The previously observed supraclavicular depot of brown adipose tissue (BAT) in adult humans was commonly believed to be the equivalent of the interscapular thermogenic organ of small mammals. This view was very recently disputed by Wu et al., based on the demonstration that this depot is made up by beige or brite brown adipocytes – a newly identified type of brown adipocyte distinct from the classical brown adipocyte that makes up the interscapular thermogenic organ of other mammals. A combination of high resolution imaging techniques, histological and biochemical analyses enabled us to provide evidence for an anatomically distinguishable interscapular BAT depot in human infants that consists of classical brown adipocytes, a cell type so far not proven to exist in humans. Based on these findings, we conclude that infants, as rodents, possess the bona fide interscapular BAT thermogenic organ made up by classical brown adipocytes essential for the survival of small mammals in a cold environment. 

Background

The openEHR project and the closely related ISO 13606 standard have defined structures   supporting the content of Electronic Health Records (EHRs). However, there is not   yet any finalized openEHR specification of a service interface to aid application   developers in creating, accessing, and storing the EHR content.

The aim of this paper is to explore how the Representational State Transfer (REST)   architectural style can be used as a basis for a platform-independent, HTTP-based   openEHR service interface. Associated benefits and tradeoffs of such a design are   also explored.

Results

The main contribution is the formalization of the openEHR storage, retrieval, and   version-handling semantics and related services into an implementable HTTP-based service   interface. The modular design makes it possible to prototype, test, replicate, distribute,   cache, and load-balance the system using ordinary web technology. Other contributions   are approaches to query and retrieval of the EHR content that takes caching, logging,   and distribution into account. Triggering on EHR change events is also explored.

A final contribution is an open source openEHR implementation using the above-mentioned   approaches to create LiU EEE, an educational EHR environment intended to help newcomers   and developers experiment with and learn about the archetype-based EHR approach and   enable rapid prototyping.

Conclusions

Using REST addressed many architectural concerns in a successful way, but an additional   messaging component was needed to address some architectural aspects. Many of our   approaches are likely of value to other archetype-based EHR implementations and may   contribute to associated service model specifications.

The aim of this study was to develop and evaluate a robust heartbeat detector for noisy electrocardiograms (ECGs) recorded with textile electrodes. We suggest a method based on weighted correlation in a multi-channel ECG to obtain a heartbeat detector. Signals were acquired during rest and at movements which simulate every day activities. From each recording a segment corresponding to a heartbeat was extracted and correlated with the whole signal. From the correlation data, heartbeat candidates were derived and weighted based on their variance similarity with the heartbeat model and previous heartbeats. Finally, the outputs of each channel were added to create the global output. The output was compared to the Pan Tompkins heartbeat detector. Results are promising for recordings at rest (sensitivity = 0.97, positive predictive value (PPV) = 0.97). For static muscle tension in the torso the results were much higher than the reference method (sensitivity = 0.77, PPV = 0.85). Corresponding values for the reference method were sensitivity = 0.96 and PPV = 0.95 at rest and sensitivity = 0.52 and PPV = 0.75 during muscle tension.

The multilinear least-squares (MLLS) problem is an extension of the linear leastsquares problem. The difference is that a multilinear operator is used in place of a matrix-vector product. The MLLS is typically a large-scale problem characterized by a large number of local minimizers. It originates, for instance, from the design of filter networks. We present a global search strategy that allows for moving from one local minimizer to a better one. The efficiency of this strategy is illustrated by results of numerical experiments performed for some problems related to the design of filter networks.

Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization- based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration. 

Background

Procedures documented by general practitioners in primary care have not been studied in relation to procedure coding systems. We aimed to describe procedures documented by Swedish general practitioners in electronic patient records and to compare them to the Swedish Classification of Health Interventions (KVÅ) and SNOMED CT.

Methods

Procedures in 200 record entries were identified, coded, assessed in relation to two procedure coding systems and analysed.

Results

417 procedures found in the 200 electronic patient record entries were coded with 36 different Classification of Health Interventions categories and 148 different SNOMED CT concepts. 22.8% of the procedures could not be coded with any Classification of Health Interventions category and 4.3% could not be coded with any SNOMED CT concept. 206 procedure-concept/category pairs were assessed as a complete match in SNOMED CT compared to 10 in the Classification of Health Interventions.

Conclusions

Procedures documented by general practitioners were present in nearly all electronic patient record entries. Almost all procedures could be coded using SNOMED CT.

Classification of Health Interventions covered the procedures to a lesser extent and with a much lower degree of concordance. SNOMED CT is a more flexible terminology system that can be used for different purposes for procedure coding in primary care.

Functional magnetic resonance imaging (fMRI) makes it possible to non-invasively measure brain activity with high spatial resolution.There are however a number of issues that have to be addressed. One is the large amount of spatio-temporal data that needsto be processed. In addition to the statistical analysis itself, several preprocessing steps, such as slice timing correction and motioncompensation, are normally applied. The high computational power of modern graphic cards has already successfully been used forMRI and fMRI. Going beyond the first published demonstration of GPU-based analysis of fMRI data, all the preprocessing stepsand two statistical approaches, the general linear model (GLM) and canonical correlation analysis (CCA), have been implementedon a GPU. For an fMRI dataset of typical size (80 volumes with 64 x 64 x 22 voxels), all the preprocessing takes about 0.5 s on theGPU, compared to 5 s with an optimized CPU implementation and 120 s with the commonly used statistical parametric mapping(SPM) software. A random permutation test with 10 000 permutations, with smoothing in each permutation, takes about 50 s ifthree GPUs are used, compared to 0.5 - 2.5 h with an optimized CPU implementation. The presented work will save time forresearchers and clinicians in their daily work and enables the use of more advanced analysis, such as non-parametric statistics, bothfor conventional fMRI and for real-time fMRI.

