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Calcium phosphate cements, primarily brushite cements, require the addition of setting retarders to ensure adequate processing time and processability. So far, citric acid has been the primary setting retarder used in this context. Due to the poor biocompatibility, it is crucial to explore alternative options for better processing. In recent years, the setting retarder phytic acid (IP6) has been increasingly investigated. This study investigates the biological behaviour of calcium phosphate cements with varying concentrations of IP6, in addition to their physical properties. Therefore cytocompatibility in vitro testing was performed using osteoblastic (MG-63) and osteoclastic (RAW 264.7 differentiated with RANKL) cells. We could demonstrate that the physical properties like the compressive strength of specimens formed with IP6 (brushite_IP6_5 = 11.2 MPa) were improved compared to the reference (brushite = 9.8 MPa). In osteoblast and osteoclast assays, IP6 exhibited significantly better cytocompatibility in terms of cell activity and cell number for brushite cements up to 11 times compared to the brushite reference. In contrast, the calcium-deficient hydroxyapatite (CDHA) cements produced similar results for IP6 (CDHA_IP6_0.25 = 27.0 MPa) when compared to their reference (CDHA = 21.2 MPa). Interestingly, lower doses of IP6 were found to be more effective than higher doses with up to 3 times higher. Additionally, IP6 significantly increased degradation in both passive and active resorption. For these reasons, IP6 is emerging as a strong new competitor to established setting retarders such as citric acid. These cements have potential applications in bone augmentation, the stabilisation of non-load bearing fractures (craniofacial), or the cementation of metal implants.
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Cementos para Huesos , Fosfatos de Calcio , Ensayo de Materiales , Osteoblastos , Osteoclastos , Ácido Fítico , Ácido Fítico/química , Animales , Fosfatos de Calcio/química , Ratones , Cementos para Huesos/química , Osteoblastos/efectos de los fármacos , Osteoblastos/citología , Células RAW 264.7 , Humanos , Osteoclastos/efectos de los fármacos , Fuerza Compresiva , Materiales Biocompatibles/química , Durapatita/químicaRESUMEN
In this study, we aimed to develop a novel prognostic algorithm for oral squamous cell carcinoma (OSCC) using a combination of pathogenomics and AI-based techniques. We collected comprehensive clinical, genomic, and pathology data from a cohort of OSCC patients in the TCGA dataset and used machine learning and deep learning algorithms to identify relevant features that are predictive of survival outcomes. Our analyses included 406 OSCC patients. Initial analyses involved gene expression analyses, principal component analyses, gene enrichment analyses, and feature importance analyses. These insights were foundational for subsequent model development. Furthermore, we applied five machine learning/deep learning algorithms (Random Survival Forest, Gradient Boosting Survival Analysis, Cox PH, Fast Survival SVM, and DeepSurv) for survival prediction. Our initial analyses revealed relevant gene expression variations and biological pathways, laying the groundwork for robust feature selection in model building. The results showed that the multimodal model outperformed the unimodal models across all methods, with c-index values of 0.722 for RSF, 0.633 for GBSA, 0.625 for FastSVM, 0.633 for CoxPH, and 0.515 for DeepSurv. When considering only important features, the multimodal model continued to outperform the unimodal models, with c-index values of 0.834 for RSF, 0.747 for GBSA, 0.718 for FastSVM, 0.742 for CoxPH, and 0.635 for DeepSurv. Our results demonstrate the potential of pathogenomics and AI-based techniques in improving the accuracy of prognostic prediction in OSCC, which may ultimately aid in the development of personalized treatment strategies for patients with this devastating disease.
