Advanced dental surgeries using fused filament fabrication and stereolithography printing: Case reports
Bibliographic record
Abstract
BACKGROUND: The widespread use of digital imaging can now be combined with additive three-dimensional (3D) printing, changing traditional clinical dentistry, especially in challenging cases. Visualizing the bone and soft tissue anatomy using computed tomography (CT) and intraoral scanning generated digital files that can be further processed for 3D printing. Among the popular 3D printing approaches, fused filament fabrication (FFF) and stereolithography (SLA) are broadly used due to their rapid production, precision, and ease of use. METHODS: The current case series outlines three challenging clinical scenarios where a combination of CT and intraoral scans were utilized for digital planning. FFF multicolor anatomical models and SLA surgical guides were produced using 3D printing technology. The first case outlines the utility of this approach to place the optimal surgical window at the lateral sinus lift with anticipated difficult access. In the second case, distinct sites for autogenous bone harvesting were identified while preserving critical adjacent structures with surgical simulation. Finally, the third case outlines this strategy for optimal surgical access to expose an impacted second premolar. RESULTS: Both clinicians and patients benefited from the educational use of FFF‒SLA 3D-printed models, and all cases were successfully treated without complications. CONCLUSIONS: These cases demonstrate the significant utility of these digital technologies and rapid prototyping for improved pre-surgical planning, patient motivation, and didactic training that contribute to improved quality of clinical care. KEY POINTS: To the authors' knowledge, this is the first case reports employing both fused filament fabrication (FFF) and stereolithography (SLA) printing techniques in dental surgery. This innovative approach addresses a range of clinically challenging scenarios presented in this report. Computed tomography (CT) and intraoral scanning are essential for three-dimensional (3D) reconstruction. Specialized software is required to design the guide with precise specifications, and FFF and SLA printers are necessary for fabricating the 3D model. Three-dimensional reconstruction can be time-intensive, particularly when manual segmentation is necessary. Acquiring proficiency in the software may require additional time, and multicolor 3D printing also demands extended printing durations. PLAIN LANGUAGE SUMMARY: This study explores how digital imaging and three-dimensional (3D) printing can improve complex dental surgeries. Using tools such as computed tomography scans and intraoral scans, dentists can create detailed 3D models of a patient's bone and soft tissues. Two popular 3D printing methods-fused-filament fabrication (FFF) and stereolithography (SLA)-were used to make these models, which help with surgical planning. The study includes three cases where 3D-printed models were used to prepare for difficult dental procedures. In the first case, the 3D model helped plan the best way to access a difficult area for sinus surgery. The second case used the model to identify the best sites for bone harvesting. The third case used the model to plan how to safely expose an impacted tooth. These helped both the dentist and the patient understand the procedure better. All surgeries were successful, demonstrating how FFF and SLA 3D printing enhance planning, making advanced dental surgeries safer and more efficient.
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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 | 0.001 |
| 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".