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Record W4399765836 · doi:10.1002/acm2.14438

The feasibility of CT simulation‐free adaptive radiation therapy

2024· article· en· W4399765836 on OpenAlexaff
R. Lee MacDonald, Clara Fallone, Krista Chytyk‐Praznik, James L. Robar, Amanda Cherpak

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2024
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsQueen Elizabeth II Health Sciences CentreDalhousie University
FundersSiemens HealthineersVarian Medical Systems
KeywordsImaging phantomContouringHounsfield scaleComputer scienceQuality assuranceCone beam computed tomographyDosimetryMedical physicsImage-guided radiation therapyRadiation treatment planningNuclear medicineRadiation therapyMedicineRadiologyComputed tomographyComputer graphics (images)

Abstract

fetched live from OpenAlex

BACKGROUND: Novel on-board CBCT allows for improved image quality and Hounsfield unit accuracy. When coupled with online adaptive tools, this may have potential to allow for simulation and treatment to be completed in a single on-table session. PURPOSE: To study the feasibility of a high-efficiency radiotherapy treatment workflow without the use of a separate session for simulation imaging. The dosimetric accuracy, overall efficiency, and technical feasibility were used to evaluate the clinical potential of CT simulation-free adaptive radiotherapy. METHODS: Varian's Ethos adaptive radiotherapy treatment platform was upgraded with a novel CBCT system, HyperSight which reports image quality and Hounsfield unit accuracy specifications comparable to standard fan-beam CT. Using in-house developed MATLAB software, CBCT images were imported into the system and used for planning. Two test cases were completed on anthropomorphic phantoms equipped with small volume ion chambers (cross-calibrated to an ADCL traceable dose standard) to evaluate the feasibility and accuracy of the workflows. A simulated palliative spine treatment was planned with 8 Gy in one fraction, and an intact prostate treatment was planned with 60 Gy in 20 fractions. The CBCTs were acquired using HyperSight with default thorax and pelvis imaging protocols and reconstructed using an iterative algorithm with scatter removal, iCBCT Acuros. CBCTs were used for contouring and planning, and treatment was delivered via an online adaptive workflow. In addition, an external dosimetry audit was completed using only on-board CBCT imaging in an end-to-end head and neck phantom irradiation. RESULTS: An extended-field CBCT acquisition can be acquired in 12 s, in addition to the time for longitudinal table shifts, and reconstructed in approximately 1 min. The superior-inferior extent for the CBCT planning images was 38.2 cm, which captured the full extent of relevant anatomy. The contouring and treatment planning for the spine and prostate were completed in 30 and 18 min, respectively. The dosimetric agreement between ion chamber measurements and the treatment plan was within a range of -1.4 to 1.6%, and a mean and standard deviation of 0.41 ± 1.16%. All metrics used in the external audit met the passing criteria, and the dosimetric comparison between fan-beam and CBCT techniques had a gamma passing rate of 99.0% with a criteria of 2%/2 mm. CONCLUSION: Using an in-house workflow, CT simulation-free radiation therapy was shown to be feasible with acceptable workflow efficiency and dosimetric accuracy. This approach may be particularly applicable for urgent palliative treatments. With the availability of software to enable this workflow, and the continued advancement of on-treatment adaptation, single-visit radiation therapy may replace current practice for some clinical indications.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.057
GPT teacher head0.417
Teacher spread0.360 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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".

Quick stats

Citations20
Published2024
Admission routes1
Has abstractyes

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