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Record W2024556380 · doi:10.1118/1.2836417

A deformable phantom for 4D radiotherapy verification: Design and image registration evaluation

2008· article· en· W2024556380 on OpenAlexafffund
Monica Serban, Emily Heath, Gabriela Stroian, D. Louis Collins, Jan Seuntjens

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersCanadian Institutes of Health Research
KeywordsImaging phantomReproducibilityBreathingImage registrationBiomedical engineeringMaterials sciencePiston (optics)Nuclear medicineComputer sciencePhysicsComputer visionOpticsMedicineMathematicsImage (mathematics)Anatomy

Abstract

fetched live from OpenAlex

Motion of thoracic tumors with respiration presents a challenge for three-dimensional (3D) conformal radiation therapy treatment. Validation of techniques aimed at measuring and minimizing the effects of respiratory motion requires a realistic deformable phantom for use as a gold standard. The purpose of this study was to develop and study the characteristics of a reproducible, tissue equivalent, deformable lung phantom. The phantom consists of a Lucite cylinder filled with water containing a latex balloon stuffed with dampened natural sponges. The balloon is attached to a piston that mimics the human diaphragm. Nylon wires and Lucite beads, emulating vascular and bronchial bifurcations, were uniformly glued at various locations throughout the sponges. The phantom is capable of simulating programmed irregular breathing patterns with varying periods and amplitudes. A tissue equivalent tumor, suitable for holding radiochromic film for dose measurements was embedded in the sponge. To assess phantom motion, eight 3D computed tomography data sets of the static phantom were acquired for eight equally spaced positions of the piston. The 3D trajectories of 12 manually chosen point landmarks and the tumor center-of-mass were studied. Motion reproducibility tests of the deformed phantom were established on seven repeat scans of three different states of compression. Deformable image registration (DIR) of the extreme breathing phases was performed. The accuracy of the DIR was evaluated by visual inspection of image overlays and quantified by the distance-to-agreement (DTA) of manually chosen point landmarks and triangulated surfaces obtained from 3D contoured structures. In initial tests of the phantom, a 20-mm excursion of the piston resulted in deformations of the balloon of 20 mm superior-inferior, 4 mm anterior-posterior, and 5 mm left-right. The change in the phantom mean lung density ranged from 0.24 (0.12 SD) g/cm3 at peak exhale to 0.19 (0.12 SD) g/cm3 at peak inhale. The SI displacement of the landmarks varied between 94% and 3% of the piston excursion for positions closer and farther away from the piston, respectively. The reproducibility of the phantom deformation was within the image resolution (0.7 x 0.7 x 1.25 mm3). Vector average registration accuracy based on point landmarks was found to be 0.5 (0.4 SD) mm. The tumor and lung mean 3D DTA obtained from triangulated surfaces were 0.4 (0.1 SD) mm and 1.0 (0.8 SD) mm, respectively. This phantom is capable of reproducibly emulating the physically realistic lung features and deformations and has a wide range of potential applications, including four-dimensional (4D) imaging, evaluation of deformable registration accuracy, 4D planning and dose delivery.

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)0.004
metaresearch head score (Gemma)0.007
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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.035
GPT teacher head0.329
Teacher spread0.294 · 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
GenreEmpirical

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".

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Citations99
Published2008
Admission routes2
Has abstractyes

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