Volume 57, Issue 5

Accidental hypothermia and its variant, perioperative hypothermia, is a rather common clinical phenomenon in patients. This is surprising because the negative effects on clinical outcomes are well described and effective patient-warming devices are available today. The aim of this paper is to describe the physiologic background of accidental and perioperative hypothermia, the clinical relevance and existing prophylaxis and treatment options. Patient warming techniques will be discussed in detail. Remaining technical and clinical challenges and the need for further research will be addressed. We will present existing guidelines and standards and analyse the impact of accidental and perioperative hypothermia on cost effectiveness.

Hearing screening is important for the early detection of hearing loss. The requirements of specialized equipment, skilled personnel, and quiet environments for valid screening results limit its application in schools and health clinics. This study aimed to develop an automated hearing screening kit (auto-kit) with the capability of realtime noise level monitoring to ensure that the screening is performed in an environment that conforms to the standard. The auto-kit consists of a laptop, a 24-bit resolution sound card, headphones, a microphone, and a graphical user interface, which is calibrated according to the American National Standards Institute S3.6-2004 standard. The auto-kit can present four test tones (500, 1000, 2000, and 4000 Hz) at 25 or 40 dB HL screening cut-off level. The clinical results at 40 dB HL screening cut-off level showed that the auto-kit has a sensitivity of 92.5% and a specificity of 75.0%. Because the 500 Hz test tone is not included in the standard hearing screening procedure, it can be excluded from the auto-kit test procedure. The exclusion of 500 Hz test tone improved the specificity of the auto-kit from 75.0% to 92.3%, which suggests that the auto-kit could be a valid hearing screening device. In conclusion, the auto-kit may be a valuable hearing screening tool, especially in countries where resources are limited.

Moving tumors, for example in the vicinity of the lungs, pose a challenging problem in radiotherapy, as healthy tissue should not be irradiated. Apart from gating approaches, one standard method is to irradiate the complete volume within which a tumor moves plus a safety margin containing a considerable volume of healthy tissue. This work deals with a system for tumor motion compensation using the HexaPOD ® robotic treatment couch (Medical Intelligence GmbH, Schwabmünchen, Germany). The HexaPOD, carrying the patient during treatment, is instructed to perform translational movements such that the tumor motion, from the beams-eye view of the linear accelerator, is eliminated. The dynamics of the HexaPOD are characterized by time delays, saturations, and other non-linearities that make the design of control a challenging task. The focus of this work lies on two control methods for the HexaPOD that can be used for reference tracking. The first method uses a model predictive controller based on a model gained through system identification methods, and the second method uses a position control scheme useful for reference tracking. We compared the tracking performance of both methods in various experiments with real hardware using ideal reference trajectories, prerecorded patient trajectories, and human volunteers whose breathing motion was compensated by the system.

Conventional fusion devices (“cages”) are often used to join two vertebrae of the human spine and generally remain in the body for a lifetime and can theoretically lead to any complications. Therefore, an absorbable hybrid fusion cage consisting of a magnesium skeleton infiltrated with an absorbable polymer [poly-ε-caprolactone (PCL)] has been developed. The primary objective of the cage is to ensure an adequate stiffness of the disc space directly after the operation and to encourage the ingrowth of the new bone tissue to secure long life stability. Once a sufficiently rigid bone connection is formed, the implant should be absorbed. The purpose of this first study on the new absorbable fusion cage was to investigate the mechanical properties in vitro . Tensile tests were performed with tensile specimens type 1BA according to DIN EN ISO 527 made of PCL foamed using controlled expansion of saturated polymers (CESP). Furthermore, cyclic compression tests and compression tests with steady movement were performed with different designs of the new cage. Compression tests were also performed with vertebral endplates of ovine cadaveric spines. Foaming of PCL resulted in a modulus of elasticity of 135 MPa, which is approximately one third of unfoamed PCL. The results indicate that the initial compression strength of the implants should be adequate for the implantation in the cervical spine.

The similar bone structure of reindeer antler to human bone permits studying the osseointegration of dental implants in the jawbone. As the friction is one of the major factors that have a significant influence on the initial stability of immediately loaded dental implants, it is essential to define the frictional coefficient of the implant-antler interface. In this study, the kinetic frictional forces at the implant-antler interface were measured experimentally using an optomechanical setup and a stepping motor controller under different axial loads and sliding velocities. The corresponding mean values of the static and kinetic frictional coefficients were within the range of 0.5–0.7 and 0.3–0.5, respectively. An increase in the frictional forces with increasing applied axial loads was registered. The measurements showed an evidence of a decrease in the magnitude of the frictional coefficient with increasing sliding velocity. The results of this study provide a considerable assessment to clarify the suitable frictional coefficient to be used in the finite element contact analysis of antler specimens.

Objectives: This study was designed to determine and statistically analyze bone-to-implant contact (BIC) values for human specimens segmented in at least two different locations. Materials and methods: Samples of human bone with fractured osseointegrated implants were obtained from six patients. Sections were prepared, dehydrated, and resin infiltrated. Undecalcified bone sections were produced using the thin-section technique according to Donath, ultimately obtaining a section thickness of approximately 20 μm. Fifteen specimens were available for histomorphometry. The bone sections were digitized and analyzed. The bone-to-metal contact (BMC) parameter was determined histomorphometrically. The BMC was returned in terms of the visibly bone-covered implant surfaces as a percentage of the total implant surface shown. Results: The values obtained for the six implants were arranged as six maximum-distance pairs and tested for significance using the t-test for dependent samples. The mean difference in BIC was 11.69±9.79%. The two-sided test showed a significant difference (p=0.033). Conclusion: The accidental or deliberate choice of section plane for a bone-implant block has an influence on the BIC value. To make BIC values more comparable, a standardization of section planes is desirable.

