http://www.endoexperience.com/documents/DeVos2009.pdf

Cone-beam computerized tomography (CBCT) imaging of the oral and maxillofacial region: a systematic review of the literature.

Aims (i) To carry out meta-analyses to quantify the influence of the clinical factors on the efficacy of primary root canal treatment and (ii) to identify the best treatment protocol based on the current evidence.

Methodology  The evidence for the effect of each clinical factor on the success rate (SR) of primary root canal treatment was gathered in three different ways: (i) intuitive synthesis of reported findings from individual studies; (ii) weighted pooled SR by each factor under investigation was estimated using random-effect meta-analysis; (iii) weighted effect of the factor under investigation on SR were estimated and expressed as odds ratio for the dichotomous outcomes (success or failure) using fixed- and random-effects meta-analysis. Statistical heterogeneity amongst the studies was assessed by Cochran’s (Q) test. Potential sources of statistical heterogeneity were investigated by exploring clinical heterogeneity using meta-regression models which included study characteristics in the regression models.

Results  Out of the clinical factors investigated, pre-operative pulpal and periapical status were most frequently investigated, whilst the intra-operative factors were poorly studied in the 63 studies. Four factors were found to have a significant effect on the primary root canal treatment outcome, although the data heterogeneity was substantial, some of which could be explained by some of the study characteristics.

Conclusions  Four conditions (pre-operative absence of periapical radiolucency, root filling with no voids, root filling extending to 2 mm within the radiographic apex and satisfactory coronal restoration) were found to improve the outcome of primary root canal treatment significantly. Root canal treatment should therefore aim at achieving and maintaining access to apical anatomy during chemo-mechanical debridement, obturating the canal with densely compacted material to the apical terminus without extrusion into the apical tissues and preventing re-infection with a good quality coronal restoration.

/pdf/outcome-of-primary-root-canal-treatment-systematic-review-of-3bb8w8goxh.pdf

Outcome of primary root canal treatment: systematic review of the literature -- Part 2. Influence of clinical factors.

Patel S, Dawood A, Pitt Ford T, Whaites E. The potential applications of cone beam computed tomography in the management of endodontic problems. International Endodontic Journal, 40, 818– 830, 2007. Aim To provide core information on cone beam computed tomography (CBCT) technology and its potential applications in endodontic practice. Summary CBCT has been specifically designed to produce undistorted three-dimensional information of the maxillofacial skeleton as well as three-dimensional images of the teeth and their surrounding tissues. This is usually achieved with a substantially lower effective dose compared with conventional medical computed tomography (CT). Periapical disease may be detected sooner using CBCT compared with periapical views, and the true size, extent, nature and position of periapical and resorptive lesions can be assessed. Root fractures, root canal anatomy and the true nature of the alveolar bone topography around teeth may be assessed. CBCT scans are desirable to assess posterior teeth prior to periapical surgery, as the thickness of the cortical and cancellous bone can be accurately determined as can the inclination of roots in relation to the surrounding jaw. The relationship of anatomical structures such as the maxillary sinus and inferior dental nerve to the root apices may also be clearly visualized. Key learning points • CBCT has a low effective dose in the same order of magnitude as conventional dental

/pdf/the-potential-applications-of-cone-beam-computed-tomography-1wvvmiafet.pdf

The potential applications of cone beam computed tomography in the management of endodontic problems.

https://www.odontoscan.com.br/imagens/gerais/anexo_562a890d92ee9.pdf

Endodontic Applications of Cone-Beam Volumetric Tomography

Accuracy of cone beam computed tomography and panoramic and periapical radiography for detection of apical periodontitis.

Objective The purpose of this study was to use meta-analysis statistics to determine the influence of factors such as apical limit (short vs. overextension), status of the pulp (vital vs. nonvital), and periapical status (presence or absence of radiolucency) on endodontic prognosis. Study design The study-list was obtained by using a MEDLINE search and Japana Centra Revuo Medicina search. Only those papers in which the criteria for success or failure was exactly described were accepted. Results The cumulative success rate of 82.8 ± 1.19% (average ±95% confidence interval) was obtained for vital pulp; and 78.9 ± 1.05%, for nonvital ones. There was a significant difference between the 2 groups. The cumulative success rates with overextension, flush, and underextension in vital teeth were 70.8 ± 1.44, 86.5 ± 0.88, and 85.5 ± 0.98% respectively. There was a significant difference between flush and overextension and between flush and underextension. The rates for nonvital pulp were similar to those for vital ones. Conclusion The root canal should be filled to within 2 mm of the radiographic apex.

Success rate of endodontic treatment of teeth with vital and nonvital pulps. A meta-analysis

Effectiveness of dental computed tomography in diagnostic imaging of periradicular lesion of each root of a multirooted tooth: a case report.

The aim of this study was to evaluate the use of a convolutional neural network (CNN) system for detecting vertical root fracture (VRF) on panoramic radiography. Three hundred panoramic images containing a total of 330 VRF teeth with clearly visible fracture lines were selected from our hospital imaging database. Confirmation of VRF lines was performed by two radiologists and one endodontist. Eighty percent (240 images) of the 300 images were assigned to a training set and 20% (60 images) to a test set. A CNN-based deep learning model for the detection of VRFs was built using DetectNet with DIGITS version 5.0. To defend test data selection bias and increase reliability, fivefold cross-validation was performed. Diagnostic performance was evaluated using recall, precision, and F measure. Of the 330 VRFs, 267 were detected. Twenty teeth without fractures were falsely detected. Recall was 0.75, precision 0.93, and F measure 0.83. The CNN learning model has shown promise as a tool to detect VRFs on panoramic images and to function as a CAD tool.

Kyoko Inamoto

Papers

Success rate of endodontic treatment of teeth with vital and nonvital pulps. A meta-analysis

Effectiveness of dental computed tomography in diagnostic imaging of periradicular lesion of each root of a multirooted tooth: a case report.

Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography

A survey of the incidence of single-visit endodontics.

Experimental pain in the gingiva and its impact on prefrontal cortical hemodynamics: A functional near-infrared spectroscopy study