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AI-Assisted Implant Planning Using CBCT Data (AIP-CBCT)

13. maj 2026 opdateret af: 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.

Studieoversigt

Status

Aktiv, ikke rekrutterende

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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.

Undersøgelsestype

Observationel

Tilmelding (Anslået)

100

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiesteder

  • Rusland
    • Sankt-Peterburg
      • Saint Petersburg, Sankt-Peterburg, Rusland, 197022
        • Pavlov First Saint Petersburg State Medical University

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Ældre voksen

Tager imod sunde frivillige

Ingen

Prøveudtagningsmetode

Ikke-sandsynlighedsprøve

Studiebefolkning

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.

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

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

Kohorter og interventioner

Gruppe / kohorte
Intervention / Behandling
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.
Andet: AI-Assisted Implant Planning Workflow
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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Clinical acceptability of AI-generated implant plans
Tidsramme: 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

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Geometric agreement between AI-generated and expert reference implant plans
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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
Tidsramme: 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

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

St. Petersburg State Pavlov Medical University

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

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

16. februar 2026

Primær færdiggørelse (Anslået)

30. juli 2026

Studieafslutning (Anslået)

30. oktober 2026

Datoer for studieregistrering

Først indsendt

8. maj 2026

Først indsendt, der opfyldte QC-kriterier

13. maj 2026

Først opslået (Faktiske)

19. maj 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

19. maj 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

13. maj 2026

Sidst verificeret

1. maj 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Andre undersøgelses-id-numre

  • LEC-05-26-N

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

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.

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

Kliniske forsøg med Tandimplantat

Kliniske forsøg med AI-Assisted Implant Planning Workflow

Søg i lignende forsøg

Sponsorer og samarbejdspartnere

Medicinske tilstande

Narkotikainterventioner

CROs by country

CROs in Peru

Betingelser

Sjældne sygdomme

Narkotikainterventioner

Kosttilskud

Sponsor / samarbejdspartnere

Placeringer

Abonner