bluuebunny/crossref_metadata_2025_split huggingface dataset:
Independent associations between liver fat, visceral adipose tissue, and metabolic risk factors in men
Authors: McMillan Kathleen P. , Kuk Jennifer L. , Church Timothy S. , Blair Steven N. , Ross Robert 
Published: May 2007

The independent associations between liver fat, visceral adipose tissue (AT), and metabolic risk factors are unclear. Although it has been reported that visceral AT is the strongest predictor of metabolic risk, liver fat has also been reported as a strong independent associate of a deleterious metabolic profile. We examined the independent associations between liver fat, visceral AT, and metabolic risk factors in a sample of 293 men varying widely in adiposity. Liver fat and abdominal AT were measured by computed tomography (CT). Univariate analysis revealed that liver fat was associated (p < 0.05) with triglycerides (TG), systolic blood pressure (SBP), and total cholesterol (TC), but not with glucose or high-density lipoprotein cholesterol (HDLC). Liver fat remained a significant correlate (p < 0.05) of TG and TC after control for age and subcutaneous AT or cardiorespiratory fitness (CRF), but not after adjustment for visceral AT alone. Conversely, visceral AT remained significantly associated with TG, SBP, glucose, HDLC (p < 0.01), and TC (p = 0.05) independent of liver fat, subcutaneous AT, CRF, and age. Both liver fat and visceral AT were associated with metabolic risk in men. However, when controlled for each other, visceral AT was the only independent associate of metabolic risk.
A Patient-specific in vivo Tumor and Normal Tissue Model for Prediction of the Response to Radiotherapy
Authors: Antipas V. P. , Uzunoglu N. K. , Stamatakos G. S. 
Published: May 2007

Summary

Objectives:
Integration of multiscale experimental cancer biology through the development of computer simulation models seems to be a necessary step towards the better understanding of cancer and patient-individualized treatment optimization. The integration of a four-dimensional patient-specific model of in vivo tumor response to radiotherapy developed by our group with a model of slowly responding normal tissue based on W. Duechting’s approach is presented in this paper. The case of glioblastoma multiforme and its surrounding neural tissue is addressed as a modeling paradigm.

Methods:
A cubic discretizing mesh is superimposed upon the anatomic region of interest as is reconstructed from pertinent imaging (e.g. MRI) data. On each geometrical cell of the mesh the most crucial biological “laws” e.g. metabolism, cell cycling, tumor geometry changes, cell kill following irradiation etc. are applied. Slowly responding normal neural tissue is modeled by a functional compartment containing indivisible cells and a divisible compartment containing glial cells.

Results:
The model code has been executed for a simulated period normally covering the radiotherapy course duration and extending a few days after its completion. The following schemes have been simulated: standard fractionation, hyperfractionation, accelerated fractionation, accelerated hyperfractionation and hypofractionation. The predictions are in agreement with the outcome of the RTOG 83-02 phase I/II trial, the retrospective study conducted by Sugawara et al. and the theoretical predictions of Duechting et al.

Conclusions:
The presented model, although oversimplified, may serve as a basis for a refined simulation of the biological mechanisms involved in tumor and normal tissue response to radiotherapy.
Respiratory-phase Domain Analysis of Heart Rate Variability Can Accurately Estimate Cardiac Vagal Activity during a Mental Arithmetic Task
Authors: Tachibana M. , Takamasu K. , Kotani K. 
Published: May 2007

Summary

Objectives:
The objectives of this paper were to present a method to extract the amplitude of RSA in the respiratory-phase domain, to compare that with subjective or objective indices of the MWL (mental workload), and to compare that with a conventional frequencyanalysis in terms of its accuracy during a mental arithmetic task.

Methods:
HRV (heart rate variability), ILV (instantaneous lung volume), and motion of the throat were measured under a mental arithmetic experiment and subjective and objective indices were also obtained. The amplitude of RSA was extracted in the respiratory-phase domain, and its correlation with the load level was compared with the results of the frequencydomain analysis, which is the standard analysis of the HRV.

Results:
The subjective and objective indices decreased as the load level increased, showing that the experimental protocol was appropriate. Then, the amplitude of RSA in the respiratory-phase domain also decreased with the increase in the load level. The results of the correlation analysis showed that the respiratory-phase domain analysis has higher negative correlations, −0.84 and −0.82, with the load level as determined bysimplecorrelation and rankcorrelation, respectively, than does frequencyanalysis, for which the correlations were found to be −0.54 and −0.63, respectively. In addition, it was demonstrated thatthe proposed method could be applied to the short-term extraction of RSA amplitude.

