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Record W2028236386 · doi:10.1118/1.4895013

AAPM and GEC‐ESTRO guidelines for image‐guided robotic brachytherapy: Report of Task Group 192

2014· review· en· W2028236386 on OpenAlexaff
Tarun K. Podder, Luc Beaulieu, Barrett S. Caldwell, Robert A. Cormack, J. Crass, Adam P. Dicker, Aaron Fenster, Gábor Fichtinger, Michael Meltsner, Marinus A. Moerland, Ravinder Nath, Mark J. Rivard, Septimiu E. Salcudean, Danny Y. Song, Bruce Thomadsen, Yan Yu

Bibliographic record

VenueMedical Physics · 2014
Typereview
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsUniversity of British ColumbiaQueen's UniversityRobarts Clinical TrialsCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsBrachytherapyQuality assuranceMedical physicsTask groupDosimetryRadiation treatment planningMedicineProstate brachytherapyComputer scienceRadiation therapyNuclear medicineRadiologyEngineering

Abstract

fetched live from OpenAlex

In the last decade, there have been significant developments into integration of robots and automation tools with brachytherapy delivery systems. These systems aim to improve the current paradigm by executing higher precision and accuracy in seed placement, improving calculation of optimal seed locations, minimizing surgical trauma, and reducing radiation exposure to medical staff. Most of the applications of this technology have been in the implantation of seeds in patients with early-stage prostate cancer. Nevertheless, the techniques apply to any clinical site where interstitial brachytherapy is appropriate. In consideration of the rapid developments in this area, the American Association of Physicists in Medicine (AAPM) commissioned Task Group 192 to review the state-of-the-art in the field of robotic interstitial brachytherapy. This is a joint Task Group with the Groupe Européen de Curiethérapie-European Society for Radiotherapy & Oncology (GEC-ESTRO). All developed and reported robotic brachytherapy systems were reviewed. Commissioning and quality assurance procedures for the safe and consistent use of these systems are also provided. Manual seed placement techniques with a rigid template have an estimated in vivo accuracy of 3-6 mm. In addition to the placement accuracy, factors such as tissue deformation, needle deviation, and edema may result in a delivered dose distribution that differs from the preimplant or intraoperative plan. However, real-time needle tracking and seed identification for dynamic updating of dosimetry may improve the quality of seed implantation. The AAPM and GEC-ESTRO recommend that robotic systems should demonstrate a spatial accuracy of seed placement ≤1.0 mm in a phantom. This recommendation is based on the current performance of existing robotic brachytherapy systems and propagation of uncertainties. During clinical commissioning, tests should be conducted to ensure that this level of accuracy is achieved. These tests should mimic the real operating procedure as closely as possible. Additional recommendations on robotic brachytherapy systems include display of the operational state; capability of manual override; documented policies for independent check and data verification; intuitive interface displaying the implantation plan and visualization of needle positions and seed locations relative to the target anatomy; needle insertion in a sequential order; robot-clinician and robot-patient interactions robustness, reliability, and safety while delivering the correct dose at the correct site for the correct patient; avoidance of excessive force on radioactive sources; delivery confirmation of the required number or position of seeds; incorporation of a collision avoidance system; system cleaning, decontamination, and sterilization procedures. These recommendations are applicable to end users and manufacturers of robotic brachytherapy systems.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.404
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations96
Published2014
Admission routes1
Has abstractyes

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