Bibliographic record
Abstract
Full three‐dimensional (3D) dosimetry using volumetric chemical dosimeters probed by 3D imaging systems has long been a promising technique for the radiation therapy clinic, since it provides a unique methodology for dose measurements in the volume irradiated using complex conformal delivery techniques such as IMRT and VMAT. To date true 3D dosimetry is still not widely practiced in the community; it has been confined to centres of specialized expertise especially for quality assurance or commissioning roles where other dosimetry techniques are difficult to implement. The potential for improved clinical applicability has been advanced considerably in the last decade by the development of improved 3D dosimeters (e.g., radiochromic plastics, radiochromic gel dosimeters and normoxic polymer gel systems) and by improved readout protocols using optical computed tomography or magnetic resonance imaging. In this session, established users of some current 3D chemical dosimeters will briefly review the current status of 3D dosimetry, describe several dosimeters and their appropriate imaging for dose readout, present workflow procedures required for good dosimetry, and analyze some limitations for applications in select settings. We will review the application of 3D dosimetry to various clinical situations describing how 3D approaches can complement other dose delivery validation approaches already available in the clinic. The applications presented will be selected to inform attendees of the unique features provided by full 3D techniques. Learning Objectives: L. John Schreiner: Background and Motivation Understand recent developments enabling clinically practical 3D dosimetry, Appreciate 3D dosimetry workflow and dosimetry procedures, and Observe select examples from the clinic. Sofie Ceberg: Application to dynamic radiotherapy Observe full dosimetry under dynamic radiotherapy during respiratory motion, and Understand how the measurement of high resolution dose data in an irradiated volume can help understand interplay effects during TomoTherapy or VMAT. Titania Juang: Special techniques in the clinic and research Understand the potential for 3D dosimetry in validating dose accumulation in deformable systems, and Observe the benefits of high resolution measurements for precision therapy in SRS and in MicroSBRT for small animal irradiators Geoffrey S. Ibbott: 3D Dosimetry in end‐to‐end dosimetry QA Understand the potential for 3D dosimetry for end‐to‐end radiation therapy process validation in the in‐house and external credentialing setting. Canadian Institutes of Health Research; L. Schreiner, Modus QA, London, ON, Canada; T. Juang, NIH R01CA100835
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.014 |
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".