Search Results (34)

Background and Objectives: The extraction of mandibular third molars poses challenges due to their proximity to the mandibular canal and risk of inferior alveolar nerve (IAN) injury. Accurate preoperative evaluation is essential to minimize complications. This study assessed the three-dimensional positional relationship between the mandibular canal and lower third molars using cone-beam computed tomography (CBCT), aiming to identify anatomical positions associated with increased surgical risk. Materials and Methods: This retrospective study analyzed 253 CBCT scans of fully developed lower third molars. The mandibular canal position was classified as apical (Class I), buccal (Class II), lingual (Class III), or interradicular (Class IV). Contact was categorized as no contact, contact with a complete or defective white line, or canal penetration. In no-contact cases, the apex–canal distance was measured. Statistical analysis included descriptive and contingency analyses using the Chi-Square Likelihood Ratio test. Results: Class I was most common (70.8%) and presented the lowest risk, while Classes III and IV showed significantly higher frequencies of canal contact or penetration. Class II exhibited shorter distances even in no-contact cases, suggesting residual risk. Statistically significant associations were found between canal position and both contact type (p < 0.001) and apex–canal distance (p = 0.046). Conclusions: CBCT offers valuable insight into the anatomical relationship between third molars and the mandibular canal. High-risk positions—particularly lingual and interradicular—require careful assessment. Even in the absence of contact, close proximity may pose a risk and should inform surgical planning. Full article

The use of local anesthetics in dentistry is crucial for pain control. Their efficacy may be related to multiple factors, including gender, the clinical status of the patient, anatomical factors, the type of anesthetic, premedication treatment, and the experience of the professional. Aim: The objective of this study was to analyze whether premedication or the degree of patient anxiety influences the anesthetic efficacy of 4% articaine with epinephrine 1:100,000 and 0.5% bupivacaine with epinephrine 1:100,000 in patients undergoing root canal treatment for symptomatic irreversible pulpitis in the upper and lower molars. The null hypothesis (H0) of this study was that articaine and bupivacaine would have a similar anesthetic efficacy when used during the treatment of symptomatic irreversible pulpitis of the posterior mandibular and maxillary teeth, independent of non-steroidal anti-inflammatory drugs (NSAIDs) premedication or the patient’s anxiety levels. Methods: A total of 140 patients presenting with pulpitis in the upper and lower molars were randomly assigned to one of two anesthetics: articaine or bupivacaine. Before root canal treatment, patients completed the Modified Corah Dental Anxiety Scale (MDAS) and a Visual Analog Scale (VAS) for pain intensity. Inferior alveolar nerve block was performed for the lower molars and buccal infiltration for the upper molars, and the anesthetic efficacy was verified by the Endo Coldspray^® test. During the procedure, the patients’ heart rate and oxygen saturation were monitored using a pulse oximeter. The patients reported their pain levels using a VAS twenty-four hours postoperatively. Results: High levels of dental anxiety were significantly associated with higher pain scores (p = 0.000) for both groups. The hemodynamic changes during treatment remained within normal limits. The need for anesthetic reinforcement was higher in the bupivacaine group (p = 0.004). The patients in both groups reported low-intensity postoperative pain, although the pain level was slightly lower in the bupivacaine group. Conclusions: The anesthetic efficacy of articaine and bupivacaine in patients with irreversible pulpitis did not appear to be influenced by the degree of anxiety or the intake of AINEs as premedication. The intrinsic anesthetic efficacy was higher for articaine, which required less reinforcement than bupivacaine. Comparing the results obtained when performing buccal infiltration and inferior alveolar nerve block further highlighted the differences between the two anesthetics; these differences were more pronounced in the bupivacaine group, leading to rejection of the null hypothesis proposed at the beginning of the study. Full article

