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In recent years, there has clearly been a trend towards widespread dissemination of scientific results and achievements by sharing them in the form of educational materials. The application of the results of a research project in the education and knowledge development of students, young researchers and scientists, brings an added value to the outcomes of the scientific project. This work aims at contributing to the global process of free access to scientific materials by sharing the experience of a research group from the Medical University of Varna (MUV) in systematizing the results of three research projects, their transformation into educational resources and their application in innovative courses. The consolidated and systematized results of a research project are valuable assets for development of innovative educational materials. These resources, uploaded in a shared online repository, contribute to strengthen the international scientific community networking.

The aim of this work is to outline the management and risk management activities related to the successful implementation of scientific projects, which have been severely affected by the pandemic situation. The methodology includes a comparative analysis between planned and implemented activities on running scientific projects. Time, budget and scope are the main three constraints of the project used in the assessment. Five main groups of activities are analysed: Management, Scientific, Educational, Dissemination and Production. While published studies present qualitative and quantitative risk analysis due to the pandemic, this work goes a step forward by suggesting risk response planning, management procedures and activities to reduce threats to the project’s objectives. To the best of authors’ knowledge, there is no research systemized by other research groups. © 2021, Czestochowa University of Technology. All rights reserved.

BACKGROUND AND OBJECTIVE: The development, control and optimisation of new x-ray breast imaging modalities could benefit from a quantitative assessment of the resulting image textures. The aim of this work was to develop a software tool for routine radiomics applications in breast imaging, which will also be available upon request. METHODS: The tool (developed in MATLAB) allows image reading, selection of Regions of Interest (ROI), analysis and comparison. Requirements towards the tool also included convenient handling of common medical and simulated images, building and providing a library of commonly applied algorithms and a friendly graphical user interface. Initial set of features and analyses have been selected after a literature search. Being open, the tool can be extended, if necessary. RESULTS: The tool allows semi-automatic extracting of ROIs, calculating and processing a total of 23 different metrics or features in 2D images and/or in 3D image volumes. Computations of the features were verified against computations with other software packages performed with test images. Two case studies illustrate the applicability of the tool - (i) features on a series of 2D 'left' and 'right' CC mammograms acquired on a Siemens Inspiration system were computed and compared, and (ii) evaluation of the suitability of newly proposed and developed breast phantoms for x-ray-based imaging based on reference values from clinical mammography images. Obtained results could steer the further development of the physical breast phantoms. CONCLUSIONS: A new image analysis toolbox was realized and can now be used in a multitude of radiomics applications, on both clinical and test images. ispartof: PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS vol:89 pages:114-128 ispartof: location:Italy status: published

Purpose We present the development and the current state of the MaXIMA Breast Lesions Models Database, which is intended to provide researchers with both segmented and mathematical computer-based breast lesion models with realistic shape. Methods The database contains various 3D images of breast lesions of irregular shapes, collected from routine patient examinations or dedicated scientific experiments. It also contains images of simulated tumour models. In order to extract the 3D shapes of the breast cancers from patient images, an in-house segmentation algorithm was developed for the analysis of 50 tomosynthesis sets from patients diagnosed with malignant and benign lesions. In addition, computed tomography (CT) scans of three breast mastectomy cases were added, as well as five whole-body CT scans. The segmentation algorithm includes a series of image processing operations and region-growing techniques with minimal interaction from the user, with the purpose of finding and segmenting the areas of the lesion. Mathematically modelled computational breast lesions, also stored in the database, are based on the 3D random walk approach. Results The MaXIMA Imaging Database currently contains 50 breast cancer models obtained by segmentation of 3D patient breast tomosynthesis images; 8 models obtained by segmentation of whole body and breast cadavers CT images; and 80 models based on a mathematical algorithm. Each record in the database is supported with relevant information. Two applications of the database are highlighted: inserting the lesions into computationally generated breast phantoms and an approach in generating mammography images with variously shaped breast lesion models from the database for evaluation purposes. Both cases demonstrate the implementation of multiple scenarios and of an unlimited number of cases, which can be used for further software modelling and investigation of breast imaging techniques. The created database interface is web-based, user friendly and is intended to be made freely accessible through internet after the completion of the MaXIMA project. Conclusions The developed database will serve as an imaging data source for researchers, working on breast diagnostic imaging and on improving early breast cancer detection techniques, using existing or newly developed imaging modalities.

