Three-Dimensional Printing: A Novel Approach to the Creation of Obturator Prostheses Following Palatal Resection for Malignant Palate Tumors
Bibliographic record
Abstract
BACKGROUND: A subgroup of patients who have an oronasal fistula live in areas that have limited access to oral prosthetics. For these individuals, a temporary prosthesis, such as a palatal obturator, may be necessary in order to speak, eat, and breath properly. The creation of an obturator, which requires a highly trained prosthodontist, can take time and can be expensive. Through the current proof-of-concept study, there is an attempt to create a patient-specific palatal obturator through use of free and publicly available software, and a low-cost desktop 3-dimensional printer. The ascribed study may provide a means to increase global access to oral prosthetics if suitable biomaterials are developed. METHODS: Computerized tomography data were acquired from a patient who had an oronasal fistula. Through use of free software, these data were converted into a 3-dimensional image. The image was manipulated in order to isolate the patient's maxilla and was subsequently printed. The palatal obturator models were designed, and reformed, in correspondence with the maxilla model design. A final suitable obturator was determined and printed with 2 differing materials in order to better simulate a patient obturator. RESULTS: Creating a suitable palatal obturator for the specified patient model was possible with a low-cost printer and free software. CONCLUSIONS: With further development in biomaterials, it may be possible to design and create an oral prosthesis through use of low-cost 3-dimensional printing technology and freeware. This can empower individuals to attain good healthcare, even if they live in rural, developing, or underserviced areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".