Development of 1.45-mm resolution four-layer DOI-PET detector for simultaneous measurement in 3T MRI

Detectors in positron emission tomography

Positron emission tomography is a highly sensitive molecular imaging modality, based on the coincident detection of annihilation photons after positron decay. The most used detector is based on dense, fast, and luminous scintillators read out by light sensors. This review covers the various detector concepts for clinical and preclinical systems.

Development of dual-ended depth-of-interaction detectors using laser-induced crystals for small animal PET systems

Sensitivity and spatial resolution of positron emission tomography (PET) scanners can be improved by using thicker scintillation crystals with depth-of-interaction (DOI) encoding. Subsurface laser engraving (SSLE) can be used to segment crystals of a scintillation detector in order to fabricate a DOI detector. We previously applied SSLE to crystal bars of 3 × 3 × 20 mm³and 1.5 × 1.5 × 20 mm³and developed two dual-ended detectors with DOI segments of 3 mm and 1.5 mm, respectively. To further improve the DOI resolution, our SSLE detector design can be used with smaller pitch crystal bars, making them excellent detector candidates for small animal PET scanners with submillimetre resolution. In the present study, three small crystal bars of 1 × 1 × 20 mm³, 2 × 1 × 20 mm³, and 2 × 1 × 40 mm³were laser engraved to 12, 20 and 40 segments, respectively, by applying SSLE in their height directions. The segmented crystal bars were characterised in three prototype detector arrangements. First, the 1 × 1 × 20 mm³crystal bars were characterised in an 8 × 8 crystal array designed for DOI encoding along crystal height in a conventional small animal PET design. Second, a 4 × 8 crystal array of 2 × 1 × 20 mm³crystal bars was characterised for using the DOI information for crystal interaction positioning along the axial axis of a small animal PET scanner. Finally, the third part of the study was performed on a single 2 × 1 × 40 mm³crystal bar with 40 segments to investigate the feasibility of DOI estimation in longer crystals for application in a system with extended axial length. We evaluated the capability of segment identification and energy resolution of theses detectors. The 3D position maps of the detectors were obtained using the Anger-type calculation and the crystal identification performance was evaluated for each detector. Clear segment separation was obtained for the crystal arrays with 12 (segment pitch of 1.67 mm) and 20 (segment pitch of 1 mm) segments. Mean energy resolutions of 8.8% ± 0.4% and 9.6% ± 0.8% at 511 keV were obtained for the segments in the central regions of the 8 × 8 array with 12 segments and the 4 × 8 array with 20 segments, respectively. Clear segment identification was found to be difficult for the detector with 40 segments, especially for the segments at the middle of the crystal. Energy and interaction positioning characterisation results suggest that both prototype detectors with 12 and 20 segments are well suited for small animal PET scanners with high spatial resolution.

Sub-2 mm depth of interaction localization in PET detectors with prismatoid light guide arrays and single-ended readout using convolutional neural networks

PURPOSE

Depth of interaction (DOI) readout in PET imaging has been researched in efforts to mitigate parallax error, which would enable the development of small diameter, high-resolution PET scanners. However, DOI PET has not yet been commercialized due to the lack of practical, cost-effective, and data efficient DOI readout methods. The rationale for this study was to develop a supervised machine learning algorithm for DOI estimation in PET that can be trained and deployed on unique sets of crystals.

METHODS

Depth collimated flood data was experimentally acquired using a Na-22 source with a depth-encoding single-ended readout Prism-PET module consisting of lutetium yttrium orthosilicate (LYSO) crystals coupled 4-to-1 to 3×3  mm 2 silicon photomultiplier (SiPM) pixels on one end and a segmented prismatoid light guide array on the other end. A convolutional neural network (CNN) was trained to perform DOI estimation on data from center, edge and corner crystals in the Prism-PET module using (a) all non-zero readout pixels and (b) only the 4 highest readout signals per event. CNN testing was performed on data from crystals not included in CNN training.

RESULTS

An average DOI resolution of 1.84 mm full width at half maximum (FWHM) across all crystals was achieved when using all readout signals per event with the CNN compared to 3.04 mm FWHM DOI resolution using classical estimation. When using only the 4 highest signals per event, an average DOI resolution of 1.92 mm FWHM was achieved, representing only a 4% dropoff in CNN performance compared to using all non-zero pixels per event.

CONCLUSIONS

Our CNN-based DOI estimation algorithm provides the best reported DOI resolution in a single-ended readout module and can be readily deployed on crystals not used for model training.