Anthropomorphic phantoms are models of real or virtual parts of the body, organ or tissue, represented by tissue-equivalent materials that aim to provide a realistic and accurate representation of their anatomy and properties. The aim of this study is to evaluate experimentally the suitability of 3D printed materials in the production of both, physical breast phantoms and abnormalities, to be used in optimization tasks in breast imaging. For this purpose, we designed three computational breast models, composed of skin, duct tree, adipose compartments and lesions. Subsequently, they were printed by using two 3D printing technologies and different printing materials, which were previously studied in details. The physical phantoms were scanned at a mammography machine, which allows 2D and 3D mammography (tomosynthesis) modes. The images were evaluated from an experienced radiologist. The results showed that tomosynthesis images are characterized with better realism compared to 2D mammography images. Next step is improvement in the printing quality of tumour formations as well as quantitative evaluation of the obtained results.

A complete software platform based on anthropomorphic breast models used with both planar and three-dimensional phase contrast breast imaging is presented and subjectively validated. For the development of the platform, tests with three anthropomorphic breast phantoms, available both in computational and physical form, were designed and implemented. The models are characterized with different complexity: two phantoms are with spheres and one anthropomorphic. Further on, two of the physical breast models were created with the use of 3D printing techniques. These phantoms with thickness of 40 mm and 31 mm, respectively, were based on digital phantoms created with in-house developed software tools. The third physical breast phantom is the L1 phantom developed at Katholieke Universiteit Leuven with 58 mm thickness. Based on this physical phantom, a computational one was created. The three physical breast phantoms were imaged at ID17 biomedical imaging line at ESRF. Two acquisition setups were used: planar and limited angle tomography modes. Simulated and experimental planar and three-dimensional images were compared in terms of visual reproducibility. Results showed that phantoms characterized with more simple structure produce subjectively similar experimental and simulation appearance in terms of object reproduction and similar edge effects. The thicker phantom demonstrated lower visual coincidence between the two types of planar images, due to higher thickness and higher energy incident beam. The results of this study will be used in the design of new experimental study, to be conducted at lower incident beam energy as well as improving the modelling of phase contrast imaging by using Monte Carlo techniques.

Introduction: In X-ray imaging, test objects reproducing breast anatomy characteristics are realized to optimize issues such as image processing or reconstruction, lesion detection performance, image quality and radiation induced detriment. Recently, a physical phantom with a structured background has been introduced for both 2D mammography and breast tomosynthesis. A software version of this phantom and a few related versions are now available and a comparison between these 3D software phantoms and the physical phantom will be presented. Methods: The software breast phantom simulates a semi-cylindrical container filled with spherical beads of different diameters. Four computational breast phantoms were generated with a dedicated software application and for two of these, physical phantoms are also available and they are used for the side by side comparison. Planar projections in mammography and tomosynthesis were simulated under identical incident air kerma conditions. Tomosynthesis slices were reconstructed with an in-house developed reconstruction software. In addition to a visual comparison, parameters like fractal dimension, power law exponent β and second order statistics (skewness, kurtosis) of planar projections and tomosynthesis reconstructed images were compared. Results: Visually, an excellent agreement between simulated and real planar and tomosynthesis images is observed. The comparison shows also an overall very good agreement between parameters evaluated from simulated and experimental images. Conclusion: The computational breast phantoms showed a close match with their physical versions. The detailed mathematical analysis of the images confirms the agreement between real and simulated 2D mammography and tomosynthesis images. The software phantom is ready for optimization purpose and extrapolation of the phantom to other breast imaging techniques.

Virtual clinical trials (VCTs) have been proposed to overcome the limitations of clinical trials using a patient population. VCTs are in-silico reproductions of medical examinations using digital models of the patients and simulated imaging devices. In this work, we present a VCT framework for imaging and dosimetry in breast computed tomography (BCT), digital breast tomosynthesis (DBT) and 2D digital mammography (DM), realized by Univ. Napoli Federico II in collaboration with the medical physics teams at Univ. California Davis and the Medical University of Varna, Bulgaria. Computational phantoms of the uncompressed (pendant) breast were generated by clinical BCT scans acquired at UC Davis. A dataset of digital breast phantoms was produced by means of voxel classification of the uncompressed breast CT images. The voxels were classified as air, skin, adipose and glandular tissue using a semi-automatic algorithm. A software compression algorithm (developed at U. Varna) applied to the 3D phantoms produces compressed breast digital phantoms for virtual DM and DBT investigations using a clinical scanners' technical specifications and geometry as inputs. Monte Carlo simulations, based on Geant4, were used to provide in-silico reproductions of real scans of a given patient breast model. The software permits the estimation of mean glandular dose (MGD) in 2D and 3D imaging as well as the 3D dose distribution. The platform produces breast projection images which are then reconstructed using analytical or iterative algorithms. Patient-specific MGD estimations, as well as simulated BCT volume data sets were compared with the clinical BCT scans. The VCT platform reported herein will be used for scanner optimization and for virtual trials comparing BCT against mammography and DBT, in terms of image quality and glandular dose distributions. In addition to in-silico evaluation, 3D printing methods were used to produce compressed and uncompressed anthropomorphic breast phantoms from the patient image-derived digital breast phantoms for the purpose of experimental validation.

