Intracranial stereotactic positioning systems: Report of the American Association of Physicists in Medicine Radiation Therapy Committee Task Group No. 68
Bibliographic record
Abstract
Intracranial stereotactic positioning systems (ISPSs) are used to position patients prior to precise radiation treatment of localized lesions of the brain. Often, the lesion is located in close proximity to critical anatomic features whose functions should be maintained. Many types of ISPSs have been described in the literature and are commercially available. These are briefly reviewed. ISPS systems provide two critical functions. The first is to establish a coordinate system upon which a guided therapy can be applied. The second is to provide a method to reapply the coordinate system to the patient such that the coordinates assigned to the patient's anatomy are identical from application to application. Without limiting this study to any particular approach to ISPSs, this report introduces nomenclature and suggests performance tests to quantify both the stability of the ISPS to map diagnostic data to a coordinate system, as well as the ISPS's ability to be realigned to the patient's anatomy. For users who desire to develop a new ISPS system, it may be necessary for the clinical team to establish the accuracy and precision of each of these functions. For commercially available systems that have demonstrated an acceptable level of accuracy and precision, the clinical team may need to demonstrate local ability to apply the system in a manner consistent with that employed during the published testing. The level of accuracy and precision required of an individual ISPS system is dependent upon the clinical protocol (e.g., fractionation, margin, pathology, etc.). Each clinical team should provide routine quality assurance procedures that are sufficient to support the assumptions of accuracy and precision used during the planning process. The testing of ISPS systems can be grouped into two broad categories, type testing, which occurs prior to general commercialization, and site testing, performed when a commercial system is installed at a clinic. Guidelines to help select the appropriate tests as well as recommendations to help establish the required frequency of testing are provided. Because of the broad scope of different systems, it is important that both the manufacturer and user rigorously critique the system and set QA tests appropriate to the particular device and its possible weaknesses. Major recommendations of the Task Group include: introduction of a new nomenclature for reporting repositioning accuracy; comprehensive analysis of patient characteristics that might adversely affect positioning accuracy; performance of testing immediately before each treatment to establish that there are no gross positioning errors; a general request to the Medical Physics community for improved QA tools; implementation of weekly portal imaging (perhaps cone beam CT in the future) as a method of tracking fractionated patients (as per TG 40); and periodic routine reviews of positioning accuracy.
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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 | 0.022 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".