Objective. The purposes of this study were to determine what microbial flora were present in teeth after failed root canal therapy and to establish the outcome of conservative re-treatment.

Study design. Fifty-four root-filled teeth with persisting periapical lesions were selected for re-treatment. After removal of the root filling, canals were sampled by means of advanced microbiologic techniques. The teeth were then re-treated and followed for up to 5 years.

Results. The microbial flora was mainly single species of predominantly gram-positive organisms. The isolates most commonly recovered were bacteria of the species Enterococcus faecalis. The overall success rate of re-treatment was 74%.

Conclusions. The microbial flora in canals after failed endodontic therapy differed markedly from the flora in untreated teeth. Infection at the time of root filling and size of the periapical lesion were factors that had a negative influence on the prognosis. Three of four endodontic failures were successfully managed by re-treatment.

Microbiologic analysis of teeth with failed endodontic treatment and the outcome of conservative re-treatment

Aim To evaluate clinically and radiographically the long-term clinical outcome of nonsurgical root canal treatment using calcium hydroxide in teeth with large cyst-like periapical lesions.

Summary  A total of 42 mature anterior teeth with large periapical lesions ranging in size from 7 to 18 mm in diameter were included in this study. Fluid samples from the lesions contained cholesterol crystals, which were identified by light microscopy. After adequate draining, the teeth were treated endodontically using calcium hydroxide as the intracanal medicament. All cases were followed up for a period of 2–10 years. Complete healing was observed in 73.8% and incomplete healing in a further 9.5% of cases.

Key learning points
• Root canal treatment using calcium hydroxide as an antibacterial dressing was successful in healing large cyst-like periapical lesions.

• This study suggests that the size of a periapical lesion is not a major determining factor in the decision to perform conventional root canal treatment or surgical removal of the lesion. Even large cyst-like periapical lesions containing cholesterol crystals can heal following nonsurgical root canal treatment.

Prognosis of large cyst‐like periapical lesions following nonsurgical root canal treatment: a clinical review

Summary

Apical periodontitis is caused primarily by microorganisms residing in the root canals of affected teeth. Nevertheless, there is convincing evidence implicating other independent factors that adversely affect the outcome of conventional root canal therapy. In this paper, morphological evidence is presented in support of die potential role of two endogenous factors that may interfere with post-endodontic healing of the periapex. The specimens consisted of a surgical biopsy of an asymptomatic peri-apical lesion which persisted for a follow-up period of 44 months. The biopsy was processed for correlated light and electron microscopy. The lesion was characterized by the presence of a large central lumen lined by a stratified squamous epithelium. The most striking feature of the lesion was the presence of vast numbers of cholesterol crystals which congregated in the connective tissue surrounding the cyst cavity. Extensive light and electron microscopic investigation of the apical part of the root canal and the lesion foiled to reveal the presence of microorganisms.



These findings strongly suggest that intrinsic factors like the accumulation of certain tissue break-down products such as cholesterol crystals, and the cystic condition of the lesion itself, can adversely affect the healing process of the periapex following root canal therapy. Consequently, such apical lesions can remain refractory to conventional endodontic therapy for long periods of time.

Radicular cyst affecting a root-filled human tooth: a long-term post-treatment follow-up

Aim To verify the diagnostic performance of an artificial intelligence system based on the deep convolutional neural network method to detect periapical pathosis on cone-beam computed tomography (CBCT) images. Methodology images of 153 periapical lesions obtained from 109 patients were included. The specific area of the jaw and teeth associated with the periapical lesions were then determined by a human observer. Lesion volumes were calculated using the manual segmentation methods using Fujifilm-Synapse 3D software (Fujifilm Medical Systems, Tokyo, Japan). The neural network was then used to determine (i) whether the lesion could be detected; (ii) if the lesion was detected, where it was localized (maxilla, mandible or specific tooth); and (iii) lesion volume. Manual segmentation and artificial intelligence (AI) (Diagnocat Inc., San Francisco, CA, USA) methods were compared using Wilcoxon signed rank test and Bland-Altman analysis. Results The deep convolutional neural network system was successful in detecting teeth and numbering specific teeth. Only one tooth was incorrectly identified. The AI system was able to detect 142 of a total of 153 periapical lesions. The reliability of correctly detecting a periapical lesion was 92.8%. The deep convolutional neural network volumetric measurements of the lesions were similar to those with manual segmentation. There was no significant difference between the two measurement methods (P > 0.05). Conclusions Volume measurements performed by humans and by AI systems were comparable to each other. AI systems based on deep learning methods can be useful for detecting periapical pathosis on CBCT images for clinical application.

Lawrence I. Carnes

Papers

The relationship of lesion size to diagnosis, incidence, and treatment of periapical cysts and granulomas