We propose a novel approach for the fabrication of realistic in shape, size as well as in x-ray absorption properties 3D physical breast models. The approach eliminates the need for segmentation of breast tissues by directly mimicking the radiodensity of each voxel in a computed tomography (CT) image. This is done through a recently published study that enables the use of variable filament extrusion rate when creating 3D phantoms with fused deposition modeling printers. We use the CT image of a real patient’s breast to produce a model through the suggested approach. We then validate the fabricated physical breast phantom by obtaining a CT scan of it and comparing the latter to the original CT image of the source patient’s breast.

3D breast modelling for 2D and 3D breast x-ray imaging would benefit from the availability of digital and physical phantoms that reproduce accurately the complexity of the breast anatomy. While a number of groups have produced digital phantoms with increasing level of complexity, physical phantoms reproducing that software approach have been scarcely developed. One possibility is offered by 3D printing technology. This implies the assessment of the energy dependent absorption index β of 3D printing materials for absorption based imaging, as well as the assessment of the refractive index decrement, δ, of the printing material, for phase contrast imaging studies, at the energies of interest for breast imaging. In this work we set-up a procedure and performed a series of measurements (at 30, 45 and 60 keV, at the European Synchrotron Radiation Facility) for assessing the relative value of δ with respect to that of breast tissues, for twelve 3D printing materials. The method included propagation based phase contrast 2D imaging and retrieval of the estimated phase shift map, using the Paganin's algorithm. Breast glandular, adipose and skin tissues were used as reference materials of known ratio δ/β. A percentage difference Δδ was introduced to assess the suitability of the printing materials as tissue substitutes. The accuracy of the method (about 4%) was assessed based on the properties of PMMA and Nylon, acting as gold standard. Results show that, for the above photon energies, ABS is a good substitute for adipose tissue, Hybrid as a substitute of the glandular tissue and PET-G for simulating the skin. We plan to realize a breast phantom manufactured by fused deposition modelling (FDM) technology using ABS, Hybrid and PET-G as substitutes of the glandular and skin tissue and a second phantom by stereolithography (SLA) technology with the resins Flex, Tough and Black.

This paper presents a method for creation of computational models of breast lesions with irregular shapes from patient Digital Breast Tomosynthesis (DBT) images or breast cadavers and whole-body Computed Tomography (CT) images. The approach includes six basic steps: (a) normalization of the intensity of the tomographic images; (b) image noise reduction; (c) binarization of the lesion area, (d) application of morphological operations to further decrease the level of artefacts; (e) application of a region growing technique to segment the lesion; and (f) creation of a final 3D lesion model. The algorithm is semi-automatic as the initial selection of the region of the lesion and the seeds for the region growing are done interactively. A software tool, performing all of the required steps, was developed in MATLAB. The method was tested and evaluated by analysing anonymized sets of DBT patient images diagnosed with lesions. Experienced radiologists evaluated the segmentation of the tumours in the slices and the obtained 3D lesion shapes. They concluded for a quite satisfactory delineation of the lesions. In addition, for three DBT cases, a delineation of the tumours was performed independently by the radiologists. In all cases the abnormality volumes segmented by the proposed algorithm were smaller than those outlined by the experts. The calculated Dice similarity coefficients for algorithm-radiologist and radiologist-radiologist showed similar values. Another selected tumour case was introduced into a computational breast model to recursively assess the algorithm. The relative volume difference between the ground-truth tumour volume and the one obtained by applying the algorithm on the synthetic volume from the virtual DBT study is 5% which demonstrates the satisfactory performance of the proposed segmentation algorithm. The software tool we developed was used to create models of different breast abnormalities, which were then stored in a database for use by researchers working in this field. ispartof: PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS vol:57 pages:80-87 ispartof: location:Italy status: published

The current contribution presents an approach for creation of complex computational breast phantoms, with included breast abnormalities. In-house developed and validated software tool, called BreastSimulator, is used to create different models of healthy breasts, by varying parameters like shape, size, duct tree features, Cooper ligaments, skin, etc. Separately, different 3D tumour models are constructed from segmented tumour regions on sets of real tomosynthesis images from real patients. A semi-automatic algorithm was developed to segment the abnormalities in the images. The algorithm applies a series of image processing operations and region-growing techniques with minimal interaction from the user to find the areas of the lesions. The flat tumour images are then correctly stacked and stored in a 3D voxel matrix, matching the desired resolution. Relevant information about the lesion (voxel size, matrix size, geometrical centre, etc.) is also saved. Selected tumour models are then inserted at various locations into the computational models of the healthy breasts. Examples of simulated mammographic and tomosynthesis images from such breast phantoms are presented to illustrate the potential of the proposed approach. Combining mathematical breast modelling with segmented real 3D tumour shapes results in the creation of realistic breast phantoms. The approach allows implementation of multiple scenarios and unlimited number of cases, which can be used for further software modelling and investigation of breast imaging techniques.