Background/Objectives: This study aims to determine the validity of a recently developed and published index (the modified Composite Radiographic Index—CRIm) as an indicator of disease gravity and progression in the CBCT scans of patients with medication-related osteonecrosis of the jaw (MRONJ) and to detect possible correlations between the radiologic findings and clinical staging of the disease. Methods: This study included 43 MRONJ patients with CBCT scans from the School of Dentistry of National and Kapodistrian University of Athens, approved by the Research Ethics Committee. Clinical staging (0–3) was provided based on AAOMS 2022 guidelines. A total of 52 CBCT scans were analyzed, with maxillae and mandibles evaluated separately when both were involved. Two independent observers assessed eight radiologic features, including lytic changes, sclerosis, periosteal reaction, sequestration, non-healing extraction sockets, and other findings (sinus involvement, inferior alveolar canal involvement, and jaw fracture). The CRIm was applied to quantify osseous changes, scoring each feature (0 (absent), 1 (localized/single), 2 (extensive/multiple)), yielding a range of 0–12. For the statistical analysis, Fisher’s exact test and Spearman’s correlation coefficient were used. Results: Clinical Stage 1 consisted of 19 jaws, Stage 2 consisted of 16 jaws, and Stage 3 consisted of 17 jaws. No affected jaws were recorded with Stage 0. A statistically significant correlation between the clinical stage and lytic changes, sequestration, and inferior alveolar canal involvement was found (p-value < 0.05). Extensive lytic changes, sclerosis, sequestration, periosteal bone formation, and inferior alveolar canal involvement were mostly observed in clinical Stage 3. Furthermore, a statistically significant correlation between clinical stage and CRIm classification was found (rho = 0.446; p-value < 0.001). Conclusions: The CRIm tends to increase as the clinical stages of MRONJ advance, suggesting a correlation between them. Full article

Background and Objectives: the mandibular foramen is an essential anatomic landmark in performing various dental and surgical procedures, including inferior alveolar nerve block (IANB). However, its position may vary based on the individual morpho-functional features of the skull and face. This study aims to conduct a personalized assessment of the location of the mandibular foramen in various shapes of skulls, faces, and mandibles. Materials and Methods: this anatomic morphometric cross-sectional study was performed using one hundred and six (n = 106) certified human cadaver heads of both sexes. The cranial index (CI) and Izard’s facial index (FI) were calculated, the linear anatomic parameters of the skull and mandible were measured, the location of the mandibular foramen was identified, and the shapes of the skulls and mandibles were determined. Quantitative statistical data were obtained based on the location of the mandibular foramen, considering different shapes of skulls and faces. Results: there is a significant correlation between the location of the mandibular foramen, the high lengthy index (HLI) of the mandible, and the longitudinal latitude index (LLI) of the mandibular process. Conclusions: personalized assessment of the mandibular foramen based on a comprehensive analysis of craniometric characteristics can contribute to preventing unwanted dental and surgical complications, such as inferior alveolar nerve damage. Full article

Background and Clinical Significance: Among the odontogenic tumors, ameloblastoma is one of the most notorious, although it remains relatively rare, accounting for approximately one percent of all oral tumors. This neoplasm, derived from odontogenic epithelium, may arise from the developing enamel organ, epithelial cell rests of dental lamina, epithelial lining of odontogenic cysts, and basal cells of oral epithelium. This is a case presentation of a mural unicystic ameloblastoma, the most aggressive subtype and the one with the highest chance of recurrence. Case Presentation: A patient was referred by his dentist for root canal treatment at the Emergency Dental Clinic of Boston University. The patient complained of mandibular numbness. A panoramic radiograph was acquired, revealing a radiolucent lesion in the right mandible. Clinical examination detected a soft swelling perforating the buccal cortex in the area of #27–#30. A Cone-Beam CT (CBCT) was acquired in the Oral and Maxillofacial Radiology Clinic revealing a well-defined, partially corticated entity in the periapical area of teeth #27 through #30, with evidence of scalloping borders. The internal structure was unilocular and uniformly low-density. The entity caused interruption of the lamina dura of the associated teeth and inferior displacement of the inferior alveolar canal. Differential diagnoses included unicystic ameloblastoma (UA) and central giant cell granuloma as a second less likely diagnosis. An incisional biopsy was performed for further evaluation. Biopsy confirmed UA with mural involvement. Conclusions: UAs typically exhibit less aggressive behavior. However, cases like this one, where mural involvement is noted and no associated impaction is detected, underline the possibility of variable radiographic presentation and the significance of a multidisciplinary approach in correct diagnosis and treatment. Histological subtyping is crucial for guiding treatment. Full article

