AI-Assisted Implant Planning Using CBCT Data (AIP-CBCT)
13 de mayo de 2026 actualizado por: 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.
Descripción general del estudio
Estado
Activo, no reclutando
Condiciones
Intervención / Tratamiento
Descripción detallada
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.
Tipo de estudio
De observación
Inscripción (Estimado)
100
Contactos y Ubicaciones
Esta sección proporciona los datos de contacto de quienes realizan el estudio e información sobre dónde se lleva a cabo este estudio.
Ubicaciones de estudio
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Sankt-Peterburg
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Saint Petersburg, Sankt-Peterburg, Rusia, 197022
- Pavlov First Saint Petersburg State Medical University
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Criterios de participación
Los investigadores buscan personas que se ajusten a una determinada descripción, denominada criterio de elegibilidad. Algunos ejemplos de estos criterios son el estado de salud general de una persona o tratamientos previos.
Criterio de elegibilidad
Edades elegibles para estudiar
- Adulto Mayor
Acepta Voluntarios Saludables
No
Método de muestreo
Muestra no probabilística
Población de estudio
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.
Descripción
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.
Plan de estudios
Esta sección proporciona detalles del plan de estudio, incluido cómo está diseñado el estudio y qué mide el estudio.
¿Cómo está diseñado el estudio?
Detalles de diseño
Cohortes e Intervenciones
Grupo / Cohorte |
Intervención / Tratamiento |
|---|---|
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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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¿Qué mide el estudio?
Medidas de resultado primarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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Clinical acceptability of AI-generated implant plans
Periodo de tiempo: 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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Medidas de resultado secundarias
Medida de resultado |
Medida Descripción |
Periodo de tiempo |
|---|---|---|
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Geometric agreement between AI-generated and expert reference implant plans
Periodo de tiempo: 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.
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Baseline
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Anatomical safety of AI-generated implant plans
Periodo de tiempo: 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
Periodo de tiempo: 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
Periodo de tiempo: 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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Colaboradores e Investigadores
Aquí es donde encontrará personas y organizaciones involucradas en este estudio.
Patrocinador
Investigadores
- Investigador principal: Roman A Rozov, MD, DSc, St. Petersburg State Pavlov Medical University
- Director de estudio: Karina Sh Oisieva, DDS, MSc, Saint Petersburg State University, Russia
Fechas de registro del estudio
Estas fechas rastrean el progreso del registro del estudio y los envíos de resultados resumidos a ClinicalTrials.gov. Los registros del estudio y los resultados informados son revisados por la Biblioteca Nacional de Medicina (NLM) para asegurarse de que cumplan con los estándares de control de calidad específicos antes de publicarlos en el sitio web público.
Fechas importantes del estudio
Inicio del estudio (Actual)
16 de febrero de 2026
Finalización primaria (Estimado)
30 de julio de 2026
Finalización del estudio (Estimado)
30 de octubre de 2026
Fechas de registro del estudio
Enviado por primera vez
8 de mayo de 2026
Primero enviado que cumplió con los criterios de control de calidad
13 de mayo de 2026
Publicado por primera vez (Actual)
19 de mayo de 2026
Actualizaciones de registros de estudio
Última actualización publicada (Actual)
19 de mayo de 2026
Última actualización enviada que cumplió con los criterios de control de calidad
13 de mayo de 2026
Última verificación
1 de mayo de 2026
Más información
Términos relacionados con este estudio
Palabras clave
Otros números de identificación del estudio
- LEC-05-26-N
Plan de datos de participantes individuales (IPD)
¿Planea compartir datos de participantes individuales (IPD)?
NO
Descripción del plan IPD
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.
Información sobre medicamentos y dispositivos, documentos del estudio
Estudia un producto farmacéutico regulado por la FDA de EE. UU.
No
Estudia un producto de dispositivo regulado por la FDA de EE. UU.
No
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