Key insights into antiresorptive drug use and osteonecrosis in osteoporotic patients undergoing tooth extractions: A clinical and CBCT assessment.

This study investigates the effects of antiresorptive drugs and risk factors for medication-related osteonecrosis of the jaws in osteoporotic patients undergoing tooth extraction. Among the findings, antiresorptive-treated patients had thicker lamina dura and longer healing times. Additionally, corticosteroid intake and multi-rooted teeth carried a higher osteonecrosis risk. Bone sequestrum indicated osteonecrosis. PURPOSE: To describe the effects of antiresorptive drugs (ARD) in the maxilla and mandible and risk factors for medication-related osteonecrosis of the jaws (MRONJ) in osteoporotic patients undergoing tooth extractions using clinical data and cone beam computed tomography (CBCT). METHODS: This retrospective cohort study collected clinical and CBCT data from 176 patients. The study group (n = 78; 224 extractions) received ARD treatment, underwent tooth extraction, and had a pre-operative CBCT. Additionally, age-, sex-, and tooth-matched controls were selected (n = 98; 227 extractions). Radiographic examinations were performed independently by three calibrated examiners. Statistical analysis included Chi-square, Fisher's exact, Mann-Whitney U, and t-tests to contrast clinical and radiographic data between study and control, MRONJ + and MRONJ - , and bisphosphonate and denosumab patients/sites. Significance was set at p ≤ 0.05. RESULTS: From the study group, 4 patients (5%) and 5 sites (2%) developed MRONJ after tooth extraction. ARD-treated patients exhibited significantly more thickening of the lamina dura and a longer average mucosal healing time (4.4 weeks) than controls (2.6 weeks). In the study group, MRONJ risk significantly increased with corticosteroid intake and in multi-rooted teeth. No significant differences between bisphosphonates and denosumab use were seen in the tomographic features (p > 0.05). Lastly, bone sequestrum was exclusively observed in osteoporotic patients, who exhibited post-operative exposed bone or histological evidence of osteonecrosis. CONCLUSION: Osteoporotic patients under ARD may exhibit thickening of the lamina dura and prolonged post-operative healing. Among these patients, multi-rooted teeth are at higher risk for MRONJ than single-rooted teeth. Sequester formation is a radiographic indicator of osteonecrosis.

Radiographic diagnosis of periodontal diseases - Current evidence versus innovations.

Accurate diagnosis of periodontal and peri-implant diseases relies significantly on radiographic examination, especially for assessing alveolar bone levels, bone defect morphology, and bone quality. This narrative review aimed to comprehensively outline the current state-of-the-art in radiographic diagnosis of alveolar bone diseases, covering both two-dimensional (2D) and three-dimensional (3D) modalities. Additionally, this review explores recent technological advances in periodontal imaging diagnosis, focusing on their potential integration into clinical practice. Clinical probing and intraoral radiography, while crucial, encounter limitations in effectively assessing complex periodontal bone defects. Recognizing these challenges, 3D imaging modalities, such as cone beam computed tomography (CBCT), have been explored for a more comprehensive understanding of periodontal structures. The significance of the radiographic assessment approach is evidenced by its ability to offer an objective and standardized means of evaluating hard tissues, reducing variability associated with manual clinical measurements and contributing to a more precise diagnosis of periodontal health. However, clinicians should be aware of challenges related to CBCT imaging assessment, including beam-hardening artifacts generated by the high-density materials present in the field of view, which might affect image quality. Integration of digital technologies, such as artificial intelligence-based tools in intraoral radiography software, the enhances the diagnostic process. The overarching recommendation is a judicious combination of CBCT and digital intraoral radiography for enhanced periodontal bone assessment. Therefore, it is crucial for clinicians to weigh the benefits against the risks associated with higher radiation exposure on a case-by-case basis, prioritizing patient safety and treatment outcomes.

Smartphone applications for facial scanning: A technical and scoping review.

