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

TL;DR

This paper introduces a novel super-resolution technique for PET imaging using an intensity modulator to overcome resolution limits, demonstrating improved resolution in simulations with potential clinical applications.

Contribution

A new super-resolution PET method inspired by structured illumination microscopy, utilizing a rotating intensity modulator and an advanced reconstruction algorithm.

Findings

Resolved 0.9 mm sources with noise-free data

Resolved 1.5 mm sources with noisy data

Improved visualization of small structures despite sensitivity loss

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.