Comparing planar image quality of rotating slat and parallel hole collimation: influence of system modeling

• Published in: Physics in medicine & biology 2008-04, Vol.53 (7), p.1989-2002
• Main Authors: Van Holen, Roel, Vandenberghe, Stefaan, Staelens, Steven, Lemahieu, Ignace
• Format: Article
• Language: English
• Subjects: Algorithms; Computers; Gamma Cameras; Humans; Image Interpretation, Computer-Assisted - methods; Image Processing, Computer-Assisted; Likelihood Functions; Models, Statistical; Models, Theoretical; Monte Carlo Method; Neoplasm Metastasis; Neoplasms - pathology; Phantoms, Imaging; Software; Tomography, X-Ray Computed - methods
• ISSN: 0031-9155; 1361-6560
• DOI: 10.1088/0031-9155/53/7/013

The main remaining challenge for a gamma camera is to overcome the existing trade-off between collimator spatial resolution and system sensitivity. This problem, strongly limiting the performance of parallel hole collimated gamma cameras, can be overcome by applying new collimator designs such as rotating slat (RS) collimators which have a much higher photon collection efficiency. The drawback of a RS collimated gamma camera is that, even for obtaining planar images, image reconstruction is needed, resulting in noise accumulation. However, nowadays iterative reconstruction techniques with accurate system modeling can provide better image quality. Because the impact of this modeling on image quality differs from one system to another, an objective assessment of the image quality obtained with a RS collimator is needed in comparison to classical projection images obtained using a parallel hole (PH) collimator. In this paper, a comparative study of image quality, achieved with system modeling, is presented. RS data are reconstructed to planar images using maximum likelihood expectation maximization (MLEM) with an accurate Monte Carlo derived system matrix while PH projections are deconvolved using a Monte Carlo derived point-spread function. Contrast-to-noise characteristics are used to show image quality for cold and hot spots of varying size. Influence of the object size and contrast is investigated using the optimal contrast-to-noise ratio (CNR(o)). For a typical phantom setup, results show that cold spot imaging is slightly better for a PH collimator. For hot spot imaging, the CNR(o) of the RS images is found to increase with increasing lesion diameter and lesion contrast while it decreases when background dimensions become larger. Only for very large background dimensions in combination with low contrast lesions, the use of a PH collimator could be beneficial for hot spot imaging. In all other cases, the RS collimator scores better. Finally, the simulation of a planar bone scan on a RS collimator revealed a hot spot contrast improvement up to 54% compared to a classical PH bone scan.