Prismatoid light guide array for enhanced gamma ray localization in PET: a Monte Carlo simulation study of scintillation photon transport

High spatial resolution PET relies on having excellent depth-of-interaction (DOI) resolution and small detector elements. Depth-encoding in PET modules has traditionally been performed using dual-ended readout. In recent years, researchers have explored the feasibility of replacing the second readout array with a light guide at the entrance layer that introduces intercrystal light sharing in order to reduce cost and and make depth-encoding modules more compact. However, single-ended readout depth-encoding modules have suboptimal and non-uniform crystal separation and DOI performance due to the random light sharing patterns of the uniform light guide, resulting in degraded peformance along the edges and corners of the detector arrays. In this paper, we introduce and characterize a segmented light guide composed of an array of prism mirrors which introduce deterministic intercrystal light sharing in single-ended readout PET detectors. We determined the expected spatial performance of our modules with our light guide using optical ray tracing Monte Carlo simulations. We demonstrate that having controlled, deterministic light sharing improves both DOI and crystal identification performance, enabling uniform spatial performance throughout the detector array. Designed specifically for high resolution PET, our prismatoid light guide array can be used to build cost-effective total-body and organ-dedicated PET systems with single-ended readout depth-encoding modules.

Improving depth-of-interaction resolution in pixellated PET detectors using neural networks

Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation position and therefore degrades the spatial resolution. A way to address this issue is depth-of-interaction (DOI) estimation. In this work we propose two machine learning-based algorithms, a dense and a convolutional neural network (NN), as well as a multiple linear regression (MLR)-based method to estimate DOI in depolished PET detector arrays with single-sided readout. The algorithms were tested on an 8× 8 array of 1.53× 1.53× 15 mm³ crystals and a 4× 4 array of 3.1× 3.1× 15 mm³ crystals, both made of Ce:LYSO scintillators and coupled to a 4× 4 array of 3× 3 mm³ silicon photomultipliers (SiPMs). Using the conventional linear DOI estimation method resulted in an average DOI resolution of 3.76 mm and 3.51 mm FWHM for the 8× 8 and the 4× 4 arrays, respectively. Application of MLR outperformed the conventional method with average DOI resolutions of 3.25 mm and 3.33 mm FWHM, respectively. Using the machine learning approaches further improved the DOI resolution, to an average DOI resolution of 2.99 mm and 3.14 mm FWHM, respectively, and additionally improved the uniformity of the DOI resolution in both arrays. Lastly, preliminary results obtained by using only a section of the crystal array for training showed that the NN-based methods could be used to reduce the number of calibration steps required for each detector array.

Advances in PET/MR instrumentation and image reconstruction

The combination of positron emission tomography (PET) and MRI has attracted the attention of researchers in the past approximately 20 years in small-animal imaging and more recently in clinical research. The combination of PET/MRI allows researchers to explore clinical and research questions in a wide number of fields, some of which are briefly mentioned here. An important number of groups have developed different concepts to tackle the problems that PET instrumentation poses to the exposition of electromagnetic fields. We have described most of these research developments in preclinical and clinical experiments, including the few commercial scanners available. From the software perspective, an important number of algorithms have been developed to address the attenuation correction issue and to exploit the possibility that MRI provides for motion correction and quantitative image reconstruction, especially parametric modelling of radiopharmaceutical kinetics. In this work, we give an overview of some exemplar applications of simultaneous PET/MRI, together with technological hardware and software developments.

Improved image quality using monolithic scintillator detectors with dual-sided readout in a whole-body TOF-PET ring: a simulation study

We have recently built and characterized the performance of a monolithic scintillator detector based on a 32 mm  ×  32 mm  ×  22 mm LYSO:Ce crystal read out by digital silicon photomultiplier (dSiPM) arrays coupled to the crystal front and back surfaces in a dual-sided readout (DSR) configuration. The detector spatial resolution appeared to be markedly better than that of a detector consisting of the same crystal with conventional back-sided readout (BSR). Here, we aim to evaluate the influence of this difference in the detector spatial response on the quality of reconstructed images, so as to quantify the potential benefit of the DSR approach for high-resolution, whole-body time-of-flight (TOF) positron emission tomography (PET) applications. We perform Monte Carlo simulations of clinical PET systems based on BSR and DSR detectors, using the results of our detector characterization experiments to model the detector spatial responses. We subsequently quantify the improvement in image quality obtained with DSR compared to BSR, using clinically relevant metrics such as the contrast recovery coefficient (CRC) and the area under the localized receiver operating characteristic curve (ALROC). Finally, we compare the results with simulated rings of pixelated detectors with DOI capability. Our results show that the DSR detector produces significantly higher CRC and increased ALROC values than the BSR detector. The comparison with pixelated systems indicates that one would need to choose a crystal size of 3.2 mm with three DOI layers to match the performance of the BSR detector, while a pixel size of 1.3 mm with three DOI layers would be required to get on par with the DSR detector.