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Record W3145750898 · doi:10.1088/1361-6560/abf606

RF shielding materials for highly-integrated PET/MRI systems

2021· article· en· W3145750898 on OpenAlexaff
Laiyin Yin, Franziska Schrank, Nicolas Groß‐Weege, David Schug, Volkmar Schulz

Bibliographic record

VenuePhysics in Medicine and Biology · 2021
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsHyperion Technologies (Canada)
FundersTechnische Universiteit DelftDeutsche Forschungsgemeinschaft
KeywordsScintillatorElectromagnetic shieldingDetectorMaterials scienceLyso-PhotodetectorOpticsSilicon photomultiplierOptoelectronicsScintillationAttenuationMedical physicsPhysics

Abstract

fetched live from OpenAlex

Abstract Integration of magnetic resonance imaging (MRI) and positron emission tomography (PET) into a simultaneous device calls for adaptations of the radio frequency (RF) shielding concept. Conventional PET module housings fully encase the entire PET detector to reduce mutual interference. Excluding passive components, i.e. scintillators, from the housings, offers integration advantages, e.g. by reducing the overall housing volume or utilizing bigger scintillators. However, locating the scintillator outside of the RF shielding requires an optically transparent RF shielding interface between the scintillators and the photodetector to close the aperture. Therefore, a careful evaluation and selection of RF materials is essential to ensure an excellent PET/MRI system performance. To this end, we examined 10 materials (coated glasses, coated foils, meshes). The shielding effectiveness (SE) was evaluated at 100 and 300 MHz. PET performance was tested for single event registration and coincident events by integrating the material into the PET detector stack between the digital silicon photomultiplier photodetector array and one-to-one coupled scintillator. We determined photon attenuation (PA), energy resolution (dE/E), and coincidence resolving time (CRT) and compared to reference measurements for each material group. MRI compatibility was assessed by analyzing the material influence on the main magnetic field (B 0 ) homogeneity. The coated glasses and foils exhibited SEs of up to 25 dB at 300 MHz. Both had a PA < 23% with dE/E and CRT comparable to the reference measurements, and no measurable impact on the B 0 field was registered. The meshes exhibited higher SEs up to 56 dB, but also a PA > 58% with a higher impact on dE/E and CRT. Only one mesh affected B 0 homogeneity. Overall, we recommend the coated foil HS 9400 for integration concepts as it exhibited a good performance with SE = 25 dB, PA = 22%, resulting in a PET performance of dE/E = 12% and CRT = 274 ps.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.187
GPT teacher head0.428
Teacher spread0.242 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2021
Admission routes1
Has abstractyes

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