Deep learning image reconstruction algorithm for carotid dual-energy computed tomography angiography: evaluation of image quality and diagnostic performance
Chenyu Jiang,Dan Jin,Zhuoheng Liu,Yan Zhang,Ming Ni,Hui-zong Yuan +5 more
TL;DR: In this article , the authors evaluated image quality and diagnostic performance of carotid dual-energy computed tomography angiography (DECTA) using deep learning image reconstruction (DLIR) compared with images using adaptive statistical iterative reconstruction-Veo (ASIR-V).
read more
Abstract: To evaluate image quality and diagnostic performance of carotid dual-energy computed tomography angiography (DECTA) using deep learning image reconstruction (DLIR) compared with images using adaptive statistical iterative reconstruction-Veo (ASIR-V).Carotid DECTA datasets of 28 consecutive patients were reconstructed at 50 keV using DLIR at low, medium, and high levels (DLIR-L, DLIR-M, and DLIR-H) and 80% ASIR-V algorithms. Mean attenuation, image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) at different levels of arteries were measured and calculated. Image quality for noise and texture, depiction of arteries, and diagnostic performance toward carotid plaques were assessed subjectively by two radiologists. Quantitative and qualitative parameters were compared between the ASIR-V, DLIR-L, DLIR-M, and DLIR-H groups.The image noise at aorta and common carotid artery, SNR, and CNR at all level arteries of DLIR-H images were significantly higher than those of ASIR-V images (p = 0.000-0.040). The quantitative analysis of DLIR-L and DLIR-M showed comparable denoise capability with ASIR-V. The overall image quality (p = 0.000) and image noise (p = 0.000-0.014) were significantly better in the DLIR-M and DLIR-H images. The image texture was improved by DLR at all level compared to ASIR-V images (p = 0.000-0.008). Depictions of head and neck arteries and diagnostic performance were comparable between four groups (p > 0.05).Compared with 80% ASIR-V, we recommend DLIR-H for clinical carotid DECTA reconstruction, which can significantly improve the image quality of carotid DECTA at 50 keV but maintain a desirable diagnostic performance and arterial depiction.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
CT image denoising methods for image quality improvement and radiation dose reduction.
Rabeya Sadia,Jin Chen,Jie Zhang +2 more
TL;DR: A thorough analysis of existing literature on CT denoising methods focuses on pivotal aspects, including model training, validation, testing, generalizability, vulnerability, and evaluation methods, to raise awareness of the various facets involved in CT image denoising.
10
•Posted Content
Systematic Review on Learning-based Spectral CT
18 Apr 2023
TL;DR: In this paper , the authors present the state-of-the-art data-driven techniques for spectral computed tomography (CT) and compare them with the traditional single-energy CT.
9
Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT
Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong,Jingyu Zhong +12 more
TL;DR: Deep learning image reconstruction generates thinner slice iodine maps with improved image quality and diagnostic acceptability in abdominal DECT.
3
A Systematic Literature Review of 3D Deep Learning Techniques in Computed Tomography Reconstruction
Hameedur Rahman,Abdur Rehman Khan,Touseef Sadiq,Ashfaq Hussain Farooqi,Inam Ullah Khan,Wei Hong Lim +5 more
TL;DR: 3D deep learning may increase the effectiveness of CT image reconstruction, boost image quality, and lower radiation exposure, by using these deep learning approaches, which may be made more precise and effective, improving patient outcomes, diagnostic accuracy, and healthcare system productivity.
2
Application of deep learning image reconstruction-high algorithm in one-stop coronary and carotid-cerebrovascular CT angiography with low radiation and contrast doses
Peiyao Li,Yuting Wen,Tao Shuai,Yong He,Yongchun You,Jianqun Yu,Kaiyue Diao,Bin Song +7 more
TL;DR: This study validates the feasibility of one-stop coronary and carotid-cerebrovascular CT angiography with low radiation and contrast doses using deep learning image reconstruction with high setting (DLIR-H) algorithm, achieving 48% radiation and 30% contrast dose reduction with comparable image quality.
1
References
Guidelines for prevention of stroke in patients with ischemic stroke or transient ischemic Attack : A statement for healthcare professionals from the American Heart Association/American Stroke Association Council on Stroke : Co-sponsored by the Council on Cardiovascular Radiology and Intervention : The American Academy of Neurology affirms the value of this guideline
Ralph L. Sacco,Robert J. Adams,Greg Albers,Mark J. Alberts,Oscar R. Benavente,Karen L. Furie,Larry B. Goldstein,Philip B. Gorelick,Jonathan L. Halperin,Robert E. Harbaugh,S. Claiborne Johnston,Irene L. Katzan,Margaret Kelly-Hayes,Edgar J. Kenton,Michael P. Marks,Lee H. Schwamm,Thomas A. Tomsick +16 more
TL;DR: In this paper, the authors provide comprehensive and timely evidence-based recommendations on the prevention of ischemic stroke among survivors of stroke or transient ischemi stroke, including the control of risk factors, interventional approaches for atherosclerotic disease, antithrombotic treatments for cardioembolism, and the use of antiplatelet agents for noncardioembolic stroke.
1.9K
Dual- and Multi-Energy CT: Principles, Technical Approaches, and Clinical Applications
TL;DR: The underlying motivation and physical principles of dual- or multi-energy CT are reviewed, the current and evolving clinical applications are introduced and each of the current technical approaches is described.
1.3K
Population-based study of event-rate, incidence, case fatality, and mortality for all acute vascular events in all arterial territories (Oxford Vascular Study)
Peter M. Rothwell,A J Coull,Louise E. Silver,J. F. Fairhead,Matthew F. Giles,Caroline E. Lovelock,Jne Redgrave,Linda M. Bull,Sjv Welch,Fiona C. Cuthbertson,L E Binney,Sergei A. Gutnikov,P Anslow,Adrian P. Banning,David Mant,Ziyah Mehta +15 more
TL;DR: The high rates of acute vascular events outside the coronary arterial territory and the steep rise in event rates with age in all territories have implications for prevention strategies, clinical trial design, and the targeting of funds for service provision and research.
939
State of the Art: Iterative CT Reconstruction Techniques
Lucas L. Geyer,U. Joseph Schoepf,Felix G. Meinel,John W. Nance,Gorka Bastarrika,Jonathon Leipsic,Narinder Paul,Marco Rengo,Andrea Laghi,Carlo N. De Cecco,Carlo N. De Cecco +10 more
TL;DR: In this contribution, the technical bases of IR are reviewed and the currently available algorithms released by the major CT manufacturers are described and the current status of their clinical implementation is surveyed.
647
2011 ASA/ACCF/AHA/AANN/AANS/ACR/ASNR/CNS/SAIP/SCAI/SIR/SNIS/SVM/SVS Guideline on the Management of Patients With Extracranial Carotid and Vertebral Artery Disease: Executive Summary
Thomas G. Brott,Jonathan L. Halperin,Suhny Abbara,J. Michael Bacharach,John D. Barr,Ruth L. Bush,Christopher U. Cates,Mark A. Creager,Susan B. Fowler,Gary Friday,Vicki S. Hertzberg,E. Bruce McIff,Wesley S. Moore,Peter D. Panagos,Thomas S. Riles,Robert H. Rosenwasser,Allen J. Taylor +16 more
TL;DR: Recommendations for Management of Diabetes Mellitus in Patients With Atherosclerosis of the Extracranial Carotid or Vertebral Arteries and for Control of Hyperlipidemia.
606