The use of image denoising techniques is an important part of many medical imaging applications. One common application isto improve the image quality of low-dose, i.e. noisy, computed tomography (CT) data. The medical imaging domain has seen atremendous development during the last decades. It is now possible to collect time resolved volumes, i.e. 4D data, with a number ofmodalities (e.g. ultrasound (US), CT, magnetic resonance imaging (MRI)). While 3D image denoising previously has been appliedto several volumes independently, there has not been much work done on true 4D image denoising, where the algorithm considersseveral volumes at the same time (and not a single volume at a time). By using all the dimensions, it is for example possibleto remove some of the time varying reconstruction artefacts that exist in CT volumes. The problem with 4D image denoising,compared to 2D and 3D denoising, is that the computational complexity increases exponentially.In this paper we describe a novel algorithm for true 4D image denoising, based on local adaptive filtering, and how to implementit on the graphics processing unit (GPU). The algorithm was applied to a 4D CT heart dataset of the resolution 512 x 512 x 445 x 20.The result is that the GPU can complete the denoising in about 25 minutes if spatial filtering is used and in about 8 minutes if FFTbased filtering is used. The CPU implementation requires several days of processing time for spatial filtering and about 50 minutesfor FFT based filtering. Fast spatial filtering makes it possible to apply the denoising algorithm to larger datasets (compared to ifFFT based filtering is used). The short processing time increases the clinical value of true 4D image denoising significantly.

Aim: The influences on the SNR of DENSE MRI of field strength, receiver coil sensitivity and choice of flip angle strategy have been previously investigated individually. In this study, all of these parameters have been investigated in the same setting, and a mutual comparison of their impact on SNR is presented.

Materials and methods: Ten healthy volunteers were imaged in a 1.5T and a 3T MRI system, using standard 5 or 6 channel cardiac coils as well as 32 channel coils, with four different excitation patterns. Variation of spatial coil sensitivity was assessed by regional SNR analysis.

Results: SNR ranging from 2.8 to 30.5 was found depending on the combination of excitation patterns, coil sensitivity and field strength. The SNR at 3T was 53 ± 26% higher than at 1.5T (p<0.001), whereas spatial differences of 59 ± 26% were found in the ventricle (p<0.001). 32 channel coils provided 52 ± 29% higher SNR compared to standard 5 or 6 channel coils (p<0.001). A fixed flip angle strategy provided an excess of 50% higher SNR in half of the imaged cardiac cycle compared to a sweeping flip angle strategy, and a single phase acquisition provided a six-fold increase of SNR compared to a cine acquisition.

Conclusion: The effect of field strength and receiver coil sensitivity influences the SNR with the same order of magnitude, whereas flip angle strategy can have a larger effect on SNR. Thus, careful choice of imaging hardware in combination with adaptation of the acquisition protocol is crucial in order to realize sufficient SNR in DENSE MRI.

Hypothesis: The structure of the mastoid air cells can be described by quantitative imaging analysis of high-resolution CT-scans, which may contribute to understand its function in normal and pathological ears. Background: Negative middle ear pressure is a common factor in middle ear diseases resulting from an imbalance between mastoid gas exchange and Eustachian tube function. While the Eustachian tube function has been the main focus of research, more recent studies indicate that the mastoid may play an active role in pressure regulation. The mastoid structure with numerous air cells reflects a large area to volume ratio (AV-ratio) adapted to efficient gas exchange. Imaging analysis applied to high resolution CT-scanning can describe quantitative measures, which may reveal important information about mastoid function and its role in healthy and diseased ears. Materials and methods: Quantitative analysis was performed on a series of unselected high resolution CT-scans (voxel size: 0.29 _ 0.29 _ 0.625 mm) from 36 ears in 24 patients. Area and volume were determined using Cavalieri’s method, i.e. by summing cross-sectional areas. The AV-ratio was computed for each scan. Results: Mean area was 69 cm² (range: 23–134cm²), mean volume was 4 cm³ (range: 1.3–10.8 cm³), and mean AV-ratio was 16 cm^-1 (range: 11.2–21.0 cm^-1). The area correlated linearly to the volume by A = 17.2*V-0.2. Conclusion: The area and volume values corresponded with previous studies, and the additional AV-ratio reflected the functional properties of the mastoid in terms of capability for gas exchange. Due to a series of similarities between structure and function of the lungs and mastoid, it seems likely to propose a tree-structure of dividing mastoid cells. In respiratory research, analysis describing the dimensions of series of bronchi generations has been applied, and based on current results; our aim of future research is to establish similar details of mastoid tree-structure. Funding source: Various private Danish funds.

Background Primary care (PC) in Sweden provides ambulatory and home health care outside hospitals. Within the County Council of Stockholm coding of diagnoses in PC is mandatory and is done by general practitioners (GPs) using a Swedish primary care version of the International Statistical Classification of Diseases version 10 (ICD-10). ICD-10 has a mono-hierarchical structure. SNOMED CT is poly-hierarchical and belongs to a new generation of terminology systems with attributes (characteristics) that connect concepts in SNOMED CT and build relationships. Mapping terminologies and classifications has been pointed out as a way to attain additional advantages in describing and documenting healthcare data. A poly-hierarchical system supports the representation and aggregation of healthcare data on the basis of specific medical aspects and various levels of clinical detail. Objective To describe and compare diagnoses and health problems in KSH97-P/ICD-10 and SNOMED CT using primary care diagnostic data and to explore and exemplify complementary aggregations of diagnoses and health problems generated from a mapping to SNOMED CT. Methods We used diagnostic data collected throughout 2006 and coded in electronic patient records (EPRs) and a mapping from KSH97-P/ICD-10 to SNOMED CT to aggregate the diagnostic data with SNOMED CT defining hierarchical relationship Is a and selected attribute relationships. Results The chapter level comparison between ICD-10 and SNOMED CT showed minor differences except for infectious and digestive system disorders. The relationships chosen aggregated the diagnostic data to 2861 concepts showing a multidimensional view on different medical and specific levels and also including clinically relevant characteristics through attribute relationships. Conclusions SNOMED CT provides a different view of diagnoses and health problems on a chapter level and adds significant new views of the clinical data with aggregations generated from SNOMED CT Is a and attribute relationships. A broader use of SNOMED CT is therefore of importance when describing and developing primary care. © 2010 PHCSG, British Computer Society.

The segmentation of blood vessels is a common problem in medical imagingand various applications are found in diagnostics, surgical planning, trainingand more. Among many dierent techniques, the use of multiple scales andline detectors is a popular approach. However, the typical line lters usedare sensitive to intensity variations and do not target the detection of vesselwalls explicitly. In this article, we combine both line and edge detection usingquadrature lters across multiple scales. The lter result gives well denedvessels as linear structures, while distinct edges facilitate a robust segmentation.We apply the lter output to energy optimization techniques for segmentationand show promising results in 2D and 3D to illustrate the behavior of ourmethod. The conference version of this article received the best paper award inthe bioinformatics and biomedical applications track at ICPR 2008.

