Evaluation of working length determination based on the analysis of cone-beam computed tomographic images and an electronic apex locator: a retrospective study^*

Abstract

IntroductionDetermining the length of a root canal is a significant outcome predictor for endodontic treatment. The aim of this retrospective, clinical study was to evaluate the accuracy of working length (WL) determination using pre-existing conebeam computed tomography (CBCT) images and to compare them with data of the clinical WL determined with an electronic apex locator (EAL) in treated teeth, found in patient records.Materials and methodsThirty five medical records of patients who underwent root canal treatment (RCT) by an endodontist in a private dental practice in Łódź, Poland were analysed. Evaluations were conducted on the data concerning: the WL of the treated tooth as found in the patient’s records, the RadioVisioGraphy (RVG) image after final obturation used as a control, and the CBCT scan before RCT. The Shapiro–Wilk normality test and Student’s t-test were used in statistical analysis. The significance level was set at p < 0.05.ResultsThere were no statistically significant differences between compared groups in terms of WL determined with an EAL than CBCT (p > 0.05). In the case of medical diagnosis (pulpitis vs. necrotic pulp) and treatment (primary vs. retreatment), the obtained results were also statistically insignificant (p > 0.05).ConclusionsThis retrospective, clinical study showed that CBCT scans can be successfully used for endodontic WL determination. Future investigations are needed to evaluate whether pre-existing CBCT scans may replace initial periapical radiographs (PARs).

[Retracted] Rehabilitation of Post‐Stroke Swallowing Dysfunction with Repeated Transcranial Magnetic Stimulation RTMS Based on Tomographic Images

“…Reference [7] used 3 Hz stimulation of the affected cerebral hemisphere as the treatment group, and sham stimulation as the control group. e patients with unilateral ischemic stroke were intervened.…”

“…Some scholars have studied the tomographic images. Pietrzycka et al evaluated the accuracy of determining the length of a tooth's root canal using preexisting cone beam computed tomography images [7]. Frank et al used deep learning algorithms to automatically segment cone beam computed tomography images and detect periapical lesions [8].…”