Optimisation of monolithic nanocomposite and transparent ceramic scintillation detectors for positron emission tomography.

Keenan J Wilson, Roumani Alabd, Mehran Abolhasan, Mitra Safavi-Naeini, Daniel R Franklin

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In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Deep learning based localisation and classification of gamma photon interactions in thick nanocomposite and ceramic monolithic scintillators.Scientific reports · 2025
Article

4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Keenan J WilsonSchool of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia.

Roumani AlabdSchool of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia.

Mehran AbolhasanSchool of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia.

Mitra Safavi-NaeiniAustralian Nuclear Science and Technology Organisation (ANSTO), Sydney, NSW, Australia.

Daniel R FranklinSchool of Electrical and Data Engineering, University of Technology Sydney, Sydney, NSW, Australia. Daniel.Franklin@uts.edu.au.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-resolution arrays of discrete monocrystalline scintillators used for gamma photon coincidence detection in PET are costly and complex to fabricate, and exhibit intrinsically non-uniform sensitivity with respect to emission angle. Nanocomposites and transparent ceramics are two alternative classes of scintillator materials which can be formed into large monolithic structures, and which, when coupled to optical photodetector arrays, may offer a pathway to low cost, high-sensitivity, high-resolution PET. However, due to their high optical attenuation and scattering relative to monocrystalline scintillators, these materials exhibit an inherent trade-off between detection sensitivity and the number of scintillation photons which reach the optical photodetectors. In this work, a method for optimising scintillator thickness to maximise the probability of locating the point of interaction of 511 keV photons in a monolithic scintillator within a specified error bound is proposed and evaluated for five nanocomposite materials (LaBr

Identifiers

PMID31996726

DOI10.1038/s41598-020-58208-y

PMCPMC6989685

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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.