On the biological basis for competing macroscopic dose descriptors for kilovoltage dosimetry: cellular dosimetry for brachytherapy and diagnostic radiology
Bibliographic record
Abstract
The purpose of this work is to investigate how alternative macroscopic dose descriptors track absorbed dose to biologically relevant subcellular targets via Monte Carlo (MC) analysis of cellular models for a variety of cancerous and normal soft tissues for kilovoltage radiation. The relative mass distributions of water, light inorganic elements, and protein components of nuclear and cytoplasm compartments for various tissues are determined from a literature review. These data are used to develop representative cell models to demonstrate the range of mass elemental compositions of these subcellular structures encountered in the literature from which radiological quantities (energy absorption and attenuation coefficients; stopping powers) are computed. Using representative models of cell clusters, doses to subcellular targets are computed using MC simulation for photon sources of energies between 20 and 370 keV and are compared to bulk medium dose descriptors. It is found that cells contain significant and varying mass fractions of protein and inorganic elements, leading to variations in mass energy absorption coefficients for cytoplasm and nuclear media as large as 10% compared to water for sub-50 keV photons. Doses to subcellular structures vary by as much as 23% compared to doses to the corresponding average bulk medium or to small water cavities embedded in the bulk medium. Relationships between cellular target doses and doses to the bulk medium or to a small water cavity embedded in the bulk medium are sensitive to source energy and cell morphology, particularly for lower energy sources, e.g., low energy brachytherapy (<50 keV). Results suggest that cells in cancerous and normal soft tissues are generally not radiologically equivalent to either water or the corresponding average bulk tissue. For kilovoltage photon sources, neither dose to bulk medium nor dose to water quantitatively tracks energy imparted to biologically relevant subcellular targets for the range of cellular morphologies and tissues considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".