Feasibility of x-ray acoustic computed tomography as a relative and in vivo dosimeter in radiotherapy applications
Bibliographic record
Abstract
Radiotherapy is an important cancer treatment modality that uses ionizing radiation to deliver a sufficient amount of energy to kill tumour cells. Many dosimetry procedures are employed to ensure that patients receive the prescribed dose of radiation. X-ray acoustic computed tomography (XACT) is a novel imaging modality capable of producing an image of the dose distribution in a sample after irradiation by an ionizing photon or electron beam. This is achieved by exploiting the phenomenon that acoustic waves with amplitude proportional to the dose deposited are induced following a radiation pulse, and can be detected with ultrasound transducers. The goal of this work is to assess the feasibility of utilizing XACT as a dosimeter in several clinically relevant relative and in vivo radiotherapy applications. An end-to-end simulation workflow to model XACT was developed using Geant4 Monte Carlo simulations, clinical treatment planning software, and k-Wave, a MATLAB based toolkit that simulates acoustic wave propagation. To evaluate this simulation workflow, the acoustic waves induced following the irradiation of a lead rod suspended in a water tank were simulated and experimentally measured. It was found that the simulations were able to accurately determine acoustic wave properties, such as the frequency and relative amplitude trends. Additionally, the correct prediction of the peak frequency of the induced acoustic waves allowed for the development of a band-pass filter that significantly improved experimental detection by mitigating background noise.The simulation workflow was used to assess the ability of XACT to act as a tool for relative dosimetry through the simulated measurement of percent depth dose curves and in-plane profiles. The feasibility of using XACT as an in vivo dosimeter was also investigated by simulating clinical cases of prostate and breast cancer irradiation. It was found that the linear relationship between peak acoustic pressure and dose enables the measurement of percent depth dose curves with XACT. The accuracy of the simulated reconstructed in-plane profiles and clinical prostate and breast dose distributions demonstrates the capability of XACT as a tool for radiotherapy imaging. Additionally, the simulated amplitude and frequency of the induced acoustic waves indicate that they should be detectable with existing ultrasound transducer technology.This work demonstrates that XACT is a feasible dosimetry technique for a variety of relative and in vivo situations. Due to its real-time, non-invasive nature and potential to combine with ultrasound imaging, the future of XACT in radiotherapy is promising.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".