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Record W4403141332 · doi:10.1111/cid.13401

Ultrasonography‐Guided Dental Implant Surgery: A Feasibility Study

2024· article· en· W4403141332 on OpenAlexvenueno aff
Paolo Nava, Hamoun Sabri, Javier Calatrava, Jacob Martin Zimmer, Zhaozhao Chen, Junying Li, Hom‐Lay Wang

Bibliographic record

VenueClinical Implant Dentistry and Related Research · 2024
Typearticle
Languageen
FieldDentistry
TopicDental Implant Techniques and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCone beam computed tomographyUltrasoundImplant3D ultrasoundAbsolute deviationNuclear medicineComputed tomographyRadiologySurgeryMathematics

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the feasibility of ultrasound-image-based computer-assisted implant planning and placement. MATERIALS AND METHODS: Intraoral scans, cone-beam computerized tomography (CBCT), and ultrasound (US) scans with a custom positioning device were acquired in nine patients. Prosthetic-driven surgical guides were planned and fabricated based on ultrasound images and intraoral scans. Implants were then placed. Postoperative implant position was obtained intra-surgically by intraoral scan. Aside from the ultrasound-based plan, conventional implant planning was performed by the same operator on a pre-surgical CBCT for comparison. Linear deviations between ultrasound and CBCT-planned implant positions were measured and compared with the intra-surgical implant position, and the position deviations between two consecutive plannings were performed on the same CBCT by the same operator. The linear deviation between the 3D scan surface of the edentulous region and the ultrasonographic soft tissue profile segmentation was also assessed with reverse-engineering software. Means, standard deviations, and root mean square differences (RMSD) were calculated for every variable. RESULTS: All the ultrasound-planned implants were successfully placed, and no complications were recorded. The mean deviations in angles, shoulders, and apexes were 5.27 ± 1.75° (RMSD: 5.53°), 0.92 ± 0.26 mm (RMSD: 0.95 mm), and 1.41 ± 0.61 mm (RMSD: 1.53 mm), respectively, between the US and CBCT-planned implants; 2.63 ± 0.43° (RMSD: 2.66°), 1.16 ± 0.30 mm (RMSD: 1.19 mm), and 1.26 ± 0.27 mm (RMSD: 1.28 mm) between the planned implant and intra-surgically recorded positions; and 2.90 ± 1.36° (RMSD: 3.18°), 0.65 ± 0.27 mm (RMSD: 0.70 mm), and 0.99 ± 0.37 mm (RMSD: 1.05 mm) between two consecutive CBCTs planning performed by the same operator. The mean deviation between the 3D surfaces of model scans and ultrasound-derived soft tissue profile in the edentulous area was 0.19 ± 0.08 mm. CONCLUSIONS: Ultrasound-guided implant surgery represents a feasible non-ionizing alternative to conventional static guided implant surgical protocols for implant placement in sites with favorable characteristics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.251
GPT teacher head0.521
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2024
Admission routes1
Has abstractyes

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