Collimator optimization in myocardial perfusion SPECT using the ideal observer and realistic background variability for lesion detection and joint detection and localization tasks

Abstract

In SPECT imaging, collimators are a major factor limiting image quality and largely determine the noise and resolution of SPECT images. In this paper, we seek the collimator with the optimal tradeoff between image noise and resolution with respect to performance on two tasks related to myocardial perfusion SPECT: perfusion defect detection and joint detection and localization. We used the Ideal Observer (IO) operating on realistic background-known-statistically (BKS) and signal-known-exactly (SKE) data. The areas under the receiver operating characteristic (ROC) and localization ROC (LROC) curves (AUCd, AUCd+l), respectively, were used as the figures of merit for both tasks. We used a previously developed population of 54 phantoms based on the eXtended Cardiac Torso Phantom (XCAT) that included variations in gender, body size, heart size and subcutaneous adipose tissue level. For each phantom, organ uptakes were varied randomly based on distributions observed in patient data. We simulated perfusion defects at six different locations with extents and severities of 10% and 25%, respectively, which represented challenging but clinically relevant defects. The extent and severity are, respectively, the perfusion defect's fraction of the myocardial volume and reduction of uptake relative to the normal myocardium. Projection data were generated using an analytical projector that modeled attenuation, scatter, and collimator-detector response effects, a 9% energy resolution at 140 keV, and a 4 mm full-width at half maximum (FWHM) intrinsic spatial resolution. We investigated a family of eight parallel-hole collimators that spanned a large range of sensitivity-resolution tradeoffs. For each collimator and defect location, the IO test statistics were computed using a Markov Chain Monte Carlo (MCMC) method for an ensemble of 540 pairs of defect-present and -absent images that included the aforementioned anatomical and uptake variability. Sets of test statistics were computed for both tasks and analyzed using ROC and LROC analysis methodologies. The results of this study suggest that collimators with somewhat poorer resolution and higher sensitivity than those of a typical low-energy high-resolution (LEHR) collimator were optimal for both defect detection and joint detection and localization tasks in myocardial perfusion SPECT for the range of defect sizes investigated. This study also indicates that optimizing instrumentation for a detection task may provide near-optimal performance on the more challenging detection-localization task.

Figure 1

Sample short axis images showing a normal heart (left) and a defective heart at six different locations of the myocardial wall (d₁ to d₆ from left to right). For illustrative purposes, defects shown have 100% severity.

Figure 2

Sample short axis images showing a heart with a perfusion defect at two different locations (d₂ (top row) and d₅ (bottom row)) in the heart and extents of 5%, 10% and 25%, from left to right.

Figure 3

Sample noise-free (top row) and noisy (bottom row) projection images of the heart acquired at an anterior view using collimators C₁ to C₈, respectively, from left to right. From left-to-right note the decreasing noise (in the bottom row) and sharpness of the images, as expected.

Figure 4

A plot of the likelihood ratio with iteration number for an input projection image with a perfusion defect located at the anterolateral wall (location d₂).

Figure 5

The ideal Observer performance measured in terms of AUC_d for the different collimators.

Figure 6

Observer performance in terms of AUC_d for various defect sizes located at d₂.

Figure 7

Observer performance in terms of AUC_d for various defect sizes located at d₅.

Figure 8

AUC_d values for the different sub populations.

Figure 9

The ideal Observer performance measured in terms of AUC_d+l for the different collimators.