Segmentation Enhanced Elastic Image Registration for 2D Speckle Tracking Echocardiography—Performance Study In Silico

Although the two dimensional Speckle Tracking Echocardiography has gained a strong position among medical diagnostic techniques in cardiology, it still requires further developments to improve its repeatability and reliability. Few works have attempted to incorporate the left ventricle segmentation results in the process of displacements and strain estimation to improve its performance. We proposed the use of mask information as an additional penalty in the elastic image registration based displacements estimation. This approach was studied using a short axis view synthetic echocardiographic data, segmented using an active contour method. The obtained masks were distorted to a different degree, using different methods to assess the influence of the segmentation quality on the displacements and strain estimation process. The results of displacements and circumferential strain estimations show, that even though the method is dependent on the mask quality, the potential loss in accuracy due to the poor segmentation quality is much lower than the potential accuracy gain in cases where the segmentation performs well.

Review of the algorithms used in exhaled breath analysis for the detection of diabetes

Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.

DNA Aptamers Specific for Legionella Pneumophila: Systematic Evolution of Ligands by Exponential Enrichment in Whole Bacterial Cells

Legionella pneumophila is the major causative agent of Legionnaires’ disease and Pontiac fever, which pose major public health problems. Rapid detection of L. pneumophila is important for global control of these diseases. Aptamers, short oligonucleotides that bind to targets with high affinity and specificity, have great potential for use in pathogenic bacterium detection, diagnostics, and therapy. Here, we used a whole-cell SELEX (systematic evolution of ligands by exponential enrichment) method to isolate and characterize single-stranded DNA (ssDNA) aptamers against L. pneumophila. A total of 60 ssDNA sequences were identified after 17 rounds of selection. Other bacterial species (Escherichia coli, Bacillus subtilis, Pseudomonas syringae, Staphylococcus aureus, Legionella quateirensis, and Legionella adelaidensis) were used for counterselection to enhance the specificity of ssDNA aptamers against L. pneumophila. Four ssDNA aptamers showed strong affinity and high selectivity for L. pneumophila, with Kd values in the nanomolar range. Bioinformatic analysis of the most specific aptamers revealed predicted conserved secondary structures that might bind to L. pneumophila cell walls. In addition, the binding of these four fluorescently labeled aptamers to the surface of L. pneumophila was observed directly by fluorescence microscopy. This is the first study to use SELEX to target L. pneumophila whole cells. The aptamers identified in this study could be used in the future to develop medical diagnostic tools and public environmental detection assays for L. pneumophila.

Asumu Fractional Derivative Applied to Edge Detection on SARS-COV2 Images

Edge detection consists of a set of mathematical methods which identifies the points in a digital image where image brightness changes sharply. In the traditional edge detection methods such as the first-order derivative filters, it is easy to lose image information details and the second-order derivative filters are more sensitive to noise. To overcome these problems, the methods based on the fractional differential-order filters have been proposed in the literature. This paper presents the construction and implementation of the Prewitt fractional differential filter in the Asumu definition sense for SARS-COV2 image edge detection. The experiments show that these filters can avoid noise and detect rich edge details. The experimental comparison show that the proposed method outperforms some edge detection methods. In the next paper, we are planning to improve and combine the proposed filters with artificial intelligence algorithm in order to program a training system for SARS-COV2 image classification with the aim of having a supplemental medical diagnostic.

An improved Random Forest based on Feature Selection and Feature weighting for case retrieval in CBR system Application to medical data

: The medical diagnostic process works very similarly to the Case Based Reasoning (CBR) cycle scheme. CBR is a problem solving approach based on the reuse of past experiences called cases. To improve the performance of the retrieval phase, a Random Forest (RF) model is proposed, in this respect we used this algorithm in three different ways (three different algorithms): Classic Random Forest (CRF) algorithm, Random Forest with Feature Selection (RF_FS) algorithm where we selected the most important attributes and deleted the less important ones and Weighted Random Forest (WRF) algorithm where we weighted the most important attributes by giving them more weight. We did this by multiplying the entropy with the weight corresponding to each attribute.We tested our three algorithms CRF, RF_FS and WRF with CBR on data from 11 medical databases and compared the results they produced. We found that WRF and RF_FS give better results than CRF. The experiemental results show the performance and robustess of the proposed approach.

