ArticlePhysics in medicine and biology2020
A digital phoswich detector using time-over-threshold for depth of interaction in PET.
Article in Physics in medicine and biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 24 citations in OpenAlex.
- Impact of DOI Capability on Detector Performance: A Comparative Study of DOI and Non-DOI Detectors for High-Resolution and Sensitivity Organ-Specific PET Inserts.IEEE transactions on radiation and plasma medical sciences · 2026Article
- Energy estimation methods for positron emission tomography detectors composed of multiple scintillators.Biomedical engineering letters · 2025Article
- A time-based single transmission-line readout with position multiplexing.Biomedical engineering letters · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 3 countries.
Funding
Abstract
We present the performance of a digital phoswich positron emission tomography (PET) detector, composed by layers of pixilated scintillator arrays, read out by solid state light detectors and an application specific integrated circuit (ASIC). We investigated the use of integrated charge from the scintillation pulses along with time-over-threshold (ToT) to determine the layer of interaction (DOI) in the scintillator. Simulations were performed to assess the effectiveness of the ToT measurements for separating the scintillator events and identifying cross-layer-crystal-scatter (CLCS) events. These simulations indicate that ToT and charge integration from such a detector provide sufficient information to determine the layer of interaction. To demonstrate this in practice, we used a pair of prototype LYSO/BGO detectors. One detector consisted of a 19 × 19 array of 7 mm long LYSO crystals (1.36 mm pitch) coupled to a 16 × 16 array of 8 mm long BGO crystals (1.63 mm pitch). The other detector was similar except the LYSO crystal pitch was 1.63 mm. These detectors were coupled to an 8 × 8 multi-pixel photon counter mounted on a PETsys TOFPET2 ASIC. This high performance ASIC provided digital readout of the integrated charge and ToT from these detectors. We present a method to separate the events from the two scintillator layers using the ToT, and also investigate the performance of this detector. All the crystals within the proposed detector were clearly resolved, and the peak to valley ratio was 11.8 ± 4.0 and 10.1 ± 2.9 for the LYSO and BGO flood images. The measured energy resolution was 9.9% ± 1.3% and 28.5% ± 5.0% respectively for the LYSO and BGO crystals in the phoswich layers. The timing resolution between the LYSO-LYSO, LYSO-BGO and BGO-BGO coincidences was 468 ps, 1.33 ns and 2.14 ns respectively. Results show ToT can be used to identify the crystal layer where events occurred and also identify and reject the majority of CLCS events between layers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.