@article{VollmerVollmerLangetal.2023, author = {Vollmer, Andreas and Vollmer, Michael and Lang, Gernot and Straub, Anton and K{\"u}bler, Alexander and Gubik, Sebastian and Brands, Roman C. and Hartmann, Stefan and Saravi, Babak}, title = {Automated assessment of radiographic bone loss in the posterior maxilla utilizing a multi-object detection artificial intelligence algorithm}, series = {Applied Sciences}, volume = {13}, journal = {Applied Sciences}, number = {3}, issn = {2076-3417}, doi = {10.3390/app13031858}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-305050}, year = {2023}, abstract = {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.}, language = {en} } @article{MertensAndriesKurzetal.2022, author = {Mertens, Griet and Andries, Ellen and Kurz, Anja and Tȧvora-Vieira, Dayse and Calvino, Miryam and Amann, Edda and Anderson, Ilona and Lorens, Artur}, title = {Towards a consensus on an ICF-based classification system for horizontal sound-source localization}, series = {Journal of Personalized Medicine}, volume = {12}, journal = {Journal of Personalized Medicine}, number = {12}, issn = {2075-4426}, doi = {10.3390/jpm12121971}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297319}, year = {2022}, abstract = {The study aimed to develop a consensus classification system for the reporting of sound localization testing results, especially in the field of cochlear implantation. Against the background of an overview of the wide variations present in localization testing procedures and reporting metrics, a novel classification system was proposed to report localization errors according to the widely accepted International Classification of Functioning, Disability and Health (ICF) framework. The obtained HEARRING_LOC_ICF scale includes the ICF graded scale: 0 (no impairment), 1 (mild impairment), 2 (moderate impairment), 3 (severe impairment), and 4 (complete impairment). Improvement of comparability of localization results across institutes, localization testing setups, and listeners was demonstrated by applying the classification system retrospectively to data obtained from cohorts of normal-hearing and cochlear implant listeners at our institutes. The application of our classification system will help to facilitate multi-center studies, as well as allowing better meta-analyses of data, resulting in improved evidence-based practice in the field.}, language = {en} } @article{HuflageFieberFaerberetal.2022, author = {Huflage, Henner and Fieber, Tabea and F{\"a}rber, Christian and Knarr, Jonas and Veldhoen, Simon and Jordan, Martin C. and Gilbert, Fabian and Bley, Thorsten Alexander and Meffert, Rainer H. and Grunz, Jan-Peter and Schmalzl, Jonas}, title = {Interobserver reliability of scapula fracture classifications in intra- and extra-articular injury patterns}, series = {BMC Musculoskeletal Disorders}, volume = {23}, journal = {BMC Musculoskeletal Disorders}, number = {1}, doi = {10.1186/s12891-022-05146-7}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-299795}, year = {2022}, abstract = {Background Morphology and glenoid involvement determine the necessity of surgical management in scapula fractures. While being present in only a small share of patients with shoulder trauma, numerous classification systems have been in use over the years for categorization of scapula fractures. The purpose of this study was to evaluate the established AO/OTA classification in comparison to the classification system of Euler and R{\"u}edi (ER) with regard to interobserver reliability and confidence in clinical practice. Methods Based on CT imaging, 149 patients with scapula fractures were retrospectively categorized by two trauma surgeons and two radiologists using the classification systems of ER and AO/OTA. To measure the interrater reliability, Fleiss kappa (κ) was calculated independently for both fracture classifications. Rater confidence was stated subjectively on a five-point scale and compared with Wilcoxon signed rank tests. Additionally, we computed the intraclass correlation coefficient (ICC) based on absolute agreement in a two-way random effects model to assess the diagnostic confidence agreement between observers. Results In scapula fractures involving the glenoid fossa, interrater reliability was substantial (κ = 0.722; 95\% confidence interval [CI] 0.676-0.769) for the AO/OTA classification in contrast to moderate agreement (κ = 0.579; 95\% CI 0.525-0.634) for the ER