Validity and reliability of intraoral scanners compared to conventional gypsum models measurements: a systematic review
Bibliographic record
Abstract
BACKGROUND: The development of 3D technology and the trend of increasing the use of intraoral scanners in dental office routine lead to the need for comparisons with conventional techniques. OBJECTIVE: To determine if intra- and inter-arch measurements from digital dental models acquired by an intraoral scanner are as reliable and valid as the similar measurements achieved from dental models obtained through conventional intraoral impressions. SEARCH METHODS: An unrestricted electronic search of seven databases until February 2015. SELECTION CRITERIA: Studies that focused on the accuracy and reliability of images obtained from intraoral scanners compared to images obtained from conventional impressions. DATA COLLECTION AND ANALYSIS: After study selection the QUADAS risk of bias assessment tool for diagnostic studies was used to assess the risk of bias (RoB) among the included studies. RESULTS: Four articles were included in the qualitative synthesis. The scanners evaluated were OrthoProof, Lava, iOC intraoral, Lava COS, iTero and D250. These studies evaluated the reliability of tooth widths, Bolton ratio measurements, and image superimposition. Two studies were classified as having low RoB; one had moderate RoB and the remaining one had high RoB. Only one study evaluated the time required to complete clinical procedures and patient's opinion about the procedure. Patients reported feeling more comfortable with the conventional dental impression method. LIMITATIONS: Associated costs were not considered in any of the included study. CONCLUSIONS AND IMPLICATIONS: Inter- and intra-arch measurements from digital models produced from intraoral scans appeared to be reliable and accurate in comparison to those from conventional impressions. This assessment only applies to the intraoral scanners models considered in the finally included studies. Digital models produced by intraoral scan eliminate the need of impressions materials; however, currently, longer time is needed to take the digital images. REGISTRATION: PROSPERO (CRD42014009702). FUNDING: None.
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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 | 0.039 | 0.191 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".