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Revolutionizing cardiac imaging: GE HealthCare’s Sonic DL Cine installed in over 100 sites globally

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Gallery Image 2
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Sonic DL™ Cine acquisitions. (A) short axis with breath-hold, 1.4 x 1.1 x 8 mm, temporal resolution=21 ms, 12 sec. and (B) 2-chamber with breath-hold, 1.4 x 1.1 x 8 mm, temporal resolution=21 ms, 13 sec.

In a significant advancement for healthcare innovation, GE HealthCare is pleased to announce the successful implementation of Sonic DL™ Cine, its revolutionary cardiac MR solution, at over 100 sites since its launch in August 2023.

 

Sonic DL™ Cine has emerged as a transformative technology in healthcare, greatly improving patient access to cardiac imaging, especially for those unable to comply with breath-holding requirements due to underlying health conditions. By accelerating cardiac cine acquisitions to as fast as one heartbeat, Sonic DL™ Cine has transformed patient care, reducing acquisition times by an impressive 83% and expediting cardiac examinations to as little as 15 minutes (see article).

 

At GE HealthCare, innovation is central to our mission. Sonic DL™ Cine represents the latest advancement in our mission to push the boundaries of cardiac MR technology. Learn more about how Sonic DL™ Cine works (see article).

 

Sonic DL™ Cine embodies our dedication to seamless deep-learning solutions and clinical excellence. By making precision medicine accessible to all, we empower healthcare providers to explore new frontiers in medical diagnostics.

 

The significance of cardiac imaging cannot be overstated, especially in addressing coronary artery disease, a leading cause of death worldwide.1 While MR has long been recognized as the gold standard for diagnostic cardiac imaging, traditional MR acquisition methods can be time-consuming and challenging for patients, necessitating a shift in imaging technology.2

 

 

 

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References

  1. World Health Organization. Cardiovascular Diseases, Fact Sheet. Available at: https://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)
  2. Zucker EJ, Sandino CM, Kino A, Lai P, Vasanawala SS. Free-breathing Accelerated Cardiac MRI Using Deep Learning: Validation in Children and Young Adults. Radiology. 2021 Sep;300(3):539-548.