Vibroarthrography is a radiation-free and inexpensive method of assessing the condition of knee cartilage damage during extension-flexion movements. Acoustic sensors were placed on the patella and medial tibial plateau (two accelerometers) as well as on the lateral tibial plateau (a piezoelectric disk) to measure the structure-borne noise in 59 asymptomatic knees and 40 knees with osteoarthritis. After semi-automatic segmentation of the acoustic signals, frequency features were generated for the extension as well as the flexion phase. We propose simple and robust features based on relative high-frequency components. The normalized nature of these frequency features makes them insusceptible to influences on the signal gain, such as attenuation by fat tissue and variance in acoustic coupling. We analyzed their ability to serve as classification features for detection of knee osteoarthritis, including the effect of normalization and the effect of combining frequency features of all three sensors. The features permitted a distinction between asymptomatic and non-healthy knees. Using machine learning with a linear support vector machine, a classification specificity of approximately 0.8 at a sensitivity of 0.75 could be achieved. This classification performance is comparable to existing diagnostic tests and hence qualifies vibroarthrography as an additional diagnostic tool. Graphical Abstract Acoustic frequency features were used to detect knee osteoarthritis at 80% specificity and 75% sensitivity.

A new microcatheter-delivered, highly-flexible, fully-retrievable intracranial stent has been developed in order to facilitate the endovascular treatment of wide-necked aneurysms, though it might also prove useful for other intracranial pathology. The nitinol stent has radiopaque proximal and distal markers, is available in a wide range of sizes and is as flexible as a micro-guidewire. It is electrolytically detached, allowing retrieval even after full deployment. The stent is compatible with all currently available embolic agents and does not degrade MR images.

The choice of stent material and changes in stent geometry as well as the optimization of the flip angle of the CE-MRA may reduce susceptibility and radiofrequency artifacts, rendering feasible the CE-MRA of a stented carotid artery.

Vibroarthrography describes the detection of joint pathologies by analysis of vibrations emitted during joint movement. In our study, 30 healthy volunteers and 39 patients with various degrees of chondromalacia or osteoarthritis were selected and accelerometers and piezoelectric sensors were placed on prominent bone structures of patients' knee joints (patella, lateral and medial tibial plateau) in order to measure the structure-borne noise during active extension and flexion of the joint. After semi-automatic signal segmentation had been applied to isolate flexion and extension cycles, features based on relative high-frequency components were generated. Using machine learning with a linear support vector machine, these signals were classified as healthy, exhibiting chondromalacia °II-IV or osteoarthritis. 84% of healthy subjects were identified correctly, while the classification accuracy for individual stages of chondromalacia or osteoarthritis ranged from 11% (CM °II) to 50% (CM °III). In order to make results easily interpretable without resorting to machine learning techniques, we propose a normalized score between 0 and 1 and show that this "v-score" for flexion and extension significantly correlates with the achieved multi-class classification. Vibroarthrography may qualify as potent screening tool for the detection and grading of joint cartilage defects and aid physicians in the choice and estimation of urgency of further diagnostic and therapeutic decisions.