Purpose – The purpose of this paper is to develop a realistic computational model of carbon fibre reinforced polymer (CFRP) structures dedicated for in-silico investigations of the use of X-ray-based imaging techniques as non-destructive testing (NDT) of CFRP parts. Design/methodology/approach – CFRPs contain layers of carbon-fibres bundles within resin. Bundles’ orientation in the different layers is arranged with respect to each other at a well-defined primary direction. In the model, the bundle was simulated as a circular cylinder. The resulted model is a stack of layers of unidirectional bundles having orientation of 0°/90°/45°/−45°. Two CFRP structures were modelled: a flat CFRP part and a real shaped CFRP clip. A porous layer and non-carbon fibres were inserted within each model, respectively. X-ray projection images were generated with a dedicated simulation programme. Three setups were investigated: radiography, tomosynthesis and cone-beam CT (CBCT). Findings – Results showed that porosity and non-carbon fibres were visible with all X-ray-based techniques. Tomosynthesis and CBCT, however, provide higher quality image of defects. Practical implications – The CFRP computational model is a valuable tool in design, testing and optimization phase of X-ray-based imaging techniques for use in NDT of composite materials. Simulated images are generated within a short time; thus results from virtual optimization and testing are obtained very fast and at low cost. Originality/value – An innovative computational model of CFRP structures, dedicated for X-ray imaging simulations, has been developed. The model is characterized by simplicity in its creation and realistic visual appearance of the produced X-ray images.

Preoperative assessment of the liver volume and function of the remnant liver is a mandatory prerequisite before performing major hepatectomy. The aim of this work is to develop and test a software application for evaluation of the residual function of the liver prior to the intervention of the surgeons. For this purpose, a complete software platform consisting of three basic modules: liver volume segmentation, visualization, and virtual cutting, was developed and tested. Liver volume segmentation is based on a patient examination with non-contrast abdominal Computed Tomography (CT). The basis of the segmentation is a multiple seeded region growing algorithm adapted for use with CT images without contrast-enhancement. Virtual tumor resection is performed interactively by outlining the liver region on the CT images. The software application then processes the results to produce a three-dimensional (3D) image of the “resected” region. Finally, 3D rendering module provides possibility for easy and fast interpretation of the segmentation results. The visual outputs are accompanied with quantitative measures that further provide estimation of the residual liver function and based on them the surgeons could make a better decision. The developed system was tested and verified with twenty abdominal CT patient sets consisting of different numbers of tomographic images. Volumes, obtained by manual tracing of two surgeon experts, showed a mean relative difference of 4.5%. The application was used in a study that demonstrates the need and the added value of such a tool in practice and in education.

INTRODUCTION: Nowadays, simulators have become part of most medical universities’ educational strategy. In recent years, Medical University of Varna has been equipped with the most modern medical simulators, aiming to meet the practical training needs of all specialties taught at the university. AIM: The aim of this study is to perform an initial assessment of the effectiveness in the use of simulators, as well as simulation-based training provided at the Medical University of Varna. MATERIALS AND METHODS: We developed a set of criteria to evaluate the effectiveness of the simulation training including: simulators accessibility, complexity and safety, as well as training environment and trainers’ preparedness. Based on these criteria, a questionnaire was developed and a survey conducted to study the students’ opinion on the training quality with two medical simulators: dental and anesthesiology. RESULTS AND CONCLUSION: Two groups of medical students - 73 students in dental medicine and 186 students in anesthesiology and intensive care, were enrolled in the study. The results showed a strong relationship between the students’ specialty and simulation training in all evaluation criteria except one. The results revealed that medical simulators play an essential role in the practical training of medical students, and may substantially improve their future medical performance. Medical University of Varna effectively integrates simulation medicine into its educational program.