INTRODUCTION: Facial scanning through smartphone scanning applications (SSA) is increasingly being used for medical applications as cost-effective, chairside method. However, clinical validation is lacking. This review aims to address: (1) Which SSA could perform facial scanning? (2) Which SSA can be clinically used? (3) Which SSA have been reported and scientifically validated for medical applications? METHODS: Technical search for SSA designed for face or object scanning was conducted on Google, Apple App Store, and Google Play Store from August 2022 to December 2023. Literature search was performed on PubMed, Cochrane, EMBASE, MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, Clinicaltrials.gov, ICTRP (WHO) and preprints up to 2023. Eligibility criteria included English-written scientific articles incorporating at least one SSA for clinical purposes. SSA selection and data extraction were executed by one reviewer, validated by second, with third reviewer being consulted for discordances. RESULTS: Sixty-three applications designed for three-dimensional object scanning were retrieved, with 52 currently offering facial scanning capabilities. Fifty-six scientific articles, comprising two case reports, 16 proof-of-concepts and 38 experimental studies were analysed. Thirteen applications (123D Catch, 3D Creator, Bellus 3D Dental Pro, Bellus 3D Face app, Bellus 3D Face Maker, Capture, Heges, Metascan, Polycam, Scandy Pro, Scaniverse, Tap tap tap and Trnio) were reported in literature for digital workflow integration, comparison or proof-of-concept studies. CONCLUSION: Fifty-two SSA can perform facial scanning currently and can be used clinically, offering cost-effectiveness, portability and user-friendliness. Although clinical validation is crucial, only 13 SSA were scientifically validated, underlying awareness of potential pitfalls and limitations.

Three-dimensional evaluation of secondary alveolar bone grafting in patients with unilateral cleft lip and palate: A 2-3 year post-operative follow-up.

OBJECTIVES: The present study aims to quantitatively assess secondary alveolar bone graft (SABG) resorption in unilateral cleft lip, alveolus and palate (UCLAP) patients in a 2-3 year longitudinal follow-up setting by using a validated 3D protocol. Furthermore, the potential relation of SABG resorption with maxillary canine position and a number of patient-related factors was investigated. METHODS: UCLAP patients who underwent SABG and had good quality CBCT images at the following timepoints were included in the study: pre-operative (T0), immediate (T1), 6 months (T2) and either 1-2 years (T3) or 2-3 years (T4) post-operative. The final bone grafted region was defined on the T1 scans and refined in the registered T0 scans. The bone graft after resorption was determined by applying threshold-based segmentation on the registered T2, T3 or T4 scans within the segmented bone graft volume. The position of the canines was determined at every timepoint at the cleft and non-cleft side. RESULTS: Forty-five UCLAP patients (mean age 9.0 ± 1.3 years) were included. In the first 6 months after SABG, 43.6% bone resorption was recorded. 2-3 years post-operative, 56% bone resorption was found if the maxillary canine was not yet erupted and 42.7% if it erupted through the graft. The vertical position of the canines was significantly higher on the cleft side at T3. CONCLUSIONS: The present study reports significant SABG resorption over time. However, no correlation was found between SABG resorption and canine position, nor between other patient-related factors.

Optimization of orofacial cleft imaging protocols using device-specific low-dose cone-beam computed tomography.

OBJECTIVE: The aim of this study was to present optimized device-specific low-dose cone-beam computed tomography (CBCT) protocols with sufficient image quality for pre-surgical diagnostics and three-dimensional (3D) modelling of cleft defects. METHODS: Six paediatric skulls were acquired, and an artificial bony cleft was created. A high-resolution CBCT scan acted as a reference standard (Accuitomo 170, Morita, Kyoto, Japan) for comparing eight low-dose protocols of Newtom VGi-evo (QR Verona, Cefla, Verona, Italy), which included Eco and Regular protocols with different field of views (FOVs). Delineation of lamina dura, cementoenamel junction (CEJ), trabecular bone and bony bridge were assessed. A 3D model of the defect was also evaluated. RESULT: The dose area product of low-dose protocols ranged from 31 to 254 mGy*cm2. Despite the dose difference of up to eight times between applied protocols, trabecular bone and CEJ exhibited appropriate image quality in all scans. However, Regular small FOV protocols (5 × 5 and 8 × 5 cm2), for both lamina dura and bony bridge, demonstrated a significant improvement in image quality compared to Eco FOV counterparts. Based on 3D defect analysis, no significant difference existed between low-dose protocols and the reference standard. CONCLUSION: The findings highlight the possibility of achieving a considerable reduction (up to eight times) in the radiation dose using low-dose CBCT protocols while maintaining sufficient image quality for assessing anatomical structures and 3D modelling in cleft cases.

Novel AI-based tool for primary tooth segmentation on CBCT using convolutional neural networks: A validation study.

