• HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
Sunday, September 7, 2025
BIOENGINEER.ORG
No Result
View All Result
  • Login
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
  • HOME
  • NEWS
  • EXPLORE
    • CAREER
      • Companies
      • Jobs
        • Lecturer
        • PhD Studentship
        • Postdoc
        • Research Assistant
    • EVENTS
    • iGEM
      • News
      • Team
    • PHOTOS
    • VIDEO
    • WIKI
  • BLOG
  • COMMUNITY
    • FACEBOOK
    • INSTAGRAM
    • TWITTER
No Result
View All Result
Bioengineer.org
No Result
View All Result
Home NEWS Science News Biology

Deep Learning, Subtraction Technique Optimal for Coronary Stent Evaluation by CTA

Bioengineer by Bioengineer
August 10, 2022
in Biology
Reading Time: 2 mins read
0
57-year-old man who underwent coronary CTA using two-breath-hold subtraction technique to assess patency of coronary artery stent.
Share on FacebookShare on TwitterShare on LinkedinShare on RedditShare on Telegram

Leesburg, VA, August 10, 2022—According to ARRS’ American Journal of Roentgenology (AJR), the combination of deep-learning reconstruction (DLR) and a subtraction technique yielded optimal diagnostic performance for the detection of in-stent restenosis by coronary CTA.

57-year-old man who underwent coronary CTA using two-breath-hold subtraction technique to assess patency of coronary artery stent.

Credit: ARRS and AJR

Leesburg, VA, August 10, 2022—According to ARRS’ American Journal of Roentgenology (AJR), the combination of deep-learning reconstruction (DLR) and a subtraction technique yielded optimal diagnostic performance for the detection of in-stent restenosis by coronary CTA.

Noting that these findings could guide patient selection for invasive coronary stent evaluation, combining DLR with a two-breath-hold subtraction technique “may help overcome challenges related to stent-related blooming artifact,” added corresponding author Yi-Ning Wang from the State Key Laboratory of Complex Severe and Rare Diseases at China’s Peking Union Medical College Hospital.

Between March 2020 and August 2021, Wang and team studied 30 patients (22 men, 8 women; mean age, 63.6 years) with a total of 59 coronary stents who underwent coronary CTA using the two-breath-hold technique (i.e., noncontrast and contrast-enhanced acquisitions). Conventional and subtraction images were reconstructed for hybrid iterative reconstruction (HIR) and DLR, while maximum visible in-stent lumen diameter was measured. Two readers independently evaluated images for in-stent restenosis (≥50% stenosis).

Ultimately, coronary CTA using DLR and subtraction technique—with a combined (conventional and subtraction images) interpretation—yielded PPV, NPV, and accuracy for in-stent restenosis for reader 1 of 73.3%, 93.2%, and 88.1%, and for reader 2 of 75.0%, 84.3%, and 83.1%, respectively.

Acknowledging that the two-breath-hold subtraction technique requires an additional noncontrast acquisition (and thus a higher radiation dose), “DLR allows a reduction in radiation exposure, while improving image quality,” the authors of this AJR article pointed out.


North America’s first radiological society, the American Roentgen Ray Society (ARRS) remains dedicated to the advancement of medicine through the profession of medical imaging and its allied sciences. An international forum for progress in radiology since the discovery of the x-ray, ARRS maintains its mission of improving health through a community committed to advancing knowledge and skills with the world’s longest continuously published radiology journal—American Journal of Roentgenology—the ARRS Annual Meeting, InPractice magazine, topical symposia, myriad multimedia educational materials, as well as awarding scholarships via The Roentgen Fund®.

MEDIA CONTACT:

Logan K. Young, PIO

44211 Slatestone Court

Leesburg, VA 20176

703-858-4332

[email protected]



Journal

American Journal of Roentgenology

DOI

10.2214/AJR.22.27983

Method of Research

Imaging analysis

Subject of Research

People

Article Title

Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique

Article Publication Date

10-Aug-2022

COI Statement

All other authors have no conflict of interest to disclose.

Share12Tweet8Share2ShareShareShare2

Related Posts

Turtle Meat Trade in Indonesia: Minimal Economic Impact

Turtle Meat Trade in Indonesia: Minimal Economic Impact

September 7, 2025
Winter Waterbirds Adapt to Severe Drought Challenges

Winter Waterbirds Adapt to Severe Drought Challenges

September 7, 2025

Honey Bee Gene Expression Altered by Electric Fields

September 7, 2025

Porcine Placenta Peptide Boosts Hair Health: Studies

September 7, 2025

POPULAR NEWS

  • blank

    Breakthrough in Computer Hardware Advances Solves Complex Optimization Challenges

    150 shares
    Share 60 Tweet 38
  • New Drug Formulation Transforms Intravenous Treatments into Rapid Injections

    116 shares
    Share 46 Tweet 29
  • First Confirmed Human Mpox Clade Ib Case China

    55 shares
    Share 22 Tweet 14
  • A Laser-Free Alternative to LASIK: Exploring New Vision Correction Methods

    47 shares
    Share 19 Tweet 12

About

We bring you the latest biotechnology news from best research centers and universities around the world. Check our website.

Follow us

Recent News

Zidesamtinib Demonstrates Lasting Efficacy in ROS1 TKI-Pretreated NSCLC, Including Cases with CNS Involvement and ROS1 G2032R Mutations

Crizotinib Does Not Enhance Disease-Free Survival in Resected Early-Stage ALK-Positive NSCLC

FLAURA2 Trial Demonstrates Enhanced Overall Survival with Osimertinib and Chemotherapy in EGFR-Mutated Advanced NSCLC

  • Contact Us

Bioengineer.org © Copyright 2023 All Rights Reserved.

Welcome Back!

Login to your account below

Forgotten Password?

Retrieve your password

Please enter your username or email address to reset your password.

Log In
No Result
View All Result
  • Homepages
    • Home Page 1
    • Home Page 2
  • News
  • National
  • Business
  • Health
  • Lifestyle
  • Science

Bioengineer.org © Copyright 2023 All Rights Reserved.