A common approach in the development and improvement of diagnostic imaging techniques is the use of anthropomorphic phantoms. These phantoms can be physical or computational. In this study the creation of computational breast phantoms with included pathological formations is presented. The creation of the realistic phantoms is achieved by utilizing real patient data in the form of tomographic images. The 3D tumour models are generated by segmenting the regions containing tumour formations in the patient images. The segmentation is performed with a developed software tool based on a semi-automatic algorithm, which makes use of a series of image processing and region growing techniques. The software tool also provides the user an opportunity for corrections after the automated segmentation. Then the acquired flat images are stacked in a 3D voxel matrix. Creation of the computational healthy breast model as well as the compression procedure is achieved with a software tool called BreastSimulator. The healthy breast model and the segmented tumour formation are then interactively combined with a software tool called XRAYImagingSimulator. While the user can select a location for the tumour formation, also an automatic software processing is applied for integration between the two computational models. The simulation procedure for acquiring tomographic images from the created realistic breast phantom with included tumour formation is performed with the XRAYImagingSimulator software tool. Finally, the acquired simulation images are reconstructed with a software tool called FDKR. The combination of mathematical models of the breast and tumour models segmented from real patient data leads to the creation of realistic breast phantoms, which can be used in X-ray imaging simulation studies. The presented approach gives an opportunity for generation of multiple cases of breast cancer; thus allowing for further progress in already existing software models and techniques in diagnostic imaging. Acknowledgements This research is supported by the Bulgarian National Science Fund under grant agreement DN17/2. This project also has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692097.

Physical phantoms are a basic tool for the assessment and verification of performance standards in daily clinical practice of X-ray imaging modalities. Most of the physical phantoms have a homogeneous background with inserted test objects. For research purposes, many of the existing phantoms should be developed to a next degree of sophistication in order to mimic the real objects more closely in terms of radiographic and anatomical properties. The development of 3D printing technologies opens potentially new possibilities for phantom manufacturing. The aim of this study is to explore the absorption properties of common 3D printing materials such as resins, PLA, ABS, etc. and to estimate their potential for production of the anthropomorphic phantoms. To achieve this goal, step-wedge phantoms were computationally modeled and then manufactured using two popular 3D printing technologies: stereolithographic and fused-deposition modeling. X-ray images of the phantoms were acquired, using monochromatic beam at ID17, ESRF, Grenoble for three energies – 30 keV, 45 keV and 60 keV. Experimental data were further processed to obtain the linear attenuation coefficients of these materials. Comparison with theoretical data for the linear attenuation coefficients for breast tissues was performed. Based on the results, several breast anthropomorphic phantoms were manufactured. Finally, a practical approach for printing anthropomorphic phantoms has been established and verified. From the studied materials, most of the resins, Hybrid, PET-G show absorption properties close to the glandular tissue, while ABS shows absorption characteristics close to these of the adipose tissue. It allows the production of complex shapes, which are very advantageous for the case of breast phantoms. Acknowledgements This research is supported by the Bulgarian National Science Fund under grant agreement DN17/2. This project also has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 692097.

Aim of this study is to present a software tool designed to extract texture parameters from x-ray images. The tool is developed in the MATLAB environment and is dedicated to facilitate the research in x-ray imaging. A program called BreastSimulator is used to generate an anthropomorphic software model of an averaged in size breast. Further on, the computer model undergoes simulated mechanical compression to mimic the conditions during mammographic acquisition, and subsequently exported as STL file used for 3D printing. The physical model is printed with a stereolithographic 3D printer with resolution of 100 µm from Clear Resin. The model is then filled with animal fat and irradiated at GE Senographe digital mammography unit. On the other side, the software model is “irradiated” by a specialized program. The resulting x-ray images from both the simulated and the physical models are compared by their parameters, extracted with the help of the created software tool.

OBJECTIVE The aim of this study is to investigate the validity of using the Multiple Projection Algorithm (MPA) for Breast Tomosynthesis (BT) using real projection images acquired with phantoms at a clinical setting. METHODS The CIRS-BR3D phantom with ranging thicknesses between 3 cm and 6 cm was used for all image quality evaluations. Five sets of measurements were acquired, each comprised of a 2D mammographic image followed by a set of 25 projections within an arc length of 50°. A reconstruction algorithm based on the MPA was adapted for partial isocentric rotation using a stationary detector. For reference purposes, a Back Projection (BP) algorithm was also developed for this geometry. The performance of the algorithms was evaluated, in combination with pre-filtering of the projections, in comparative studies that involved also a comparison between tomosynthesis slices and 2D mammograms. RESULTS Evaluation of tomosynthesis slices reconstructed with BP and MPA showed close performance for the two algorithms with no considerable differences in feature detection, size and appearance of the background tissue with the MPA running faster the overall process. Pre-filtering of the projections, led to better BT images compared to non-filtering. Increased thickness resulted in limited detection of the features of interest, especially the smaller sized ones. In these cases, the filtered BT slices allowed improved visualization due to removed superimposed tissue compared to the 2D images. The different breast-like slab arrangements in phantoms of the same thickness demonstrated a slight influence on the quality of reconstructed features. CONCLUSIONS The MPA which had been applied previously to reconstruct tomograms from projections acquired at synchrotron facilities, is a time efficient algorithm, and is fully compliant with and can be successfully used in BT clinical systems. Compared to 2D mammography, BT shows advantage in visualizing features of small size and for increased phantom thickness or features within a dense background with superimposed structures.

