Multidisciplinary management of an advanced mandibular ameloblastoma: Etiopathogenesis, surgical management and prosthetic rehabilitation
Bibliographic record
Abstract
The ameloblastoma is a benign but locally aggressive epithelial odontogenic neoplasm. Although rare, the ameloblastoma is the most common odontogenic tumor associated with the maxillofacial complex which possesses a significant propensity for local recurrence in the setting of conservative treatment. Concordantly, definitive therapy is predicated on wide surgical excision with reconstruction of ablative defects dictated by the resultant tissue defects. The purpose of this report is to highlight specific treatment and reconstructive challenges, emphasizing the essential need for collaborative patient care within a large multidisciplinary team. A 31-year-old Vietnamese-speaking male was referred for management of an extensive ameloblastoma associated with the left mandible. Management consisted of a bilateral composite mandibular resection and reconstruction via free tissue transfer utilizing an osteocutaneous fibular free flap. Histopathologic analysis confirmed the diagnosis of a conventional ameloblastoma. Delayed oral rehabilitation employing virtual surgical planning to facilitate the placement of endosseous implants with immediate loading of a fixed acrylic prosthesis was accomplished in the post-operative period without any evidence of recurrence. Multidisciplinary collaboration in the setting of advanced odontogenic tumors is paramount in enhancing treatment outcomes. This case strengthens the need for accurate and rapid diagnosis in the primary care setting with collaborative interprofessional management utilizing advances in digital technologies to optimize both functional and aesthetic outcomes which have significant influence over long-term quality-of-life.
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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 | 0.000 | 0.000 |
| 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".