Assessment of the type and length of separated endodontic instruments in root-filled mandibular molars: A comparative study using digital periapical radiographs and CBCT
Bibliographic record
Abstract
Purpose: This study aimed to compare the diagnostic performance of cone-beam computed tomography (CBCT) and digital periapical radiography in detecting separated endodontic instruments (SI) according to their type and length in filled root canals of mandibular molars.Materials and Methods: Forty-two extracted mandibular molars were divided into 2 groups: control (without SI) and experimental (with SI).In the experimental group, SI fragments (2 or 3 mm) from 3 endodontic instruments (WaveOne Gold, Reciproc Blue, and ProTaper Next) were inserted into the mesiobuccal canals of 30 teeth.CBCT scans were obtained using the KAVO OP 3D PRO device, and digital periapical radiographs (orthoradial, distal, and mesial) were acquired using the Focus X-ray unit with the RVG 5200 solid sensor.Three experts independently evaluated all images for SI detection using a 5-point scale.Diagnostic performance metrics were calculated for each imaging method, and comparisons were performed using 1-way analysis of variance with Tukey post-hoc tests.The significance level was set at 5% (P = 0.05).Results: Digital periapical radiography demonstrated higher area under the receiver operating characteristic curve (Az), sensitivity, and specificity values than CBCT.ProTaper Next SI on CBCT scans showed the lowest Az values (0.58 and 0.56 for 2-and 3-mm fragments, respectively).These values were significantly different from those of the other SI conditions (both CBCT and digital periapical radiography) (P<0.05).Conclusion: Digital periapical radiography outperformed CBCT in detecting SI in filled root canals of mandibular molars and should be the preferred modality.Furthermore, SI detectability varies with imaging modality, depending on instrument type and fragment length.(
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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".