Background: Exchange of Electronic Health Record (EHR) data between systems from different suppliers is a major challenge. EHR communication based on archetype methodology has been developed by openEHR and CEN/ISO. The experience of using archetypes in deployed EHR systems is quite limited today. Currently deployed EHR systems with large user bases have their own proprietary way of representing clinical content using various models. This study was designed to investigate the feasibility of representing EHR content models from a regional EHR system as openEHR archetypes and inversely to convert archetypes to the proprietary format. Methods: The openEHR EHR Reference Model (RM) and Archetype Model (AM) specifications were used. The template model of the Cambio COSMIC, a regional EHR product from Sweden, was analyzed and compared to the openEHR RM and AM. This study was focused on the convertibility of the EHR semantic models. A semantic mapping between the openEHR RM/AM and the COSMIC template model was produced and used as the basis for developing prototype software that performs automated bidirectional conversion between openEHR archetypes and COSMIC templates. Results: Automated bi-directional conversion between openEHR archetype format and COSMIC template format has been achieved. Several archetypes from the openEHR Clinical Knowledge Repository have been imported into COSMIC, preserving most of the structural and terminology related constraints. COSMIC templates from a large regional installation were successfully converted into the openEHR archetype format. The conversion from the COSMIC templates into archetype format preserves nearly all structural and semantic definitions of the original content models. A strategy of gradually adding archetype support to legacy EHR systems was formulated in order to allow sharing of clinical content models defined using different formats. Conclusion: The openEHR RM and AM are expressive enough to represent the existing clinical content models from the template based EHR system tested and legacy content models can automatically be converted to archetype format for sharing of knowledge. With some limitations, internationally available archetypes could be converted to the legacy EHR models. Archetype support can be added to legacy EHR systems in an incremental way allowing a migration path to interoperability based on standards.

Purpose: To report initial results from a European ICU surveillance programme focussing on antibiotic consumption, microbial resistance and infection control.

Methods: Thirty-five ICUs participated during 2005. Microbial resistance, antibiotic consumption and infection control stewardship measures were entered locally into a web-application. Results were validated locally, aggregated by project leaders and fed back to support local audit and benchmarking.

Results: Median (range) antibiotic consumption was 1,254 (range 348–4,992) DDD per 1,000 occupied bed days. The proportion of MRSA was median 11.6% (range 0–100), for ESBL phenotype of E. coli and K. pneumoniae 3.9% (0–80) and 14.3% (0–77.8) respectively, and for carbapenem-resistant P. aeruginosa 22.5% (0–100). Screening on admission for alert pathogens was commonly omitted, and there was a lack of single rooms for isolation.

Conclusions: The surveillance programme demonstrated wide variation in antibiotic consumption, microbial resistance and infection control measures. The programme may, by providing rapid access to aggregated results, promote local and regional audit and benchmarking of antibiotic use and infection control practices.

Background: Earlier studies have reported that hippocampal atrophy can to some extent predict which patients with mild cognitive impairment (MCI) will subsequently convert to dementia, and that converters have an enhanced rate of hippocampal volume loss. Objective: To further validate the hypothesis that hippocampal atrophy predicts conversion from MCI to dementia, to relate baseline hippocampal volume to different forms of dementia, and to investigate the role of hippocampal side differences and rate of volume loss over time. Patients: The subjects (N = 68) include patients with MCI at baseline and progression to dementia at the two-year follow-up (N = 21), stable MCI patients (N = 21), and controls (N = 26). Among the progressing patients, 13 were diagnosed as having AD. Methods: The Göteborg MCI study is a clinically based longitudinal study with biannual clinical assessments. Hippocampal volumetry was performed manually on the MRI investigations at baseline and at the two-year follow-up. Results: Hippocampal volumetry could predict conversion to dementia in both the AD and the non-AD subgroup of converters. Left hippocampal volume in particular discriminated between converting and stable MCI. Cut off points for individual discrimination were shown to be potentially useful. The converting MCI group had a significantly higher rate of hippocampal volume loss as compared to the stable MCI group. Conclusions: In MCI patients, hippocampal volumetry at baseline gives prognostic information about possible development of AD and non-AD dementia. Contrary to earlier studies, we found that left hippocampal volume has the best predictive power. Reliable predictions appear to be possible in many individual cases. © 2008 Elsevier B.V. All rights reserved.

Background Statistics from primary health care in Sweden, as well as from other Nordic countries, have been sparse. The electronic patient records (EPR) will be an increasingly important source of clinical information. The aim of this study was to investigate types of encounters, managed diseases and health problems, and characteristics of patients and general practitioners (GPs) in everyday general practice using EPR.

Methods A multi-centre, cross-sectional database study of EPR in primary health care in Stockholm, Sweden. Twenty-six randomly selected GPs with 20 randomly selected encounters each. Main outcome measures were the number and distribution of diseases and health problems, age and gender of patients and GPs, and type of encounter.

Results The mean age of the patients was 51.2 years, 30.2% were aged 75 years or older, and 57.5% were women. The mean number of managed problems per encounter was 1.4. The most common specific diagnoses were essential hypertension (9.3% of the encounters) and acute upper respiratory infections (8.8%). Older patients had more health problems in each encounter (P = 0.000001). GPs differed regarding the characteristics of their patients, including sex, age and number of health problems managed at each encounter. The patients of different GPs differed regarding sex, age and number of health problems managed. Female and male patients had different diagnostic panoramas and they had a tendency to encounter a GP of the same sex (odds ratio 1.5, P = 0.053).

Conclusions We found that two diagnoses (essential hypertension and acute upper respiratory infections), four diagnostic groups, women and the elderly are predominant. Female and male patients have different diagnostic panoramas and they have a tendency to encounter a GP of the same sex. GPs differ regarding the characteristics of their patients, including sex, age and number of health problems managed at each encounter.

We present a class of adaptive filtering techniques of functional magnetic resonance imaging (fMRI) data related to bilateral filtering. This class of methods average activities in consistent regions rather than regions that maximize correlation with a BOLD model. Similarity measures based on signal similarity and anatomical similarity are discussed and compared experimentally to standard linear low pass filtering. It is demonstrated that adaptive filtering provides improved detection of activated regions.

