Super-resolution positron emission tomography by intensity modulation: Proof of concept

TL;DR

This paper addresses the limitation of clinical PET resolution by adapting SR-SIM principles to PET through a rotating intensity modulator in front of a stationary detector ring, enabling bandwidth expansion and aliasing suppression. The authors formulate a 2-D SR-PET model, derive how modulated projections can be inverted with OSEM, and systematically evaluate the approach using analytic and GATE Monte-Carlo simulations. They demonstrate that, in noise-free data, 0.9 mm sources can be resolved, and with Poisson noise, 1.5 mm structures remain detectable with improved visibility and CRC-STD performance, particularly using a modulator with moderate period (M2) and variable tungsten depth. The work provides a strong proof-of-concept that on-demand super-resolution PET is feasible with rotating ring modulators, highlighting potential practical impact while acknowledging substantial factors (attenuation, scatter, randoms, DOI) that require future investigation and optimization for clinical translation.

Abstract

We proposed a new approach, which is inspired by the method of super-resolution (SR) structured illumination microscopy (SIM) for overcoming the resolution limit in microscopy due to diffraction of light, for increasing the resolution of clinical positron emission tomography (PET) beyond its instrumentation limit. We implemented the key idea behind SR-SIM by using a rotating intensity modulator in front of a stationary PET detector ring. Its function is to modulate down high-frequency signals of the projection data that originally were above the system's bandwidth and unobservable to appear as aliased lower-frequency ones that are detectable. We formulated a model that relates an image whose resolution is above the instrumentation limit to several thus obtained limited-resolution measurements at various rotational positions of the modulator. We implemented an ordered-subsets expectation-maximization algorithm for inverting the model. Using noise-free data produced by an analytic projector, we showed this approach can resolve 0.9 mm sources when applied to a PET system that employs 4.2 mm width detectors. With noisy data, the SR performance remains promising. In particular, 1.5 mm sources were resolvable, and the visibility and quantification of small sources and fine structures were improved despite the sensitivity loss incurred by the modulator. These observations remain valid when using more realistic Monte-Carlo simulation data. More studies are needed to better understand the theoretical aspects of the proposed method and to optimize the design of the modulator and the reconstruction algorithm.

Figures (15)

• Figure 1: Schematics of four modulators having different periods on top of the detectors (white rectangles). The transmission values in the red and green segments are 0.76 (emulating 5 mm thick tungsten) and 1 (emulating air), respectively. For purpose of visualization, these drawings are not properly scaled; the detectors shall have the same width.
• Figure 2: Activity phantoms employed. See text for details.
• Figure 3: S image using 1 mm pixels (a) and 0.3 mm pixels (b), and M0 images using 0.3 mm pixels (c) obtained from noise-free data by using 50 (top) and 500 (bottom) OSEM iterations. The phantom was placed at the center.
• Figure 4: M0.5 (a), M1 (b), M2 (c), and M4 (d) images obtained from noise-free data by using 50 (top) and 500 (bottom) OSEM iterations. The phantom was placed at the center.
• Figure 5: From left to right are images obtained from 1M-, 2M-, 4M-, 8M-, and 16M-event data by using 10, 20, 30, 40 and 50 iterations, respectively.