Optical scan and 3D printing guided radiation therapy – an application and provincial experience in cutaneous nasal carcinoma
Bibliographic record
Abstract
BACKGROUND: Single field Orthovoltage radiation is an acceptable modality used for the treatment of nasal cutaneous cancer. However, this technique has dosimetric pitfalls and unnecessary excessive exposure of radiation to organs at risk (OAR). We present the clinical outcome of a case series of cutaneous nasal tumours using a novel technique incorporating an optical scanner and a 3-dimensional (3D) printer to deliver treatments using parallel opposed (POP) fields. MATERIALS AND METHODS: The POP delivery method was validated using ion chamber and phantom measurements before implementation. A retrospective chart review of 26 patients treated with this technique between 2015 and 2019 was conducted. Patients' demographics and treatment outcomes were gathered and tabulated. These patients first underwent an optical scan of their faces to collect topographical data. The data were then transcribed into 3D printing algorithms, and positive impressions of the faces were printed. Custom nose block bolus was made with wax encased in an acrylic shell; 4 cm thick using the printed face models. Custom lead shielding was also generated. Treatments were delivered using 250 KeV photons POP arrangement with 4 cm diameter circle applicator cone and prescribed to the midplane. Dose and fractionation were as per physician discretion. RESULTS: Phantom measurements at mid-plane were found to match the prescribed dose within ±0.5%. For the 26 cases in this review, the median age was 78.5 years, with 15 females and 11 males. 85% of cases had Basal cell carcinoma (BCC); 1 had squamous cell carcinoma (SCC), one had synchronous BCC + SCC, and 1 had Merkel cell carcinoma. Twenty-one cases had T1N0 disease, 4 had T2N0, and 1 had T3N0. Dose and fractionation delivered were 40Gy in 10 fractions for the majority of cases. The complete response rate at a median follow-up of 6 months was 88%; 1 patient had a refractory tumour, and one patient had a recurrence. Toxicities were minor with 81% with no reported side effects. Three patients experienced grade 3 skin toxicity. CONCLUSIONS: Utilization of optic scanner and 3D printing technology, with the innovative approach of using POP orthovoltage beams, allows an effective and efficient way of treatment carcinomas of the nose with a high control rate and low toxicity profiles.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".