Microstructural heterogeneities in cardiac tissue, such as embedded connective tissue secondary to fibrosis, may lead to complex patterns of electrical activation that are reflected in the fractionation of extracellularly recorded electrograms. The decomposition of such electrograms into non-fractionated components is expected to provide additional information to allow a more precise classification of the microstructural properties adjacent to a given recording site. For the sake of this, an analytic signal model is introduced in this study that is capable of reliably identifying extracellular waveforms associated with sites of initiating, free-running, and terminating or colliding activation wavefronts. Using this signal model as a template, a procedure is developed for the automatic decomposition of complex fractionated electrograms into non-fractionated components. The decomposition method has been validated using electrograms obtained from one- and two-dimensional computer simulations in which all relevant intracellular and extracellular quantities are accessible at a very high spatiotemporal resolution and can be manipulated in a controlled manner. Fractionated electrograms were generated in these models by incorporating microstructural obstacles that mimicked inlays of connective tissue. Using this signal model, fractionated electrograms emerging from microstructural heterogeneities in the submillimeter range with latencies between components down to 0.6 ms can be decomposed.

The main aim of our work was to assess the reliability of indirect abdominal electrocardiography as an alternative to the commonly used Doppler ultrasound monitoring technique. As a reference method, we used direct fetal electrocardiography. Direct and abdominal signals were acquired simultaneously, using dedicated instrumentation. The developed method of maternal signal suppression as well as fetal QRS complexes detection was presented. Recordings were collected during established labors, each consisted of four signals from the maternal abdomen and the reference signal acquired directly from the fetal head. After assessing the performance of the QRS detector, the accuracy of fetal heart rate measurement was evaluated. Additionally, to reduce the influence of inaccurately detected R-waves, some validation rules were proposed. The obtained results revealed that the indirect method is able to provide an accuracy sufficient for a reliable assessment of fetal heart rate variability. However, the method is very sensitive to recording conditions, influencing the quality of signals. Our investigations confirmed that abdominal electrocardiography, even in its current stage of development, offers an accuracy equal to or higher than an ultrasound method, at the same time providing some additional features.

In this article, we propose a feature selection strategy using a binary particle swarm optimization algorithm for the diagnosis of different medical diseases. The support vector machines were used for the fitness function of the binary particle swarm optimization. We evaluated our proposed method on four databases from the machine learning repository, including the single proton emission computed tomography heart database, the Wisconsin breast cancer data set, the Pima Indians diabetes database, and the Dermatology data set. The results indicate that, with selected less number of features, we obtained a higher accuracy in diagnosing heart, cancer, diabetes, and erythematosquamous diseases. The results were compared with the traditional feature selection methods, namely, the F-score and the information gain, and a superior accuracy was obtained with our method. Compared to the genetic algorithm for feature selection, the results of the proposed method show a higher accuracy in all of the data, except in one. In addition, in comparison with other methods that used the same data, our approach has a higher performance using less number of features.

Interoperability is one of the most challenging concerns that face healthcare information system (HIS) actors. Interoperability implementation in this context may be a data exchange interfacing, a service oriented interaction or even a composition of new composite healthcare processes. In fact, optimizing efforts of interoperability achievement is a key requirement to effectively setup, develop and evolve intra- and interorganizational collaboration. To ensure interoperability project effectiveness, this paper proposes a modeling representation of health processes interoperability evolution. Interoperability degrees of involved automated processes are assessed using a ratio metric, taking into account all significant aspects, such as potentiality, compatibility and operational performance. Then, a particle swarm optimization algorithm (PSO) is used as a heuristic optimization method to find the best distribution of effort needed to establish an efficient healthcare collaborative network.

Background and aims: Because there is no complete three-dimensional (3D) hybrid detector integrated PET+MRI internationally, this study aims to investigate a registration approach for a two-dimensional (2D) hybrid based on characteristic localization to achieve a 3D fusion from the images of PET and MRI as a whole. Methods: A cubic-oriented scheme of “9-point and 3-plane” for a coregistration design was verified to be geometrically practical. Through 3D reconstruction and virtual dissection, human internal feature points were sorted to combine with preselected external feature points for matching process. By following the procedure of feature extraction and image mapping, the processes of “picking points to form planes” and “picking planes for segmentation” were executed. Eventually, the image fusion was implemented at the real-time workstation Mimics based on auto-fuse techniques called “information exchange” and “signal overlay”. Results: A complementary 3D image across PET+MRI modalities, which simultaneously present metabolic activities and anatomic structures, was created with a detectable rate of 56%. This is equivalent to the detectable rate of PET+CT or MRI+CT with no statistically significant difference, and it facilitates a 3D vision that is not yet functional for 2D hybrid imaging. Conclusions: This cross-modality fusion is doubtless an essential complement for the existing toolkit of a 2D hybrid device. Thus, it would potentially improve the efficiency of diagnosis and therapy for oncology.