BACKGROUND: Primary teeth segmentation on cone beam computed tomography (CBCT) scans is essential for paediatric treatment planning. Conventional methods, however, are time-consuming and necessitate advanced expertise. AIM: The aim of this study was to validate an artificial intelligence (AI) cloud-based platform for automated segmentation (AS) of primary teeth on CBCT. Its accuracy, time efficiency, and consistency were compared with manual segmentation (MS). DESIGN: A dataset comprising 402 primary teeth (37 CBCT scans) was retrospectively retrieved from two CBCT devices. Primary teeth were manually segmented using a cloud-based platform representing the ground truth, whereas AS was performed on the same platform. To assess the AI tool's performance, voxel- and surface-based metrics were employed to compare MS and AS methods. Additionally, segmentation time was recorded for each method, and intra-class correlation coefficient (ICC) assessed consistency between them. RESULTS: AS revealed high performance in segmenting primary teeth with high accuracy (98 ± 1%) and dice similarity coefficient (DSC; 95 ± 2%). Moreover, it was 35 times faster than the manual approach with an average time of 24 s. Both MS and AS demonstrated excellent consistency (ICC = 0.99 and 1, respectively). CONCLUSION: The platform demonstrated expert-level accuracy, and time-efficient and consistent segmentation of primary teeth on CBCT scans, serving treatment planning in children.

Navigating the complexities and controversies of medication-related osteonecrosis of the jaw (MRONJ): a critical update and consensus statement.

OBJECTIVES: To provide a critical update identifying the knowledge gaps and controversies in medication-related osteonecrosis of the jaw (MRONJ) within the Belgian healthcare context and outline opportunities for improvement and research in these areas. METHODS: A literature review was performed to identify guidelines from international clinical societies in oncology or oral and maxillofacial surgery on diagnosing, preventing, and treating MRONJ. The recommendations were critically assessed in light of recent developments in the field and confronted with the clinical experience of experts. RESULTS: Despite progress in the diagnostic criteria of MRONJ, the continued need for an 8-week timeout period should be reconsidered. Furthermore, 3D imaging techniques should be introduced to improve diagnosis and staging. The staging system remains ambiguous regarding Stage 0 MRONJ, and ongoing confusion exists regarding the term non-exposed MRONJ. The prevention of MRONJ should be tailored, considering the individual patient's risk of MRONJ, frailty, and life expectancy. More research seems needed into the efficacy and safety of drug holidays, considering the risks of rebound remodeling on fractures. With renewed interest in surgical and adjunct management techniques, adequately designed clinical studies are needed to help translate trial outcomes into universally applicable treatment guidelines taking into account individual patient characteristics. CONCLUSIONS: Important knowledge gaps remain and hamper the development of clinical guidelines. Several controversies were identified where consensus is lacking, and further harmonization between stakeholders is necessary. Finally, the need for randomized controlled comparative clinical trials in MRONJ resonates harder than ever to identify the best treatment for individual patients.

Validation and comparison of 2D grading scales and 3D volumetric measurements for outcome assessment of bone-grafted alveolar clefts in children.

BACKGROUND: Several methods have been proposed to assess outcome of bone-grafted alveolar clefts on cone beam computed tomography (CBCT), but so far these methods have not been compared and clinically validated. OBJECTIVES: To validate and compare methods for outcome assessment of bone-grafted clefts with CBCT and provide recommendations for follow-up. METHODS: In this observational follow-up study, two grading scales (Suomalainen; Liu) and the volumetric bone fill (BF) were used to assess the outcome of 23 autogenous bone-grafted unilateral alveolar clefts. The mean age at bone grafting was 9 years. The volumetric BF was assessed in five vertical sections. The bone-grafted cleft outcome was based on a binary coding (success or regraft) on a clinical multidisciplinary expert consensus meeting. Grading scales and volumetric assessment were compared in relation to the bone-grafted cleft outcome (success or regraft). Reliability for the different outcome variables was analyzed with intra-class correlation and by calculating kappa values. LIMITATIONS: The study had a limited sample size. Clinical CBCT acquisitions had a varying tube current and exposure time. RESULTS: Volumetric 3D measurements allowed for outcome assessment of bone-grafted alveolar clefts with high reliability and validity. The two grading scales showed highly reliable outcomes, yet the validity was high for the Suomalainen grading scale but low for the Liu grading scale. CONCLUSIONS: Volumetric 3D measurement as well as the Suomalainen grading can be recommended for outcome assessment of the bone-grafted cleft. Yet, one must always make a patient-specific assessment if there is a need to regraft.

