Quantifying Radiobiological Variation in Cancer Radiotherapy Using Monte Carlo Simulation and Doped Plastic Scintillators
Bibliographic record
Abstract
This dissertation examines the extent to which radiobiological variations occur in photon radiotherapy, and then presents a novel methodology and detector prototype to measure this variation. In the first section, I examine the change in maximum RBE (RBEM) outside the primary field in open and composite 6 MV x-ray beams. This is done using Monte Carlo simulation and microdosimetric techniques. It was found that when comparing an open 10 10 cm2 6 MV beam to a composite 10 10 cm2 beam comprising one hundred 1x 1 cm2 beamlets, the out-of-field increase in RBE occurs much closer to the field edge in the composite case. This finding may have consequences for IMRT cases in which large amount of scattered radiation may be causing a higher than expected effective dose to organs at risk. In the second section, the maximum RBE variation is examined in the context of brachytherapy. The sources examined include 192Ir, 125I, and 169Yb. It was determined that maximum RBE of 125I relative to the source position did not vary significantly as distance from the source was increased, however, 192Ir and 169Yb were found to exhibit RBEM increases of 3.0% and 6.6% at a distance of 8 cm, respectively. Also, the impact of this variation on an HDR 192Ir prostate treatment plan was examined; it was found that RBEM hotspots of +3.6% occur at the treatment plan’s periphery. In the third part, the impact of lead doping on plastic scintillator response is quantified, a major step required for the development of the LET detector prototype. In this stage, 4 differently doped plastic scintillators were obtained, and measurements were conducted in low and medium LET beams. Using Geant4 Monte Carlo and the measured scintillator responses, the scintillator parameters: kB and L0 were determined as a function of dopant concentration and effective atomic number. Finally, the uniquely energy dependent scintillators were combined into a detector prototype used to measure the LET spectra produced by five low energy photon beams. These beams included four orthovoltage energies (100, 180, 250, and 300 kVp) along with an 192Ir HDR source. In this proof-of-principle work, the detector prototype and technique was found to accurately determine the LET spectra and the mean LET for all beams with the exception of the 100 kVp orthovoltage beam. Potential applications for the real-time LET detector prototype and technique described in this dissertation include LET measurement in radiotherapy, allowing for biologically optimized treatment plans improving patient care. This technique and prototype also has numerous applications in non-medical fields such as health physics, space travel dosimetry, and nuclear safety.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".