Artifacts at Cardiac CT: Physics and Solutions

Kevin Kalisz1, Ji Buethe1, Sachin S Saboo1

  • 1From the Department of Radiology, University Hospitals Cleveland Medical Center, Cleveland, Ohio (K.K., J.B.); Department of Radiology, Cardiothoracic Imaging, UT Southwestern Medical Center, E6.120 B, Mail Code 9316, 5323 Harry Hines Blvd, Dallas, TX 75390-8896 (S.S.S., S.A., P.R.); and Philips Healthcare, Cleveland, Ohio (S.H.).

Insights

Computed tomography (CT) imaging is prone to artifacts from patient motion, technique, and unique cardiac factors. Strategies to reduce motion artifacts include optimizing heart rate, scan duration, and using advanced reconstruction algorithms.

Area of Science:

  • Medical Imaging
  • Radiology
  • Computed Tomography

Background:

  • Computed tomography (CT) is susceptible to numerous artifacts.
  • Patient- and technique-specific artifacts can impact image quality, especially in cardiac imaging.
  • Motion artifacts are the most prevalent type, stemming from patient, cardiac, or respiratory movement.

Purpose of the Study:

  • To comprehensively review common artifacts encountered in computed tomography (CT).
  • To detail the causes of various CT artifacts, including motion, partial volume averaging, beam hardening, metal, and quantum mottle.
  • To outline strategies for mitigating these artifacts to improve diagnostic accuracy.

Main Methods:

  • Review of literature on computed tomography (CT) artifacts.
  • Categorization of artifacts based on origin (patient, technique, cardiac).
  • Description of artifact reduction techniques for each category.

Main Results:

  • Motion artifacts (cardiac and respiratory) can be reduced through heart rate control, scan optimization, and advanced algorithms.
  • Partial volume averaging is mitigated by improved spatial resolution and higher x-ray energy.
  • Beam hardening, metal artifacts, and quantum mottle have specific causes and reduction strategies involving filtration, energy, positioning, and reconstruction algorithms.

Conclusions:

  • Understanding the causes of CT artifacts is crucial for effective mitigation.
  • Implementing specific technical and algorithmic adjustments can significantly reduce artifacts.
  • Optimizing CT protocols enhances image quality and diagnostic confidence in various clinical applications.

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