Can artificial intelligence-driven cephalometric analysis replace manual tracing? A systematic review and meta-analysis.

OBJECTIVES: This systematic review and meta-analysis aimed to investigate the accuracy and efficiency of artificial intelligence (AI)-driven automated landmark detection for cephalometric analysis on two-dimensional (2D) lateral cephalograms and three-dimensional (3D) cone-beam computed tomographic (CBCT) images. SEARCH METHODS: An electronic search was conducted in the following databases: PubMed, Web of Science, Embase, and grey literature with search timeline extending up to January 2024. SELECTION CRITERIA: Studies that employed AI for 2D or 3D cephalometric landmark detection were included. DATA COLLECTION AND ANALYSIS: The selection of studies, data extraction, and quality assessment of the included studies were performed independently by two reviewers. The risk of bias was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A meta-analysis was conducted to evaluate the accuracy of the 2D landmarks identification based on both mean radial error and standard error. RESULTS: Following the removal of duplicates, title and abstract screening, and full-text reading, 34 publications were selected. Amongst these, 27 studies evaluated the accuracy of AI-driven automated landmarking on 2D lateral cephalograms, while 7 studies involved 3D-CBCT images. A meta-analysis, based on the success detection rate of landmark placement on 2D images, revealed that the error was below the clinically acceptable threshold of 2 mm (1.39 mm; 95% confidence interval: 0.85-1.92 mm). For 3D images, meta-analysis could not be conducted due to significant heterogeneity amongst the study designs. However, qualitative synthesis indicated that the mean error of landmark detection on 3D images ranged from 1.0 to 5.8 mm. Both automated 2D and 3D landmarking proved to be time-efficient, taking less than 1 min. Most studies exhibited a high risk of bias in data selection (n = 27) and reference standard (n = 29). CONCLUSION: The performance of AI-driven cephalometric landmark detection on both 2D cephalograms and 3D-CBCT images showed potential in terms of accuracy and time efficiency. However, the generalizability and robustness of these AI systems could benefit from further improvement. REGISTRATION: PROSPERO: CRD42022328800.

Tissue-engineered bone construct promotes early osseointegration of implants with low primary stability in oversized osteotomy.

OBJECTIVES: To evaluate the histological parameters and bone mechanical properties around implants with low primary stability (PS) in grafted bone substitutes within an oversized osteotomy. MATERIALS AND METHODS: An oversized osteotomy penetrating the double cortical bone layers was made on both femora of 24 New Zealand white rabbits. Bilaterally in the femur of all animals, 48 implants were installed, subdivided into four groups, corresponding to four prepared tissue-engineering bone complexes (TEBCs), which were placed between the implant surface and native bone wall: A: tricalcium phosphate ß (TCP-ß); B: autologous adipose derived-stem cells with TCP-ß (ASCs/TCP-ß); C: ASCs transfected with the enhanced-GFP gene with TCP-ß (EGFP-ASCs/TCP-ß); D: ASCs transfected with the BMP-2 gene with TCP-ß (BMP2-ASCs/TCP-ß). Trichrome fluorescent labeling was conducted. Animals were sacrificed after eight weeks. The trichromatic fluorescent labeling (%TFL), area of new bone (%NB), residual material (%RM), bone-implant contact (%BIC), and the removal torque force (RTF, N/cm) were assessed. RESULTS: ASCs were successfully isolated from adipose tissue, and the primary ASCs were induced into osteogenic, chondrogenic, and adipogenic differentiation. The BMP-2 overexpression of ASCs sustained for ten days and greatly enhanced the expression of osteopontin (OPN). At eight weeks post-implantation, increased %NB and RTF were found in all groups. The most significant value of %TFL, %BIC and lowest %RM was detected in group D. CONCLUSION: The low PS implants osseointegrate with considerable new bone in grafted TEBCs within an oversized osteotomy. Applying BMP-2 overexpressing ASCs-based TEBC promoted earlier osseointegration and more solid bone mechanical properties on low PS implants. Bone graft offers a wedging effect for the implant with low PS at placement and promotes osteogenesis on their surface in the healing period.

