Surgical experience and patient morbidity after third molar removal

Risk assessment of inferior alveolar nerve injury after wisdom tooth removal using 3D AI-driven models: A within-patient study

OBJECTIVE

To compare a three-dimensional (3D) artificial intelligence (AI)- driven model with panoramic radiography (PANO) and cone-beam computed tomography (CBCT) in assessing the risk of inferior alveolar nerve (IAN) injury after mandibular wisdom tooth (M3M) removal through a within-patient controlled trial.

METHODS

From a database of 6,010 patients undergoing M3M surgery, 25 patients met the inclusion criteria of bilateral M3M removal with postoperative unilateral IAN injury. In this within-patient controlled trial, preoperative PANO and CBCT images were available, while 3D-AI models of the mandibular canal and teeth were generated from the CBCT images using the Virtual Patient Creator AI platform (Relu BV, Leuven, Belgium). Five examiners, who were blinded to surgical outcomes, assessed the imaging modalities and assigned scores indicating the risk level of IAN injury (high, medium, or low risk). Sensitivity, specificity, and area under receiver operating curve (AUC) for IAN risk assessment were calculated for each imaging modality.

RESULTS

For IAN injury risk assessment after M3M removal, sensitivity was 0.87 for 3D-AI, 0.89 for CBCT versus 0.73 for PANO. Furthermore, the AUC and specificity values were 0.63 and 0.39 for 3D-AI, 0.58 and 0.28 for CBCT, and 0.57 and 0.41 for PANO, respectively. There was no statistically significant difference (p>0.05) among the imaging modalities for any diagnostic parameters.

CONCLUSION

This within-patient controlled trial study revealed that risk assessment for IAN injury after M3M removal was rather similar for 3D-AI, PANO, and CBCT, with a sensitivity for injury prediction reaching up to 0.87 for 3D-AI and 0.89 for CBCT.

CLINICAL SIGNIFICANCE

This within-patient trial is pioneering in exploring the application of 3D AI-driven models for assessing IAN injury risk after M3M removal. The present results indicate that AI-powered 3D models based on CBCT might facilitate IAN risk assessment of M3M removal.

Factors affecting number of third molars extracted in a single visit

OBJECTIVE

This cross-sectional study evaluated the number and characteristics of third molars extracted in a single visit in primary care and their associations with patient's age and sex and operator's experience.

MATERIALS AND METHODS

The data included all appointments where routine and surgical extractions of third molars were performed in 2016 in primary care of the City of Helsinki. Statistics included χ2 and Mann-Whitney U tests, and binomial logistic regression.

RESULTS

In total of 10,894 appointments, the number of extracted third molars was 12,728, yielding an average of 1.2 third molars per visit. Mean age of patients (55% women, 45% men) at extraction was 32.2 years (range 12 - 97 years). Most appointments (83.7%, n = 9,118) comprised extraction of one, 15.8% two, 0.4% three, and 0.1% four third molars. Number of teeth extracted at a time did not differ by sex. Increasing age was associated with a reduction in the likelihood of several third molar extractions in a visit (OR 0.96; 95% confidence interval (CI) 0.96-0.97). Multiple third molars were extracted significantly more likely if the operator was experienced (OR 2.32; 95%CI 1.90-2.84). Multiple extractions were also associated with the mandible, operative extractions, unerupted teeth and caries.

CONCLUSIONS

Third molars were typically extracted one at a time. In health care units, it is appropriate to consider extraction of several third molars in a single visit, if need for extraction of other third molars exist. Concentrating the extractions of younger patients on experienced operators would reduce the number of patients' visits.

Development of a risk prediction model for surgical site infection after lower third molar surgery

BACKGROUND

There is little evidence regarding risk prediction for surgical site infection (SSI) after lower third molar (L3M) surgery.

METHODS

We conducted a nested case-control study to develop a multivariable logistic model for predicting the risk of SSI after L3M surgery. Data were obtained from Hokkaido University Hospital from April 2013 to March 2020. Multiple imputation was applied for the missing values. We conducted decision tree (DT) analysis to evaluate the combinations of factors affecting SSI risk.

RESULTS

We identified 648 patients. The final model retained the available distal space (Pell & Gregory II [p = 0.05], Pell & Gregory III [p < 0.01]), depth (Pell & Gregory B [p < 0.01], Pell & Gregory C [p < 0.01]), surgeon's experience (3-10 years [p = 0.25], <3 years [p < 0.01]), and simultaneous extraction of both L3M [p < 0.01]; the concordance-statistic was 0.72. The DT analysis demonstrated that patients with Pell and Gregory B or C and simultaneous extraction of both L3M had the highest risk of SSI.

CONCLUSIONS

We developed a model for predicting SSI after L3M surgery with adequate predictive metrics in a single center. This model will make the SSI risk prediction more accessible.

Do anatomical variations of the mandibular canal pose an increased risk of inferior alveolar nerve injury after third molar removal?

OBJECTIVES

The present study aimed to assess whether anatomical variations of the mandibular canal are associated with neurosensory disturbances of the inferior alveolar nerve (IAN) following mandibular third molar removal.

METHODS

Two observers compared the detection of third molar root-nerve relations and bifurcations of the mandibular canal on panoramic radiographs and CBCT images of 201 patients undergoing removal of 357 mandibular third molars. Potential neurosensory disturbances of the IAN were surveyed ten days after surgery. Fisher's Exact was performed to correlate presence of canal variations to postoperative neurosensory disturbances. Positive and negative predictive values (PPV, NPV) and likelihood ratios (LR + , LR-) were calculated.

RESULTS

Thirteen patients reported postoperative altered sensation of the lower lip, with 2 of them having mandibular canal bifurcations on the ipsilateral side of the injury. Fisher's Exact showed that the studied mandibular canal variations were not related to postoperative neurosensory disturbances. CBCT was superior in visualization of anatomical variations of the mandibular canal. Prevalence of bifurcations was 14% on CBCT and 7% on panoramic radiographs. In both imaging modalities and for all parameters, PPVs were low (0.04 - 0.06) and NPVs were high (0.92 - 0.98), with LR ranging around 1.

CONCLUSION

In the present study, the assessed mandibular canal variations had limited predictive value for IAN neurosensory disturbances following third molar removal.

CLINICAL RELEVANCE

While a close relation between the third molar and the mandibular canal remains a high risk factor, mandibular canal variations did not pose an increased risk of postoperative IAN injury after third molar removal.