Conclusions:
We proposed a simple and effective method to extract the amplitude of the respiratory sinus arrhythmia (RSA) in the respiratory-phase domain and the results show that this method can estimate cardiac vagal activity more accurately than frequency analysis.
Modeling Length of Stay as an Optimized Two-class Prediction Problem
Authors: Peek N. , Voorbraak F. , Jonge E. de , Mol B. A. J. M. de , Verduijn M. 
Published: May 2007

Summary

Objectives:
To develop a predictive model for the outcome length of stay at the Intensive Care Unit (ICU LOS), including the choice of an optimal dichotomization threshold for this outcome. Reduction of prediction problems of this type of outcome to a two-class problem is a common strategy to identify high-risk patients.

Methods:
Threshold selection and model development are performed simultaneously. From the range of possible threshold values, the value is chosen for which the corresponding predictive model has maximal precision based on the data. To compare the precision of models for different dichotomizations of the outcome, the MALOR performance statistic is introduced. This statistic is insensitive to the prevalence of positive cases in a two-class prediction problem.

Results:
The procedure is applied to data from cardiac surgery patients to dichotomize the outcome ICU LOS. The class probabilitytree method is used to develop predictive models. Within our data, the best model precision is found at the threshold of seven days.

Conclusions:
The presented method extends existing procedures for predictive modeling with optimization of the outcome definition for predictive purposes. The method can be applied to all prediction problems where the outcome variable needs to be dichotomized, and is insensitive to changes in the prevalence of positive cases with different dichotomization thresholds.
Optimizing the Interventional Cardiology Facility: Services Integration in Routine Workflow
Authors: Kalogeropoulos A. , Alexopoulos D. , Nikiforidis G. , Gortzis L. 
Published: May 2007

Summary

Objectives:
Integration of administrative and clinical data, imaging, and expert services, although challenging, is a key requirement in contemporary interventional cardiology facilities (ICF). We propose a workflow-oriented hybrid system to support the ICF and investigate its feasibility and effectiveness in a referral medical center.

Methods:
We have developed a Java-powered hybrid system (NetCARDIO), able to support over web synchronous and asynchronous data management, realtime multimedia data telemonitoring and continuous telementoring. Data regarding procedural rates, treatment planning and radiation exposure were collected over a two-year period of routine NetCARDIO implementation (July 2002 to June 2004) and compared with data from an immediately preceding period of equal duration (January 2000 to December 2001).

Results:
During the NetCARDIO period, 163 ±11 coronary procedures per month were performed vs. 77 ±15 during the control period (p <0.001). Percutaneous coronary intervention was delivered ‘ad hoc’ in 88% of eligible patients vs. 45% (p <0.001). Mean fluoroscopy time per coronary lesion treated decreased from 594 ± 82sto 540 ±94s (p < 0.001). Annual radiation exposure of expert interventionistswas decreased by 22%. Electronic storage significantly reduced archiving costs.

Conclusions:
Real-time multimodal services sharing combined with powerful database capabilities is feasible through a web-based structure, significantly enhancing performance and cost-effectiveness of ICF. Further research is needed to promote integration of additional data sources and services.
Systematic Analysis of Signaling Pathways Using an Integrative Environment
Authors: Breit M. , Pfeifer B. , Baumgartner C. , Modre-Osprian R. , Tilg B. , Visvanathan M. 
Published: May 2007

Summary

Introduction:
Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways.

Methods:
This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer.

Results:
The TNFα-mediated NF-κB signal transduction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results.

Conclusion:
The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.
Towards Semantic Interoperability for Electronic Health Records
Authors: Knaup P. , Hovenga E. J. S. , Heard S. , Garde S. 
Published: May 2007

Summary

Objectives:
In the field of open electronic health records (EHRs), openEHR as an archetype-based approach is being increasingly recognised. It is the objective of this paper to shortly describe this approach, and to analyse how openEHR archetypes impact on health professionals and semantic interoperability.

Methods:
Analysis of current approaches to EHR systems, terminology and standards developments. In addition to literature reviews, we organised face-to-face and additional telephone interviews and tele-conferences with members of relevant organisations and committees.