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Carcinoma de Células Escamosas , Neoplasias de Cabeza y Cuello , Neoplasias de la Boca , Humanos , Carcinoma de Células Escamosas/genética , Carcinoma de Células Escamosas de Cabeza y Cuello/genética , Inteligencia Artificial , Neoplasias de la Boca/genéticaRESUMEN
BACKGROUND: This study investigated whether patient-specific condylar positioning devices (CPDs) are beneficial compared to the conventional manual positioning of the condyles. METHODS: In this prospective, randomized trial, patients undergoing orthognathic surgery with a bilateral sagittal split osteotomy of the mandible were included. The ascending ramus was positioned with computer-aided designed and computer-aided manufactured (CAD/CAM) patient-specific devices in the CPD group and manually in the control group. Postoperatively, cone-beam computed tomography (CBCT) was performed to align the virtually planned position with the postoperative result. RESULTS: Thirty patients were enrolled in the study, with 14 randomized to the CPD group and 16 to the control group. In the CPD group, the ascending ramus differed in the postoperative CBCT scan from the virtually planned position by 0.8 mm in the left/right, 0.8 mm in the front/back, and 1.3 mm in the cranial/caudal direction. The corresponding control-group values were 1.1 mm, 1.3 mm, and 1.6 mm. CPD and controls differed significantly for the left/right movement of the rami (p = 0.04) but not for the other directions or rotations (p > 0.05). CONCLUSIONS: The results demonstrate that both methods are accurate, and postoperative results matched the virtually planned position precisely. It can be assumed that the described CPDs are beneficial when a condylar position different from the preoperative is desired.
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OBJECTIVES: Recent research has demonstrated that platelet-rich fibrin (PRF) is an appropriate carrier for ampicillin/sulbactam. The aim of the study was to investigate whether PRF is also a suitable bio-carrier for clindamycin (CLI). METHODS: PRF membranes were produced from 36 patients receiving intravenous therapy with CLI (e.g. due to the diagnosis of an osteonecrosis of the jaw or infections). Concentrations of CLI in PRF membranes were measured with liquid chromatography-tandem mass spectrometry, and the antimicrobial effects were investigated in vitro in agar diffusion tests with fresh PRF and PRF stored for 24 h. Storage was performed in an incubator at 36 °C to simulate the in-vivo situation. RESULTS: The mean concentration of CLI in plasma was 1.0 ± 0.3 µg/100 mg plasma; in resulting PRF membranes 0.7 ± 0.4 µg/100 mg PRF. Agar diffusion tests were performed with Staphylococcus aureus, Streptococcus pneumoniae, Streptococcus mitis, Porphyromonas gingivalis, and Fusobacterium nucleatum. Mean inhibition zones, in mm, for fresh PRF were 17.3, 12.2, 18.8, 17.1, 25.8 and 18.1, 12.7, 19.2, 17.3, and 26.3 for stored PRF, respectively. CONCLUSION: The results demonstrate that PRF is a suitable bio-carrier for CLI when administered systemically to patients. The concentration in PRF generated from patients after infusion of 600 mg CLI dose suffices to target clinically relevant bacteria. CLINICAL RELEVANCE: Using PRF as a carrier for local antibiotic application can prevent infections in oral and maxillofacial surgery. Within the study limitations, the findings could expand the scope of PRF application by adding CLI as a new antibiotic to the spectrum of PRF therapy.
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Fibrina Rica en Plaquetas , Humanos , Clindamicina/farmacología , Agar , Antibacterianos/farmacología , Staphylococcus aureusRESUMEN
The aim of this study was to investigate the jawbone concentration of clindamycin (CLI) in patients with an osteonecrosis of the jaw (ONJ). Patients with medication-related ONJ (MRONJ) and osteoradionecrosis (ORN) with an antibiotic treatment with CLI were included. Plasma, vital and necrotic bone samples were collected. Plasma and jawbone samples were analyzed by liquid chromatography-tandem mass spectrometry. Patients with MRONJ exhibited a mean plasma CLI concentration of 9.6 µg/mL (SD ± 3.6 µg/mL) and mean concentrations of 2.3 µg/g CLI (SD ± 1.4 µg/g) and 2.1 µg/g CLI (SD ± 2.4 µg/g) in vital and necrotic bone samples, without statistical significance (p = 0.79). In patients with ORN, mean concentration in plasma was 12.0 µg/mL (SD ± 2.6 µg/mL), in vital bone 2.1 µg/g (SD ± 1.5 µg/g), and in necrotic bone 1.7 µg/g (SD ± 1.2 µg/g). Vital and necrotic bone concentrations did not differ significantly (p = 0.88). The results demonstrate that CLI concentrations are considerably lower than in plasma, but sufficient for most bacteria present in ONJ. Within the limitations of the study, it seems that CLI is a relevant alternative to other antibiotics in the treatment of ONJ because it reaches adequate concentrations in jawbone.