3D CRANI, a novel MR neurography sequence, can reliable visualise the extraforaminal cranial and occipital nerves.

OBJECTIVES: We aim to validate 3D CRANI, a novel high-field STIR TSE, MR neurography sequence in the visualisation of the extraforaminal cranial and occipital nerve branches on a 3-T system. Furthermore, we wish to evaluate the role of gadolinium administration and calculate nerve benchmark values for future reference. METHODS: Eleven consecutive patients underwent MR imaging including the 3D CRANI sequence before and immediately after intravenous gadolinium administration. Two observers rated suppression quality and nerve visualisation using Likert scales before and after contrast administration. Extraforaminal cranial and occipital nerves were assessed. Nerve calibers and signal intensities were measured at predefined anatomical landmarks, and apparent signal intensity ratios were calculated. RESULTS: The assessed segments of the cranial and occipital nerves could be identified in most cases. The overall intrarater agreement was 79.2% and interrater agreement was 82.7% (intrarater κ = .561, p < .0001; interrater κ = .642, p < .0001). After contrast administration, this significantly improved to an intrarater agreement of 92.7% and interrater agreement of 93.6% (intrarater κ = .688, p < .0001; interrater κ = .727, p < .0001). Contrast administration improved suppression quality and significant changes in nerve caliber and signal intensity measurements. Nerve diameter and signal intensity benchmarking values were obtained. CONCLUSION: 3D CRANI is reliable for the visualization of the extraforaminal cranial and occipital nerves. Intravenous gadolinium significantly improves MR neurography when applying this sequence. Benchmarking data are published to allow future assessment of the 3D CRANI sequence in patients with pathology of the extraforaminal cranial and occipital nerves. KEY POINTS: • MR neurography using the 3D CRANI sequence is a reliable method to evaluate the extraforaminal cranial and occipital nerves. • Gadolinium contrast administration significantly improves suppression quality and nerve visualisation. • Benchmarking values including apparent signal intensity ratios and nerve calibers depend on contrast administration and might play an important role in future studies evaluating extraforaminal cranial and occipital neuropathies.

Accuracy of MR neurography as a diagnostic tool in detecting injuries to the lingual and inferior alveolar nerve in patients with iatrogenic post-traumatic trigeminal neuropathy.

OBJECTIVES: MR neurography has the ability to detect and depict peripheral nerve injuries. This study evaluated the potential of MR neurography in the diagnosis of post-traumatic trigeminal neuropathy. METHODS: Forty-one participants prospectively underwent MR neurography of the lingual and inferior alveolar nerves using a 3D TSE STIR black-blood sequence. Two blinded and independent observers recorded the following information for each nerve of interest: presence of injury, nerve thickness, nerve signal intensity, MR neurography Sunderland class, and signal gap. Afterwards, the apparent nerve-muscle contrast-to-noise ratio and apparent signal-to-noise ratio were calculated. Clinical data (neurosensory testing score and clinical Sunderland class) was extracted retrospectively from the medical records of patients diagnosed with post-traumatic trigeminal neuropathy. RESULTS: Compared to neurosensory testing, MR neurography had a sensitivity of 38.2% and specificity of 93.5% detecting nerve injuries. When differentiated according to clinical Sunderland class, sensitivity was 19.1% in the presence of a low class injury (I to III) and improved to 83.3% in the presence of a high class (IV to V). Specificity remained unchanged. The area under the curve using the apparent nerve-muscle contrast-to-noise ratio, apparent signal-to-noise ratio, and nerve thickness to predict the presence of an injury was 0.78 (p < .05). Signal intensities and nerve diameter increased in injured nerves (p < .05). Clinical and MR neurography Sunderland scores positively correlated (correlation coefficient = 0.53; p = .005). CONCLUSIONS: This study shows that MR neurography can accurately differentiate between injured and healthy nerves, especially in the presence of a more severe nerve injury. CLINICAL RELEVANCE STATEMENT: MR neurography is not only able to detect trigeminal nerve injuries, but it can also provide information about the anatomical specifications of the injury, which is not possible with clinical neurosensory testing. This makes MR neurography an added value in the management of post-traumatic trigeminal neuropathy. KEY POINTS: • The current diagnosis of post-traumatic trigeminal neuropathy is mainly based on clinical examination. • MR neurography is able to visualize and stratify peripheral trigeminal nerve injuries. • MR neurography contributes to the diagnostic process as well as to further decision-making.