The inferior alveolar nerve (IAN), contained within the mandibular canal (MC), is a structure prone to damage in clinical and surgical procedures on the mandible. This study aimed to analyze the MC morphology and its anatomical variants in a Chilean subpopulation using cone beam computed tomography (CBCT). In total, 342 images from patients with the following parameters were observed: 120 kV, 9 mA, field of view 12 × 9 MC, and voxel size 0.12 mm. The average length of the MC recorded a mean value of 70.493 ± 4.987 mm on the right side and 70.805 ± 5.177 mm on the left side. The location of the mental foramen (MF) was most frequently found between the mandibular first and second premolar. The greatest bone thickness was found at the level of the basilar border of the 2MPM. The root closest to the MC was distal from the mandibular second molar. The lowest thickness was in the lingual area at 1MM. The prevalence of the anterior loop (AL) (61.5%) and the retromolar canal (RC) (17.5%) showed no significant differences between men and women. The results obtained showed that the morphology of the MC in the Chilean subpopulation can vary. Full article

Objective: This systematic review aims to summarize the evidence on the use and applicability of AI in impacted mandibular third molars. Methods: Searches were performed in the following databases: PubMed, Scopus, and Google Scholar. The study protocol is registered at the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202460081). The retrieved articles were subjected to an exhaustive review based on the inclusion and exclusion criteria for the study. Articles on the use of AI for diagnosis, treatment, and treatment planning in patients with impacted mandibular third molars were included. Results: Twenty-one articles were selected and evaluated using the Scottish Intercollegiate Guidelines Network (SIGN) evidence quality scale. Most of the analyzed studies dealt with using AI to determine the relationship between the mandibular canal and the impacted mandibular third molar. The average quality of the articles included in this review was 2+, which indicated that the level of evidence, according to the SIGN protocol, was B. Conclusions: Compared to human observers, AI models have demonstrated decent performance in determining the morphology, anatomy, and relationship of the impaction with the inferior alveolar nerve canal. However, the prediction of eruptions and future horizons of AI models are still in the early developmental stages. Additional studies estimating the eruption in mixed and permanent dentition are warranted to establish a comprehensive model for identifying, diagnosing, and predicting third molar eruptions and determining the treatment outcomes in the case of impacted teeth. This will help clinicians make better decisions and achieve better treatment outcomes. Full article

Background: This study evaluates the diagnostic accuracy of an AI-assisted tool in assessing the proximity of the mandibular canal (MC) to the root apices (RAs) of mandibular teeth using computed tomography (CT). Methods: This study involved 57 patients aged 18–30 whose CT scans were analyzed by both AI and human experts. The primary aim was to measure the closest distance between the MC and RAs and to assess the AI tool’s diagnostic performance. The results indicated significant variability in RA-MC distances, with third molars showing the smallest mean distances and first molars the greatest. Diagnostic accuracy metrics for the AI tool were assessed at three thresholds (0 mm, 0.5 mm, and 1 mm). Results: The AI demonstrated high specificity but generally low diagnostic accuracy, with the highest metrics at the 0.5 mm threshold with 40.91% sensitivity and 97.06% specificity. Conclusions: This study underscores the limited potential of tested AI programs in reducing iatrogenic damage to the inferior alveolar nerve (IAN) during dental procedures. Significant differences in RA-MC distances between evaluated teeth were found. Full article

Accurate inferior alveolar nerve (IAN) canal segmentation has been considered a crucial task in dentistry. Failing to accurately identify the position of the IAN canal may lead to nerve injury during dental procedures. While IAN canals can be detected from dental cone beam computed tomography, they are usually difficult for dentists to precisely identify as the canals are thin, small, and span across many slices. This paper focuses on improving accuracy in segmenting the IAN canals. By integrating our proposed frequency-domain attention mechanism in UNet, the proposed frequency attention UNet (FAUNet) is able to achieve $75.55\%$ and $81.35\%$ in the Dice and surface Dice coefficients, respectively, which are much higher than other competitive methods, by adding only 224 parameters to the classical UNet. Compared to the classical UNet, our proposed FAUNet achieves a $2.39\%$ and $2.82\%$ gain in the Dice coefficient and the surface Dice coefficient, respectively. The potential advantage of developing attention in the frequency domain is also discussed, which revealed that the frequency-domain attention mechanisms can achieve better performance than their spatial-domain counterparts. Full article

