Emerging technologies in stereotactic body radiotherapy
Bibliographic record
Abstract
Stereotactic body radiation therapy (SBRT) stems from the initial developments of intra-cranial stereotactic radiosurgery (SRS). Despite similarity in their names and clinical goals of delivering a sufficiently high tumoricidal dose, maximal sparing of the surrounding normal tissues and a short treatment course, SBRT technologies have transformed from the early days of body frame-based treatments with X-ray verification to primarily image-guided procedures with cone-beam CT or stereoscopic X-ray systems and non-rigid body immo-bilization. As a result of the incorporation of image-guidance systems and multi-leaf col-limators into mainstream linac systems, and treatment planning systems that have also evolved to allow for routine dose calculations to permit intensity modulated radiotherapy and volumetric modulated arc therapy (VMAT), SBRT has disseminated rapidly in the community to manage many disease sites that include oligometastases, spine lesions, lung, prostate, liver, renal cell, pelvic tumors, and head and neck tumors etc. In this article, we review the physical principles and paradigms that led to the widespread adoption of SBRT practice as well as technical caveats specific to individual SBRT technologies. From the perspective of treatment delivery, we categorically described (I) C-arm linac-based SBRT technologies; (II) robotically manipulated X-band CyberKnife® technology; and (III) emerging specialized systems for SBRT that include integrated MRI-linear accelerators and the imaged-guided Gamma Knife Perfexion Icon system with expanded multi-isocenter treatments of skull-based tumors, head-and-neck and cervical-spine lesions.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".