Medical devices are used today in virtually every healthcare delivery process, and the range and complexity of issues that can arise from their use is very diverse. The need for a comprehensive program for medical technology management, able to ensure that all technologies in use are performing as intended by the manufacturer and are safe for the patients and the personnel, is evident. For the overall management of medical technology, Clinical Engineering Departments (CEDs) were established in the 1970s and their role remains essential. CEDs’ activities encompass services covering all aspects of the lifespan of medical devices used in hospitals, it starts from purchase planning and acquisition, involves equipment maintenance and training, covers vigilance aspects, and follows the devices up to their disposal. In order to reliably perform these rather complex tasks related to medical equipment management, hospitals have to establish well-structured programs, usually applying specifically designed medical equipment management systems. These are nowadays complex database management tools used to collect, store, and analyze data related to medical equipment, often network-based and interconnected with other hospital information systems. In the future, an even more accelerated development of new healthcare technologies which will be largely interoperable is expected. This expansion of technologies used will further contribute toward an improvement of healthcare delivery, but at the same time, toward the introduction of new demands for comprehensive medical technology management. This chapter gives an overview of various aspects related to the management of medical technology in the hospital environment and discusses some of the future trends and perspectives in the field.

The paper presents an approach to be used in the face-to-face and the on-line phases of one of the chapters in module from the EUTEMPE-RX project. The module and the project are aimed at the training of medical physics experts in radiology. The approach consists of: (a) generation of computational anthropomorphic phantoms, (b) program scripts, specifically developed to convert computational phantoms to suitable formats used with 3D printing devices, and (c) 3D printing of software models. In this paper, the design and printing of a 3D breast glandular system has been demonstrated. Two small size breast phantoms differing in the complexity of their duct tree system were generated with a dedicated program. A set of image processing techniques were applied on the obtained breast phantoms to obtain an STereoLithography (STL) file format of the breast’s duct tree that was imported within the software of the 3D printer used to print the sample breast tree.

The future of Biomedical Engineering (BME) profession has been shown to be in high demand and countries, which do not invest in BME education will be unable to use efficiently the forthcoming healthcare technologies.

Digital tomosynthesis is a method of limited angle reconstruction of tomographic images produced at variable heights, on the basis of a set of angular projections taken in an arc around human anatomy. Reconstructed tomograms from unprocessed original projection images, however, are invariably affected by tomographic noise such as blurred images of objects lying outside the plane of interest and superimposed on the focused image of the fulcrum plane. The present work investigates the performance of two approaches for generation of tomograms with a reduced noise: a generalised post-processing method, based on constructing a noise mask from all planes in the reconstructed volume, and its subsequent subtraction from the in-focus plane and a filtered Multiple Projection Algorithm. The comparison between the two algorithms shows that the first method provides reconstructions with very good quality in case of high contrast features, especially for those embedded into a heterogeneous background.

The mean radiation dose to the glandular tissue and its dependence on the irradiation geometry, beam quality, breast size and composition in digital breast tomosynthesis (DBT) exams have been studied extensively via Monte Carlo calculations [1] . On the other hand, there are few comprehensive studies on the dose distribution within the irradiated breast [2] . The distribution of glandular dose for breast irradiation from a plurality of angles, as occurs in DBT, may be of large interest in scanner optimization as well as for developing suitable models for the evaluation of the cancer risk related to the X-ray exposure for non–homogeneous irradiation. For this reason, it is of interest to evaluate the level of homogeneity of the dose spread, via the assessment of 3D dose maps in breast models during a DBT scan. This work aimed at evaluating, via Monte Carlo (MC) simulations and measurements using radiochromic films, the dose distribution within compressed layered breast phantoms during DBT scans. For this purpose, two phantoms were employed: a PMMA homogeneous phantom and a heterogeneous phantom simulating a 50% glandular breast. A series of pre-calibrated (vs free-in-air air kerma) film pieces were inserted between the phantom slices and the 3D dose maps were measured for a set of DBT scans on different commercial units, for different sample thicknesses, at various exposure technique factors. We developed an MC code based on GEANT4 toolkit ver. 10.00, simulating the clinical setup specifications, whose results have been compared to measurements. This project received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 692097 for the MaXIMA project: Three dimensional breast cancer models for X-ray imaging research.