Analysis of patient medical exposure in X-ray diagnostics in Russia for half a century (1970–2019)

During last 50 years, firstly in the RSFSR in the USSR (1970-80), then in the Russian Federation - RF (1990-2019), the authors studied the radiation safety issues of patients from medical exposure. The reader is offered a complex radiation-hygienic analysis of the 50-year medical exposure of patients and of the population in Russia to inform and analyze the available data on the most common type of use of ionizing radiation sources in the national economy. For a half century, several generations of people have changed and medical diagnostic X-ray equipment and technologies have also radically changed. The information from this article was obtained on the basis of radiation-hygienic statistics, as well as considered our research. The data is presented at the federal level in the form of the volume of research carried out- determined by the number of X-ray procedures, as well as the level of medical exposure in the form of effective dose of patients in Russia - a huge region with a population of about 150 million people, where about 200 million X-Ray procedures were performed annually, i.e. about 10 billion X-Ray procedures for the entire observation period. During the study, a collective effective dose was - 6.5 million person-Sv at the rate of 100 thousand person-Sv and more per year. The paper presents the dynamics and the structure of the studied indicators depending on the type of medical exposure, as well as its localization. The contribution of the X-ray diagnostics to the total volume of radiation diagnostics, which is developing dynamically, is presented. It was found that throughout the study, there were two oppositely directed processes: an increase in the number of X-Ray procedures and a decrease in the effective doses of patients. At present, the minimum dose has been reached, after that it has been increasing began, associated with the use of new computer technologies. It was determined that, depending on the localization, the main radiation load during X-ray procedures falls on the skeleton and digestive organs. It is shown that during the study period (in 1986) there was an accident at the Chernobyl, which significantly affected on medical activities and, in particular, X-ray diagnostic indicators. The paper shows the consequences of these situations. In general, the data presented is huge in volume and significant in information content. The information obtained on the basis of such a unique data is representative and allows, firstly, to analytically study the issues of radiation protection of patients and, secondly, to plan the strategy and tactics of its development.

Radioactive nuclei for β + γ PET and theranostics: selected candidates

Positron emission tomography (PET) is an established medical diagnostic imaging method. Continuous improvements are aimed at refining image reconstruction, reducing the amount of radioactive tracer and combining with targeted therapy. Time-of-flight (TOF)-PET provides the localization of the tracer through improved time resolution, nuclear physics may contribute to this goal via selection of radioactive nuclei emitting additional γ-rays. This additional radiation, when properly detected, localizes the decay of the tracer at the line of response (LoR) determined by two detected 511 keV quanta. Selected candidates are presented. Some are particularly interesting, as they are strong candidates for theranostic applications.

A magánkiadások hatása a hazai egészségügyi diagnosztikai szolgáltatók pénzügyi helyzetére : The Impact of Private Healthcare Spending on the Hungarian Medical Diagnostic Companies