Radiographic perception of anatomical structures and bony changes in oncologic patients under antiresorptive therapy.

PURPOSE: To assess radiographic presentation of anatomical structures, bony changes and soft tissue calcifications on panoramic radiographs of oncologic patients under high dose antiresorptive drug therapy (ART) before exposure to dental extraction. METHODS: Panoramic radiographs of 57 patients under ART, taken previously to tooth extraction, and 57 control patients were evaluated by two oral radiologists regarding bone pattern, anatomical structures visibility, estimation of cortical width, mandibular cortical index (MCI), and presence of soft tissue calcifications. Parameters were compared between ART and age- and gender-matched healthy control groups. Bone patterns were further assessed by regions with or without tooth extractions and according to uneventful healing or MRONJ development. All comparisons were made using chi-square test with significance level set at 5%. RESULTS: Mandible and posterior maxilla presented more sclerotic bone patterns in patients under ART, regardless of tooth extraction and MRONJ development status (p < 0.05). Heterogeneous bone pattern was identified in two regions that both were subsequently affected by MRONJ. Anatomical structure visibility and presence of soft tissue calcifications was not different among groups (p > 0.05). ART patients showed significantly more C0 (thickening) and C1 MCI (p < 0.05). CONCLUSION: Sclerotic bone pattern and thicker mandibular cortices may represent a consequence of ART rather than MRONJ specific findings. Prospective studies on larger patient samples radiographically followed-up during the ART treatment are advised, with specific attention to heterogenous trabecular bone pattern as a possible MRONJ predictor.

Individual "alveolar phenotype" limits dimensions of lateral bone augmentation.

AIM: Alveolar ridge resorption following tooth extraction often renders a lateral bone augmentation inevitable. Some patients, however, suffer from severe early (during graft healing, Eres ) and/or late (during follow-up, Lres ) graft resorption. We explored the hypothesis that the "individual phenotypic dimensions" may partially explain the degree of such resorptions. MATERIALS AND METHODS: Patients who underwent a guided bone regeneration (GBR) procedure were screened for inclusion according to the following criteria: (1) a relatively symmetrical maxillary arch; (2) an intact contra-lateral alveolar bone dimension; (3) the availability of a pre-operative cone-beam CT (CBCT); (4) a CBCT taken immediately after GBR, and (5) at least one CBCT scan ≥6 months after surgery. CBCT scans from different timepoints were registered and imported into the Mimics software (Materialise, Leuven, Belgium). Bone dimensions of the contra-lateral site of the augmentation, representing the "individual phenotypical dimension (IPD) of the alveolar crest", were superimposed on the augmented site and registered accordingly. As such, Eres and Lres could be measured over time, in relation to the IPD (in two dimensions; per millimetre apically from the alveolar crest, in the centre of the GBR), as well as in three dimensions (the entire GBR, 2 mm away from the mesial, distal, and apical border for standardization). RESULTS: A total of 17 patients (23 augmented sites) were included. After Eres , the outline of the augmentation was in general located ±1 mm outside the IPD, but ≥1.5 years after GBR, it further moved towards the IPD (85% within 0.5 mm distance). CONCLUSIONS: Within the limitations of this study, the results indicate that the dimensions of a lateral bone augmentation are defined by the "individual phenotypic bone boundaries" of the patient.

Retrospective cohort assessment of survival and complications of zygomatic implants in atrophic maxillae.

OBJECTIVES: To report on zygomatic implant (ZI) survival rate and associated complications through a longitudinal retrospective cohort assessment. MATERIAL AND METHODS: A total of 940 ZIs (rough: 781, machined: 159; immediate loading: 454, delayed loading: 486) and 451 standard implants (rough: 195, machined: 256; immediate loading: 58, delayed loading: 393) were placed in 302 adult patients with atrophic maxilla from December 1998 till September 2020. Following data collection reported complications were grouped based on their origin as infectious/ non-infectious biological and mechanical. Statistical analysis was performed to identify risk factors and preceding complications leading to implant loss (P < 0.05). RESULTS: The survival rate of ZI was found to be 89.9% and the average time between implant placement and an eventual loss was 4.8 years. The mean ZI follow-up period was 7.9 ± 4.9 years. Amongst the infectious biological complications, sinusitis was the most reported (n = 138) occurring at a mean follow-up time-point of 4.5 years, whereas infraorbital nerve hypoesthesia occurred more frequently in the non-infectious biological category (n = 8, meantime: 0.3 years). The prosthetic screw fracture was the most reported complication of mechanical origin (n = 29, meantime: 4 years). Furthermore, sinusitis, standard implant loss, zygomatic/peri-zygomatic region infection, and oroantral communication were significantly associated with ZI loss. CONCLUSIONS: ZI placement offered a high survival rate for the rehabilitation of severely atrophied maxilla with most losses occurring within the first 5 years at follow-up. The most frequently observed complication was sinusitis which tends to develop several years following implant placement.

