An image-based kinematic model of the tibiotalar and subtalar joints and its application to gait analysis in children with Juvenile Idiopathic Arthritis

In vivo estimates of tibiotalar and the subtalar joint kinematics can unveil unique information about gait biomechanics, especially in the presence of musculoskeletal disorders affecting the foot and ankle complex. Previous literature investigated the ankle kinematics on ex vivo data sets, but little has been reported for natural walking, and even less for pathological and juvenile populations. This paper proposes an MRI-based morphological fitting methodology for the personalised definition of the tibiotalar and the subtalar joint axes during gait, and investigated its application to characterise the ankle kinematics in twenty patients affected by Juvenile Idiopathic Arthritis (JIA). The estimated joint axes were in line with in vivo and ex vivo literature data and joint kinematics variation subsequent to inter-operator variability was in the order of 1°. The model allowed to investigate, for the first time in patients with JIA, the functional response to joint impairment. The joint kinematics highlighted changes over time that were consistent with changes in the patient’s clinical pattern and notably varied from patient to patient. The heterogeneous and patient-specific nature of the effects of JIA was confirmed by the absence of a correlation between a semi-quantitative MRI-based impairment score and a variety of investigated joint kinematics indexes. In conclusion, this study showed the feasibility of using MRI and morphological fitting to identify the tibiotalar and subtalar joint axes in a non-invasive patient-specific manner. The proposed methodology represents an innovative and reliable approach to the analysis of the ankle joint kinematics in pathological juvenile populations

Minimal Reporting Standards for Active Middle Ear Hearing Implants.

There is currently no standardized method for reporting audiological, surgical and subjective outcome measures in clinical trials with active middle ear implants (AMEIs). It is often difficult to compare studies due to data incompatibility and to perform meta-analyses across different centres is almost impossible. A committee of ENT and audiological experts from Germany, Austria and Switzerland decided to address this issue by developing new minimal standards for reporting the outcomes of AMEI clinical trials. The consensus presented here aims to provide a recommendation to enable better inter-study comparability

A Patient-Specific Foot Model for the Estimate of Ankle Joint Forces in Patients with Juvenile Idiopathic Arthritis

Juvenile idiopathic arthritis (JIA) is the leading cause of childhood disability from a musculoskeletal disorder. It generally affects large joints such as the knee and the ankle, often causing structural damage. Different factors contribute to the damage onset, including altered joint loading and other mechanical factors, associated with pain and inflammation. The prediction of patients' joint loading can hence be a valuable tool in understanding the disease mechanisms involved in structural damage progression. A number of lower-limb musculoskeletal models have been proposed to analyse the hip and knee joints, but juvenile models of the foot are still lacking. This paper presents a modelling pipeline that allows the creation of juvenile patient-specific models starting from lower limb kinematics and foot and ankle MRI data. This pipeline has been applied to data from three children with JIA and the importance of patient-specific parameters and modelling assumptions has been tested in a sensitivity analysis focused on the variation of the joint reaction forces. This analysis highlighted the criticality of patient-specific definition of the ankle joint axes and location of the Achilles tendon insertions. Patient-specific detection of the Tibialis Anterior, Tibialis Posterior, and Peroneus Longus origins and insertions were also shown to be important

Automatisierte Analyse und Visualisierung der Koronararterien und großen Kavitäten des Herzens für die klinische Anwendung

Es werden verschiedene Verfahren zur Analyse von Bilddaten des kardiovaskulären Systems behandelt. Damit wird eine Verbesserung sowohl der Diagnose als auch der Planung von eventuell notwendigen Eingriffen erreicht. Die beschriebenen Verfahren zeichnen sich durch eine hohe Automatisierung und Reproduzierbarkeit der Analyseergebnisse sowie ihre klinische Anwendbarkeit aus. Augenmerk wird vor allem auf die auf der Oberfläche des Herzens liegenden Herzkranzgefäße und die den Hauptteil des Herzens bildenden Kavitäten – das linke und rechte Ventrikel gelegt. Hier werden verschiedene im Rahmen dieser Arbeit entwickelte, neue Segmentierungs- und Analyseverfahren vorgestellt und diskutiert. Im Falle der Herzkranzgefäße sind das trackingbasierte Segmentierungsansätze, die die Basis für eine Analyse des Gefäßes hinsichtlich der Detektion und Vermessung von Stenosen, des Vorhandenseins von harten Arterienverkalkungen und der Zusammensetzung des umliegenden Gewebes bilden. Desweiteren wird ein Verfahren vorgestellt, das es ermöglicht, die damit erreichten Ergebnisse mit der Koronarangiographie – dem Gold-Standard – zu vergleichen. Für eine angepaßte Präsentation der Analyseergebnisse werden speziell entwickelte Verfahren für deren optimale Visualisierung als auch die der Bilddaten selbst vorgestellt. Letztere betreffend wird ein automatisches Verfahren eingeführt, mit dessen Hilfe sich Strukturen wie der Brustkorb ausmaskieren lassen, die die direkte Sicht auf das Herz stören. Für die Analyse von linkem (LV) und rechtem Ventrikel (RV) werden automatisierte Segmentierungsverfahren vorgestellt, aus deren Ergebnis sich die die Dynamik der Ventrikel beschreibenden physikalischen Parameter ableiten lassen. Für das LV wird eine umfassende, automatische und detaillierte Analyse der Wandbewegung, Wanddickenzunahme und Volumenänderung vorgestellt. Als neuer Deskriptor für die Dynamik wird die Asynchronität eingeführt. Die für das LV entwickelten Analyseverfahren werden auf das RV übertragen und ermöglichen so eine ganz neue Qualität dessen Analyse. Die Präsentation der berechneten Parameter erfolgt in einer standardisierten Weise entsprechend den Empfehlungen der American Heart Association. Als Erweiterung dieser Darstellungsmöglichkeit wird die direkte Visualisierung dieser Größen zusammen mit einem 3D-Rendering des LV eingeführt. Dies fließt ein in eine kombinierte Darstellung von dynamischen Parametern und Infarktbereichen des Herzens. Letztere werden zudem automatisch quantifiziert