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Osteonecrosis de los Maxilares Asociada a Difosfonatos , Conservadores de la Densidad Ósea , Osteonecrosis , Osteorradionecrosis , Humanos , Clindamicina/uso terapéutico , Estudios Prospectivos , Osteonecrosis/inducido químicamente , Osteorradionecrosis/etiología , Maxilares , Osteonecrosis de los Maxilares Asociada a Difosfonatos/etiología , DifosfonatosRESUMEN
INTRODUCTION: The aim of the study was to investigate the impact of different aminopenicillin administration routes on the antimicrobial effects of platelet-rich fibrin (PRF). METHODS: We enrolled patients undergoing treatment with amoxicillin/clavulanic acid (AMC) orally or ampicillin/sulbactam (SAM) intravenously. AMC was applied in a single oral dose (875/125 mg), or in a double oral dose (1750/250 mg), and SAM in a dose of 2000/1000 mg. Blood was obtained one hour after the intake of AMC or 15 min after the infusion of SAM ended. Antimicrobial effects were investigated in agar diffusion tests with fresh PRF, PRF stored for 24, and PRF stored for 48 h. Agar diffusion tests were performed with Escherichia coli, Staphylococcus aureus, Streptococcus pneumoniae, Haemophilus influenzae, and Porphyromonas gingivalis. Inhibition zones (IZs) around a 6 mm PRF disc were measured after 24 h. RESULTS: IZs for fresh PRF and the single oral dose of AMC were 0.0, 4.7, 15.2, 2.3, and 0.9 mm (E. coli, S. aureus, S. pneumoniae, H. influenzae, and P. gingivalis, respectively). For the double oral dose, these values were 0.0, 11.4, 20.0, 8.1, and 7.4 mm. IZs for SAM were 11.9, 18.2, 24.7, 20.3, and 22.1 mm. Differences between parenteral and oral application as well as between different oral doses were significant (p<0.0001, one-way ANOVA). DISCUSSION: The results of our study demonstrate that oral administration is a suitable route to load PRF with these drugs. This could expand the scope of PRF application to prevent infections at the surgical site, especially in an outpatient setting in which drugs are normally applied orally.
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Background: Medical resource management can be improved by assessing the likelihood of prolonged length of stay (LOS) for head and neck cancer surgery patients. The objective of this study was to develop predictive models that could be used to determine whether a patient's LOS after cancer surgery falls within the normal range of the cohort. Methods: We conducted a retrospective analysis of a dataset consisting of 300 consecutive patients who underwent head and neck cancer surgery between 2017 and 2022 at a single university medical center. Prolonged LOS was defined as LOS exceeding the 75th percentile of the cohort. Feature importance analysis was performed to evaluate the most important predictors for prolonged LOS. We then constructed 7 machine learning and deep learning algorithms for the prediction modeling of prolonged LOS. Results: The algorithms reached accuracy values of 75.40 (radial basis function neural network) to 97.92 (Random Trees) for the training set and 64.90 (multilayer perceptron neural network) to 84.14 (Random Trees) for the testing set. The leading parameters predicting prolonged LOS were operation time, ischemia time, the graft used, the ASA score, the intensive care stay, and the pathological stages. The results revealed that patients who had a higher number of harvested lymph nodes (LN) had a lower probability of recurrence but also a greater LOS. However, patients with prolonged LOS were also at greater risk of recurrence, particularly when fewer (LN) were extracted. Further, LOS was more strongly correlated with the overall number of extracted lymph nodes than with the number of positive lymph nodes or the ratio of positive to overall extracted lymph nodes, indicating that particularly unnecessary lymph node extraction might be associated with prolonged LOS. Conclusions: The results emphasize the need for a closer follow-up of patients who experience prolonged LOS. Prospective trials are warranted to validate the present results.
