Research

Variability of myocardial perfusion dark rim Gibbs artifacts due to sub-pixel shifts

Pedro Ferreira¹ , Peter Gatehouse^1,2 , Peter Kellman³ , Chiara Bucciarelli-Ducci^1,2 and David Firmin^1,2

¹  National Heart and Lung Institute, Imperial College, London, UK

²  Royal Brompton Hospital, London, UK

³  National Institutes of Health, Bethesda, MD, USA

author email corresponding author email

Journal of Cardiovascular Magnetic Resonance 2009, 11:17doi:10.1186/1532-429X-11-17

Published:	27 May 2009

Abstract

Background

Gibbs ringing has been shown as a possible source of dark rim artifacts in myocardial perfusion studies. This type of artifact is usually described as transient, lasting a few heart beats, and localised in random segments of the myocardial wall. Dark rim artifacts are known to be unpredictably variable. This article aims to illustrate that a sub-pixel shift, i.e. a small displacement of the pixels with respect to the endocardial border, can result in different Gibbs ringing and hence different artifacts. Therefore a hypothesis for one cause of dark rim artifact variability is given based on the sub-pixel position of the endocardial border. This article also demonstrates the consequences for Gibbs artifacts when two different methods of image interpolation are applied (post-FFT interpolation, and pre-FFT zero-filling).

Results

Sub-pixel shifting of in vivo perfusion studies was shown to change the appearance of Gibbs artifacts. This effect was visible in the original uninterpolated images, and in the post-FFT interpolated images. The same shifted data interpolated by pre-FFT zero-filling exhibited much less variability in the Gibbs artifact. The in vivo findings were confirmed by phantom imaging and numerical simulations.

Conclusion

Unless pre-FFT zero-filling interpolation is performed, Gibbs artifacts are very dependent on the position of the subendocardial wall within the pixel. By introducing sub-pixel shifts relative to the endocardial border, some of the variability of the dark rim artifacts in different myocardial segments, in different patients and from frame to frame during first-pass perfusion due to cardiac and respiratory motion can be explained. Image interpolation by zero-filling can be used to minimize this dependency.