classification system. Diagnostic confidence for intra-articular fracture patterns was superior using the AO/OTA classification compared to ER (p < 0.001) with higher confidence agreement (ICC: 0.882 versus 0.831). For extra-articular fractures, ER (κ = 0.817; 95\% CI 0.771-0.863) provided better interrater reliability compared to AO/OTA (κ = 0.734; 95\% CI 0.692-0.776) with higher diagnostic confidence (p < 0.001) and superior agreement between confidence ratings (ICC: 0.881 versus 0.912). Conclusions The AO/OTA classification is most suitable to categorize intra-articular scapula fractures with glenoid involvement, whereas the classification system of Euler and R{\"u}edi appears to be superior in extra-articular injury patterns with fractures involving only the scapula body, spine, acromion and coracoid process.}, language = {en} } @article{VollmerVollmerLangetal.2022, author = {Vollmer, Andreas and Vollmer, Michael and Lang, Gernot and Straub, Anton and K{\"u}bler, Alexander and Gubik, Sebastian and Brands, Roman C. and Hartmann, Stefan and Saravi, Babak}, title = {Performance analysis of supervised machine learning algorithms for automatized radiographical classification of maxillary third molar impaction}, series = {Applied Sciences}, volume = {12}, journal = {Applied Sciences}, number = {13}, issn = {2076-3417}, doi = {10.3390/app12136740}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-281662}, year = {2022}, abstract = {Background: Oro-antral communication (OAC) is a common complication following the extraction of upper molar teeth. The Archer and the Root Sinus (RS) systems can be used to classify impacted teeth in panoramic radiographs. The Archer classes B-D and the Root Sinus classes III, IV have been associated with an increased risk of OAC following tooth extraction in the upper molar region. In our previous study, we found that panoramic radiographs are not reliable for predicting OAC. This study aimed to (1) determine the feasibility of automating the classification (Archer/RS classes) of impacted teeth from panoramic radiographs, (2) determine the distribution of OAC stratified by classification system classes for the purposes of decision tree construction, and (3) determine the feasibility of automating the prediction of OAC utilizing the mentioned classification systems. Methods: We utilized multiple supervised pre-trained machine learning models (VGG16, ResNet50, Inceptionv3, EfficientNet, MobileNetV2), one custom-made convolutional neural network (CNN) model, and a Bag of Visual Words (BoVW) technique to evaluate the performance to predict the clinical classification systems RS and Archer from panoramic radiographs (Aim 1). We then used Chi-square Automatic Interaction Detectors (CHAID) to determine the distribution of OAC stratified by the Archer/RS classes to introduce a decision tree for simple use in clinics (Aim 2). Lastly, we tested the ability of a multilayer perceptron artificial neural network (MLP) and a radial basis function neural network (RBNN) to predict OAC based on the high-risk classes RS III, IV, and Archer B-D (Aim 3). Results: We achieved accuracies of up to 0.771 for EfficientNet and MobileNetV2 when examining the Archer classification. For the AUC, we obtained values of up to 0.902 for our custom-made CNN. In comparison, the detection of the RS classification achieved accuracies of up to 0.792 for the BoVW and an AUC of up to 0.716 for our custom-made CNN. Overall, the Archer classification was detected more reliably than the RS classification when considering all algorithms. CHAID predicted 77.4\% correctness for the Archer classification and 81.4\% for the RS classification. MLP (AUC: 0.590) and RBNN (AUC: 0.590) for the Archer classification as well as MLP 0.638) and RBNN (0.630) for the RS classification did not show sufficient predictive capability for OAC. Conclusions: The results reveal that impacted teeth can be classified using panoramic radiographs (best AUC: 0.902), and the classification systems can be stratified according to their relationship to OAC (81.4\% correct for RS classification). However, the Archer and RS classes did not achieve satisfactory AUCs for predicting OAC (best AUC: 0.638). Additional research is needed to validate the results externally and to develop a reliable risk stratification tool based on the present findings.