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Background: The development of artificial intelligence (AI)-based algorithms and advances in medical domains rely on large datasets. A recent advancement in text-to-image generative AI is GLIDE (Guided Language to Image Diffusion for Generation and Editing). There are a number of representations available in the GLIDE model, but it has not been refined for medical applications. Methods: For text-conditional image synthesis with classifier-free guidance, we have fine-tuned GLIDE using 10,015 dermoscopic images of seven diagnostic entities, including melanoma and melanocytic nevi. Photorealistic synthetic samples of each diagnostic entity were created by the algorithm. Following this, an experienced dermatologist reviewed 140 images (20 of each entity), with 10 samples originating from artificial intelligence and 10 from original images from the dataset. The dermatologist classified the provided images according to the seven diagnostic entities. Additionally, the dermatologist was asked to indicate whether or not a particular image was created by AI. Further, we trained a deep learning model to compare the diagnostic results of dermatologist versus machine for entity classification. Results: The results indicate that the generated images possess varying degrees of quality and realism, with melanocytic nevi and melanoma having higher similarity to real images than other classes. The integration of synthetic images improved the classification performance of the model, resulting in higher accuracy and precision. The AI assessment showed superior classification performance compared to dermatologist. Conclusion: Overall, the results highlight the potential of synthetic images for training and improving AI models in dermatology to overcome data scarcity.
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OBJECTIVES: Different platelet-rich fibrin (PRF) protocols exist and are known to differ in resulting mechanical and bioactive properties. Centrifugation parameters may also influence drug release, in particular antibiotics, when using PRF as a bio-carrier. We thus evaluated three common protocols regarding effects on the bio-carrier properties. MATERIALS AND METHODS: In a prospective trial comprising 33 patients, we compared different protocols for PRF as a bio-carrier for ampicillin/sulbactam (SAM). Blood samples were taken shortly after a single dose of ampicillin/sulbactam (2 g/1 g) was administered to patients intravenously. PRF was obtained by centrifugation and three protocols were used: protocol A (1300 rpm, 8 min, RCF-max = 208 g), B (2300 rpm, 12 min, RCF-max = 652 g), and C (1500 rpm, 14 min, RCF-max = 276 g). The antibacterial activity of PRF was investigated against five oral species in vitro, based on agar diffusion methodology. RESULTS: The study demonstrates that a single dose of SAM is sufficient to reach high concentrations in PRF in all protocols (150 µg/ml), which is comparable to the plasma SAM concentration. Antibacterial activity was inferred from the diameter of inhibition zones seen in agar diffusion tests using PRF discs. Protocol B resulted in the largest inhibition zones. One-way ANOVA revealed statistically improved results for protocol B for some bacteria. CONCLUSIONS: The study provides valuable data on PRF antibiotic enrichment, notably SAM. A single dose of SAM is sufficient to reach clinically relevant concentrations in PRF. CLINICAL RELEVANCE: These findings potentially extend the application of PRF, for example in patients with osteonecrosis of the jaw or in oral surgery (e.g., stick bone).
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Fibrina Rica en Plaquetas , Humanos , Sulbactam/farmacología , Agar , Estudios Prospectivos , Péptidos y Proteínas de Señalización Intercelular , Centrifugación/métodos , Antibacterianos/farmacología , Ampicilina/farmacologíaRESUMEN
Clavicle fractures healed in shortening or malposition are extremely rare, especially in adolescence. In extreme cases, they can result in massive pain and limitation of movement. A causal therapeutic approach is lengthening osteotomy using the sagittal split technique with tricortical iliac crest interposition. In the context of the case study of a young patient, the procedure, operation as well as documentation of the postoperative results are reported.