In recent years, there has been a significant increase in collaboration between medical imaging and artificial intelligence technology. The use of automated techniques for detecting medical symptoms has become increasingly prevalent. However, there has been a lack of research on the relationship between impacted teeth and the inferior alveolar nerve (IAN) in DPR images. The severe compression of teeth against the IAN may necessitate the requirement for nerve canal treatment. To reduce the occurrence of such events, this study aims to develop an auxiliary detection system capable of precisely locating the relative positions of the IAN and impacted teeth through object detection and image enhancement. This system is designed to shorten the duration of examinations for dentists while concurrently mitigating the chances of diagnostic errors. The innovations in this research are as follows: (1) using YOLO_v4 to identify impacted teeth and the IAN in DPR images achieves an accuracy of 88%. However, the developed algorithm in this study achieves an accuracy of 93%. (2) Image enhancement is utilized in this study to expand the dataset, with an accuracy of up to 2~3% enhancement in detecting diseases. (3) The segmentation technique proposed in this study surpasses previous methods by achieving 6% higher accuracy in dental diagnosis. Full article

Study Design: Original Article. Objective: The surgical treatment of mandibular fractures has undergone several changes over the past 100 years, since the use of wires and intermaxillary fixation, until today where most of the fractures are treated with internal fixation using plates and screws. For the correct use of this hardware, the surgeon must have adequate knowledge of jaw anatomy to prevent complications during the insertion of screws like in fractures of the mandibular body and angle, when the screws of the plate installed in the compression zone can damage the inferior alveolar nerve within the mandibular canal. Methods: To minimize this complication, 66 hemimandibles of adult patients were analyzed in CT scans and manipulated with Dental Slice^® software, (BioParts^®, Brazil) and measured the shortest distance from the inferior cortex of the mandibular canal to the inferior cortex of the mandibular body during the path of the inferior alveolar nerve, since the mandibular foramen until the mental foramen. Results: The result obtained showed a wide variation of the shortest distance measured (3.52 mm–11.5 mm) with an average of 7.99 mm. Conclusion: The conclusion demonstrated a minimum distance of 3.52 mm below the cortical mandibular canal to the lower border of the mandible and should be considered as a safety margin during the application of fixing the material in the region of the mandibular body. Full article

This retrospective study aims to investigate the impact of cone-beam computed tomography (CBCT) viewing parameters such as contrast, slice thickness, and sharpness on the identification of the inferior alveolar nerve (IAC). A total of 25 CBCT scans, resulting in 50 IACs, were assessed by two investigators using a three-score system (good, average, and poor) on cross-sectional images. Slice thicknesses of 0.25 mm, 0.5 mm, and 1 mm were tested, along with varying sharpness (0, 6, 8, and 10) and contrast (0, 400, 800, and 1200) settings. The results were statistically analyzed to determine the optimal slice thickness for improved visibility of IAC, followed by evaluating the influence of sharpness and contrast using the optimal thickness. The identified parameters were then validated by performing semi-automated segmentation of the IACs and structure overlapping to evaluate the mean distance. Inter-rater and intra-rater reliability were assessed using Kappa statistics, and inferential statistics used Pearson’s Chi-square test. Inter-rater and intra-rater reliability for all parameters were significant, ranging from 69% to 83%. A slice thickness of 0.25 mm showed consistently “good” visibility (80%). Sharpness values of zero and contrast values of 1200 also demonstrated high frequencies of “good” visibility. Overlap analysis resulted in an average mean distance of 0.295 mm and a standard deviation of 0.307 mm across all patients’ sides. The study revealed that a slice thickness of 0.25 mm, zero sharpness value, and higher contrast value of 1200 improved the visibility and accuracy of IAC segmentation in CBCT scans. The individual patient’s characteristics, such as anatomical variations, decreased bone density, and absence of canal walls cortication, should be considered when using these parameters. Full article