Background: The guideline for postmastectomy radiotherapy (PMRT), which is prescribed to reduce recurrence of breast cancer in the chest wall and improve overall survival, is not always followed. Identifying and extracting important patterns of non-compliance are crucial in maintaining the quality of care in Oncology.

Methods: Analysis of 759 patients with malignant breast cancer using decision tree induction (DTI) found patterns of non-compliance with the guideline. The PMRT guideline was used to separate cases according to the recommendation to receive or not receive PMRT. The two groups of patients were analyzed separately. Resulting patterns were transformed into rules that were then compared with the reasons that were extracted by manual inspection of records for the non-compliant cases.

Results: Analyzing patients in the group who should receive PMRT according to the guideline did not result in a robust decision tree. However, classification of the other group, patients who should not receive PMRT treatment according to the guideline, resulted in a tree with nine leaves and three of them were representing non-compliance with the guideline. In a comparison between rules resulting from these three non-compliant patterns and manual inspection of patient records, the following was found:

In the decision tree, presence of perigland growth is the most important variable followed by number of malignantly invaded lymph nodes and level of Progesterone receptor. DNA index, age, size of the tumor and level of Estrogen receptor are also involved but with less importance. From manual inspection of the cases, the most frequent pattern for non-compliance is age above the threshold followed by near cut-off values for risk factors and unknown reasons.

Conclusion: Comparison of patterns of non-compliance acquired from data mining and manual inspection of patient records demonstrates that not all of the non-compliances are repetitive or important. There are some overlaps between important variables acquired from manual inspection of patient records and data mining but they are not identical. Data mining can highlight non-compliance patterns valuable for guideline authors and for medical audit. Improving guidelines by using feedback from data mining can improve the quality of care in oncology.

Background: Appropriate pain assessment is a necessary prerequisite for adequate pain control. A way to follow-up on the pain is to let patients use paper-based or electronic pain diaries.

Purpose: The aim was to explore and describe palliative home care patients’ experiences of assessing their pain by using a pain diary together with digital pen and mobile Internet technology.

Methods: A system for the follow-up of pain treatment was developed and evaluated by means of a qualitative cross-case content analysis. From December 2002 until September 2003 12 palliative patients, who initially assessed VAS pain ≥ 35 mm (VAS 0–100 mm), used the system. Patients reported their momentary pain intensity and the number of consumed extra doses of analgesics three times per day. Analysis data were collected from interviews with patients and spouses, questionnaires, medical records, and the system log.

Results: In spite of severe illness and difficulties in comprehending the technology and system intervention, patients found the pain diary and digital pen easy to use for pain assessment. Patients took a greater part in their own care and experienced an improved contact with their caregivers, which led to a sense of increased security. The medical records showed a quick response to variations in the patients’ health status by means of changes in medical treatment.

Conclusions: The pain assessment system for palliative patients using pain diaries together with digital pen and wireless Internet technology constitutes an effortless method and has positive influences on the care.

Background. Automatic word alignment of parallel texts with the same content in different languages is among other things used to generate dictionaries for new translations. The quality of the generated word alignment depends on the quality of the input resources. In this paper we report on automatic word alignment of the English and Swedish versions of the medical terminology systems ICD-10, ICF, NCSP, KSH97-P and parts of MeSH and how the terminology systems and type of resources influence the quality. Methods. We automatically word aligned the terminology systems using static resources, like dictionaries, statistical resources, like statistically derived dictionaries, and training resources, which were generated from manual word alignment. We varied which part of the terminology systems that we used to generate the resources, which parts that we word aligned and which types of resources we used in the alignment process to explore the influence the different terminology systems and resources have on the recall and precision. After the analysis, we used the best configuration of the automatic word alignment for generation of candidate term pairs. We then manually verified the candidate term pairs and included the correct pairs in an English-Swedish dictionary. Results. The results indicate that more resources and resource types give better results but the size of the parts used to generate the resources only partly affects the quality. The most generally useful resources were generated from ICD-10 and resources generated from MeSH were not as general as other resources. Systematic inter-language differences in the structure of the terminology system rubrics make the rubrics harder to align. Manually created training resources give nearly as good results as a union of static resources, statistical resources and training resources and noticeably better results than a union of static resources and statistical resources. The verified English-Swedish dictionary contains 24,000 term pairs in base forms. Conclusion. More resources give better results in the automatic word alignment, but some resources only give small improvements. The most important type of resource is training and the most general resources were generated from ICD-10. © 2007 Nyström et al, licensee BioMed Central Ltd.

This paper presents a novel method for performing fast estimation of data samples on a desired output grid from samples on an irregularly sampled grid. The output signal is estimated using integration of signals over a neighbourhood employing a local model of the signal using discrete filters. The strength of the method is demonstrated in motion compensation examples by comparing to traditional techniques.

Breast malignancy is the second most common cause of cancer death among women in Western countries. Identifying high-risk patients is vital in order to provide them with specialized treatment. In some situations, such as when access to experienced oncologists is not possible, decision support methods can be helpful in predicting the recurrence of cancer. Three thousand six hundred ninety-nine breast cancer patients admitted in south-east Sweden from 1986 to 1995 were studied. A decision tree was trained with all patients except for 100 cases and tested with those 100 cases. Two domain experts were asked for their opinions about the probability of recurrence of a certain outcome for these 100 patients. ROC curves, area under the ROC curves, and calibration for predictions were computed and compared. After comparing the predictions from a model built by data mining with predictions made by two domain experts, no significant differences were noted. In situations where experienced oncologists are not available, predictive models created with data mining techniques can be used to support physicians in decision making with acceptable accuracy.

Frequent pain assessment by the use of pain diaries for the follow-up of pain treatment can facilitate the caregivers' work with pain control in home health care. The aim was to explore and describe professional caregivers' experiences of palliative home health-care patients' use of pain diaries and digital pen technology for frequent pain assessment. A system for the follow-up of pain treatment was implemented in routine care and evaluated by means of a qualitative content analysis. Three nurses, two physicians and one secretary were interviewed. Additional analysis data were collected from patients' medical records, and the system log. The caregivers showed a shifting outlook towards the pain-assessment method, an initial cautious outlook due to low expectations of the patients' abilities to use the pain assessment method. Despite this, the caregivers experienced positive outcomes in terms of an increased awareness of pain, and positive patient influences including increased participation in their care, increased security, and improved changes in pain treatment as a response to reported pain assessments. Pain assessment by the use of pain diaries and digital pen technology has positive influences on palliative home-care patients and supports the caregivers' focus on the pain.