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Clavícula , Fracturas Óseas , Adolescente , Humanos , Clavícula/diagnóstico por imagen , Resultado del Tratamiento , Fracturas Óseas/diagnóstico por imagen , Fijación Interna de Fracturas/métodos , Osteotomía/métodosRESUMEN
Objective: This study aims to critically evaluate the effectiveness and accuracy of a time safing and cost-efficient open-source algorithm for in-house planning of mandibular reconstructions using the free osteocutaneous fibula graft. The evaluation focuses on quantifying anatomical accuracy and assessing the impact on ischemia time. Methods: A pilot study was conducted, including patients who underwent in-house planned computer-aided design and manufacturing (CAD/CAM) of free fibula flaps between 2021 and 2023. Out of all patient cases, we included all with postoperative 3D imaging in the study. The study utilized open-source software tools for the planning step, and three-dimensional (3D) printing techniques. The Hausdorff distance and Dice coefficient metrics were used to evaluate the accuracy of the planning procedure. Results: The study assessed eight patients (five males and three females, mean age 61.75 ± 3.69 years) with different diagnoses such as osteoradionecrosis and oral squamous cell carcinoma. The average ischemia time was 68.38 ± 27.95â min. For the evaluation of preoperative planning vs. the postoperative outcome, the mean Hausdorff Distance was 1.22 ± 0.40. The Dice Coefficients yielded a mean of 0.77 ± 0.07, suggesting a satisfactory concordance between the planned and postoperative states. Dice Coefficient and Hausdorff Distance revealed significant correlations with ischemia time (Spearman's rho = -0.810, p = 0.015 and Spearman's rho = 0.762, p = 0.028, respectively). Linear regression models adjusting for disease type further substantiated these findings. Conclusions: The in-house planning algorithm not only achieved high anatomical accuracy, as reflected by the Dice Coefficients and Hausdorff Distance metrics, but this accuracy also exhibited a significant correlation with reduced ischemia time. This underlines the critical role of meticulous planning in surgical outcomes. Additionally, the algorithm's open-source nature renders it cost-efficient, easy to learn, and broadly applicable, offering promising avenues for enhancing both healthcare affordability and accessibility.
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A number of cross-sectional epidemiological studies suggest that poor oral health is associated with respiratory diseases. However, the number of cases within the studies was limited, and the studies had different measurement conditions. By analyzing data from the National Health and Nutrition Examination Survey III (NHANES III), this study aimed to investigate possible associations between chronic obstructive pulmonary disease (COPD) and periodontitis in the general population. COPD was diagnosed in cases where FEV (1)/FVC ratio was below 70% (non-COPD versus COPD; binary classification task). We used unsupervised learning utilizing k-means clustering to identify clusters in the data. COPD classes were predicted with logistic regression, a random forest classifier, a stochastic gradient descent (SGD) classifier, k-nearest neighbors, a decision tree classifier, Gaussian naive Bayes (GaussianNB), support vector machines (SVM), a custom-made convolutional neural network (CNN), a multilayer perceptron artificial neural network (MLP), and a radial basis function neural network (RBNN) in Python. We calculated the accuracy of the prediction and the area under the curve (AUC). The most important predictors were determined using feature importance analysis. Results: Overall, 15,868 participants and 19 feature variables were included. Based on k-means clustering, the data were separated into two clusters that identified two risk characteristic groups of patients. The algorithms reached AUCs between 0.608 (DTC) and 0.953% (CNN) for the classification of COPD classes. Feature importance analysis of deep learning algorithms indicated that age and mean attachment loss were the most important features in predicting COPD. Conclusions: Data analysis of a large population showed that machine learning and deep learning algorithms could predict COPD cases based on demographics and oral health feature variables. This study indicates that periodontitis might be an important predictor of COPD. Further prospective studies examining the association between periodontitis and COPD are warranted to validate the present results.
