Refine
Has Fulltext
- yes (23)
Is part of the Bibliography
- yes (23)
Document Type
- Journal article (23)
Language
- English (23) (remove)
Keywords
- HNSCC (5)
- artificial intelligence (5)
- head and neck cancer (5)
- caloric restriction (3)
- deep learning (3)
- machine learning (3)
- prediction (3)
- ARONJ (2)
- HGF (2)
- Met (2)
Institute
- Klinik und Poliklinik für Mund-, Kiefer- und Plastische Gesichtschirurgie (23)
- Comprehensive Cancer Center Mainfranken (4)
- Pathologisches Institut (3)
- Poliklinik für Zahnärztliche Prothetik (3)
- Theodor-Boveri-Institut für Biowissenschaften (3)
- Institut für Hygiene und Mikrobiologie (2)
- Institut für Pharmazie und Lebensmittelchemie (2)
- Medizinische Klinik und Poliklinik II (2)
- Institut für diagnostische und interventionelle Radiologie (Institut für Röntgendiagnostik) (1)
- Klinik und Poliklinik für Hals-, Nasen- und Ohrenkrankheiten, plastische und ästhetische Operationen (1)
Sonstige beteiligte Institutionen
Background
Mandibular pseudocarcinomatous hyperplasia is a rare and generally benign pathology. We report on one of these rare cases.
Case presentation
The case history of a 73-year-old white man stated that he had a carcinoma of the oropharynx, which was primarily treated with radiotherapy and chemotherapy 4 years prior. As a result of radiotherapy he developed an osteoradionecrosis of his mandible and a consecutive pathological fracture of his left mandibular angle. Subsequent osteosynthesis was performed with a reconstruction plate. When we first saw him, his reconstruction plate was partially exposed with intraoral and extraoral fistulation. The resected bone of his defect-bordering jaw showed the typical pathohistological findings of an intraosseous mandibular pseudocarcinomatous hyperplasia. After a first reconstruction attempt with an iliac crest graft failed, definitive reconstruction of his mandible with a microvascular anastomosed fibula graft was achieved.
Conclusions
Intraosseous pseudocarcinomatous hyperplasia of the mandible is a rare differential diagnosis in maxillofacial surgery. Besides other benign epithelial neoplasms, such as calcifying epithelial odontogenic tumor, squamous odontogenic tumor, or different forms of ameloblastoma, the far more frequent invasive squamous cell carcinoma needs to be excluded. A misinterpretation of pseudocarcinomatous hyperplasia as squamous cell carcinoma must be avoided because it can lead to a massive overtreatment.
Introduction
Spindle cell rhabdomyosarcoma of the head and neck is a very rare tumor in adults. We report on one case with long-term survival.
Case presentation
A 41-year-old nonsmoking Caucasian man presented in June 2007 with a painless swelling under his tongue. A diagnosis of a soft tissue sarcoma, and a myofibrosarcoma in particular, was made via biopsy. After multimodal treatment, including local and systemic therapy, our patient remained disease-free until September 2010. The local recurrence was treated unsuccessfully with various chemotherapy regimens. In September 2011, our patient underwent surgical resection again, and a spindle cell rhabdomyosarcoma was diagnosed. To analyze the mismatch between the original diagnosis of a myofibrosarcoma and the second diagnosis, the two specimens were reassessed, and a final diagnosis of a spindle cell rhabdomyosarcoma was made. In 2012 and 2013, our patient suffered further recurrences that were surgically treated, and he is still alive with disease six years and 10 months after the initial diagnosis in June 2007.
Conclusions
In adults, the spindle cell rhabdomyosarcoma tumor is very rare in the head and neck region. In contrast to childhood tumors, spindle cell rhabdomyosarcoma in adulthood is often associated with a poor prognosis. In the present case, the radical surgical treatment might have helped to prolong the patient’s overall survival, which has lasted more than six years. To our knowledge, this is the longest overall survival reported so far for this tumor entity in the head and neck region.