Blood gas changes occurring in the lung undergo delay and damping on their way to a peripheral artery sampling site. Knowledge of the time components of circulatory transfer is important for the understanding of respiratory control and cardiovascular reflexes in response to blood gas transients. Providing steady state with regard to V̇A/ Q̇ distribution, cardiac output and peripheral blood flow, the relationship between the time courses of small end-tidal and peripheral PO2 changes is determined by the transfer function of the interposed vascular segment. This transfer function, expressed as delay time TD and mean transit time (MTT), was measured in six well-trained subjects, allowing the calculation of arterial time-courses from end-tidal to the reverse. They were studied at rest and during four different dynamic leg exercise intensities in the supine posture. TD and MTT amounted to 15.8 ± 1.7 (mean ± SEM) and 18.3 ± 2.1 s at rest and were shortened to 7.7 ± 0.6 and 11.5 ± 1.8 s during exercise at 170 W. The shortening of TD and MTT did not appear to be simply an inverse function of cardiac output, suggesting that the shortening occurs in the central circulatory segment but not in the arm segment. © Springer-Verlag 2006.

Purpose

To develop a new volumetric imaging method resolved over both the cardiac and respiratory cycles, to enable future physiological and pathophysiological studies of respiratory-related cardiac motion.

Materials and Methods

An acquisition scheme is proposed whereby the k-space acquisition order is controlled in real-time by the current cardiac and respiratory phases. To reduce eddy-current effects induced by sudden jumps in k-space, the acquisition order is further optimized by the use of a Hilbert curve trajectory in the k_y-k_z plane. A complete three-dimensional (3D) k-space is acquired for all combinations of cardiac and respiratory phases, yielding a five-dimensional (5D) data set after retrospective reconstruction.

Results

Left (LV) and right ventricular (RV) wall excursion was measured in a healthy volunteer. Diastolic LV diameter was shown to increase during expiration and decrease during inspiration, as expected from previous echocardiography studies. The LV volume was estimated for all cardiac and respiratory phases with the use of a fully 3D segmentation tool. The results confirmed that the diastolic LV volume increased during expiration and decreased during inspiration.

Conclusion

With its ability to measure motion anywhere in the heart, the described technique provides a promising approach for in-depth description of interventricular coupling, including 3D ventricular volumes, during both the cardiac and respiratory cycles.

The paper discusses which properties of filter sets used in local structure estimation that are the most important. Answers are provided via the introduction of a number of fundamental invariances. Mathematical formulations corresponding to the required invariances leads up to the introduction of a new class of filter sets termed loglets. Loglets are polar separable and have excellent uncertainty properties. The directional part uses a spherical harmonics basis. Using loglets it is shown how the concepts of quadrature and phase can be defined in n-dimensions. It is also shown how a reliable measure of the certainty of the estimate can be obtained by finding the deviation from the signal model manifold. Local structure analysis algorithms are quite complex and involve a lot more than the filters used. This makes comparisons difficult to interpret from a filter point of view. To reduce the number 'free' parameters and target the filter design aspects a number of simple 2D experiments have been carried out. The evaluation supports the claim that loglets are preferable to other designs. In particular it is demonstrated that the loglet approach outperforms a Gaussian derivative approach in resolution and robustness. (c) 2005 Elsevier B.V. All rights reserved.

[No abstract available]

Background

A common approach in exploring register data is to find relationships between outcomes and predictors by using multiple regression analysis (MRA). If there is more than one outcome variable, the analysis must then be repeated, and the results combined in some arbitrary fashion. In contrast, Canonical Correlation Analysis (CCA) has the ability to analyze multiple outcomes at the same time.

One essential outcome after breast cancer treatment is recurrence of the disease. It is important to understand the relationship between different predictors and recurrence, including the time interval until recurrence. This study describes the application of CCA to find important predictors for two different outcomes for breast cancer patients, loco-regional recurrence and occurrence of distant metastasis and to decrease the number of variables in the sets of predictors and outcomes without decreasing the predictive strength of the model.

Methods

Data for 637 malignant breast cancer patients admitted in the south-east region of Sweden were analyzed. By using CCA and looking at the structure coefficients (loadings), relationships between tumor specifications and the two outcomes during different time intervals were analyzed and a correlation model was built.

Results

The analysis successfully detected known predictors for breast cancer recurrence during the first two years and distant metastasis 2–4 years after diagnosis. Nottingham Histologic Grading (NHG) was the most important predictor, while age of the patient at the time of diagnosis was not an important predictor.

Conclusion

In cancer registers with high dimensionality, CCA can be used for identifying the importance of risk factors for breast cancer recurrence. This technique can result in a model ready for further processing by data mining methods through reducing the number of variables to important ones.

In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

As a way of exploring differences between medical domains regarding management of urinary tract infections, we investigated the MEDLINE® database for differences in indexing patterns. Further, our intention was to assess the MEDLINE® database as a source for studying medical domains. We examined the use of main headings, subheadings and the level of main headings in six medical domains that manage urinary tract infections. Many intuitive but also some counterintuitive results were found indicating that the MEDLINE® database is difficult to use for studying medical domains mainly due to unclear semantics both in the headings and the indexing process, which results in variability in indexing. This variability probably hides sig-nificant results. We also conclude that the differences found indicate that in addition to differences between domains, there are also large variations within domains.