}, language = {en} } @article{MerkelLindnerGaberetal.2022, author = {Merkel, Helena and Lindner, Dirk and Gaber, Khaled and Ziganshyna, Svitlana and Jentzsch, Jennifer and Mucha, Simone and Gerhards, Thilo and Sari, Sabine and Stock, Annika and Vothel, Felicitas and Falter, Lea and Qu{\"a}schling, Ulf and Hoffmann, Karl-Titus and Meixensberger, J{\"u}rgen and Halama, Dirk and Richter, Cindy}, title = {Standardized classification of cerebral vasospasm after subarachnoid hemorrhage by digital subtraction angiography}, series = {Journal of Clinical Medicine}, volume = {11}, journal = {Journal of Clinical Medicine}, number = {7}, issn = {2077-0383}, doi = {10.3390/jcm11072011}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-270638}, year = {2022}, abstract = {Background: During the last decade, cerebral vasospasm after aneurysmal subarachnoid hemorrhage (SAH) was a current research focus without a standardized classification in digital subtraction angiography (DSA). This study was performed to investigate a device-independent visual cerebral vasospasm classification for endovascular treatment. Methods: The analyses are DSA based rather than multimodal. Ten defined points of intracranial arteries were measured in 45 patients suffering from cerebral vasospasm after SAH at three time points (hospitalization, before spasmolysis, control after six months). Mathematical clustering of vessel diameters was performed to generate four objective grades for comparison. Six interventional neuroradiologists in two groups scored 237 DSAs after a new visual classification (grade 0-3) developed on a segmental pattern of vessel contraction. For the second group, a threshold-based criterion was amended. Results: The raters had a reproducibility of 68.4\% in the first group and 75.2\% in the second group. The complementary threshold-based criterion increased the reproducibility by about 6.8\%, while the rating deviated more from the mathematical clustering in all grades. Conclusions: The proposed visual classification scheme of cerebral vasospasm is suitable as a standard grading procedure for endovascular treatment. There is no advantage of a threshold-based criterion that compensates for the effort involved. Automated vessel analysis is superior to compare inter-group results in research settings.}, language = {en} } @article{EvdokimovDinkelFranketal.2020, author = {Evdokimov, Dimitar and Dinkel, Philine and Frank, Johanna and Sommer, Claudia and {\"U}{\c{c}}eyler, Nurcan}, title = {Characterization of dermal skin innervation in fibromyalgia syndrome}, series = {PLoS One}, volume = {15}, journal = {PLoS One}, number = {1}, doi = {10.1371/journal.pone.0227674}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229299}, year = {2020}, abstract = {Introduction We characterized dermal innervation in patients with fibromyalgia syndrome (FMS) as potential contribution to small fiber pathology. Methods Skin biopsies of the calf were collected (86 FMS patients, 35 healthy controls). Skin was immunoreacted with antibodies against protein gene product 9.5, calcitonine gene-related peptide, substance P, CD31, and neurofilament 200 for small fiber subtypes. We assessed two skin sections per patient; on each skin section, two dermal areas (150 x 700 mu m each) were investigated for dermal nerve fiber length (DNFL). Results In FMS patients we found reduced DNFL of fibers with vessel contact compared to healthy controls (p<0.05). There were no differences for the other nerve fiber subtypes. Discussion We found less dermal nerve fibers in contact with blood vessels in FMS patients than in controls. The pathophysiological relevance of this finding is unclear, but we suggest the possibility of a relationship with impaired thermal tolerance commonly reported by FMS patients.}, language = {en} } @phdthesis{Wilde2019, author = {Wilde, Sabrina}, title = {Einsatz von mechanistischen Biomarkern zur Charakterisierung und Bewertung von \(in\) \(vitro\) Genotoxinen}, doi = {10.25972/OPUS-18278}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-182782}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2019}, abstract = {Die verf{\"u}gbaren in vitro Genotoxizit{\"a}tstests weisen hinsichtlich ihrer Spezifit{\"a}t und ihres Informationsgehalts zum vorliegenden Wirkmechanismus (Mode of Action, MoA) Einschr{\"a}nkungen auf. Um diese M{\"a}ngel zu {\"u}berwinden, wurden in dieser Arbeit zwei Ziele verfolgt, die zu der Entwicklung und Etablierung neuer in vitro Methoden zur Pr{\"u}fung auf Genotoxizit{\"a}t in der Arzneimittelentwicklung beitragen. 