The foundations of computer assisted surgery

Using navigation systems in general orthopaedic surgery and, in particular, knee replacement is becoming more and more accepted. This paper describes the basic technological concepts of modern computer assisted surgical systems. It explains the variation in currently available systems and outlines research activities that will potentially influence future products. In general, each navigation system is defined by three components: (1) the therapeutic object is the anatomical structure that is operated on using the navigation system, (2) the virtual object represents an image of the therapeutic object, with radiological images or computer generated models potentially being used, and (3) last but not least, the navigator acquires the spatial position and orientation of instruments and anatomy thus providing the necessary data to replay surgical action in real-time on the navigation system's screen.

The performance of computer-aided detection when analyzing prior mammograms of newly detected breast cancers with special focus on the time interval from initial imaging to detection

PURPOSE: The clinical role of CAD systems to detect breast cancer, which have not been on cancer containing mammograms not detected by the radiologist was proven retrospectively. METHODS: All patients from 1992 to 2005 with a histologically verified malignant breast lesion and a mammogram at our department, were analyzed in retrospect focussing on the time of detection of the malignant lesion. All prior mammograms were analyzed by CAD (CADx, USA). The resulting CAD printout was matched with the cancer containing images yielding to the radiological diagnosis of breast cancer. CAD performance, sensitivity as well as the association of CAD and radiological features were analyzed. RESULTS: 278 mammograms fulfilled the inclusion criteria. 111 cases showed a retrospectively visible lesion (71 masses, 23 single microcalcification clusters, 16 masses with microcalcifications, in one case two microcalcification clusters). 54/87 masses and 34/41 microcalcifications were detected by CAD. Detection rates varied from 9/20 (ACR 1) to 5/7 (ACR 4) (45% vs. 71%). The detection of microcalcifications was not influenced by breast tissue density. CONCLUSION: CAD might be useful in an earlier detection of subtle breast cancer cases, which might remain otherwise undetected.

A systematic review on the accuracy and the clinical outcome of computer-guided template-based implant dentistry

Introduction: The aim of this systematic review was to analyze the dental literature regarding accuracy and clinical application in computer-guided template-based implant dentistry. Materials and methods: An electronic literature search complemented by manual searching was performed to gather data on accuracy and surgical, biological and prosthetic complications in connection with computer-guided implant treatment. For the assessment of accuracy meta-regression analysis was performed. Complication rates are descriptively summarized. Results: From 3120 titles after the literature search, eight articles met the inclusion criteria regarding accuracy and 10 regarding the clinical performance. Meta-regression analysis revealed a mean deviation at the entry point of 1.07 mm (95% CI: 0.76-1.22 mm) and at the apex of 1.63 mm (95% CI: 1.26-2 mm). No significant differences between the studies were found regarding method of template production or template support and stabilization. Early surgical complications occurred in 9.1%, early prosthetic complications in 18.8% and late prosthetic complications in 12% of the cases. Implant survival rates of 91-100% after an observation time of 12-60 months are reported in six clinical studies with 537 implants mainly restored immediately after flapless implantation procedures. Conclusion: Computer-guided template-based implant placement showed high implant survival rates ranging from 91% to 100%. However, a considerable number of technique-related perioperative complications were observed. Preclinical and clinical studies indicated a reasonable mean accuracy with relatively high maximum deviations. Future research should be directed to increase the number of clinical studies with longer observation periods and to improve the systems in terms of perioperative handling, accuracy and prosthetic complications.

An Application-Layer RESTful Sleepy Nodes Implementation For Internet of Things Systems

Two of the main issues in wireless industrial Internet of Things applications are interoperability and network lifetime. In this work we extend a semantic interoperability platform and introduce an application-layer sleepy nodes protocol that can leverage on information stored in semantic repositories. We propose an integration platform for managing the sleep states and an application layer protocol based upon the Constraint Application Layer protocol. We evaluate our system on windowing based task allocation strategies, aiming for lower overall energy consumption that results in higher network lifetime.

Outcome of computer-assisted surgery in patients with chronic rhinosinusitis

To compare the complication rates and outcome of computer-assisted versus non-computer-assisted functional endoscopic sinus surgery.

Uncovering the dynamics of cardiac systems using stochastic pacing and frequency domain analyses

Alternans of cardiac action potential duration (APD) is a well-known arrhythmogenic mechanism which results from dynamical instabilities. The propensity to alternans is classically investigated by examining APD restitution and by deriving APD restitution slopes as predictive markers. However, experiments have shown that such markers are not always accurate for the prediction of alternans. Using a mathematical ventricular cell model known to exhibit unstable dynamics of both membrane potential and Ca2+ cycling, we demonstrate that an accurate marker can be obtained by pacing at cycle lengths (CLs) varying randomly around a basic CL (BCL) and by evaluating the transfer function between the time series of CLs and APDs using an autoregressive-moving-average (ARMA) model. The first pole of this transfer function corresponds to the eigenvalue (λalt) of the dominant eigenmode of the cardiac system, which predicts that alternans occurs when λalt≤−1. For different BCLs, control values of λalt were obtained using eigenmode analysis and compared to the first pole of the transfer function estimated using ARMA model fitting in simulations of random pacing protocols. In all versions of the cell model, this pole provided an accurate estimation of λalt. Furthermore, during slow ramp decreases of BCL or simulated drug application, this approach predicted the onset of alternans by extrapolating the time course of the estimated λalt. In conclusion, stochastic pacing and ARMA model identification represents a novel approach to predict alternans without making any assumptions about its ionic mechanisms. It should therefore be applicable experimentally for any type of myocardial cell.