Artificial Intelligence-Assisted CBCT Evaluation of Root Canal Morphology and Cross-Sectional Anatomy of Permanent Mandibular Premolars: A Retrospective Study

European Journal of Prosthodontics and Restorative Dentistry (2026) 34(1s), 76–88

Artificial intelligence; Root canal morphology; Cone beam computed tomography; Digital dentistry; Mandibular premolars; Endodontics; Restorative dentistry.

Haider Ali Hasan1
PhD Oral and Maxillofacial RadiologyDepartment of Oral surgery, College of
Dentistry, University of Babylon-Iraq.
Israa Hussein Ali2*
MSc Paediatric Dentistry- Department of
Pediatric and Preventive Dentistry, College of
Dentistry, University of Babylon-Iraq.
Ayman Hameed Uraibi3
MSc Oral and Maxillofacial RadiologyDepartment of Oral surgery, College of
Dentistry, University of Babylon-Iraq.
Ahmed Ghanim Alhelal 4s
PhD Conservative Dentistry- Conservative
Dentistry Department, College of Dentistry,
University of Babylon, Iraq.
PhD Conservative Dentistry- Conservative
Dentistry Department n, College of Dentistry,
University of Al-Ameed, Karbala, Iraq.
Correspondence to:
*Israa Hussein Ali (MSc in Paediatric
Dentistry, United Kingdom)
E-mail: [email protected]
ORCID: https://orcid.org/0000-0002-57967365

Artificial
IntelligenceAssisted CBCT Evaluation of
Root Canal Morphology and
Cross-Sectional Anatomy of
Permanent
Mandibular
Premolars: A Retrospective
Study.

Artificial intelligence (AI)-supported diagnostic imaging has emerged as a transformative approach in restorative dentistry and endodontics, improving the precision of anatomical interpretation and treatment planning. This retrospective CBCT-based study aimed to evaluate the root morphology, root canal configuration, and cross-sectional anatomy of permanent mandibular premolars with a focus on the clinical significance of AI-assisted imaging technologies in contemporary dental diagnostics.

A retrospective analysis was conducted on 249 cone beam computed tomography (CBCT) scans from Iraqi patients between the ages of 15 and 45. The root number, canal number, Vertucci-classified canal configuration, and root cross-sectional morphology at the coronal, middle, and apical levels of mandibular first and second premolars were assessed. After calibrated observer training, standardised CBCT image evaluation was carried out in the axial, sagittal, and coronal planes. Pearson's Chi-square test was used for statistical analysis to identify differences based on tooth side and sex (p < 0.05).

In mandibular first premolars (85.6%) and second premolars (98.7%), single-root morphology predominated. Similarly, 83.1% and 98.1% of first and second premolars, respectively, had single canals. The Vertucci Type I canal configuration was the most prevalent morphology in mandibular first (81.4%) and second (97.5%) premolars, followed by Type V configurations. Cross-sectional analysis revealed elongated oval morphology as the dominant configuration at coronal and middle levels, whereas round morphology predominated apically. Mandibular first premolars demonstrated greater anatomical complexity and variability compared with second premolars.

Considerable anatomical variation exists in mandibular premolar root canal systems despite the predominance of single-rooted and single-canaled patterns. CBCT imaging provides detailed three-dimensional anatomical visualization essential for restorative and endodontic procedures. The integration of AI-assisted CBCT interpretation may further enhance automated canal detection, morphological classification, and precisionguided treatment planning in restorative dentistry and oral rehabilitation.

In the dental field, learning about root canal morphology is crucial, particularly if successful endodontics is the goal. The intricacy of root canal

Received: 01.04.2026 Revised: 24.04.2026 Accepted: 11.05.2026

10.1922/ejprd.v34i1s.1365

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