Evidence map›Paper›PMID 34169535›Full record

ArticleMedical physics2021

Silicon photomultiplier-based scintillation detectors for photon-counting CT: A feasibility study.

Stefan J van der Sar, Stefan E Brunner, Dennis R Schaart

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Article in Medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Guidelines for the Selection of Scintillators for Indirect Photon-Counting X-ray Detectors.Chemistry of materials : a publication of the American Chemical Society · 2025
    Review
  6. The potential of scintillator-based photon counting detectors: evaluation using Monte Carlo simulations.Proceedings of SPIE--the International Society for Optical Engineering · 2025
    Article
  7. Imaging performance of a LaBrMedical physics · 2025
    Article
  8. Framework for evaluating photon-counting detectors under pile-up conditions.Journal of medical imaging (Bellingham, Wash.) · 2024
    Article
  9. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Stefan J van der SarDepartment of Radiation Science and Technology, Delft University of Technology, Delft, The Netherlands.
Stefan E BrunnerBroadcom Inc., Regensburg, Germany.
Dennis R SchaartDepartment of Radiation Science and Technology, Delft University of Technology, Delft, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe implementation of photon-counting detectors is widely expected to be the next breakthrough in X-ray computed tomography (CT) instrumentation. A small number of prototype scanners equipped with direct-conversion detectors based on room-temperature semiconductors, such as CdTe and CdZnTe (CZT), are currently installed at medical centers. Here, we investigate the feasibility of using silicon photomultiplier (SiPM)-based scintillation detectors in photon-counting computed tomography (PCCT) scanners, as a potential alternative to CdTe and CZT detectors.

methodsWe introduce a model that allows us to compute the expected energy resolution as well as the expected pulse shape and associated rate capability of SiPM-based PCCT detectors. The model takes into account SiPM saturation and optical crosstalk, because these phenomena may substantially affect the performance of SiPM-based PCCT detectors with sub-mm pixels. We present model validation experiments using a single-pixel detector consisting of a 0.9 × 0.9 × 1.0 mm

resultsThe model was found to be in good agreement with the validation experiments, both with respect to energy resolution and pulse shape. It shows how saturation progressively degrades the energy resolution of detectors equipped with currently available SiPMs as the pixel size decreases. Moreover, the expected pulse duration is relatively long (~200 ns) with these SiPMs. However, when LuAP:Ce and LaBr

conclusionsThis work provides first evidence that it may be feasible to develop SiPM-based scintillation detectors for PCCT that can compete with CdTe and CZT detectors in terms of energy resolution and rate capability.

Indexed as

Cadmium CompoundsQuantum DotsFeasibility StudiesPositron-Emission TomographyScintillation CountingTelluriumTomography, X-Ray ComputedCadmium Compoundscadmium tellurideTelluriumenergy resolutionphoton-counting computed tomographypulse shapescintillatorsilicon photomultiplier

Identifiers

PMID34169535
PMCPMC8596580

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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.