Recent developments in time-of-flight PET

Abstract

While the first time-of-flight (TOF)-positron emission tomography (PET) systems were already built in the early 1980s, limited clinical studies were acquired on these scanners. PET was still a research tool, and the available TOF-PET systems were experimental. Due to a combination of low stopping power and limited spatial resolution (caused by limited light output of the scintillators), these systems could not compete with bismuth germanate (BGO)-based PET scanners. Developments on TOF system were limited for about a decade but started again around 2000. The combination of fast photomultipliers, scintillators with high density, modern electronics, and faster computing power for image reconstruction have made it possible to introduce this principle in clinical TOF-PET systems. This paper reviews recent developments in system design, image reconstruction, corrections, and the potential in new applications for TOF-PET. After explaining the basic principles of time-of-flight, the difficulties in detector technology and electronics to obtain a good and stable timing resolution are shortly explained. The available clinical systems and prototypes under development are described in detail. The development of this type of PET scanner also requires modified image reconstruction with accurate modeling and correction methods. The additional dimension introduced by the time difference motivates a shift from sinogram- to listmode-based reconstruction. This reconstruction is however rather slow and therefore rebinning techniques specific for TOF data have been proposed. The main motivation for TOF-PET remains the large potential for image quality improvement and more accurate quantification for a given number of counts. The gain is related to the ratio of object size and spatial extent of the TOF kernel and is therefore particularly relevant for heavy patients, where image quality degrades significantly due to increased attenuation (low counts) and high scatter fractions. The original calculations for the gain were based on analytical methods. Recent publications for iterative reconstruction have shown that it is difficult to quantify TOF gain into one factor. The gain depends on the measured distribution, the location within the object, and the count rate. In a clinical situation, the gain can be used to either increase the standardized uptake value (SUV) or reduce the image acquisition time or administered dose. The localized nature of the TOF kernel makes it possible to utilize local tomography reconstruction or to separate emission from transmission data. The introduction of TOF also improves the joint estimation of transmission and emission images from emission data only. TOF is also interesting for new applications of PET-like isotopes with low branching ratio for positron fraction. The local nature also reduces the need for fine angular sampling, which makes TOF interesting for limited angle situations like breast PET and online dose imaging in proton or hadron therapy. The aim of this review is to introduce the reader in an educational way into the topic of TOF-PET and to give an overview of the benefits and new opportunities in using this additional information.

Keywords: PET; Reconstruction; Time-of-flight.

Fig. 1

Compared to conventional PET, the estimated time-of-flight difference (Δ t) between the arrival times of photons on both detectors in TOF-PET allows localization (with a certain probability) of the point of annihilation on the line of response. In TOF-PET, the distance to the origin of scanner (Δ x) is proportional to the TOF difference via the relation: Δ t: $\mathrm{\Delta x}=\frac{\mathrm{c\Delta t}}{2}$, where c is the speed of light. t ₁ is the arrival time on the first detector, and t ₂ is the arrival time on the second detector

Fig. 2

A clinical TOF-PET scanner is a well-balanced combination of fast scintillators, readout hardware, and accurate reconstruction and corrections

Fig. 3

Using a wrong TOF kernel in reconstruction can lead to undershoot (too small TOF kernel) or overshoot (too wide TOF kernel) in the reconstructed image

Fig. 4

The acquisition methods for obtaining TOF offset calibration data. a Using a rotating line source. An emission from the line source (red) is detected by crystal pairs connecting via straight line through the point. b Using a scattering phantom (indicated in blue) and a point source. An emission from point source (red) is detected after scattering at 1 or 2. c Using an annulus shape source. The set of close LORs (in black) is averaged and used to calculate the average offset per detector pixel

Fig. 5

TOF gain is proportional to the ratio of object size to the spatial TOF kernel width. This calculation [4] assumes analytical reconstruction and a simple uniform cylinder of activity

Fig. 6

The use of better TOF information leads to reduced dependency of convergence on the object size

Fig. 7

TOF-based extraction of transmission data on a particular LOR for a threshold radius τ

Fig. 8

MLTR: the attenuation correction method based on the TOF separation of the transmission and the emission data

Fig. 9

A limited angle design for a breast TOF-PET scanner. From left to right: the schematic of detectors (with compression paddles) and limited angle acquisition, physical detector modules in lab (evaluated with phantoms and illustration of integration of PET with X-ray used for tomosynthesis imaging

Fig. 10

Open ring design of in-beam PET