1. Etablierung und Bewertung einer neuen in vitro Genotoxizit{\"a}tsmethode (MultiFlow Methode) Die MultiFlow Methode basiert auf DNA-schadensassoziierten Proteinantworten von γH2AX (DNA-Doppelstrangbr{\"u}che), phosphorylierten H3 (S10) (mitotische Zellen), nukle{\"a}ren Protein p53 (Genotoxizit{\"a}t) und cleaved PARP1 (Apoptose) in TK6-Zellen. Insgesamt wurden 31 Modellsubstanzen mit dem MultiFlow Assay und erg{\"a}nzend mit dem etablierten Mikrokerntest (MicroFlow MNT), auf ihre F{\"a}higkeit verschiedene MoA-Gruppen (Aneugene/Klastogene/Nicht-Genotoxine) zu differenzieren, untersucht. Die Performance der „neuen" gegen{\"u}ber der „alten" Methode f{\"u}hrte zu einer verbesserten Sensitivit{\"a}t von 95\% gegen{\"u}ber 90\%, Spezifit{\"a}t von 90\% gegen{\"u}ber 72\% und einer MoA-Klassifizierungsrate von 85\% gegen{\"u}ber 45\% (Aneugen vs. Klastogen). 2. Identifizierung mechanistischer Biomarker zur Klassifizierung genotoxischer Substanzen Die Analyse 67 ausgew{\"a}hlter DNA-schadensassoziierter Gene in der QuantiGene Plex Methode zeigte, dass mehrere Gene gleichzeitig zur MoA-Klassifizierung beitragen k{\"o}nnen. Die Kombination der h{\"o}chstrangierten Marker BIK, KIF20A, TP53I3, DDB2 und OGG1 erm{\"o}glichte die beste Identifizierungsrate der Modellsubstanzen. Das synergetische Modell kategorisierte 16 von 16 Substanzen korrekt in Aneugene, Klastogene und Nicht-Genotoxine. Unter Verwendung der Leave-One-Out-Kreuzvalidierung wurde das Modell evaluiert und erreichte eine Sensitivit{\"a}t, Spezifit{\"a}t und Pr{\"a}diktivit{\"a}t von 86\%, 83\% und 85\%. Ergebnisse der traditionellen qPCR Methode zeigten, dass Genotoxizit{\"a}t mit TP53I3, Klastogenit{\"a}t mit ATR und RAD17 und oxidativer Stress mit NFE2L2 detektiert werden kann. Durch die Untersuchungen von posttranslationalen Modifikationen unter Verwendung der High-Content-Imaging-Technologie wurden mechanistische Assoziationen f{\"u}r BubR1 (S670) und pH3 (S28) mit Aneugenit{\"a}t, 53BP1 (S1778) und FANCD2 (S1404) mit Klastogenit{\"a}t, p53 (K373) mit Genotoxizit{\"a}t und Nrf2 (S40) mit oxidativem Stress identifiziert. Diese Arbeit zeigt, dass (Geno)toxine unterschiedliche Gen- und Proteinver{\"a}nderungen in TK6-Zellen induzieren, die zur Erfassung mechanistischer Aktivit{\"a}ten und Einteilung (geno)toxischer MoA-Gruppen (Aneugen/Klastogen/ Reaktive Sauerstoffspezies) eingesetzt werden k{\"o}nnen und daher eine bessere Risikobewertung von Wirkstoffkandidaten erm{\"o}glichen.}, subject = {Genotoxizit{\"a}t}, language = {de} } @article{GilbertEdenMeffertetal.2018, author = {Gilbert, F. and Eden, L. and Meffert, R. and Konietschke, F. and Lotz, J. and Bauer, L. and Staab, W.}, title = {Intra- and interobserver reliability of glenoid fracture classifications by Ideberg, Euler and AO}, series = {BMC Musculoskeletal Disorders}, volume = {19}, journal = {BMC Musculoskeletal Disorders}, number = {89}, doi = {10.1186/s12891-018-2016-8}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176482}, year = {2018}, abstract = {Background: Representing 3\%-5\% of shoulder girdle injuries scapula fractures are rare. Furthermore, approximately 1\% of scapula fractures are intraarticularfractures of the glenoid fossa. Because of uncertain fracture morphology and limited experience, the treatment of glenoid fossa fractures is difficult. The glenoid fracture classification by Ideberg (1984) and Euler (1996) is still commonly used in literature. In 2013 a new glenoid fracture classification was introduced by the AO. The purpose of this study was to examine the new AO classification in clinical practice in comparison with the classifications by Ideberg and Euler. Methods: In total CT images of 84 patients with glenoid fossa fractures from 2005 to 2018 were included. Parasagittal, paracoronary and axial reconstructions were examined according to the classifications of Ideberg, Euler and the AO by 3 investigators (orthopedic surgeon, radiologist, student of medicine) at three individual time settings. Inter- and intraobserver reliability of the three classification systems were ascertained by computing Inter- and Intraclass (ICCs) correlation coefficients using Spearman's rank correlation coefficient, 95\%-confidence intervals as well as F-tests for correlation coefficients. Results: Inter- and intraobserver reliability for the AO classification showed a perspicuous coherence (R = 0.74 and R = 0.79). Low to moderate intraobserver