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Osteonecrosis of the jaw (ONJ) occurs typically after irradiation of the head and neck area or after the intake of antiresorptive agents. Both interventions can lead to compromised bone perfusion and can ultimately result in infection and necrosis. Treatment usually consists of surgical necrosectomy and prolonged antibiotic therapy, usually through beta-lactams such as ampicillin/sulbactam. The poor blood supply in particular raises the question as to whether this form of antibiosis can achieve sufficient concentrations in the bone. Therefore, we investigated the antibiotic concentration in plasma and bone samples in a prospective study. Bone samples were collected from the necrosis core and in the vital surrounding bone. The measured concentrations in plasma for ampicillin and sulbactam were 126.3 ± 77.6 and 60.2 ± 35.0 µg/mL, respectively. In vital bone and necrotic bone samples, the ampicillin/sulbactam concentrations were 6.3 ± 7.8/1.8 ± 2.0 µg/g and 4.9 ± 7.0/1.7 ± 1.7 µg/g, respectively. These concentrations are substantially lower than described in the literature. However, the concentration seems sufficient to kill most bacteria, such as Streptococci and Staphylococci, which are mostly present in the biofilm of ONJ. We, therefore, conclude that intravenous administration of ampicillin/sulbactam remains a valuable treatment in the therapy of ONJ. Nevertheless, increasing resistance of Escherichia coli towards beta-lactam antibiotics have been reported and should be considered.
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Osteonecrosis , Sulbactam , Humanos , Sulbactam/uso terapéutico , Proyectos Piloto , Estudios Prospectivos , Ampicilina/uso terapéutico , Antibacterianos/uso terapéutico , Escherichia coliRESUMEN
BACKGROUND: Extended skin malignancies of the head and neck region are among the most common cancer types and are associated with numerous diagnostic and therapeutical problems. The radical resection of skin cancer in the facial area often leads to severe functional and aesthetic impairment, and precise margin assessments can avoid the extensive safety margins. On the other hand, the complete removal of the cancer is essential to minimize the risk of recurrence. Reliable intraoperative assessments of the wound margins could overcome this discrepancy between minimal invasiveness and safety distance in the head and neck region. With the help of reflectance confocal laser microscopy (RCM), cells can be visualized in high resolution intraoperatively. The combination with deep learning and automated algorithms allows an investigator independent and objective interpretation of specific confocal imaging data. Therefore, we aimed to apply a deep learning algorithm to detect malignant areas in images obtained via in vivo confocal microscopy. We investigated basal cell carcinoma (BCC), as one of the most common entities with well-described in vivo RCM diagnostic criteria, within a preliminary feasibility study. PATIENTS AND METHODS: We included 62 patients with histologically confirmed BCC in the head and neck region. All patients underwent in vivo confocal laser microscope scanning. Approximately 382 images with BCC structures could be obtained, annotated, and proceeded for further deep learning model training. RESULTS: A sensitivity of 46% and a specificity of 85% in detecting BCC regions could be achieved using a convolutional neural network model ("MobileNet"). CONCLUSION: The preliminary results reveal the potential and limitations of the automated detection of BCC with in vivo RCM. Further studies with a larger number of cases are required to obtain better predictability.
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OBJECTIVES: Mechanisms of wound healing are often impaired in patients with osteonecrosis of the jaw (ONJ). According to the guidelines for the treatment of this disease, early surgical intervention is indicated. However, surgery often faces complications such as wound healing disorders. The application of platelet-rich fibrin (PRF) after necrosectomy between bone and mucosa may constitute a promising approach to improve surgical results. An aspect that was not investigated until now is that PRF acts as a "bio-carrier" for antibiotics previously applied intravenously. MATERIALS AND METHODS: We investigated the antimicrobial properties of PRF in 24 patients presenting ONJ undergoing systemic antibiosis with ampicillin/sulbactam. We measured the concentration of ampicillin/sulbactam in plasma and PRF and performed agar diffusion tests. Ampicillin/sulbactam was applied intravenously to the patient 10 minutes for blood sampling for PRF. No further incorporation of patients' blood or PRF product with antibiotic drugs was obtained. Four healthy patients served as controls. RESULTS: Our results revealed that PRF is highly enriched with ampicillin/sulbactam that is released to the environment. The antibiotic concentration in PRF was comparable to the plasma concentration of ampicillin/sulbactam. The inhibition zone (IZ) of PRF was comparable to the standard ampicillin/sulbactam discs used in sensitivity testing. CONCLUSIONS: The results of our study demonstrated that PRF is a reliable bio-carrier for systemic applied antibiotics and exhibits a large antimicrobial effect. CLINICAL RELEVANCE: We describe a clinically useful feature of PRF as a bio-carrier for antibiotics. Especially when applied to poorly perfused tissues and bone such as in ONJ, the local release of antibiotics can reduce wound healing disorders like infections.
