feasibility test of 60 kVp double-low-dose coronary CT angiography with a deep learning reconstruction algorithm.Insights into imaging · 2026Article
- Deep learning image reconstruction optimizes coronary artery calcium quantification.Frontiers in cardiovascular medicine · 2026Article
- Clinical value of the 70-kVp ultra-low-dose CT pulmonary angiography with deep learning image reconstruction.European radiology · 2026Article
- Application of 80 kVp combined with deep learning reconstruction algorithm in overweight patients coronary CT angiography: reduced radiation dose and contrast agent dose.Frontiers in radiology · 2026Article
- Ultra-low 70-kV cardiac CT angiography in neonates: a comparative dose-optimized approach with preserved image quality.Frontiers in cardiovascular medicine · 2026Article
- Differences in different reconstruction algorithms for coronary CTA demonstrating pericoronary adipose tissue attenuation.Scientific reports · 2025Article
- The application value of deep learning-based reconstruction combined with segmented contrast injection in "one-stop" cardio-cerebrovascular computed tomography angiography.Quantitative imaging in medicine and surgery · 2025Article
- The research advancements on the advantages and limitations of coronary computed tomography angiography at low tube voltage: a literature review.Quantitative imaging in medicine and surgery · 2025Review
- Effect of Deep Learning Image Reconstruction on Image Quality and Pericoronary Fat Attenuation Index.Journal of imaging informatics in medicine · 2025Article
- Trading off Iodine and Radiation Dose in Coronary Computed Tomography.Journal of cardiovascular development and disease · 2025Review
- Improving lower-extremity artery depiction and diagnostic confidence using dual-energy technique and popliteal artery monitoring in dual-low dose CT angiography.Scientific reports · 2025Article
- Achieving low radiation dose and contrast agents dose in coronary CT angiography at 60-kVp ultra-low tube voltage.BMC medical imaging · 2025Article
- Artificial intelligence in aortic CT angiography: current applications and future perspectives.Frontiers in cardiovascular medicine · 2025Review
- Research Progress of Dual-energy CT in Diagnosis and Evaluation of Curative Effect of Liver Cancer: A ReviewCurrent medical imaging · 2025Review
- Accelerated 3D whole-heart non-contrast-enhanced mDIXON coronary MR angiography using deep learning-constrained compressed sensing reconstruction.Insights into imaging · 2024Article
Corrections and comments
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Authors and funding
11 authors at 1 institution in 1 country.
Funding
Abstract
objectivesTo explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m
methodsA total of 100 patients referred to CCTA were prospectively enrolled and randomly divided into two groups: low-dose group (n = 50) with 70 kVp, Smart mA for noise index (NI) of 36HU, contrast dose rate of 16mgI/kg/s, and DLIR-H, and conventional group (n = 50) with 120 kV, Smart mA for NI of 25HU, contrast dose rate of 32mgI/kg/s, and 60%ASIR-V. Radiation and contrast dose, subjective image quality score, and objective image quality measurement (image noise, contrast-noise-ratio (CNR), and signal-noise-ratio (SNR) for vessel) were compared between the two groups.
resultsLow-dose group used significantly reduced contrast dose (23.82 ± 3.69 mL, 50.6% reduction) and radiation dose (0.75 ± 0.14 mSv, 54.5% reduction) compared to the conventional group (48.23 ± 6.38 mL and 1.65 ± 0.66 mSv, respectively) (all p < 0.001). Both groups had similar enhancement in vessels. However, the low-dose group had lower background noise (23.57 ± 4.74 HU vs. 35.04 ± 8.41 HU), higher CNR in RCA (48.63 ± 10.76 vs. 29.32 ± 5.52), LAD (47.33 ± 10.20 vs. 29.27 ± 5.12), and LCX (46.74 ± 9.76 vs. 28.58 ± 5.12) (all p < 0.001) compared to the conventional group.
conclusionsThe use of 70-kVp tube voltage combined with DLIR-H for CCTA in normal size patients significantly reduces radiation dose and contrast dose while further improving image quality compared with the conventional 120-kVp tube voltage with 60%ASIR-V. KEY POINTS: • The combination of 70-kVp tube voltage and high-strength deep learning image reconstruction (DLIR-H) algorithm protocol reduces approximately 50% of radiation and contrast doses in coronary computed tomography angiography (CCTA) compared with the conventional scan protocol. • CCTA of normal size (BMI < 26 kg/m
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.