Evaluation of root canal morphology of mandibular premolars in Pakistani population using the new classification: a CBCT study.

Background: A comprehensive understanding of the root form and canal anatomy is essential for successful endodontic treatment. This study aimed to evaluate the root canal anatomy of mandibular premolars in the Pakistani population using cone beam computed tomography (CBCT) and to classify the findings with the new classification proposed by Ahmed et al. METHODS: Ethical exemption was obtained from Aga Khan University Hospital, Karachi. A total of 707 CBCT scans from Karachi and Lahore were included, comprising 592 scans from a tertiary care hospital in Karachi and 115 scans from a radiology center in Lahore. The study focused on sound, fully formed mandibular first and second premolars, excluding those with significant caries, restorations, or prior root canal treatments. Scans from different equipment were used, and calibration was achieved between a specialist endodontist and two dental residents. Data was analyzed using the Statistical Package for the Social Sciences (SPSS) software, version 26. Descriptive statistics, Chi-square tests to determine association between the variables, and a significance level set at 5% (p <0.05) were utilized.

Results: A total of 2403 mandibular premolars were analyzed. The most common configuration was ¹MPM¹ (82.90%), with rare variations such as ¹MPM^1-3-1 (0.04%) and ²MPM^{1 B1 L2} (0.04%). Single-rooted premolars were predominant (98.87%), and no significant differences were observed when data was stratified by age or gender.

Conclusions: This is the first study in Pakistan involving multiple centers and using the classification system by Ahmed et al. to understand the anatomy of mandibular premolars. The findings indicate that while most premolars have a single root and canal, variations exist. These variations highlight the importance of understanding canal morphology for improving the success of endodontic treatment. Future studies should include a larger and more diverse dataset to fully represent the Pakistani population.