Purpose We present the development and the current state of the MaXIMA Breast Tumours Models’ Database, which is intended to provide researchers with both segmented and mathematically modelled realistic in shape computer-based breast tumours. Methods The database contains various 3D images of breast cancers of irregular shapes, collected from routine patient examinations or dedicated scientific experiments. It also contains images of simulated tumour models. To extract the 3D shapes of the breast cancers from patient images, an in–house developed and well evaluated segmentation algorithm was applied on 60 tomosynthesis sets from patients diagnosed with malignant and benign lesions. In addition, three breast mastectomy cases scanned at a CT system were added. This algorithm includes a series of image processing operations and region-growing techniques with minimal interaction from the user to find and segment the areas of the lesions. Modelled computational breast tumours are generated following different approaches and also stored in the database. Each record in the database is supported with relevant information, e.g. voxel size and resolution, matrix size, geometrical centre, etc. Results The MaXIMA Imaging Database currently contains 68 unique breast cancer models obtained by segmentation of 3D patient breast tomosynthesis images; 8 models obtained by segmentation of 3D micro CT images of biopsy specimens; and 20 models based on mathematical algorithm. An application of the tumour models is to insert them into computationally generated healthy breast phantom generated with dedicated software tools (e.g. the BreastSimulator tool). The resulted combined computational breast models are used to study the visibility of breast tumours in 3D breast imaging techniques. This approach allows implementation of multiple scenarios and unlimited number of cases, which can be used for further software modelling and investigation of breast imaging techniques. The database interface is web-based, i.e. is platform independent, user friendly and is indented to be made freely accessible through internet after the completion of the MaXIMA project. Conclusions The developed database serves as an imaging data source for researchers, working on breast imaging and early breast cancer detection with the help of existing or newly developed imaging modalities.

Purpose This paper presents a complete and validated computer-based system dedicated to X-ray phase contrast breast imaging research. The system comprises three main modules: (a) a module for generation of computational breast models, (b) a module for generation of phase-contrast X-ray images from computational phantoms in 2D and 3D acquisition setup, and (c) a module for image reconstruction. Methods The module for computational breast models is based on the BreastSimulator tool, used to generate breast models of various sizes and to compress them to a desired thickness. The module for the generation of phase-contrast images is used to model the image acquisition geometry and formation of X-ray images. The image reconstruction is done with a software tool, based on an in–house built reconstruction techniques class library, which is a dedicated object-oriented library for X-ray based applications. The capability of this system to correctly calculate phase-contrast tomographic images was tested by comparing simulated versus experimental images obtained from anthropomorphic breast phantoms. Three anthropomorphic computational breast phantoms were designed from white and grey resin by using the available stereolithography 3D printer. Experimental projection images were acquired and simulated images were generated, considering a breast tomosynthesis setup. Experiments were conducted at beamline ID17, ESRF. Simulations replicated the experimental setup. Images in a tomosynthesis mode were generated and tomograms were calculated by using the reconstruction module. Results Results show very good visual agreement between simulated and experimentally obtained tomosynthesis images. In addition, selected tomosynthesis images from the physical and computational breast phantoms were quantitatively evaluated for set of imaging parameters such as skewness, kurtosis, the power-law exponent, β , of the power spectrum and fractal dimension. Analysis and the comparison of these parameters between simulated and experimental images also show a very good coincidence. Conclusions The platform is currently used in the process of development of a dedicated breast phantom for phase contrast imaging techniques. The system will be a valuable tool in studying new X-ray imaging techniques based on phase contrast, such as phase contrast tomosynthesis and CT.

Breast physical phantoms are a basic tool for the assessment and verification of performance standards in daily clinical practice of x-ray breast imaging modalities. They are also invaluable in testing and evaluation of new x-ray breast modalities to be potentially established, e.g. breast computed tomography, dual-energy breast CT and phase-contrast mammography and tomography. Nowadays, there is a lack or there are only a limited number of breast physical phantoms available for this purpose. The aim of this study is to explore a range of 3D printing materials such as resins, PLA, ABS, Nylon etc, to determine their attenuation and refractive properties, and to finally compare them to the properties of the breast tissues: adipose, glandular and skin. To achieve this goal, step-wedge phantoms were computationally modeled and then manufactured using stereolithographic and fused-deposition modeling technologies. X-ray images of the phantoms were acquired, using monochromatic beam at ID17, ESRF, Grenoble for three energies-30 keV, 45 keV and 60 keV. Experimental data were further processed to obtain the linear attenuation coefficients of these materials. Comparison with theoretical data for the linear attenuation coefficients and the refractive indexes for breast tissues was performed. From the studied materials, most of the resins, Nylon, Hybrid, PET-G show absorption properties close to the glandular tissue, while ABS shows absorption characteristics close to these of the adipose tissue. For phase-contrast imaging, it turns out that the ABS combined with resin-based materials to represent the adipose and glandular tissues, respectively may be a good combination for manufacturing of a phantom suitable for these studies. These results can be used for the design and the construction of a new physical anthropomorphic phantom of the breast with improved anatomical and radiological characteristics dedicated for advanced mammography imaging techniques implemented at higher photon energies. ispartof: PHYSICS IN MEDICINE AND BIOLOGY vol:63 issue:17 ispartof: location:England status: published