A magánfinanszírozás modellje a kilencvenes évek kezdete óta része a hazai egészségügynek. A 2000-es évektől azonban komolyan előtérbe kerültek ezek a csatornák, különösen a képalkotó diagnosztika és laborszolgáltatások területén, ami az itt szolgáltató vállalkozások közelebbi vizsgálatát teszi szükségessé. Elsőként az Ohlson-féle O csődkockázati mutatók által adott jelzéseket vizsgáljuk meg egy öt vállalkozásból álló mintán 2006 és 2017 között. Ezt követően az Ohlson-féle O csődkockázati mutató változásának magyarázhatóságát vizsgáljuk az egészségügyi finanszírozási környezet, a tőkepiaci helyzet és a technológiai környezetet lefedő modellek keretében, panelregressziós eljárásokkal. Megállapítható, hogy az egészségügyi finanszírozás GDP-arányos változása, illetve a kórházi ágyszám változásai gyakorolták a legkomolyabb hatást a mintában szereplő vállalatok pénzügyi helyzetének alakulására. The Hungarian healthcare services are partially financed on private basis since the 1990s. This channel gained increasing popularity in the 2000s especially on the fields of medical imaging and labour diagnostics – what motivates a deeper corporate analysis on annual report data between 2006 and 2017. Financial conditions were studied with the assumption of the Ohlson O bankruptcy ratio, and their changes were monitored trough three different panel regression models: one focused on general and public healthcare spending and hospital capacities, while the second contained the financial market-related variables as the third referred on the technological environment. The changes of healthcare funding to GDP ratios and hospital bed numbers surpassed all other variables on the financial conditions of the sample companies.

Investigating the Effects of Aqueous and Alcoholic Extracts of Allium Hirtifolium and Allium Jesdianum on Keratinase Activity of Trichophyton Mentagrophytes

Background: Trichophyton spp., as pathogenic species to humans and animals, cause different forms of dermatophytosis through the production of particular enzymes, playing an essential role in tissue invasion. Among these, herein, keratinase was investigated, for the specific case of Trichophyton mentagrophytes, as a target of the effects of Allium hirtifolium and Allium jesdianum extracts, thus pharmacological potential of these plants was studied against keratinase activity. Methodology: Sampling was carried out on 20 bald patients from medical diagnostic laboratories and mycology centers, with suspected dermatophytosis of scalp. For confirming the presence of Trichophyton mentagrophytes in the specimens, different laboratory procedures were applied. Trichophyton mentagrophytes isolates were cultured on a screening medium containing keratin to verify production of the keratinase enzyme. The best enzyme-producing isolate was selected by measuring diameter of transparent halo around colony to be used in subsequent stages. Afterwards, the optimized conditions maximizing enzyme production and activity were determined. Finally, the inhibitory effect of different dilutions of aqueous and alcoholic extracts of Allium jesdianum and Allium hirtifolium on extracellular keratinase activity was studied. Results : Sixteen out of 20 fungal isolates were identified as the Trichophyton mentagrophytes. The most desirable reduction on keratinase activity was reported for dilution values of 50 and 100 mg/ml of both aqueous and ethanolic extracts of A.jesdianum, though much more significant decrease belonged to the latter, and for dilution values of 25 and 100 mg/ ml of both aqueous and ethanolic extracts of A.hirtifolium. Conclusion : Concerning our results, it is suggested that paying special attention to these natural compounds for the treatment of dermatophytosis could be remarkably effective, considering significant production of keratinase observed in T. mentagrophytes, and they are beneficial, as they have no side effects and offer an alternative to currently available medications, which are under the restriction of drug resistance.

Non-Hodgkin lymphomas and ionizing radiation: case report and review of the literature

Non-Hodgkin lymphoma (NHL) increased continuously since the last century in developed countries. While they are considered as disease in elder ages, a remarkable increasing incidence is also observed in German children and juveniles. The higher rates are interpreted by the changes in classification because diseases such as chronic lymphocytic leukaemia were also identified as NHL. Considerable rates of NHL were found in nuclear workers and liquidators of Chernobyl, i.e. in cases of low-dose chronical exposures. In Germany, we noticed three workers who developed NHL after decontamination of nuclear facilities. The bone marrow is generally considered as target organ for ionizing radiation, but NHL is obviously induced in the whole pool of lymphocytes. Therefore, the dosimetry in cases of typical occupational external and internal exposure must be revised. A high radiation sensitivity for NHL is a possible suspect and likely reason which may partly explain the continuous rise of the diseases in populations underlying the current increases of medical diagnostic exposure. NHL is also induced in children and juveniles with a history of diagnostic X-rays.