Non-invasive oral implant position assessment: An ex vivo study using a 3D industrial scan as the reference model to mimic the clinical situation.

AIM: To introduce an objective method to evaluate the accuracy of implant position assessment in partially edentulous patients by comparing different techniques (conventional impression, intraoral scan, CBCT) to a reference 3D model obtained with an industrial scanner, the latter mimicking the clinical situation. MATERIALS AND METHODS: Twenty-nine implants were placed in four human cadaver heads using a fully guided flapless protocol. Implant position was assessed using (a) a conventional impression, (b) an intraoral scan, and (c) CBCT and compared to an industrial scan. Three-dimensional models of intraoral scan body and implant were registered to the arch models and the deviation at implant shoulder, apex, and the angle of deviation were compared to each other as well as to the reference model. RESULTS: The three assessment techniques showed statistically significant deviations (p < .01) from the industrial scan, for all measurements, with no difference between the techniques. The maximum deviation at the implant shoulder was 0.16 mm. At the implant apex this increased to 0.38 mm. The intraoral scan deviated significantly more than the CBCT (0.12 mm, p < .01) and the conventional impression (0.10 mm, p = .02). The maximum implant angle deviation was 1.0°. The intraoral scan deviated more than the conventional impression (0.3°, p = .02). CONCLUSION: All assessment techniques deviated from the reference industrial scan, but the differences were relatively small. Intraoral scans were slightly less accurate than both conventional impressions and CBCT. Depending on the application, however, this inaccuracy may not be clinically relevant.

Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.

OBJECTIVES: To develop and assess the performance of a novel artificial intelligence (AI)-driven convolutional neural network (CNN)-based tool for automated three-dimensional (3D) maxillary alveolar bone segmentation on cone-beam computed tomography (CBCT) images. MATERIALS AND METHODS: A total of 141 CBCT scans were collected for performing training (n = 99), validation (n = 12), and testing (n = 30) of the CNN model for automated segmentation of the maxillary alveolar bone and its crestal contour. Following automated segmentation, the 3D models with under- or overestimated segmentations were refined by an expert for generating a refined-AI (R-AI) segmentation. The overall performance of CNN model was assessed. Also, 30% of the testing sample was randomly selected and manually segmented to compare the accuracy of AI and manual segmentation. Additionally, the time required to generate a 3D model was recorded in seconds (s). RESULTS: The accuracy metrics of automated segmentation showed an excellent range of values for all accuracy metrics. However, the manual method (95% HD: 0.20 ± 0.05 mm; IoU: 95% ± 3.0; DSC: 97% ± 2.0) showed slightly better performance than the AI segmentation (95% HD: 0.27 ± 0.03 mm; IoU: 92% ± 1.0; DSC: 96% ± 1.0). There was a statistically significant difference of the time-consumed among the segmentation methods (p < .001). The AI-driven segmentation (51.5 ± 10.9 s) was 116 times faster than the manual segmentation (5973.3 ± 623.6 s). The R-AI method showed intermediate time-consumed (1666.7 ± 588.5 s). CONCLUSION: Although the manual segmentation showed slightly better performance, the novel CNN-based tool also provided a highly accurate segmentation of the maxillary alveolar bone and its crestal contour consuming 116 times less than the manual approach.

Local radiographic risk factors for MRONJ in osteoporotic patients undergoing tooth extraction.

