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Record W4368360690 · doi:10.1002/acm2.14000

Skin/mucosa avoidance radiotherapy (SMART) versus conventional volumetric arc‐based radiotherapy (VMAT) for the treatment of head and neck cancer: Dosimetric feasibility study

2023· article· en· W4368360690 on OpenAlexaff
Cheryl Anderson, R. Lee MacDonald, Derek Wilke

Bibliographic record

VenueJournal of Applied Clinical Medical Physics · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsDalhousie UniversityNova Scotia Health Authority
Fundersnot available
KeywordsMedicineMucositisRadiation therapyNuclear medicineHead and neck cancerOral mucosaHead and neckSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Intensity modulated radiotherapy (IMRT) for head and neck cancer has led to a reduction in radiotherapy doses to normal tissues, like the salivary glands, while maintaining high rates of local control. Oral mucosal and skin toxicity is still a major source of treatment-related morbidity, occurring in most patients. PURPOSE: We conducted a dosimetric feasibility study with the goal of creating a methodology that could theoretically reduce the dose of radiation to skin and oral mucosa, while maintaining comparable avoidance of other organs at risk, and planning target volume (PTV) coverage. METHODS: The clinical plans of patients treated previously were replanned using coplanar VMAT arcs on a TrueBeam STx using the photon optimizer (PO) version 15.6 and the Acuros XB dose calculation algorithm. Comparisons were made between three methodologies: "Conventional," "Skin Sparing" and a skin/mucosa avoiding ("SMART") technique, with dose metrics being compared using analysis of variance, with a Bonferroni correction to account for multiple pairwise comparisons. The maximum grade of mucositis and radiation dermatitis during treatment was correlated to different dose-volume metrics to predict what could be clinically meaningful. RESULTS: Sixteen patients met the study criteria and were replanned using the skin sparing and SMART techniques. Maximum doses to the skin sparing structure were reduced from 64.2 Gy to 56.6 and 55.9 Gy, in the skin sparing and SMART plans (p < 0.0001), and mean doses reduced from 26.7 Gy to 20.0 and 20.2 Gy, respectively (p < 0.0001). Maximum doses to the oral cavity structure were not reduced by either technique, however mean dose to the oral cavity structure was reduced from 39.03 Gy to 33.5 Gy by the SMART technique (p < 0.0001). There was a slight reduction in PTV_High coverage by the V95% in the SMART plans (99.52% vs. 98.79%, p = 0.0073), and a similar slight reduction in PTV_Low coverage by the V95% by both the skin sparing and SMART plans (99.74% vs. 97.89% vs. 97.42%, p < 0.0001). Maximum doses to organs at risk were not statistically different between techniques. Dose to oral cavity and maximum grade experienced during radiotherapy correlated. The Spearman correlation coefficient for dose to 20%, 50%, and 80% of the volume of oral cavity was 0.5 (p = 0.048), 0.64 (p = 0.007), and 0.62 (p = 0.010), respectively. Skin toxicity grade was only found to be correlated with the D20% of the skin sparing structure (Spearman correlation coefficient of 0.58, p = 0.0177). CONCLUSION: The SMART technique appears to be able to reduce maximum and mean skin dose, as well as mean oral cavity doses, while only slightly reducing PTV coverage, with acceptable OAR doses. We feel the improvements warrant investigation in a clinical trial.

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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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.809
Threshold uncertainty score0.847

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
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 head0.063
GPT teacher head0.421
Teacher spread0.357 · 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 designOther design
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

Citations3
Published2023
Admission routes1
Has abstractyes

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