Computer-Assisted Segmentation of Craniofacial Structures and Osteotomy Planning Using CBCT and CT
Craniofacial Structure Segmentation · Virtual Osteotomy Planning
De qué trata este estudio
El registro no identifica actualmente este estudio como reclutando. Consulta su estado antes de planificar una evaluación.
- Tipo de estudio
- Observacional
- Fase
- No aplica / no indicada
- Rango de edad
- 16 años - 85 años
- Sexo admitido
- Todos los sexos
- Voluntarios sanos
- No aceptados
- Participantes
- 200 Estimado
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Acerca de la investigación
This project will develop and evaluate methods for automatic and semi-automatic segmentation of craniofacial structures and delineation of osteotomy corridors using cone-beam computed tomography (CBCT) and computed tomography (CT) images. It will assess the quality and reproducibility of expert-prepared reference segmentations, the influence of model training, and the accuracy, processing time, and errors of automated methods. Only existing clinical scans will be used, with no additional imaging or changes to patient treatment.
Leer la descripción completa
This retrospective methodological project will use pseudonymized CBCT and CT images. Expert-reviewed segmentations and virtual osteotomy plans will serve as references. Selected cases will undergo repeated and independent assessment to evaluate intra- and interobserver agreement. A development dataset of CBCT examinations will be used to assess the effects of training set size and training progression. The final model will be tested on examinations not used during development. Evaluation will include segmentation accuracy, processing time, errors, technical failures, and correction requirements. Osteotomy corridors will be assessed against reference plans and nearby critical anatomical structures.
¿Quién podría participar?
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Inclusion Criteria:
- Archived CBCT or CT examinations acquired for clinical indications.
- Patient age of 16-85 years at the time of imaging.
- Images available in DICOM format and suitable for analysis.
- Complete visualization of the anatomical structures required for the planned analysis.
- Image quality sufficient for reliable reference preparation and assessment.
Exclusion Criteria:
- Incomplete or corrupted image series.
- Insufficient imaging coverage.
- Image quality preventing reliable reference assessment.
Población del estudio
Patients aged 16-85 years at the time of clinically indicated CBCT or CT imaging, whose archived examinations meet the study eligibility criteria.
Entiende la evaluación inicialTratamiento, grupos y participación
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- Asignación
- No informado
- Enmascaramiento
- No informado
Patients with archived CBCT or CT examinations
Patients whose archived CBCT or CT examinations will be used to develop and evaluate automatic and semi-automatic craniofacial segmentation methods and virtual osteotomy planning.
Other: Computer-based craniofacial segmentation and osteotomy planning
Computer-based craniofacial segmentation and osteotomy planning OTHER
Automatic and semi-automatic segmentation of craniofacial structures and virtual delineation of osteotomy corridors using archived CBCT and CT images.
Qué evalúan los investigadores
Estas medidas indican qué se estudia. No prueban que un tratamiento funcione.
Medidas principales
Segmentation accuracy compared with expert-prepared reference segmentations
Plazo: At the time of final model evaluation, up to 6 months
Agreement between uncorrected algorithm-generated segmentation masks and expert-prepared reference masks, assessed using the Dice similarity coefficient (DSC). Scores range from 0 to 1, with higher values indicating greater overlap.
Medidas secundarias
Intraobserver and interobserver agreement of reference segmentations
Plazo: During initial, repeat, and independent reference segmentation assessments, up to 6 months
Agreement between repeated reference segmentations by the same investigator and independent reference segmentations by a second investigator, assessed using the Dice similarity coefficient (DSC). Scores range from 0 to 1, with higher values indicating greater overlap.
Segmentation processing time
Plazo: During segmentation processing, up to 6 months
Time required to generate segmentations for the evaluated examinations.
Frequency of segmentation errors, technical failures, and correction requirements
Plazo: During segmentation processing and initial expert evaluation, up to 6 months
Frequency of segmentation errors, technical failures, restarts, and correction requirements, reported separately by category.
Segmentation performance by training set size and training progression
Plazo: During model training and internal validation, up to 6 months
Dice similarity coefficient values across evaluated training set sizes and training stages during internal validation.
Evaluation of virtual osteotomy corridors
Plazo: At the time of virtual osteotomy corridor evaluation, up to 6 months
Assessment of computer-generated osteotomy corridors against expert-prepared reference plans and in relation to nearby critical anatomical structures.
Revisa las tablas completas y sus limitaciones en el registro oficial.
Abrir resultados oficiales ↗Centros de investigación (1)
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1 centros
Department of Maxillofacial Surgery, Hospital of the Ministry of InteriorKielce, PolandEstado desconocido
Equipo y fechas
- Patrocinador principal
- Hospital of the Ministry of Interior, Kielce, Poland
- Inicio del estudio
- 2026-11 Estimado
- Finalización primaria
- 2027-03 Estimado
- Finalización del estudio
- 2027-04 Estimado
- Primera publicación
- 10 nov 2026 Real
- Última actualización
- 10 nov 2026 Real
Contactos oficiales del estudio
Título oficial del estudio
Development and Evaluation of Methods for Automatic and Semi-Automatic Segmentation of Craniofacial Structures and Delineation of Osteotomy Corridors Using CBCT and CT Imaging
Consulta a Wellness Clinical Research
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Fuente: API v2 de ClinicalTrials.gov. Patrocinadores e investigadores envían la información. La NLM no aprueba la seguridad ni la ciencia de todos los estudios registrados. Aviso del registro.
Consultado: 12 nov 2026 · Última actualización del registro: 10 nov 2026