AI-Assisted Implant Planning Using CBCT Data (AIP-CBCT)
13 mei 2026 bijgewerkt door: St. Petersburg State Pavlov Medical University
Retrospective Reader Study of AI-Assisted Implant Planning Using Cone-Beam Computed Tomography Data in Edentulous Patients
This retrospective observational reader study will evaluate artificial intelligence (AI)-assisted implant planning using anonymized cone-beam computed tomography (CBCT) datasets from patients with complete edentulism or a clinically equivalent edentulous condition.
AI-generated implant plans will be compared with expert reference plans created by clinicians using the same CBCT data.
The study will assess the clinical acceptability of AI-generated implant plans, geometric agreement with expert plans, anatomical safety, workflow time, and agreement between expert reviewers where applicable.
The study uses previously acquired anonymized imaging data and does not involve patient recruitment, treatment allocation, additional imaging, clinical intervention, or prospective follow-up.
Studie Overzicht
Toestand
Actief, niet wervend
Interventie / Behandeling
Gedetailleerde beschrijving
This study is designed as a retrospective non-randomized comparative reader study.
Anonymized CBCT datasets acquired during routine clinical care will be used for implant planning assessment.
For each eligible case, expert clinicians will create reference implant plans without access to AI-generated plans.
The AI system will generate implant planning outputs from the same CBCT datasets, and expert clinicians will review the AI-generated plans using a standardized assessment approach.
The main evaluation will compare AI-generated plans with expert reference plans within the same case.
Outcomes will include clinical acceptability of the AI-generated plan, geometric agreement between AI-generated and expert plans, anatomical safety relative to relevant risk structures, time required for expert planning versus AI-plan review and correction, and inter-reader agreement where applicable.
The study does not test an autonomous AI decision-making system.
The AI workflow is evaluated as a clinical decision-support tool, and all AI-generated plans are subject to expert clinician review.
No new imaging examinations, treatment allocation, patient intervention, or prospective clinical outcome assessment will be performed.
Studietype
Observationeel
Inschrijving (Geschat)
100
Contacten en locaties
In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.
Studie Locaties
-
-
Sankt-Peterburg
-
Saint Petersburg, Sankt-Peterburg, Rusland, 197022
- Pavlov First Saint Petersburg State Medical University
-
-
Deelname Criteria
Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.
Geschiktheidscriteria
Leeftijden die in aanmerking komen voor studie
- Oudere volwassene
Accepteert gezonde vrijwilligers
Nee
Bemonsteringsmethode
Niet-waarschijnlijkheidssteekproef
Studie Bevolking
The study population will consist of anonymized CBCT cases from edentulous patients, or patients with a clinically equivalent edentulous condition, who underwent CBCT imaging during routine clinical care for implant prosthodontic planning.
No new patient recruitment, additional imaging, treatment allocation, or patient intervention will be performed.
Beschrijving
Inclusion Criteria:
- Anonymized CBCT dataset from a patient with complete edentulism or a clinically equivalent edentulous condition requiring implant prosthodontic planning.
- CBCT imaging acquired during routine clinical care.
- Sufficient field of view to assess the jaws and relevant anatomical landmarks for implant planning.
- Image quality sufficient for anatomical assessment, segmentation, and implant planning.
- Technical suitability of the CBCT dataset for expert reference planning and AI-assisted implant planning.
Exclusion Criteria:
- Severe motion artifacts or metal artifacts preventing reliable anatomical assessment.
- Incomplete field of view preventing assessment of the intended implant planning region.
- Corrupted, incomplete, duplicate, or unreadable DICOM data.
- Technical limitations preventing expert reference planning or AI-assisted implant planning.
- Missing data required for assessment of the primary outcome.
Studie plan
Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.
Hoe is de studie opgezet?
Ontwerpdetails
Cohorten en interventies
Groep / Cohort |
Interventie / Behandeling |
|---|---|
|
Retrospective CBCT Planning Cases
Anonymized cone-beam computed tomography (CBCT) cases from patients with complete edentulism or a clinically equivalent edentulous condition who underwent CBCT imaging for implant planning during routine clinical care.
Each case will be evaluated using expert reference planning and AI-assisted implant planning with expert review.
|
AI-assisted implant planning workflow applied to anonymized CBCT datasets.
The workflow generates implant planning outputs for expert review and comparison with expert reference plans.
It is evaluated as a clinical decision-support workflow and does not involve patient treatment, additional imaging, or autonomous clinical decision-making.
|
Wat meet het onderzoek?
Primaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
|
Clinical acceptability of AI-generated implant plans
Tijdsspanne: Baseline
|
Proportion of AI-generated implant plans rated by expert clinicians as accepted without modification, accepted after minor modification, accepted after major modification, or rejected.
|
Baseline
|
Secundaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
|
Geometric agreement between AI-generated and expert reference implant plans
Tijdsspanne: Baseline
|
Geometric agreement will be assessed for matched implants using entry-point deviation, apical deviation, and angular deviation between AI-generated and expert reference implant positions.
|
Baseline
|
|
Anatomical safety of AI-generated implant plans
Tijdsspanne: Baseline
|
Anatomical safety will be assessed using minimum distances from planned implants to relevant anatomical risk structures and the presence or absence of predefined safe-margin violations.
|
Baseline
|
|
Workflow time for AI-assisted planning review compared with expert planning
Tijdsspanne: Baseline
|
Time required for independent expert implant planning will be compared with the time required for expert review and correction of AI-generated implant plans.
|
Baseline
|
|
Inter-reader agreement for clinical acceptability ratings
Tijdsspanne: Baseline
|
Agreement between expert clinicians will be assessed for clinical acceptability ratings of AI-generated implant plans where more than one expert evaluates the same cases.
|
Baseline
|
Medewerkers en onderzoekers
Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.
Onderzoekers
- Hoofdonderzoeker: Roman A Rozov, MD, DSc, St. Petersburg State Pavlov Medical University
- Studie directeur: Karina Sh Oisieva, DDS, MSc, Saint Petersburg State University, Russia
Studie record data
Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.
Bestudeer belangrijke data
Studie start (Werkelijk)
16 februari 2026
Primaire voltooiing (Geschat)
30 juli 2026
Studie voltooiing (Geschat)
30 oktober 2026
Studieregistratiedata
Eerst ingediend
8 mei 2026
Eerst ingediend dat voldeed aan de QC-criteria
13 mei 2026
Eerst geplaatst (Werkelijk)
19 mei 2026
Updates van studierecords
Laatste update geplaatst (Werkelijk)
19 mei 2026
Laatste update ingediend die voldeed aan QC-criteria
13 mei 2026
Laatst geverifieerd
1 mei 2026
Meer informatie
Termen gerelateerd aan deze studie
Trefwoorden
Andere studie-ID-nummers
- LEC-05-26-N
Plan Individuele Deelnemersgegevens (IPD)
Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?
NEE
Beschrijving IPD-plan
Individual participant data will not be shared because the study uses retrospective anonymized medical imaging datasets.
CBCT/DICOM data may contain potentially re-identifiable information and cannot be publicly shared.
Aggregated results will be reported in publications.
Informatie over medicijnen en apparaten, studiedocumenten
Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel
Nee
Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct
Nee
Deze informatie is zonder wijzigingen rechtstreeks van de website clinicaltrials.gov gehaald. Als u verzoeken heeft om uw onderzoeksgegevens te wijzigen, te verwijderen of bij te werken, neem dan contact op met register@clinicaltrials.gov. Zodra er een wijziging wordt doorgevoerd op clinicaltrials.gov, wordt deze ook automatisch bijgewerkt op onze website .