Performance evaluation of side‐by‐side optically coupled monolithic LYSO crystals

Abstract

Background: Significant interest has been recently shown for using monolithic scintillation crystals in molecular imaging systems, such as positron emission tomography (PET) scanners. Monolithic-based PET scanners result in a lower cost and higher sensitivity, in contrast to systems based on the more conventional pixellated configuration. The monolithic design allows one to retrieve depth-of -interaction information of the impinging 511 keV photons without the need for additional hardware materials or complex positioning algorithms. However, the so-called edge-effect inherent to monolithic-based approaches worsens the detector performance toward the crystal borders due to the truncation of the light distribution, thus decreasing positioning accuracy. Purpose: The main goal of this work is to experimentally demonstrate the detector performance improvement when machine-learning artificial neuralnetwork (NN) techniques are applied for positioning estimation in multiple monolithic scintillators optically coupled side-by-side. Methods: In this work, we show the performance evaluation of two LYSO crystals of 33 × 25.4 × 10 mm 3 optically coupled by means of a high refractive index adhesive compound (Meltmount, refractive index n = 1.70). A 12 × 12 silicon photomultiplier array has been used as photosensor. For comparison, the same detector configuration was tested for two additional coupling cases: (1) optical grease (n = 1.46) in between crystals, and (2) isolated crystals using black paint with an air gap at the interface (named standard configuration). Regarding 2D photon positioning (XY plane), we have tested two different methods: (1) a machine-learning artificial NN algorithm and (2) a squared-charge (SC) centroid technique. Results: At the interface region of the detector, the SC method achieved spatial resolutions of 1.7 ± 0.3, 2.4 ± 0.3, and 2.6 ± 0.4 mm full-width at half -maximum (FWHM) for the Meltmount, grease, and standard configurations, respectively. These values improve to 1.0 ± 0.2, 1.2 ± 0.2, and 1.2 ± 0.3 mm FWHM when the NN algorithm was employed. Regarding energy performance, resolutions of 18 ± 2%, 20 ± 2%, and 23 ± 3% were obtained at the interface region of the detector for Meltmount, grease, and standard configurations, respectively. Conclusions: The results suggest that optically coupling together scintillators with a high refractive index adhesive, in combination with an NN algorithm, reduces edge-effects and makes it possible to build scanners with almost no gaps in between detectors.

Monolithic scintillator PET detector by using light sharing between adjacent detector modules

“…The transverse position resolution of the PET detector near the crystal edge with light sharing measured in this work is close to the result in the literature [10], but the degree of improvement relative to the black-painted case is better (see table 2 for details). Our result is poorer than that of [9], which is due to the use of thinner crystals and a coupling medium with a higher refractive index. Since the DOI resolution was not given in both references, a comparison of DOI resolution could not be made.…”

“…the critical angle of total reflection is the largest and more light goes through the interface and is transmitted to adjacent crystals. The critical angles (𝜃 𝐶 ) for the three cases are labeled in figure 5 sharing occurs when the coupling refractive index is closer to that of the crystal [9]. The bimodal distributions for grease and air are caused by poor light sharing.…”

“…The method of optical coupling between monolithic crystals has been proposed to reduce the edge effect [8][9][10], and can be a useful method to improve the uniformity of performances in the whole sensitive area. Because light sharing between adjacent crystals increases as the crystal thickness, this method allows thick crystals to be used.…”

Exploiting Cherenkov radiation with BGO-based metascintillators

“…As it has been demonstrated that variable depth-of-interaction is one of the primary mechanisms deteriorating the CTR of scintillators, we are working on developing metascintillators that include precise DOI characterization [19,20,21]. This information will be combined with the energy sharing and first photon-arrival through neural networks to improve all metascintillator specifications collectively, according to recently published works [22].…”

Position estimation using neural networks in semi-monolithic PET detectors

“…Different methods have been proposed to add depth-decoding capabilities to pixelated PET detectors, such as multi-layer detector, side-readout or poshwich configurations but, these approaches usually require an increase in production costs since extra hardware materials or more expensive crystal cutting and assembling process are needed (Surti and Karp 2020, Ito et One of the drawbacks of using monolithic-based detectors is the so-called edge effect. However, as demonstrated, it can be (partially) compensated by using sophisticated calibration and position estimation algorithms (Freire et al 2022). Moreover, the spread of the scintillation light among several SiPMs does not facilitate the collection of a high number of photons at each single photosensor element in a short time (Lamprou et al 2020), which is mandatory for good timing capabilities.…”