Monitoring Treatment Outcome: A Visualization Prototype for Left Ventricular Transformation

The analysis of cardiac dynamics - especially of the left ventricle - is a means for evaluating the healthiness of the heart. In case that a malfunction has been detected and afterwards has been treated, the question arises whether the treatment was successful or not. On a longer time scale, it is of clinical interest to compare the results of follow-up studies with those of former examinations. In this paper, we address both issues by presenting a visualization prototype for the comparison of left ventricular dynamics obtained from cine-MRI data. Our approach is based on the computation of differences for standard cardiac parameters between two time series which have been acquired prior to and after treatment. For their visualization, we use a series of bull's-eye displays allowing for an in-depth examination of the treatment outcome. Here, we focus on the special clinical application ventricular reduction surgery where we perform a retrospective evaluation for cine-MRI data acquired prior to and right after surgery as well as several months later. We compare our results with diagnosis information obtained from clinical experts

AHA conform analysis of myocardial function using and extending the toolkits ITK and VTK

Modern dynamic image acquisition techniques allow for a non-invasive imaging of the beating heart. Thus, ischemic areas of the heart's wall can be detected by anlyzing the left ventricular myocardial function. For a standardization of that task the American Heart Association (AHA) has published recommendations for the myocardial segmentation and nomenclature. We propose in this paper a comprehensive, fully automatic, and AHA conform analysis of the myocardial function that is based on the segmentation results of the left ventricular cavity for the whole cardiac cycle. The physical values wall motion, ejection fraction, and wall thickening are computed and visualized employing and extending the toolkits ITK and VTK. First test results using dynamic MRI data are presented

Computation and Visualization of Asynchronous Behavior of the Heart

Nowadays, computer-aided diagnosis is widely used in the analysis of cardiac image data. Especially, for the investigation of the dynamic behavior of the heart, automated analysis tools for 4D data sets have been developed. A small set of descriptors of the heart's dynamics are established and used in the clinical routine. However, there exists a whole lot more of such parameters that can be extracted by analyzing 4D data sets. But, many of them are not used due to several reasons: time-consuming computation, no intuitive meaning, little clinical relevance, etc.. In this work we propose a novel descriptor for the dynamic behavior of the heart that can easily be computed from 4D data sets. It describes to which extent the heart exhibits an asynchronous movement. This novel descriptor ASYNCHRONISM is based on the already established measures WALL MOTION and WALL THICKENING, but reveals new, valuable information that is not available when relying only upon the two aforementioned parameters. The ASYNCHRONISM has an intuitive meaning, since it corresponds to the clinical classification scheme of wall motion abnormalities. Beyond its computation we present in this work also methods for its visualization as well as first preliminary results for 4D cardiac magnetic resonance image data

Virtual and Augmented 3D Bronchoscopy Navigation Based on C-arm Fluoroscopy

Instrument guidance during bronchoscopy is a very intricate task, which demands profound anatomical knowledge and good orientation skills from the physician. Apart from bronchoscopic video, intraoperative C-arm images of the instruments inside the airways are the only auxiliary means available. By tracing the 2D position of the instrument on the fluoroscopy back to its 3D position inside the bronchial tree, an effective navigation support is provided. Given the intraoperative C-arm pose, a preoperative segmentation of the airways and automatic tracking of the 2D position of the instrument on the fluoroscopy, this 3D position of the bronchoscopic instruments can be followed during the whole intervention without manual user interaction. In this paper, we present a bronchoscopy navigation system for virtual preoperative planning and augmented intraoperative guidance. The whole system was successfully tested by inserting a bronchoscope into a bronchial tree model under continuous fluoroscopy. During the procedure, the current 3D position of the bronchoscope's tip could be tracked and visualized inside the bronchial tree segmentation

3D Registration Based on Normalized Mutual Information : Performance of CPU vs. GPU Implementation

Medical image registration is time-consuming but can be sped up employing parallel processing on the GPU. Normalized mutual information (NMI) is a well performing similarity measure for performing multi-modal registration. We present CUDA based solutions for computing NMI on the GPU and compare the results obtained by rigidly registering multi-modal data sets with a CPU based implementation. Our tests with RIRE data sets show a speed-up of factor 5 to 7 for our best GPU implementation