Application and Evaluation of a Measured Spatially Variant System Model for PET Image Reconstruction

Abstract

Accurate system modeling in tomographic image reconstruction has been shown to reduce the spatial variance of resolution and improve quantitative accuracy. System modeling can be improved through analytic calculations, Monte Carlo simulations, and physical measurements. The purpose of this work is to improve clinical fully-3-D reconstruction without substantially increasing computation time. We present a practical method for measuring the detector blurring component of a whole-body positron emission tomography (PET) system to form an approximate system model for use with fully-3-D reconstruction. We employ Monte Carlo simulations to show that a non-collimated point source is acceptable for modeling the radial blurring present in a PET tomograph and we justify the use of a Na22 point source for collecting these measurements. We measure the system response on a whole-body scanner, simplify it to a 2-D function, and incorporate a parameterized version of this response into a modified fully-3-D OSEM algorithm. Empirical testing of the signal versus noise benefits reveal roughly a 15% improvement in spatial resolution and 10% improvement in contrast at matched image noise levels. Convergence analysis demonstrates improved resolution and contrast versus noise properties can be achieved with the proposed method with similar computation time as the conventional approach. Comparison of the measured spatially variant and invariant reconstruction revealed similar performance with conventional image metrics. Edge artifacts, which are a common artifact of resolution-modeled reconstruction methods, were less apparent in the spatially variant method than in the invariant method. With the proposed and other resolution-modeled reconstruction methods, edge artifacts need to be studied in more detail to determine the optimal tradeoff of resolution/contrast enhancement and edge fidelity.

Resolution modeling in PET imaging: Theory, practice, benefits, and pitfalls

“…This work was incorporated within the HD-PET release by Siemens in a number of clinical PET/CT scanners, and subsequently studied in a number of applications, e.g., cardiac imaging. 84,85 The previously mentioned model S(r, z; r 0 ) by Alessio et al 70 actually showed minimal improvements relative to a further simplified model S(r; r 0 ) performing blurring only along the radial direction, which was subsequently adopted in a later work: 63 the approach involved measurement of projection-space profiles for point sources scanned at 14 radial positions across the transaxial FOV: profiles for intermediate radial positions were estimated via linear interpolations of discrete cosine transform (DCT) coefficients from the measured profiles. The resulting S(r; r 0 ) is depicted in Fig.…”

“…60 and 61) or 22 Na (e.g., Refs. 49 and 62) sources (which have very similar positron range properties to one another 63 ). Nonetheless, Sec.…”

Single scan parameterization of space-variant point spread functions in image space via a printed array: the impact for two PET/CT scanners

“…Finally Cloquet et al (2010) used a single 22 Na source and a grid to guide the source at the measured positions. Limited measurements of a 22 Na point source were also used by Alessio et al (2010) and Rapisarda et al (2010).…”

Improvement in PET/CT Image Quality with a Combination of Point-Spread Function and Time-of-Flight in Relation to Reconstruction Parameters

“…High image quality is required for an accurate diagnosis, although the spatial resolution of PET is relatively low in comparison to other imaging modalities (7). Recently, the information provided by the point-spread function (PSF) and time-of-flight (TOF) has been expected to improve the spatial resolution and signal-to-noise ratio (SNR), respectively, of PET images (8)(9)(10).…”