Monte Carlo simulation of a quantum noise limited Čerenkov detector based on air‐spaced light guiding taper for megavoltage x‐ray imaging
Bibliographic record
Abstract
PURPOSE: Electronic Portal Imaging Devices (EPIDs) have been widely used in radiation therapy and are still needed on linear accelerators (Linacs) equipped with kilovoltage cone beam CT (kV-CBCT) or MRI systems. Our aim is to develop a new high quantum efficiency (QE) Čerenkov Portal Imaging Device (CPID) that is quantum noise limited at dose levels corresponding to a single Linac pulse. METHODS: Recently a new concept of CPID for MV x-ray imaging in radiation therapy was introduced. It relies on Čerenkov effect for x-ray detection. The proposed design consisted of a matrix of optical fibers aligned with the incident x-rays and coupled to an active matrix flat panel imager (AMFPI) for image readout. A weakness of such design is that too few Čerenkov light photons reach the AMFPI for each incident x-ray and an AMFPI with an avalanche gain is required in order to overcome the readout noise for portal imaging application. In this work the authors propose to replace the optical fibers in the CPID with light guides without a cladding layer that are suspended in air. The air between the light guides takes on the role of the cladding layer found in a regular optical fiber. Since air has a significantly lower refractive index (∼ 1 versus 1.38 in a typical cladding layer), a much superior light collection efficiency is achieved. RESULTS: A Monte Carlo simulation of the new design has been conducted to investigate its feasibility. Detector quantities such as quantum efficiency (QE), spatial resolution (MTF), and frequency dependent detective quantum efficiency (DQE) have been evaluated. The detector signal and the quantum noise have been compared to the readout noise. CONCLUSIONS: Our studies show that the modified new CPID has a QE and DQE more than an order of magnitude greater than that of current clinical systems and yet a spatial resolution similar to that of current low-QE flat-panel based EPIDs. Furthermore it was demonstrated that the new CPID does not require an avalanche gain in the AMFPI and is quantum noise limited at dose levels corresponding to a single Linac pulse.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".