Results:
The openEHR archetypes approach enables syntactic interoperability and semantic interpretability – both important prerequisites for semantic interoperability. Archetypes enable the formal definition of clinical content by clinicians. To enable comprehensive semantic interoperability, the development and maintenance of archetypes needs to be coordinated internationally and across health professions. Domain knowledge governance comprises a set of processes that enable the creation, development, organisation, sharing, dissemination, use and continuous maintenance of archetypes. It needs to be supported by information technology.

Conclusions:
To enable EHRs, semantic interoperability is essential. The openEHR archetypes approach enables syntactic interoperability and semantic interpretability. However, without coordinated archetype development and maintenance, ‘rank growth’ of archetypes would jeopardize semantic interoperability. We therefore believe that openEHR archetypes and domain knowledge governance together create the knowledge environment required to adopt EHRs.
Advances in Medical Image Computing
Authors: Horsch A. , Meinzer H.-P. , Handels H. 
Published: May 2007

Summary

Objectives:
Medical image computing has become a key technology in high-tech applicationsin medicine. Nowadays, medical image computing techniques are applied in daily routine in various medical disciplines. However, further developments are needed to improve computer-aided diagnoses and computer-assisted therapy planning and performance in the future. In this issue selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing.

Methods:
The winners of scientific awards of the German Conferences on Medical Image Processing (BVM) 2005 and 2006 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, eleven excellent papers were selected to describe important aspects of recent advances in the field of medical image computing.

Results:
The selected papers give an impression of the broad range and heterogeneity of new developments in the field of medical image computing. New methods for improved image reconstruction, image segmentation, modelling of organs, as well as methodical improvements of non-linear image registration algorithms are presented together with applications of image analysis methods in different medical disciplines.

Conclusions:
The selected articles describe different aspects of the intense development in medical image computing. The image computing methods presented enable new insights into the patient’s image data and have the future potential to improve medical diagnostics and patient treatment.
Intensity Gradient Based Registration and Fusion of Multi-modal Images
Authors: Modersitzki J. , Haber E. 
Published: May 2007

Summary

Objectives:
A particular problem in image registration arises for multi-modal images taken from different imaging devices and/or modalities. Starting in 1995, mutual information has shown to be a very successful distance measure for multi-modal image registration. Therefore, mutual information is considered to be the state-of-the-art approach to multi-modal image registration. However, mutual information has also a number of well-known drawbacks. Its main disadvantage is that it is known to be highly non-convexand hastypicallymanylocal maxima.

Methods:
This observation motivates us to seek a different image similarity measure which is better suited for optimization but as well capable to handle multimodal images.

Results:
In this work, we investigate an alternative distance measure which is based on normalized gradients.

Conclusions:
As we show, the alternative approach is deterministic, much simpler, easier to interpret, fast and straightforward to implement, faster to compute, and also much more suitable to numerical optimization.
Structure-preserving Interpolation of Temporal and Spatial Image Sequences Using an Optical Flow-based Method
Authors: Säring D. , Handels H. , Ehrhardt J. 
Published: May 2007

Summary

Objectives:
Modern tomographic imaging devices enable the acquisition of spatial and temporal image sequences. But, the spatial and temporal resolution of such devices is limited and therefore image interpolation techniques are needed to represent images at a desired level of discretization. This paper presents a method for structure-preserving interpolation between neighboring slices in temporal or spatial image sequences.

Methods:
In a first step, the spatiotemporal velocity field between image slices is determined using an optical flow-based registration method in order to establish spatial correspondence between adjacent slices. An iterative algorithm is applied using the spatial and temporal image derivatives and a spatiotemporal smoothing step. Afterwards, the calculated velocity field is used to generate an interpolated image at the desired time by averaging intensities between corresponding points. Three quantitative measures are defined to evaluate the performance of the interpolation method.

Results:
The behaviorand capability of the algorithm is demonstrated by synthetic images. A population of 17 temporal and spatial image sequences are utilized to compare the optical flow-based interpolation method to linear and shape-based interpolation. The quantitative results show that the optical flow-based method outperforms the linear and shape-based interpolation statistically significantly.

