The role of medical physicists in developing stereotactic radiosurgery
Bibliographic record
Abstract
This article is a tribute to the pioneering medical physicists over the last 50 years who have participated in the research, development, and commercialization of stereotactic radiosurgery (SRS) and stereotactic radiotherapy utilizing a wide range of technology. The authors have described the evolution of SRS through the eyes of physicists from its beginnings with the Gamma Knife in 1951 to proton and charged particle therapy; modification of commercial linacs to accommodate high precision SRS setups; the multitude of accessories that have enabled fine tuning patients for relocalization, immobilization, and repositioning with submillimeter accuracy; and finally the emerging technology of SBRT. A major theme of the article is the expanding role of the medical physicist from that of advisor to the neurosurgeon to the current role as a primary driver of new technology that has already led to an adaptation of cranial SRS to other sites in the body, including, spine, liver, and lung. SRS continues to be at the forefront of the impetus to provide technological precision for radiation therapy and has demonstrated a host of downstream benefits in improving delivery strategies for conventional therapy as well. While this is not intended to be a comprehensive history, and the authors could not delineate every contribution by all of those working in the pursuit of SRS development, including physicians, engineers, radiobiologists, and the rest of the therapy and dosimetry staff in this important and dynamic radiation therapy modality, it is clear that physicists have had a substantial role in the development of SRS and theyincreasingly play a leading role in furthering SRS technology.
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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 | 0.050 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.017 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".