AI-Assisted Implant Planning Using CBCT Data (AIP-CBCT)
Retrospective Reader Study of AI-Assisted Implant Planning Using Cone-Beam Computed Tomography Data in Edentulous Patients
Studieoversigt
Status
Status
Betingelser
Betingelser
Intervention / Behandling
Intervention / Behandling
Detaljeret beskrivelse
Undersøgelsestype
Undersøgelsestype
Tilmelding (Anslået)
Tilmelding
Kontakter og lokationer
Studiesteder
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Sankt-Peterburg
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Saint Petersburg, Sankt-Peterburg, Rusland, 197022
- Pavlov First Saint Petersburg State Medical University
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Deltagelseskriterier
Berettigelseskriterier
Berettigelseskriterier
Aldre berettiget til at studere
- Ældre voksen
Tager imod sunde frivillige
Prøveudtagningsmetode
Studiebefolkning
Beskrivelse
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.
Studieplan
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
Antal grupper/kohorter
Kohorter og interventioner
Gruppe / kohorteGruppe / kohorte |
Intervention / BehandlingIntervention / Behandling |
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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.
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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.
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Hvad måler undersøgelsen?
Primære resultatmål
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
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Clinical acceptability of AI-generated implant plans
Tidsramme: Baseline
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Proportion of AI-generated implant plans rated by expert clinicians as accepted without modification, accepted after minor modification, accepted after major modification, or rejected.
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Baseline
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Sekundære resultatmål
Sekundære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
|---|---|---|
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Geometric agreement between AI-generated and expert reference implant plans
Tidsramme: Baseline
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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.
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Baseline
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Anatomical safety of AI-generated implant plans
Tidsramme: Baseline
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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.
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Baseline
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Workflow time for AI-assisted planning review compared with expert planning
Tidsramme: Baseline
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Time required for independent expert implant planning will be compared with the time required for expert review and correction of AI-generated implant plans.
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Baseline
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Inter-reader agreement for clinical acceptability ratings
Tidsramme: Baseline
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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.
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Baseline
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Samarbejdspartnere og efterforskere
Sponsor
Sponsor
Efterforskere
Efterforskere
- Ledende efterforsker: Roman A Rozov, MD, DSc, St. Petersburg State Pavlov Medical University
- Studieleder: Karina Sh Oisieva, DDS, MSc, Saint Petersburg State University, Russia
Datoer for undersøgelser
Studer store datoer
Studiestart (Faktiske)
Studiestart
Primær færdiggørelse (Anslået)
Primær færdiggørelse
Studieafslutning (Anslået)
Studieafslutning
Datoer for studieregistrering
Først indsendt
Først indsendt
Først indsendt, der opfyldte QC-kriterier
Først indsendt, der opfyldte QC-kriterier
Først opslået (Faktiske)
Først opslået
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
Sidste opdatering sendt
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
Sidst verificeret
Sidst verificeret
Mere information
Begreber relateret til denne undersøgelse
Nøgleord
Andre undersøgelses-id-numre
Andre undersøgelses-id-numre
- LEC-05-26-N
Plan for individuelle deltagerdata (IPD)
Planlægger du at dele individuelle deltagerdata (IPD)?
IPD-planbeskrivelse
Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter
Studerer et amerikansk FDA-reguleret lægemiddelprodukt
Studerer et amerikansk FDA-reguleret enhedsprodukt
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