Aim: To evaluate the correlation between standard clinical findings, radiographic (OPT) and magnetic resonance imaging (MRI) as well as to assess whether MRI is capable of providing additional information related to the severity and extent of periodontal disease.Methods: 42 patients with generalized periodontitis received pre‐interventional MRI scans. These were compared to MR images of a periodontal healthy control group (n = 34). The extent of the osseous oedema, detected by MRI, was set in correlation with clinical periodontitis‐associated findings.Results: A highly significant correlation between bone oedema and clinical testings such as probing depth (p < 0.0001) and bleeding on probing (p < 0.0001) was revealed. The oedema exceeded the extent of demineralized bone. Patients with a positive BOP test showed a 2.51‐fold increase in risk of already having a bone oedema around the respective tooth even if probing depth was ≤3 mm (logistic binary regression analysis, OR 2.51; 95% CI: 1.54–4.11; p < 0.0001).Conclusion: MRI findings correlated with standard clinical findings, and MRI was able to depict intraosseous changes before any osseous defect had occurred.

Recent repetitive TMS (rTMS) mapping protocols for language mapping revealed deficits of this method, mainly in posterior brain regions. Therefore this study analyzed the impact of different language tasks on the localization of language-positive brain regions and compared their effectiveness, especially with regard to posterior brain regions. Nineteen healthy, right-handed subjects performed object naming, pseudoword reading, verb generation, and action naming during rTMS language mapping of the left hemisphere. Synchronically, 5 Hz/10 pulses were applied with a 0 ms delay The object naming task evoked the highest error rate (14%), followed by verb generation (13%) and action naming (11%). The latter revealed more errors in posterior than in anterior areas. Pseudoword reading barely generated errors, except for phonological paraphasias. In general, among the evaluated language tasks, object naming is the most discriminative task to detect language-positive regions via rTMS. However, other tasks might be used for more specific questions.

The skeleton of a digital image is a compact representation of its topology, geometry, and scale. It has utility in many computer vision applications, such as image description, segmentation, and registration. However, skeletonization has only seen limited use in contemporary deep learning solutions. Most existing skeletonization algorithms are not differentiable, making it impossible to integrate them with gradient-based optimization. Compatible algorithms based on morphological operations and neural networks have been proposed, but their results often deviate from the geometry and topology of the true medial axis. This work introduces the first three-dimensional skeletonization algorithm that is both compatible with gradient-based optimization and preserves an object’s topology. Our method is exclusively based on matrix additions and multiplications, convolutional operations, basic non-linear functions, and sampling from a uniform probability distribution, allowing it to be easily implemented in any major deep learning library. In benchmarking experiments, we prove the advantages of our skeletonization algorithm compared to non-differentiable, morphological, and neural-network-based baselines. Finally, we demonstrate the utility of our algorithm by integrating it with two medical image processing applications that use gradient-based optimization: deep-learning-based blood vessel segmentation, and multimodal registration of the mandible in computed tomography and magnetic resonance images.

Although language mapping by repetitive navigated transcranial magnetic stimulation (rTMS) gains importance in neuropsychological research and clinical utility, neuroscientists still use different mapping protocols including different stimulation frequencies. To refine the existing language protocol, we tested two different repetition rates of 5 Hz/10 pulses and 7 Hz/10 pulses with a 0 ms delay in 19 healthy subjects. We furthermore investigated differences between both frequencies in case of performance of four different language tasks: object naming, pseudoword reading, verb generation, and action naming. Even the small variance in frequencies revealed statistically significant differences concerning the number and type of language errors. Stimulation with 5 Hz evoked a higher number of all occurred language errors in all language tasks (error rate object naming 14% (5 Hz) vs. 12% (7 Hz); pseudoword reading 4% (5 Hz) vs. 3% (7 Hz); verb generation 13% (5 Hz) vs. 11% (7 Hz); action naming 11% (5 Hz) vs. 9% (7 Hz)), whereas 7 Hz evoked specifically more total speech arrests. These findings suggest that the stimulation frequency has to be adapted to the aim of the rTMS language investigation.