Local infection control measures, antibiotic consumption and patient demographics from 1999-2000 together with bacteriological analyses were investigated in 29 ICUs participating in the ICU-STRAMA programme. The median antibiotic consumption per ICU was 1147 (range 605-2143) daily doses per 1000 occupied bed d (DDD₁₀₀₀). Antibiotics to which >90% of isolates of an organism were susceptible were defined as treatment alternatives (TA₉₀). The mean number of TA₉₀ was low (1-2 per organism) for Enterococcus faecium (vancomycin:VAN), coagulase negative staphylococci (VAN), Pseudomonas aeruginosa (ceftazidime:CTZ, netilmicin: NET) and Stenotrophomonas maltophilia (CTZ, trimethoprim-sulfamethoxazole: TSU), but higher (3-7) for Acinetobacter spp. (imipenem:IMI, NET, TSU), Enterococcus faecalis (ampicillin:AMP, IMI, VAN), Serratia spp. (ciprofloxacin:CIP, IMI, NET), Enterobacter spp. (CIP, IMI, NET, TSU), E. coli (cefuroxime:CXM, cefotaxime/ceftazidime:CTX/CTZ, CIP, IMI, NET, piperacillin-tazobactam:PTZ, TSU), Klebsiella spp. (CTX/CTZ CIP, IMI, NET, PTZ, TSU) and Staphylococcus aureus (clindamycin, fusidic acid, NET, oxacillin, rifampicin, VAN). Of S. aureus isolates 2% were MRSA. Facilities for alcohol hand disinfection at each bed were available in 96% of the ICUs. The numbers of TA₉₀ available were apparently higher than in ICUs in southern Europe and the US, despite a relatively high antibiotic consumption. This may be due to a moderate ecological impact of the used agents and the infection control routines in Swedish ICUs.

Objective: The Glasgow Coma Scale (GCS) is a well-known source of error in outcome prediction models. We compared assessment of cerebral responsiveness with the GCS and the Reaction Level Scale (RLS) in two otherwise similar outcome prediction models. Design and setting: Prospective, observational study in a general intensive care unit. Patients and participants: All admissions of patients with or at risk of developing impaired brain function between 1997 and 1998 (n=534). Measurements and results: Admissions were scored by RLS and APACHE II (includes scoring with the GCS). The RLS scores were transformed to APACHE II central nervous system scores according to a predetermined protocol. APACHE II estimated probability of death was calculated conventionally with the GCS and the RLS. Vital status 90 days after admission was secured from a national database. Bias and precision was 0.5% and 16.6%, respectively. The area under receiver operating characteristic curves was slightly but significantly greater with the RLS-based APACHE 11 model than with the GCS-based model (0.92 vs. 0.90). Discrimination was improved primarily in admissions with low and intermediate probability of death. Conclusions: Scoring of cerebral responsiveness with the RLS instead of the GCS was associated with minimal bias of the APACHE 11 probability of death estimate. Assessment of consciousness in critically ill with the RLS deserves further evaluation.

Objectives: The aim of this study was to examine priority setting for coronary artery bypass surgery, and to provide an overview of decisions and rationales used in clinical practice. Method: Questionnaires were sent to all permanently employed cardiologists, cardiothoracic surgeons, and anaesthesiologists at nine Swedish hospitals performing adult cardiothoracic surgery. Results: A total of 208 physicians responded (a 44% return rate). There was considerable agreement concerning the criteria that should be used to set priorities for coronary artery bypass interventions (clusters of factors in synthesis). However, there was a lack of accord regarding the use of national guidelines for priority setting and risk indexes. Conclusions: Basic training and the strong support of ethical principles in priority setting are lacking. The respondents indicated a need for clearer guidelines and an open dialogue or discussion. The lack of generally acknowledged plans and guidelines for priority setting may result in unequal, conditional, and unfair treatment.

Objective - To investigate textual content, health problems and diagnostic codes in everyday electronic patient records. Design - Retrospective and observational database study. Setting - Primary health care in Stockholm. Subjects - Twenty randomly selected general practitioners with 20 records each. Main outcome measures - The frequency of use of problem-oriented medical records. The number of words, problems and diagnostic codes. The completeness and correctness of the diagnostic codes. Results - About 14.5% of 400 studied records were problem-oriented. The mean number of words per record was 99.4, and the mean number of problems managed per record was 1.2. On average, there were 1.1 diagnostic codes per record and this differed widely among GPs and also among the electronic patient record systems. The mean number of codes per problem was 0.9, and the proportion of correct codes was 97.4%. Conclusions - The electronic patient records in general practice in Stockholm have an extensive textual content. A vast majority of the problems are coded and the completeness and correctness of diagnostic codes are high. It seems that problem-oriented electronic patient record systems enforce coding activities. It is feasible to establish a database of diagnostic data for research and health care planning based on electronic patient records.

Objective: To investigate necessary conditions for the establishment of a database of diseases and health problems for research and health care planning, based on electronic patient records in everyday clinical use among general practitioners (GPs). Design: Postal questionnaire study. Setting: Primary health care in Sweden. Subjects: Three hundred randomly selected GPs. Main outcome measures: Degree of computerisation of patient records. User frequency and characteristics of diagnosis classification systems and coding tools. Frequency of coding activities and retrieval of codes, and related attitudes. Opinions on a primary health care version of ICD-10. Results: A total of 184 GPs (61% of the 300 GPs) were included in the study. About 92% used an electronic record system, some type of diagnostic classification was used by 93%, and ICD based classifications by 88%. The classification in use was computerised for 74%. Mainly simple tools were used to retrieve diagnostic codes. About 76% of GPs reported classifying at least one symptom or disease per encounter. The codes were retrieved 'once a month' or more by 19%. Classification of diseases was considered important for follow-up by 83%, and for the care of the patient by 75% of the GPs. The primary health care version of ICD-10 with a total of 972 codes was considered too limited in size by 31%. Conclusion: Electronic patient records in everyday clinical use in Swedish general practice provide several fundamentals for a database of diagnostic data. However, there are several barriers to the establishment of such a database that is both valid and reliable. ⌐ 2002 Elsevier Science Ireland Ltd. All rights reserved.

Background: The purpose of this work was to study usage of antibiotics, its possible determinants, and patterns of bacterial resistance in Swedish intensive care units (ICUs).

Methods: Prospectively collected data on species and antibiotic resistance of clinical isolates and antibiotic consumption specific to each ICU in 1999 were analyzed together with answers to a questionnaire. Antibiotic usage was measured as defined daily doses per 1000 occupied bed days (DDD₁₀₀₀).

Results: Data were obtained for 38 ICUs providing services to a population of approximately 6 million. The median antibiotic consumption was 1257 DDD₁₀₀₀ (range 584–2415) and correlated with the length of stay but not with the illness severity score or the ICU category. Antibiotic consumption was higher in the ICUs lacking bedside devices for hand disinfection (2193 vs. 1214 DDD₁₀₀₀, p=0.05). In the ICUs with a specialist in infectious diseases responsible for antibiotic treatment the consumption pattern was different only for use of glycopeptides (58% lower usage than in other ICUs: 26 vs. 11 DDD_1000,P=0.02). Only 21% of the ICUs had a written guideline on the use of antibiotics, 57% received information on antibiotic usage at least every 3 months and 22% received aggregated resistance data annually. Clinically significant antimicrobial resistance was found among Enterbacter spp. to cephalosporins and among Enterococcus spp. to ampicillin.

