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Record W1995823752 · doi:10.1118/1.2008407

Segmented crystalline scintillators: An initial investigation of high quantum efficiency detectors for megavoltage x‐ray imaging

2005· article· en· W1995823752 on OpenAlexaff
Amit Sawant, Larry E. Antonuk, Youcef El‐Mohri, Qihua Zhao, Yixin Li, Zhong Su, Yi Wang, J. Yamamoto, Hong Du, Ian A. Cunningham, M. Klugerman, Kanai S. Shah

Bibliographic record

VenueMedical Physics · 2005
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsRobarts Clinical Trials
FundersNational Cancer InstituteNational Institutes of Health
KeywordsDetective quantum efficiencyOpticsScintillatorX-ray detectorDetectorImage resolutionFlat panel detectorNuclear medicinePhysicsMedical imagingRadiationMaterials scienceMedical physicsImage qualityMedicineComputer scienceRadiology

Abstract

fetched live from OpenAlex

Electronic portal imaging devices (EPIDs) based on indirect detection, active matrix flat panel imagers (AMFPIs) have become the technology of choice for geometric verification of patient localization and dose delivery in external beam radiotherapy. However, current AMFPI EPIDs, which are based on powdered-phosphor screens, make use of only approximately 2% of the incident radiation, thus severely limiting their imaging performance as quantified by the detective quantum efficiency (DQE) (approximately 1%, compared to approximately 75% for kilovoltage AMFPIs). With the rapidly increasing adoption of image-guided techniques in virtually every aspect of radiotherapy, there exist strong incentives to develop high-DQE megavoltage x-ray imagers, capable of providing soft-tissue contrast at very low doses in megavoltage tomographic and, potentially, projection imaging. In this work we present a systematic theoretical and preliminary empirical evaluation of a promising, high-quantum-efficiency, megavoltage x-ray detector design based on a two-dimensional matrix of thick, optically isolated, crystalline scintillator elements. The detector is coupled with an indirect detection-based active matrix array, with the center-to-center spacing of the crystalline elements chosen to match the pitch of the underlying array pixels. Such a design enables the utilization of a significantly larger fraction of the incident radiation (up to 80% for a 6 MV beam), through increases in the thickness of the crystalline elements, without loss of spatial resolution due to the spread of optical photons. Radiation damage studies were performed on test samples of two candidate scintillator materials, CsI(Tl) and BGO, under conditions relevant to radiotherapy imaging. A detailed Monte Carlo-based study was performed in order to examine the signal, spatial spreading, and noise properties of the absorbed energy for several segmented detector configurations. Parameters studied included scintillator material, septal wall material, detector thickness, and the thickness of the septal walls. The results of the Monte Carlo simulations were used to estimate the upper limits of the modulation transfer function, noise power spectrum and the DQE for a select number of configurations. An exploratory, small-area prototype segmented detector was fabricated by infusing crystalline CsI(Tl) in a 2 mm thick tungsten matrix, and the signal response was measured under radiotherapy imaging conditions. Results from the radiation damage studies showed that both CsI(Tl) and BGO exhibited less than approximately 15% reduction in light output after 2500 cGy equivalent dose. The prototype CsI(Tl) segmented detector exhibited high uniformity, but a lower-than-expected magnitude of signal response. Finally, results from Monte Carlo studies strongly indicate that high scintillator-fill-factor configurations, incorporating high-density scintillator and septal wall materials, could achieve up to 50 times higher DQE compared to current AMFPI EPIDs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.647
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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)0.0000.000

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 head0.011
GPT teacher head0.293
Teacher spread0.282 · 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 teacher head, 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

Citations65
Published2005
Admission routes1
Has abstractyes

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