Conclusions:
The interpolation method presented is able to generate image sequences with appropriate spatial or temporal resolution needed for image comparison, analysis or visualization tasks. Quantitative and qualitative measures extracted from synthetic phantoms and medical image data show that the new method definitely has advantages over linear and shape-based interpolation.
Ultrasound Cerebral Perfusion Analysis Based on a Mathematical Model for Diminution Harmonic Imaging
Authors: Meyer-Wiethe K. , Seidel G. , Aach T. , Kier C. 
Published: May 2007

Summary

Objectives:
Cerebral vascular diseases are detectable by CT/MRI-based methods. Drawbacks of these methods are that they are expensive, time-consuming and intolerable to critically ill patients. Ultrasound, as an inexpensive bedside method, promises to become an alternative. Among other harmonic imaging methods, the diminution harmonic imaging (DHI) method is known, which determines perfusion-related parameters by analyzing ultrasound contrast agent (UCA) diminution kinetics based on constant UCA infusion. The shortcoming of DHI is that the used mathematical model can only determine these parameters by least squares fitting the model onto the data.

Methods:
In this work, the underlying mathematical model is further developed such that it becomes possible to directly calculate the parameters from the image data. Furthermore, the new model offers an improved way to estimate the spatial distribution of the destruction coefficient necessary for accurately determining the destruction power of the ultrasound pulse on the contrast agent.

Results:
The direct calculation of the perfusion coefficient is much faster thanthe former fitting of the model. Perfusion as well as destruction coefficients are displayed as color-coded images. In an example, a region with perfusion deficits (as shown in a MR image of the same patient) is clearly identifiable.

Conclusions:
Displaying the parameters as color-coded images facilitates result interpretation for the diagnosing physician. The results are preliminary and still have to be validated, but they suggest that the new DHI model improves the significance of ultrasound as a diagnostic help.
Towards Fully Automatic Acquisition of Multimodal Cytopathological Microscopy Images with Autofocus and Scene Matching
Authors: Würflinger T. , Ropers S.-O. , Böcking A. , Aach T. , Bell A. A. 
Published: May 2007

Summary

Objectives:
To increase the chance for a cure, cancer must be detected as early as possible. This can be achieved with cytopathological diagnostic methods. For a further increase of the diagnostic accuracy of these methods we introduced the multimodal cell analysis, viz, cells on the slide have to be relocalized to enable successive analysis of identical cells in different stains. For practical reasons the relocalization step must be automated.

Methods:
For a fully automatic acquisition of successive cell images we use a passive autofocus that is adaptive to the material, i.e., to the cells, followed by a comparison of the scenes, i.e., the cell constellation, of two such obtained images from different stains. In case that no sub-scene match can be found the search is extended to the surrounding area. A set of 1 556 scenes from seven specimens have been subject to our algorithm. The automatically relocalized and acquired images from a second stain have been manually compared to the images from a first stain.

Results:
An overall relocalization rate of 85.4% is achieved. 14.3% of the images could not be relocalized and are lost for the following diagnostic process, while the critical case of erroneously matched images was observed in only 0.3% of cases.

Conclusions:
We could show that it is possible to automatically acquire images of successive stains of identical cells on cytopathological specimens. The method presented achieves acceptable relocalization rates. Wrong image acquisitions are very rare and can mostly be ascribed to images with single cells, i.e., without scene information.
Computer-assisted Diagnosis for Early Stage Pleural Mesothelioma
Authors: Jäger P. , Vogel S. , Knepper A. , Kraus T. , Aach T. , Chaisaowong K. 
Published: May 2007

Summary

Objectives:
Pleural thickenings as biomarker of exposure to asbestos may evolve into malignant pleural mesothelioma. Foritsearly stage, pleurectomy with perioperative treatment can reduce morbidity and mortality. The diagnosis is based on a visual investigation of CT images, which is a time-consuming and subjective procedure. Our aim is to develop an automatic image processing approach to detect and quantitatively assess pleural thickenings.

Methods:
We first segment the lung areas, and identify the pleural contours. A convexity model is then used together with a Hounsfield unit threshold to detect pleural thickenings. The assessment of the detected pleural thickenings is based on a spline-based model of the healthy pleura.

Results:
Tests were carried out on 14 data sets from three patients. In all cases, pleural contours were reliably identified, and pleural thickenings detected. PC-based Computation times were 85 min for a data set of 716 slices, 35 min for 401 slices, and 4 min for 75 slices, resulting in an average computation time of about 5.2 s per slice. Visualizations of pleurae and detected thickeningswere provided.

Conclusion:
Results obtained so far indicate that our approach is able to assist physicians in the tedious task of finding and quantifying pleural thickenings in CT data. In the next step, our system will undergo an evaluation in a clinical test setting using routine CT data to quantifyits performance.