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Record W2072481146 · doi:10.1118/1.3182321

TU‐C‐BRD‐03: An Integrated Robotic‐Based Irradiation System for Small Animal Research

2009· article· en· W2072481146 on OpenAlexaboutno aff
Eduardo G. Moros, Sunil Sharma, Peter M. Corry, Ming Chao, Robert J. Griffin, I Mihaylov, José Peñagarícano

Bibliographic record

VenueMedical Physics · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCone beam computed tomographyNuclear medicineCollimated lightFlat panel detectorPixelPhysicsOpticsComputer scienceFrame rateDetectorArtificial intelligenceMaterials scienceComputer visionBiomedical engineeringEngineeringComputed tomographyMedicineRadiology

Abstract

fetched live from OpenAlex

An integrated, image‐guided irradiation system for small animal research has been developed. The system is capable of precise, accurate, reproducible and quantifiable 3D conformal delivery of radiation dose distributions to organs/tumors. The main hardware components are: (1) A Seifert Isovolt Titan 225 kV X‐ray tube with beam collimation provided by a custom‐made variable diameter “cone” or a set of motor‐driven symmetric “jaws”, thereby allowing field sizes from 0.5 mm in diameter to 7 cm square field at ∼33.5 cm SSD. (2) A six‐degrees‐of‐freedom (6DOF) robotic arm (Adept Viper s650) was integrated for precise animal positioning/motion (repeatability of ±0.020 mm in XYZ direction and angular precision of ±0.2°). The system is housed in a custom 6 × 6 × 6 ft3 shielded enclosure inside a laboratory. When the beam is aimed horizontally to (3) a flat panel amorphous silicon detector (XRD 0820 CN3, Perkin Elmer, Fremont, CA) a series of 2D‐radiographs can be recorded while the robot rotates the animal. Each image is composed of 1024 by 1024 pixels with a 200 μm pixel size at a frame rate of 7.5 Hz. An open source cone beam computed tomography (CBCT) reconstruction tool (OSCAR‐2, University of Toronto) using the Feldkamp‐Davis‐Kress (FDK) filtered back projection algorithm was implemented for CBCT image reconstruction. Thus, targeting can be accomplished by the use of orthogonal radiographs and/or CBCT. A dose engine and CBCT‐based treatment planning are ongoing projects. Dosimetric measurements and preliminary animal experiments have demonstrated the basic capabilities of the system in terms of radiation dose, dose rate and precision targeting. The system has also been used successfully in experiments to detect the molecular signaling occurring after spatially fractionated radiation therapy (GRID) in vivo. A description of the system and a summary of experiments performed to date will be presented. Learning Objectives: 1. Appreciate the challenges of developing a high precision 3D conformal irradiator for small animals. 2. Learn about the main hardware components of the system and their integration. 3. Understand the advantages of using a 6DOF robot for imaging (motion) and beam delivery (positioning). 4. Learn about some of the potential research projects that such a system can make possible. This research was sponsored by the Arkansas Biosciences Institute and the Central Arkansas Radiation Therapy Institute.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.003

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.

Opus teacher head0.046
GPT teacher head0.364
Teacher spread0.317 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

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

Citations2
Published2009
Admission routes1
Has abstractyes

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