The exact knowledge of the mandibular canal position is fundamental in oral surgery and implantology. Clinicians have to be extremely cautious when operating in close proximity to this structure in order to avoid damaging the neurovascular bundle. Several anatomical variations of the mandibular canal have been described in the literature, such as bifid or trifid structures. The use of cone-beam computed tomography (CBCT) offers a detailed representation of the inferior alveolar nerve path, albeit with some difficulties of identification when dental implants or metal prosthesis are present. The aim of this study is to retrospectively evaluate the prevalence and location of bifid/trifid mandibular canals (BMC/TMC) by CBCT in Italian patients. The screening phase involved 584 patients, only 238 enrolled (97 men; 141 women), with an average age of 51 ± 17.20. A total of 36 patients (15.25%) showed at least one bifid mandibular canal; only 2 patients (0.84%) showed a trifid mandibular canal. Overall, 12 patients (5.04%) presented this variation bilaterally. There was no association with the sex of the enrolled sample. In conclusion, the presence of BMCs and TMCs may be considered as a risk factor for the onset of neurovascular complications. Being aware of changes in the mandibular canal helps clinicians to prevent inferior alveolar nerve impairments that may occur during oral surgery and implantology. Full article

Ionizing radiation is necessary for diagnostic imaging and deciding the right radiation dose is extremely critical to obtain a decent quality image. However, increasing the dosage to improve the image quality has risks due to the potential harm from ionizing radiation. Thus, finding the optimal as low as diagnostically acceptable (ALADA) dosage is an open research problem that has yet to be tackled using artificial intelligence (AI) methods. This paper proposes a new multi-balancing 3D convolutional neural network methodology to build 3D multidetector computed tomography (MDCT) datasets and develop a 3D classifier model that can work properly with 3D CT scan images and balance itself over the heavy unbalanced multi-classes. The proposed models were exhaustively investigated through eighteen empirical experiments and three re-runs for clinical expert examination. As a result, it was possible to confirm that the proposed models improved the performance by an accuracy of 5% to 10% when compared to the baseline method. Furthermore, the resulting models were found to be consistent, and thus possibly applicable to different MDCT examinations and reconstruction techniques. The outcome of this paper can help radiologists to predict the suitability of CT dosages across different CT hardware devices and reconstruction algorithms. Moreover, the developed model is suitable for clinical application where the right dose needs to be predicted from numerous MDCT examinations using a certain MDCT device and reconstruction technique. Full article

Introduction: The need of accurate three-dimensional data of anatomical structures is increasing in the surgical field. The development of convolutional neural networks (CNNs) has been helping to fill this gap by trying to provide efficient tools to clinicians. Nonetheless, the lack of a fully accessible datasets and open-source algorithms is slowing the improvements in this field. In this paper, we focus on the fully automatic segmentation of the Inferior Alveolar Canal (IAC), which is of immense interest in the dental and maxillo-facial surgeries. Conventionally, only a bidimensional annotation of the IAC is used in common clinical practice. A reliable convolutional neural network (CNNs) might be timesaving in daily practice and improve the quality of assistance. Materials and methods: Cone Beam Computed Tomography (CBCT) volumes obtained from a single radiological center using the same machine were gathered and annotated. The course of the IAC was annotated on the CBCT volumes. A secondary dataset with sparse annotations and a primary dataset with both dense and sparse annotations were generated. Three separate experiments were conducted in order to evaluate the CNN. The IoU and Dice scores of every experiment were recorded as the primary endpoint, while the time needed to achieve the annotation was assessed as the secondary end-point. Results: A total of 347 CBCT volumes were collected, then divided into primary and secondary datasets. Among the three experiments, an IoU score of 0.64 and a Dice score of 0.79 were obtained thanks to the pre-training of the CNN on the secondary dataset and the creation of a novel deep label propagation model, followed by proper training on the primary dataset. To the best of our knowledge, these results are the best ever published in the segmentation of the IAC. The datasets is publicly available and algorithm is published as open-source software. On average, the CNN could produce a 3D annotation of the IAC in 6.33 s, compared to 87.3 s needed by the radiology technician to produce a bidimensional annotation. Conclusions: To resume, the following achievements have been reached. A new state of the art in terms of Dice score was achieved, overcoming the threshold commonly considered of 0.75 for the use in clinical practice. The CNN could fully automatically produce accurate three-dimensional segmentation of the IAC in a rapid setting, compared to the bidimensional annotations commonly used in the clinical practice and generated in a time-consuming manner. We introduced our innovative deep label propagation method to optimize the performance of the CNN in the segmentation of the IAC. For the first time in this field, the datasets and the source codes used were publicly released, granting reproducibility of the experiments and helping in the improvement of IAC segmentation. Full article