Objective: X-ray microtomography (micro-CT or XMT) has been used in measuring residual voids in root filling. However, there is no agreement on a protocol that critically identifies and attempts to solve artefacts inherent to the micro-computed tomography technique. This paper aims to describe a protocol for automatic detection of voids within root filled canals taking into account the inherent artefacts with special interest in the partial volume effect. This is to reduce human errors and increase the accuracy and efficiency of void detection,
Methods: 33 human maxillary premolars were shaped, cleaned and root-filled using the cold lateral condensation (CLC) technique. Voids were detected using the proposed protocol and compared to tomographic slices individually. In this protocol, scans from the pre-obturation stage were used to identify the coordinates of the canal space. After aligning the post-obturation data sets to the pre-obturation data sets, voids in the post-obturation data sets were identified as voxels with a grey level below a set threshold.
Results: The visual inspection of slice by slice of the scanned data resulted in full agreement between the tomographic slices and the results gained from the proposed protocol. The proposed protocol is effective and offers an accurate method for detecting voids in root-filled canals.
Conclusion: The proposed protocol in this paper can improve the accuracy of void detection studies. (EEJ-2024-02-031)