Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography
ABSTRACT Root canal access is essential for successful root canal treatment, yet it poses significant risks in teeth with calcified or constricted canals, such as root perforation or excessive loss of healthy dentin. The aim of this study was to develop a predictive model that could guide the design...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-05-01
|
| Series: | Engineering Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/eng2.70184 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849730165894021120 |
|---|---|
| author | Maria Llacer‐Martínez María T. Sanz Mar Jovani‐Sancho Benjamín Martín Biedma Elisabet Palazón Radford |
| author_facet | Maria Llacer‐Martínez María T. Sanz Mar Jovani‐Sancho Benjamín Martín Biedma Elisabet Palazón Radford |
| author_sort | Maria Llacer‐Martínez |
| collection | DOAJ |
| description | ABSTRACT Root canal access is essential for successful root canal treatment, yet it poses significant risks in teeth with calcified or constricted canals, such as root perforation or excessive loss of healthy dentin. The aim of this study was to develop a predictive model that could guide the design of a conservative, accurate endodontic access in maxillary central incisors using cone beam computed tomography (CBCT). In this retrospective cross‐sectional study, CBCT scans from 135 maxillary central incisors were analyzed to obtain anatomical and demographic data. Twenty‐four variables significantly correlated with three key aspects of access design—access starting point, depth to the pulp horn, and access angle (target variables). Mathematical functions were formulated using non‐linear regression, and the resultant model was validated for the three target variables with a new set of 18 maxillary central incisors (R2 > 0.68, W > 0.90). The results showed that age, tooth length, and specific CBCT‐derived parameters, such as starting point, angle, and depth, which are related to the tooth's access opening, strongly influenced the predicted access cavity parameters. This predictive model has the potential to be integrated into dynamic navigation software, optimizing endodontic access and reducing iatrogenic errors for practitioners. |
| format | Article |
| id | doaj-art-2de4afaa6e7b480c880ac2b46e1a96a5 |
| institution | DOAJ |
| issn | 2577-8196 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Engineering Reports |
| spelling | doaj-art-2de4afaa6e7b480c880ac2b46e1a96a52025-08-20T03:08:57ZengWileyEngineering Reports2577-81962025-05-0175n/an/a10.1002/eng2.70184Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed TomographyMaria Llacer‐Martínez0María T. Sanz1Mar Jovani‐Sancho2Benjamín Martín Biedma3Elisabet Palazón Radford4Departamento de Odontología, Facultad de Ciencias de la Salud Universidad Cardenal Herrera‐CEU Valencia SpainDepartamento de Didáctica Matemática Universidad de Valencia Valencia SpainDepartamento de Odontología, Facultad de Ciencias de la Salud Universidad Cardenal Herrera‐CEU Valencia SpainDepartamento de Cirugía y Especialidades Médico‐Quirúrgicas Universidad de Santiago de Compostela Santiago de Compostela SpainDepartamento de Odontología, Facultad de Ciencias de la Salud Universidad Cardenal Herrera‐CEU Valencia SpainABSTRACT Root canal access is essential for successful root canal treatment, yet it poses significant risks in teeth with calcified or constricted canals, such as root perforation or excessive loss of healthy dentin. The aim of this study was to develop a predictive model that could guide the design of a conservative, accurate endodontic access in maxillary central incisors using cone beam computed tomography (CBCT). In this retrospective cross‐sectional study, CBCT scans from 135 maxillary central incisors were analyzed to obtain anatomical and demographic data. Twenty‐four variables significantly correlated with three key aspects of access design—access starting point, depth to the pulp horn, and access angle (target variables). Mathematical functions were formulated using non‐linear regression, and the resultant model was validated for the three target variables with a new set of 18 maxillary central incisors (R2 > 0.68, W > 0.90). The results showed that age, tooth length, and specific CBCT‐derived parameters, such as starting point, angle, and depth, which are related to the tooth's access opening, strongly influenced the predicted access cavity parameters. This predictive model has the potential to be integrated into dynamic navigation software, optimizing endodontic access and reducing iatrogenic errors for practitioners.https://doi.org/10.1002/eng2.70184cone beam computed tomographyendodontic access cavityendodontic planning and root canal treatmentnavigation systempredictive model |
| spellingShingle | Maria Llacer‐Martínez María T. Sanz Mar Jovani‐Sancho Benjamín Martín Biedma Elisabet Palazón Radford Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography Engineering Reports cone beam computed tomography endodontic access cavity endodontic planning and root canal treatment navigation system predictive model |
| title | Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography |
| title_full | Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography |
| title_fullStr | Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography |
| title_full_unstemmed | Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography |
| title_short | Predictive Model of Endodontic Access in Maxillary Central Incisors Using Cone Beam Computed Tomography |
| title_sort | predictive model of endodontic access in maxillary central incisors using cone beam computed tomography |
| topic | cone beam computed tomography endodontic access cavity endodontic planning and root canal treatment navigation system predictive model |
| url | https://doi.org/10.1002/eng2.70184 |
| work_keys_str_mv | AT mariallacermartinez predictivemodelofendodonticaccessinmaxillarycentralincisorsusingconebeamcomputedtomography AT mariatsanz predictivemodelofendodonticaccessinmaxillarycentralincisorsusingconebeamcomputedtomography AT marjovanisancho predictivemodelofendodonticaccessinmaxillarycentralincisorsusingconebeamcomputedtomography AT benjaminmartinbiedma predictivemodelofendodonticaccessinmaxillarycentralincisorsusingconebeamcomputedtomography AT elisabetpalazonradford predictivemodelofendodonticaccessinmaxillarycentralincisorsusingconebeamcomputedtomography |