Head and neck squamous cell carcinoma (HNSCC) is known to overexpress a variety of receptor tyrosine kinases, such as the HGF receptor Met. Like other malignancies, HNSCC involves a mutual interaction between the tumor cells and surrounding tissues and cells. We hypothesized that activation of HGF/Met signaling in HNSCC influences glucose metabolism and therefore substantially changes the tumor microenvironment. To determine the effect of HGF, we submitted three established HNSCC cell lines to mRNA sequencing. Dynamic changes in glucose metabolism were measured in real time by an extracellular flux analyzer. As expected, the cell lines exhibited different levels of Met and responded differently to HGF stimulation. As confirmed by mRNA sequencing, the level of Met expression was associated with the number of upregulated HGF-dependent genes. Overall, Met stimulation by HGF leads to increased glycolysis, presumably mediated by higher expression of three key enzymes of glycolysis. These effects appear to be stronger in Met\(^{high}\)-expressing HNSCC cells. Collectively, our data support the hypothesized role of HGF/Met signaling in metabolic reprogramming of HNSCC.
Positional plagiocephaly (PP) is the most common skull deformity in infants. Different classification systems exist for graduating the degree of PP, but all of these systems are based on two-dimensional (2D) parameters. This limitation leads to several problems stemming from the fact that 2D parameters are used to classify the three-dimensional (3D) shape of the head. We therefore evaluate existing measurement parameters and validate a newly developed 3D parameter for quantifying PP. Additionally, we present a new classification of PP based on a 3D parameter. 210 patients with PP and 50 patients without PP were included in this study. Existing parameters (2D and 3D) and newly developed volume parameters based on a 3D stereophotogrammetry scan were validated using ROC curves. Additionally, thresholds for the new 3D parameter of a 3D asymmetry index were assessed. The volume parameter 3D asymmetry index quantifies PP equally as well as the gold standard of 30° diagonal difference. Moreover, a 3D asymmetry index allows for a 3D-based classification of PP. The 3D asymmetry index can be used to define the degree of PP. It is easily applicable in stereophotogrammetric datasets and allows for comparability both intra- and inter-individually as well as for scientific analysis.
Periodontitis is one of the most prevalent diseases worldwide. The degree of radiographic bone loss can be used to assess the course of therapy or the severity of the disease. Since automated bone loss detection has many benefits, our goal was to develop a multi-object detection algorithm based on artificial intelligence that would be able to detect and quantify radiographic bone loss using standard two-dimensional radiographic images in the maxillary posterior region. This study was conducted by combining three recent online databases and validating the results using an external validation dataset from our organization. There were 1414 images for training and testing and 341 for external validation in the final dataset. We applied a Keypoint RCNN with a ResNet-50-FPN backbone network for both boundary box and keypoint detection. The intersection over union (IoU) and the object keypoint similarity (OKS) were used for model evaluation. The evaluation of the boundary box metrics showed a moderate overlapping with the ground truth, revealing an average precision of up to 0.758. The average precision and recall over all five folds were 0.694 and 0.611, respectively. Mean average precision and recall for the keypoint detection were 0.632 and 0.579, respectively. Despite only using a small and heterogeneous set of images for training, our results indicate that the algorithm is able to learn the objects of interest, although without sufficient accuracy due to the limited number of images and a large amount of information available in panoramic radiographs. Considering the widespread availability of panoramic radiographs as well as the increasing use of online databases, the presented model can be further improved in the future to facilitate its implementation in clinics.
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.
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.
Associations between periodontitis and COPD: An artificial intelligence-based analysis of NHANES III
(2022)
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.
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.
All forms of restriction, from caloric to amino acid to glucose restriction, have been established in recent years as therapeutic options for various diseases, including cancer. However, usually there is no direct comparison between the different restriction forms. Additionally, many cell culture experiments take place under static conditions. In this work, we used a closed perfusion culture in murine L929 cells over a period of 7 days to compare methionine restriction (MetR) and glucose restriction (LowCarb) in the same system and analysed the metabolome by liquid chromatography mass spectrometry (LC-MS). In addition, we analysed the inhibition of glycolysis by 2-deoxy-D-glucose (2-DG) over a period of 72 h. 2-DG induced very fast a low-energy situation by a reduced glycolysis metabolite flow rate resulting in pyruvate, lactate, and ATP depletion. Under perfusion culture, both MetR and LowCarb were established on the metabolic level. Interestingly, over the period of 7 days, the metabolome of MetR and LowCarb showed more similarities than differences. This leads to the conclusion that the conditioned medium, in addition to the different restriction forms, substantially reprogramm the cells on the metabolic level.