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Fibrina Rica en Plaquetas , Humanos , Sulbactam/farmacología , Ampicilina/farmacología , Antibacterianos/farmacología , Antibacterianos/uso terapéuticoRESUMEN
Reconstruction of the donor site after radial forearm flap harvesting is a common procedure in maxillofacial plastic surgery. It is normally carried out with split-thickness or full-thickness free skin grafts. Unfortunately, free skin graft transplantation faces wound healing impairments such as necrosis, (partial) graft loss, or tendon exposure. Several studies have investigated methods to reduce these impairments and demonstrated improvements if the wound bed is optimised, for example, through negative-pressure wound therapy or vacuum-assisted closure. However, these methods are device-dependent, expansive, and time-consuming. Therefore, the application of platelet-rich fibrin (PRF) to the wound bed could be a simple, cost-effective, and device-independent method to optimise wound-bed conditions instead. In this study, PRF membranes were applied between the wound bed and skin graft. Results of this study indicate improvements in the PRF versus non-PRF group (93.44% versus 86.96% graft survival, p = 0.0292). PRF applied to the wound bed increases graft survival and reduces impairments. A possible explanation for this is the release of growth factors, which stimulate angiogenesis and fibroblast migration. Furthermore, the solid PRF membranes act as a mechanical barrier ("lubrication" layer) to protect the skin graft from tendon motion. The results of this study support the application of PRF in donor-site reconstruction with free skin grafts.
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Oroantral communication (OAC) is a common complication after tooth extraction of upper molars. Profound preoperative panoramic radiography analysis might potentially help predict OAC following tooth extraction. In this exploratory study, we evaluated n = 300 consecutive cases (100 OAC and 200 controls) and trained five machine learning algorithms (VGG16, InceptionV3, MobileNetV2, EfficientNet, and ResNet50) to predict OAC versus non-OAC (binary classification task) from the input images. Further, four oral and maxillofacial experts evaluated the respective panoramic radiography and determined performance metrics (accuracy, area under the curve (AUC), precision, recall, F1-score, and receiver operating characteristics curve) of all diagnostic approaches. Cohen's kappa was used to evaluate the agreement between expert evaluations. The deep learning algorithms reached high specificity (highest specificity 100% for InceptionV3) but low sensitivity (highest sensitivity 42.86% for MobileNetV2). The AUCs from VGG16, InceptionV3, MobileNetV2, EfficientNet, and ResNet50 were 0.53, 0.60, 0.67, 0.51, and 0.56, respectively. Expert 1-4 reached an AUC of 0.550, 0.629, 0.500, and 0.579, respectively. The specificity of the expert evaluations ranged from 51.74% to 95.02%, whereas sensitivity ranged from 14.14% to 59.60%. Cohen's kappa revealed a poor agreement for the oral and maxillofacial expert evaluations (Cohen's kappa: 0.1285). Overall, present data indicate that OAC cannot be sufficiently predicted from preoperative panoramic radiography. The false-negative rate, i.e., the rate of positive cases (OAC) missed by the deep learning algorithms, ranged from 57.14% to 95.24%. Surgeons should not solely rely on panoramic radiography when evaluating the probability of OAC occurrence. Clinical testing of OAC is warranted after each upper-molar tooth extraction.