Conclusions: Availability of hand disinfection equipment at each bed and a specialist in infectious diseases responsible for antibiotic treatment were factors that correlated with lower antibiotic consumption in Swedish ICUs, whereas patient-related factors were not associated with antibiotic usage.

Accurate localization of minimally invasive devices is critical to the success of interventional procedures. Device orientation and tip position are two of the most important pieces of information needed to define device location for magnetic resonance imaging (MRI)-guided interventional procedures. While a single one-element micro coil incorporated into an interventional device has proven to be effective in some applications, it can only supply tip position information. However, multiple positions on the device are necessary to also determine its orientation. For this purpose, a novel single micro coil design with three separate winding elements that provides both the device orientation and tip position is described in this study. Definition of MR scan planes, by using the device orientation and the target tissue location, permits automatic tracking of the insertion of the device. Furthermore, devices that include this coil design are permitted to bend to a limited extent. This makes the micro coil design appropriate for many flexible interventional devices. Reliable near-real-time tracking of three points on an interventional device is demonstrated on a 0.2T MRI system with modest gradient performance. Phantom and in vivo animal experiments are used to demonstrate the utility of this new coil design. © 2001 Wiley-Liss, Inc.

Digitized data from CTG (cardiotocography) measurements (fetal heart rate and uterine contractions) have been used for categorization of typical heart rate patterns before and during delivery. Short time series of CTG data, about 7 min duration, have been used in the categorization process. In the first part of the study, selected CTG data corresponding to 10 typical cases were used for purely auto associative unsupervised training of a Self-Organizing Map Neural Network (SOM). The network may then be used for objective categorization of CTG patterns through the map coordinates produced by the network. The SOM coordinates were then compared. In the second part of the study, a hybrid neural network consisting of a SOM network and a Back-Propagation network (BP) was trained with data corresponding to a number of basic heart rate patterns as described by eight manually selected indices. Test data (different than the training data) were then used to check the performance of the network. The present study shows that the categorization process, in which neural networks were used, can be reliable and agree well with the manual categorization. Since the categorization by neural networks is very fast and does not involve human efforts, it may be useful in patient monitoring.

Implementation of problem lists and their relation to standardized coding systems have been approached and analysed in different ways. Most evaluations concern quantitative aspects such as content coverage in a specific domain. In order to reveal the qualitative aspects of diagnostic coding, medical record texts from primary health care encounters were compared with terms from a coding system that was used for describing them statistically. The records were coded by six general practitioners, and in some cases, an applied diagnostic term was found within the text, while other record text-coding system relationships were categorized as synonyms, alternative terms, and interpretations. Thus, the categories roughly corresponded to a measure of semantic distance between the terms in the record text and the rubrics of the coding system, and there was a correlation between semantic distance and inter-rater agreement. The subcategories of this scheme corresponded fairly well to recently published desiderata for clinical terminology servers, including functionality such as word normalization and spelling correction. However, not all problems could have been automatically coded by means of lexical methods, which can be partly explained by the fact that diagnostic coding also relies on clinical knowledge. In addition, proper automation relies on context representation within the records.

Objectives: Sternal wound complications often have a late onset and are detected after patients are discharged from the hospital. In an effort to catch all sternal wound complications, different postdischarge surveillance methods have to be used. Together with this long-term follow-up an analysis of risk factors may help to identify patients at risk and can lead to more effective preventive and control measures. Methods: This retrospective study of 3008 adult patients who underwent consecutive cardiac surgery from January 1996 through September 1999 at Link÷ping University Hospital, Sweden, evaluated 42 potential risk factors by univariate analysis followed by backward stepwise multivariate logistic regression analysis. Results: Two-thirds of the 291 (9.7%) sternal wound complications that occurred were identified after discharge. Of the 291 patients, 47 (1.6%) had deep sternal infections, 50 (1.7%) had postoperative mediastinitis, and 194 (6.4%) had superficial sternal wound complications. Twenty-three variables were selected by univariate analysis (P<0.15) and included in a multivariate analysis where eight variables emerged as significant (P<0.05). Preoperative risk factors for deep sternal infections/mediastinitis were obesity, insulin-dependent diabetes, smoking, peripheral vascular disease, and high New York Heart Association score. An intraoperative risk factor was bilateral use of internal mammary arteries, and a postoperative risk factor was prolonged ventilator support. Risk factors for superficial sternal wound complications were obesity, and an age of <75 years. The 30 day mortality was 2.7% for patients without sternal wound complications and 2/291 (0.7%) for all patients with sternal wound complications, 0.5% for superficial sternal wound complications, and 1.0% for deep sternal infections/mediastinitis. The 1 year mortality rate was 4.8% for patients without sternal wound complications and 11/291 (3.8%) for patients with sternal wound complications, 2.1% for superficial sternal wound complications, and 7.2% for deep sternal infections/mediastinitis. Conclusions: The risk factors found in this study have been detected and reported in previous studies. The predictive ability was stronger though for deep sternal infections/mediastinitis (those needing surgical revisions) than for superficial sternal wound complications. Earlier recognition of sternal wound complications and aggressive treatment have probably contributed to the relatively low mortality rate seen in this study. Copyright ⌐ 2001 Elsevier Science B.V.

If computer-stored information is to be useful for purposes other than patient care, reliability of the data is of utmost importance. In primary healthcare settings, however, it has been found to be poor. This paper presents a study on the influence of coding tools on reliability and user acceptance. Six general practitioners coded 152 medical problems each by means of three versions of ICD-10, one with a compositional structure. At code level the reliability was poor and was almost identical when the three versions were compared. At aggregated level the reliability was good and somewhat better in the compositional structure. Ideas for improved user acceptance arose, and the study explored the need for several different tools to retrieve diagnostic codes.