OBJECTIVE: To identify local radiographic risk factors for Medication-Related Osteonecrosis of the Jaws (MRONJ) in osteoporotic patients treated with antiresorptive drugs (ARD) and undergoing tooth extraction. MATERIAL AND METHODS: Patients were included in this retrospective, longitudinal, case-control study, if having at least one administration of ARD, underwent tooth extraction(s), and had pre- and post-operative panoramic radiographs. Additionally, a matched control group was selected. Three calibrated, blinded, and independent observers assessed each tooth extraction site. Statistical analysis compared control against study group, and within the latter, sites MRONJ+ and MRONJ-. RESULTS: In total, 120 patients (99 females/21 males) with 354 tooth extractions were included, from which nine patients (7.5%) and eleven tooth extraction sites (3.1%) developed MRONJ. When comparing control with study group, the latter showed significantly more thickened lamina dura, persistence of the alveolar socket, heterogeneous bone patterns, and sequestrum formation. In the study group, MRONJ developed significantly more in males (19%, p = 0.049), smokers (25%, p = 0.008), in the mandible (82%, p = 0.027), when identifying a radiolucent or sclerotic trabecular pattern (p = 0.004) or when extracting teeth with furcation involvement (p < 0.001), root remnants (p = 0.017), or unrestored caries lesions (p = 0.005). CONCLUSIONS: Tooth extraction sites showing radiographic signs of chronic dental infection are prone to MRONJ.

Synergy between artificial intelligence and precision medicine for computer-assisted oral and maxillofacial surgical planning.

OBJECTIVES: The aim of this review was to investigate the application of artificial intelligence (AI) in maxillofacial computer-assisted surgical planning (CASP) workflows with the discussion of limitations and possible future directions. MATERIALS AND METHODS: An in-depth search of the literature was undertaken to review articles concerned with the application of AI for segmentation, multimodal image registration, virtual surgical planning (VSP), and three-dimensional (3D) printing steps of the maxillofacial CASP workflows. RESULTS: The existing AI models were trained to address individual steps of CASP, and no single intelligent workflow was found encompassing all steps of the planning process. Segmentation of dentomaxillofacial tissue from computed tomography (CT)/cone-beam CT imaging was the most commonly explored area which could be applicable in a clinical setting. Nevertheless, a lack of generalizability was the main issue, as the majority of models were trained with the data derived from a single device and imaging protocol which might not offer similar performance when considering other devices. In relation to registration, VSP and 3D printing, the presence of inadequate heterogeneous data limits the automatization of these tasks. CONCLUSION: The synergy between AI and CASP workflows has the potential to improve the planning precision and efficacy. However, there is a need for future studies with big data before the emergent technology finds application in a real clinical setting. CLINICAL RELEVANCE: The implementation of AI models in maxillofacial CASP workflows could minimize a surgeon's workload and increase efficiency and consistency of the planning process, meanwhile enhancing the patient-specific predictability.

Three-dimensional maxillary virtual patient creation by convolutional neural network-based segmentation on cone-beam computed tomography images.

OBJECTIVE: To qualitatively and quantitatively assess integrated segmentation of three convolutional neural network (CNN) models for the creation of a maxillary virtual patient (MVP) from cone-beam computed tomography (CBCT) images. MATERIALS AND METHODS: A dataset of 40 CBCT scans acquired with different scanning parameters was selected. Three previously validated individual CNN models were integrated to achieve a combined segmentation of maxillary complex, maxillary sinuses, and upper dentition. Two experts performed a qualitative assessment, scoring-integrated segmentations from 0 to 10 based on the number of required refinements. Furthermore, experts executed refinements, allowing performance comparison between integrated automated segmentation (AS) and refined segmentation (RS) models. Inter-observer consistency of the refinements and the time needed to create a full-resolution automatic segmentation were calculated. RESULTS: From the dataset, 85% scored 7-10, and 15% were within 3-6. The average time required for automated segmentation was 1.7 min. Performance metrics indicated an excellent overlap between automatic and refined segmentation with a dice similarity coefficient (DSC) of 99.3%. High inter-observer consistency of refinements was observed, with a 95% Hausdorff distance (HD) of 0.045 mm. CONCLUSION: The integrated CNN models proved to be fast, accurate, and consistent along with a strong interobserver consistency in creating the MVP. CLINICAL RELEVANCE: The automated segmentation of these structures simultaneously could act as a valuable tool in clinical orthodontics, implant rehabilitation, and any oral or maxillofacial surgical procedures, where visualization of MVP and its relationship with surrounding structures is a necessity for reaching an accurate diagnosis and patient-specific treatment planning.