reliability for Ideberg (R = 0.46) and Euler classification (R = 0.41) was found. Furthermore, data show a low Interobserver reliability for both Ideberg and Euler classification (R < 0.2). Both the Inter- and Intraclass reliability using AO is significantly higher than those using Ideberg and Euler (p < 0.05). Using the new AO classification, it was possible to find a proper class for every glenoid fossa fracture. On average, according to Euler classification 10 of 84 fractures were not classifiable whereas to Ideberg classification 21 of 84 fractures were not classifiable. Conclusion: The new AO classification system introduced 2013 facilitates reliable grading of glenoid fossa fractures with high inter- and intraobserver reliability in 84 patients using CT images. It should possibly be applied in order to enable a valid, reliable and consistent academic description of glenoid fossa fractures. The established classifications by Euler and Ideberg are not capable of providing a similar reliability.}, language = {en} } @article{EmserJohnstonSteeleetal.2018, author = {Emser, Theresa S. and Johnston, Blair A. and Steele, J. Douglas and Kooij, Sandra and Thorell, Lisa and Christiansen, Hanna}, title = {Assessing ADHD symptoms in children and adults: evaluating the role of objective measures}, series = {Behavioral and Brain Functions}, volume = {14}, journal = {Behavioral and Brain Functions}, number = {11}, doi = {10.1186/s12993-018-0143-x}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-175717}, year = {2018}, abstract = {Background: Diagnostic guidelines recommend using a variety of methods to assess and diagnose ADHD. Applying subjective measures always incorporates risks such as informant biases or large differences between ratings obtained from diverse sources. Furthermore, it has been demonstrated that ratings and tests seem to assess somewhat different constructs. The use of objective measures might thus yield valuable information for diagnosing ADHD. This study aims at evaluating the role of objective measures when trying to distinguish between individuals with ADHD and controls. Our sample consisted of children (n = 60) and adults (n = 76) diagnosed with ADHD and matched controls who completed self- and observer ratings as well as objective tasks. Diagnosis was primarily based on clinical interviews. A popular pattern recognition approach, support vector machines, was used to predict the diagnosis. Results: We observed relatively high accuracy of 79\% (adults) and 78\% (children) applying solely objective measures. Predicting an ADHD diagnosis using both subjective and objective measures exceeded the accuracy of objective measures for both adults (89.5\%) and children (86.7\%), with the subjective variables proving to be the most relevant. Conclusions: We argue that objective measures are more robust against rater bias and errors inherent in subjective measures and may be more replicable. Considering the high accuracy of objective measures only, we found in our study, we think that they should be incorporated in diagnostic procedures for assessing ADHD.}, language = {en} } @article{BenoitGoebeler2015, author = {Benoit, Sandrine and Goebeler, Matthias}, title = {Mepacrine in recalcitrant cutaneous lupus erythematosus: old-fashioned or still useful?}, series = {Acta Dermato-Venereologica}, volume = {95}, journal = {Acta Dermato-Venereologica}, doi = {10.2340/00015555-2031}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-149181}, pages = {596-599}, year = {2015}, abstract = {Treatment of recalcitrant cutaneous lupus erythematosus (CLE) is challenging. In situations where conventional treatment approaches fail mepacrine - an antimalarial/antiinfiammatory drug that has fallen into oblivion in the last decades might still be a promising option. We retrospectively analysed medical records of 10 patients with refractory CLE that were treated with mepacrine (100-200 mg/day) as mono- or combination therapy for various time intervals between 2001 and 2013 at the University Hospital Wurzburg. Mepacrine was generally well tolerated. Side effects were mild and usually resolved after reduction or cessation. Over 50\% of the patients experienced amelioration of their symptoms despite a previously recalcitrant clinical course. Altogether, our data demonstrate that mepacrine still remains a useful and effective therapeutic option for otherwise treatment-resistant CLE.}, language = {en} }