The objective of this study was to examine a design for a World Wide Web-based decision-support system in use by clinically active physicians. A prototype implementation of the design concerned management of infective endocarditis patient cases. The design was based on an integration of hypertext and rule-based knowledge. In the study sessions, physicians in the field of internal medicine worked on managing authentic patient cases in a laboratory setting. Data was collected from interviews with the physicians using video recordings and stimulated recall technique. The qualitative data was analysed according to the constant comparative method in order to develop a model of the physicians' usage of the system. The resulting model describes perceived contributions and criteria for usefulness of the system. The ways the physicians used the system showed that it was able to provide patient-specific support for confirming clinical decisions, for higher-level patient management, and for preparing for and initiating expert consultations. Users also stated that new medical knowledge could be gained as a side effect of using the system.

One of the problems in the management of the diabetic patient is to balance the dose of insulin without exactly knowing how the patient's blood glucose concentration will respond. Being able to predict the blood glucose level would simplify the management. This paper describes an attempt to predict blood glucose levels using a hybrid AI technique combining the principal component method and neural networks. With this approach, no complicated models or algorithms need be considered. The results obtained from this fairly simple model show a correlation coefficient of 0.76 between the observed and the predicted values during the first 15 days of prediction. By using this technique, all the factors affecting this patient's blood glucose level are considered, since they are integrated in the data collected during this time period. It must be emphasized that the present method results in an individual model, valid for that particular patient under a limited period of time. However, the method itself has general validity, since the blood glucose variations over time have similar properties in any diabetic patient.

Objective: to identify and link populations and individuals that live within high risk areas. Design: census registers and disease registers which contain data on individuals can only give aggregate statistics relating to postal code districts, town, county or state boundaries. However environmental risk factors rarely, if ever, respect these man-made boundaries. What is needed is a method to rapidly identify individuals who may live within a described area or region and to further identify the disease(s) occurring among these individuals and/or in these areas. Method: this paper describes a method for linking the standard registers available in Sweden, notably the residence-property addresses they contain and the geographical coordinate setting of these, to map the population as a point coverage. Using standard GIS methods this coverage could be linked, merged or intersected with any other map to create new subsets of population. Representation of populations down to the individual level by automatised spatialisation of available census data is in its simplicity a new informatics method which in the designated GIS medium adds a new power of resolution. Results: we demonstrate this using the radon maps provided by the local communes. The Swedish annual population registration records of 1991 for the county ofÖstergötland and the property register available at the Central Statistical Bureau of Sweden formed the main data sources. By coupling the address in the population register to the property register each individual was mapped to the centroid of a property. By intersecting the population coverage with the radon maps, the population living in high, normal or low risk areas was identified and then analysed and stratified by commune, sex and age. The resulting tables can be linked to other databases, e.g. disease registers, to visualise and analyse geographical and related patterns. The methodology can be adapted for use with any other environmental map or small area. It can also be expanded to the fourth dimension by linking likewise available migration information to generate immediately coordinate-set, accumulated exposition and similar data.

Lack of an agreed infrastructure for terminology is identified as one of the major barriers to interchange of knowledge modules and integration of knowledge bases with other clinical information systems. The goal of the GALEN project is to bridge this gap between different terminology systems through the construction of a terminology server, which is based on a rich conceptual model with mapping facilities to natural language expressions and coding schemas. The long term goal is to support communication between medical information systems. Arden Syntax is a standard format for the creation of knowledge modules, with sharability as one of the main objectives. Since Arden Syntax is based on a data-driven approach, the data items used need to be adapted to locally available terminology. The GALEN approach appears to be complementary to Arden Syntax and to the development of sharable knowledge modules. The major theme of this paper is utilization of the GALEN terminology server for knowledge module authoring. Two systems are presented, a knowledge base manager and a client to the terminology server, allowing the user to navigate in the semantic network and to import concept definitions and terms into the knowledge modules. The benefit of the terminology services is discussed.

Background

In this study, we describe postoperative monitoring, pharmacologic therapy, and hemodynamic responses in patients receiving Hemopump support after postcardiotomy heart failure.

Methods

The Hemopump was used in 24 patients with severe left ventricular dysfunction after coronary artery bypass grafting.

Results

Fourteen patients (58%) were weaned from the Hemopump. Low to moderate doses of a combination of catecholamines, phosphodiesterase inhibitors, vasodilators, and vasoconstrictors were required to optimize Hemopump function and left ventricular unloading. Mean arterial blood pressure, mixed venous oxygen saturation, and urinary output were the most important therapy guidelines.

Conclusions

Together with our clinical protocol, the Hemopump effectively unloaded the failing ventricle while maintaining vital-organ perfusion. Doses of vasoactive drugs could be kept low. This approach to treatment provides good conditions for recovery of the stunned myocardium.

Aerial distance from the dependent Primary Health Center is a crude but objective measure of geographical accessibility to Primary Health care facilities. This report describes a method for calculation of distances between the PHC and the population it serves using the data available from the local health authorities and the Swedish Central Statistical Bureau. The Swedish annual population registration records of 1991 and the property register available with the Central Statistical Bureau of Sweden formed the main data sources. By coupling the address in the population register to the property register each individual was mapped to the centroid of a property. The location of the PHCs as well as the areas covered by each were obtained from the local health authorities and mapped. By intersecting the population coverage with the PHC coverage the population for each PHC area was identified. Subsequently the distance to the PHC was calculated for each individual (property centroid). The population maps so generated can be linked to other databases to visualize and analyze the spatial dimension of health and disease. The methodology can be adapted for use with postal code districts, census enumeration tracts, or any other small area.

A new form of image estimator, which takes account of linear features, is derived using a signal equivalent formulation. The estimator is shown to be a nonstationary linear combination of three stationary estimators. The relation of the estimator to human visual physiology is discussed. A method for estimating the nonstationary control information is described and shown to be effective when the estimation is made from noisy data. A suboptimal approach which is computationally less demanding is presented and used in the restoration of a variety of images corrupted by additive white noise. The results show that the method can improve the quality of noisy images even when the signal-to-noise ratio is very low.

The mathematical basis is described of a new radiographic method by which an arbitrarily thick layer of the patient may be reconstructed. The reconstruction is performed from at least 60 images of the volume under examination. Each of these images, which have to be in digital form, is subjected to a special filtration process of its spatial frequencies. The combination of all the images will form the resulting image of the layer--the ectomogram. The method has been analysed and tested in experiments simulated with a computer.