Monolithic scintillator PET detectors with intrinsic depth-of-interaction correction

Maas, Marnix C.; Schaart, Dennis R.; Laan, D.J. van der; Bruyndonckx, Peter; Lemaître, Cédric; Beekman, Freek J.; Eijk, C.W.E. van

doi:10.1088/0031-9155/54/7/003

Cited by 126 publications

(147 citation statements)

References 27 publications

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“…In previous works, it was observed that the position resolution of monolithic scintillator detectors increases near the edges of the crystal (Maas et al 2009. To investigate if the present simulations correctly reproduce these edge effects, figure 8 compares the FWHM of the measured and simulated spatial responses as a function of the x-position in the crystal, for each of the two detector geometries investigated.…”

Section: Detector Position Resolutionmentioning

confidence: 69%

“…The design and operating principle of the monolithic PET detectors investigated in this work have been described in detail elsewhere (Maas et al 2008(Maas et al , 2009). Here, we briefly summarize the features relevant for the present study.…”

Section: Description Of the Pet Detectormentioning

confidence: 99%

“…Two detector geometries were simulated that have previously been characterized experimentally (Maas et al 2008(Maas et al , 2009). The measured results can thus be used to validate the simulations.…”

Section: Description Of the Pet Detectormentioning

confidence: 99%

“…The total surface of the APD array measures 19.5 mm × 11.2 mm. The entry points of detected annihilation photons ('events') on the front surface of the crystal are estimated from the measured scintillation light distributions incident upon the APD arrays (Maas et al 2009). The position estimation algorithm uses a reference set of light distributions from a large number of events with known entry points.…”

Section: Description Of the Pet Detectormentioning

confidence: 99%

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Optical simulation of monolithic scintillator detectors using GATE/GEANT4

et al. 2010

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Much research is being conducted on position-sensitive scintillation detectors for medical imaging, particularly for emission tomography. Monte Carlo simulations play an essential role in many of these research activities. As the scintillation process, the transport of scintillation photons through the crystal(s), and the conversion of these photons into electronic signals each have a major influence on the detector performance; all of these processes may need to be incorporated in the model to obtain accurate results. In this work the optical and scintillation models of the GEANT4 simulation toolkit are validated by comparing simulations and measurements on monolithic scintillator detectors for high-resolution positron emission tomography (PET). We have furthermore made the GEANT4 optical models available within the user-friendly GATE simulation platform (as of version 3.0). It is shown how the necessary optical input parameters can be determined with sufficient accuracy. The results show that the optical physics models of GATE/GEANT4 enable accurate prediction of the spatial and energy resolution of monolithic scintillator PET detectors.

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Section: Detector Position Resolutionmentioning

confidence: 69%

Section: Description Of the Pet Detectormentioning

confidence: 99%

Section: Description Of the Pet Detectormentioning

confidence: 99%

Section: Description Of the Pet Detectormentioning

confidence: 99%

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Optical simulation of monolithic scintillator detectors using GATE/GEANT4

et al. 2010

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“…A way out could be the monolithic block detector which has been subject to several papers during the last years [3][4][5]. One continuous scintillator block is placed on a pixelated photo detector and the position is reconstructed from the light distribution on the pixels by a dedicated algorithm which even can provide the depth of interaction information [6]. In this work two different positioning algorithms where evaluated.…”

Section: Introductionmentioning

confidence: 99%

Position reconstruction in monolithic block detectors

Streun

Nöldgen

Kemmerling

et al. 2012

2012 IEEE Nuclear Science Symposium and Medical Imaging Conference Record (NSS/MIC)

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Abstract-In high resolution PET systems the detector generally uses a scintillator which consists of individual pixel elements. The scintillation light of such a pixel element will be identified and thus the interaction is localized by the pixel position. Consequently, the delivered position of such a detector can only take discrete values.A different approach is the monolithic scintillator detector. A continuous scintillator block spans over an area of several photodetector pixels and the position is reconstructed from the recorded light distribution. Manufacturing of this detector is easier and the sensitivity is generally higher as no scintillating material is wasted for optical isolation between the pixels. But the challenge is to find a dedicated algorithm in order to identify the interaction position with sufficient resolution.We will present measurements of a monolithic scintillator detector (21×18×10mm 3 LYSO) and compare different reconstruction methods. Already a Least Square Optimization algorithm based on a rather simple model delivers a resolution similar to an Artificial Neural Network approach but which requires pre-registered data for training. The comparison of the resolution to that of a pixelated detector of similar size and 2×2×10mm 3 pixels shows the superior performance of the continuous block.

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

et al. 2022

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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.

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Monolithic scintillator PET detectors with intrinsic depth-of-interaction correction

Cited by 126 publications

References 27 publications

Optical simulation of monolithic scintillator detectors using GATE/GEANT4

Optical simulation of monolithic scintillator detectors using GATE/GEANT4

Position reconstruction in monolithic block detectors

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

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