Optical Monte-Carlo Simulation to Evaluate Monolithic PET Detector Concepts

Grahe, Jan; Müller, Florian W.; Schug, David; Hallen, P.; Schulz, Volkmar

doi:10.1109/nssmic.2017.8532632

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…Usually, a deterioration of the SR close to the scintillator's edges (edge effects), mainly caused by multiple reflections of optical photons, is observed. This challenge was tackled by analytical, 26,27 simulated, 25,28,29 and experimental 24,[30][31][32] calibration approaches. However, complex calibration techniques and computational demanding algorithms for position estimation of the gamma interaction remain one of the main challenges to transfer this concept into an application with many detectors, such as clinical scanners or total-body PET.…”

Section: Introductionmentioning

confidence: 99%

A semi‐monolithic detector providing intrinsic DOI‐encoding and sub‐200 ps CRT TOF‐capabilities for clinical PET applications

et al. 2022

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Background Current clinical positron emission tomography (PET) systems utilize detectors where the scintillator typically contains single elements of 3–6‐mm width and about 20‐mm height. While providing good time‐of‐flight performance, this design limits the spatial resolution and causes radial astigmatism as the depth‐of‐interaction (DOI) remains unknown. Purpose We propose an alternative, aiming to combine the advantages of current detectors with the DOI capabilities shown for monolithic concepts, based on semi‐monolithic scintillators (slabs). Here, the optical photons spread along one dimension enabling DOI‐encoding with a still small readout area beneficial for timing performance. Methods An array of eight monolithic LYSO slabs of dimensions 3.9 × 32 × 19 mm3 was read out by a 64‐channel photosensor containing digital SiPMs (DPC3200‐22‐44, Philips Digital Photon Counting). The position estimation in the detector's monolithic and DOI direction was based on a calibration with a fan beam collimator and the machine learning technique gradient tree boosting (GTB). Results We achieved a positioning performance in terms of mean absolute error (MAE) of 1.44 mm for the monolithic direction and 2.12 mm for DOI considering a wide energy window of 300–700 keV. The energy resolution was determined to be 11.3%, applying a positional‐dependent energy calibration. We established both an analytical and machine‐learning‐based timing calibration approach and applied them for a first‐photon trigger. The analytical timing calibration corrects for electronic and optical time skews leading to 240 ps coincidence resolving time (CRT) for a pair of slab‐detectors. The CRT was significantly improved by utilizing GTB to predict the time difference based on specific training data and applied on top of the analytical calibration. We achieved 209 ps for the wide energy window and 198 ps for a narrow selection around the photopeak (411–561 keV). To maintain the detector's sensitivity, no filters were applied to the data during processing. Conclusion Overall, the semi‐monolithic detector provides attractive performance characteristics. Especially, a good CRT can be achieved while introducing DOI capabilities to the detector, making the concept suitable for clinical PET scanners.

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Section: Introductionmentioning

confidence: 99%

A semi‐monolithic detector providing intrinsic DOI‐encoding and sub‐200 ps CRT TOF‐capabilities for clinical PET applications

et al. 2022

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“…We chose the reflective wrapping to achieve a high light-output of the scintillator. An optical simulation studying the influence of several scintillator wrappings (e.g., black tape) on the position performance of GTB-models can be found in [36]. To register coincidences, we employed a 12 mm-high pixelated array with 1 mm pitch also utilized in [37], [38].…”

Section: B Scintillator Crystal and Wrappingmentioning

confidence: 99%

A Novel DOI Positioning Algorithm for Monolithic Scintillator Crystals in PET Based on Gradient Tree Boosting

Müller

Schug

Hallen

et al. 2019

IEEE Trans. Radiat. Plasma Med. Sci.

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Monolithic crystals are examined as an alternative to segmented scintillator arrays in positron emission tomography (PET). Monoliths provide good energy, timing and spatial resolution including intrinsic depth of interaction (DOI) encoding. DOI allows reducing parallax errors (radial astigmatism) at off-center positions within a PET ring. We present a novel DOI-estimation approach based on the supervised machine learning algorithm gradient tree boosting (GTB). GTB builds predictive regression models based on sequential binary comparisons (decision trees). GTB models have been shown to be implementable in FPGA if the memory requirement fits the available resources. We propose two optimization scenarios for the best possible positioning performance: One restricting the available memory to enable a future FPGA implementation and one without any restrictions. The positioning performance of the GTB models is compared with a DOI estimation method based on a single DOI observable (SO) comparable to other methods presented in literature. For a 12 mm high monolith, we achieve an averaged spatial resolution of 2.15 mm and 2.12 mm FWHM for SO and GTB models, respectively. In contrast to SO models, GTB models show a nearly uniform positioning performance over the whole crystal depth.

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Optical Monte-Carlo Simulation to Evaluate Monolithic PET Detector Concepts

Cited by 2 publications

References 8 publications

A semi‐monolithic detector providing intrinsic DOI‐encoding and sub‐200 ps CRT TOF‐capabilities for clinical PET applications

A semi‐monolithic detector providing intrinsic DOI‐encoding and sub‐200 ps CRT TOF‐capabilities for clinical PET applications

A Novel DOI Positioning Algorithm for Monolithic Scintillator Crystals in PET Based on Gradient Tree Boosting

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