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Ex vivo fluorescence confocal microscopy (FCM) is a developing tool providing rapid digital imaging of fresh tissue utilizing high-resolution optical sectioning that highly corresponds with conventional hmatoxylin and eosin (H&E)-stained slides. A very little data on oral mucosa lesions exist currently. The present work aimed to create an image atlas of benign and malignant oral tissues and compare them to the corresponding histopathology. Furthermore, we aimed to evaluate the learning curve for confocal image interpretation. From 50 samples obtained from the oral mucosa, including oral squamous cell carcinoma (OSCC), dysplasia, and healthy oral tissue, ex vivo FCM images and corresponding H&E slides were created and collected into a tissue atlas. Additionally, two experts were asked to analyze the images to assess the learning curve. Ex vivo FCM images revealed high comparability with histopathological images. Tissues including OSCC, dysplasia, and normal oral mucosa were implemented in the image atlas to provide the diagnostic fundament for pathologists and surgeons; the learning curve was short. Future studies on this topic will be advantageous for the development of artificial intelligence-based diagnostic approaches. The current work provides a novel set of data that are structured as an atlas of common pathologies of the mucosa to enhance the existing knowledge and material on confocal images.
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Carcinoma de Células Escamosas , Neoplasias de la Boca , Inteligencia Artificial , Carcinoma de Células Escamosas/diagnóstico por imagen , Carcinoma de Células Escamosas/patología , Humanos , Curva de Aprendizaje , Microscopía Confocal/métodos , Mucosa Bucal/diagnóstico por imagen , Mucosa Bucal/patología , Neoplasias de la Boca/diagnósticoRESUMEN
OBJECTIVES: Accurate visualization of dental root canals is vital for the correct diagnosis and subsequent treatment. This work assesses the improvement of a dedicated new coil for dental magnetic resonance imaging (MRI) in comparison to conventional ones in terms of signal-to-noise ratio (SNR) and visibility. MATERIALS AND METHODS: A newly developed intraoral flexible coil was used to display dental roots with MRI, and it provides improved sensitivity with a loop design and size adjusted to a single tooth anatomy. Ex vivo and in vivo measurements were performed on a 3 T clinical MR system, and results were compared with conventional head and surface coil images. Additional comparison was performed with a modified fast spin echo sequence and a constructive interference in steady-state sequence. RESULTS: Ex vivo, an SNR gain of 6.3 could be achieved with the intraoral flexible coil setup, and higher visibility down to 200 µm was possible, whereas the external loop coil is limited to 400 µm. In vivo measurements in a volunteer resulted in an SNR gain of up to 4.5 with an improved delineation of the root canals, especially for the branch tissue splitting of the mesial root canal into mesial-buccal and mesial-lingual. CONCLUSIONS: In summary, we showed the feasibility of implementing a wireless coil approach with readily available dental practice materials for sealing and placement. Highly improved MRI scans can be acquired within clinically feasible scan times, and this might provide additional medical findings to supplement available x-ray images.
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Cavidad Pulpar , Imagen por Resonancia Magnética , Cavidad Pulpar/diagnóstico por imagen , Diseño de Equipo , Humanos , Imagen por Resonancia Magnética/métodos , Fantasmas de Imagen , Relación Señal-RuidoRESUMEN
BACKGROUND: Ex vivo fluorescent confocal microscopy (FCM) is a novel and effective method for a fast-automatized histological tissue examination. In contrast, conventional diagnostic methods are primarily based on the skills of the histopathologist. In this study, we investigated the potential of convolutional neural networks (CNNs) for automatized classification of oral squamous cell carcinoma via ex vivo FCM imaging for the first time. MATERIAL AND METHODS: Tissue samples from 20 patients were collected, scanned with an ex vivo confocal microscope immediately after resection, and investigated histopathologically. A CNN architecture (MobileNet) was trained and tested for accuracy. RESULTS: The model achieved a sensitivity of 0.47 and specificity of 0.96 in the automated classification of cancerous tissue in our study. CONCLUSION: In this preliminary work, we trained a CNN model on a limited number of ex vivo FCM images and obtained promising results in the automated classification of cancerous tissue. Further studies using large sample sizes are warranted to introduce this technology into clinics.