A practical technique for verification of three‐dimensional conformal dose distributions in stereotactic radiosurgery
Bibliographic record
Abstract
The trend toward conformal techniques in stereotactic radiosurgery necessitates an accurate and practical method for verification of irregular three-dimensional dose distributions. This work presents the design and evaluation of a phantom system facilitating the measurement of conformal dose distributions using one or more arrays of up to 20 radiographic films separated by 3.2 mm-thick tissue-equivalent spacers. Using Electron Gamma Shower version 4 (EGS4) Monte Carlo simulation, we show that for 6 MV radiosurgical photon beams this arrangement preserves tissue-equivalence to within 1%. The phantom provides 0.25 mm in-plane spatial resolution and multiple sets of films may be used to resample the dose volume in orthogonal planes. Dedicated software has been developed to automate the process of ordering and orienting of scanned film images, conversion of scanned pixel value to dose, resampling of one or more sets of film images and subsequent export of images in DICOM format for coregistration of planned and measured dose volumes. Calculated and measured isodose surfaces for a simple, circular-beam treatment agree to within 1.5 mm throughout the dose volume. For conformal radiosurgical applications, the measured and planned dose distributions agree to within the uncertainty of the manufacture of irregularly shaped collimators. The sensitivity of this technique to minor spatial inaccuracies in beam shaping is also demonstrated.
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".