Medical devices play a vital role in the delivery of high quality healthcare with their numbers increasing exponentially during the past fifty years. Although recent technological advancements have led to much more reliable and safer Medical Devices (MDs), potential risks of failure and the associated adverse incidents cannot be ignored. To create a safer environment for the patient in terms of technology, it is necessary to provide rapid and accurate information on adverse events, in order to avoid their repetition. The traditional approach of MD Vigilance based only on official user reports of adverse incidents has been proven inadequate today. A modern approach, also used in this work, to the problem is based on the introduction of additional means, such as data mining, extraction, standardization and codification of the information, from different direct and indirect sources worldwide, and its systematic classification and archiving in dedicated databases. The aim is to timely extract information on potentially hazardous MDs and to make it available where appropriate.

The use of medical equipment management software tools has been introduced in the field of clinical engineering since the beginning of the 80’s. Nowadays the tremendous expansion of Internet has changed both the way these tools function and the capabilities they provide to the user. This work presents a medical equipment management software system which has been developed to operate as a web service. In addition, its main characteristics are presented in comparison with the previous client-server and standalone versions. Finally, the benefits of such an implementation are discussed.

Major hepatectomy causes a risk of postoperative liver dysfunction, failure, and infections like surgical site infection. Preoperative assessment of the liver volume and function of the remnant liver is a mandatory prerequisite before performing such surgery. The aim of this work is to develop and test a software application for evaluation of the residual function of the liver prior to the intervention of the surgeons. For this purpose, a technique for evaluation of liver volume from computed tomography (CT) images has been developed. Furthermore, the methodology algorithms were implemented and incorporated within a software tool with three basic functionalities: volume determination based on segmentation of liver from CT images, virtual tumour resection and estimation of the residual liver function and 3D visualisation. Forty-one sets of abdominal CT images consisting of different number of tomographic slice images were used to test and evaluate the proposed approach. Volumes that were obtained after manual tracing by two surgeon experts showed a relative difference of 3.5 %. The suggested methodology was encapsulated within an application with user-friendly interface that allows surgeons interactively to perform virtual tumour resection, to evaluate the relative residual liver and render the final result. Thereby, it is a tool in the surgeons’ hands that significantly facilitates their duties, saves time, and allows them to objectively evaluate the situation and take the right decisions. At the same time, the tool appears to be appropriate educational instrument for virtual training of young surgeon specialists.

The purpose of the present work is to present up-to-date information concerning MD recalls due to software failures. For this purpose, data from the United States Food and Drug Administration (FDA) Enforcement Reports for the period 1999-2010 have been used. The outcomes from data collection and analysis are presented through the use of ratio indicators and their distribution over the time. Furthermore, classifications of the MD recalls according to reasons of failure and the level of health hazard have been performed.

Biomedical Engineering (BME) is one of the fastest growing fields with an impressive multidisciplinary dimension and direct consequences not only for the health care sector but for the society in general, since it is the basis of the impressive advancement and progress of health care delivery. Nowadays, Biomedical Engineers must be prepared to meet existing and forecasted needs by means of knowledge, skills and attitudes that address the demands of the work environment in the broader health care related sector. The objective of the TEMPUS IV BME-ENA project is to promote BME Education in the Eastern Neighbouring Area, through the creation of 4 joint multidisciplinary MSc programs in BME, with major positive effects in both the health technology industry and the health delivery system. The BME-ENA project will enable Armenia, Georgia, Moldova and Ukraine to face the challenges of biomedical technology through capacity and institutional building measures.

Emerging X-ray breast imaging applications require the use of realistic physical three-dimensional phantoms are breast CT, phase-contrast mammography and the existing breast Tomosynthesis, dedicated to screen as early as possible and diagnose cancer in breast. However, manufacturing of such phantoms meets difficulties related to the current technology, suitable materials, manufacturing precision, format of the software models. This paper reports the preliminary results from simulation studies aiming to investigate mixtures prepared from epoxy resin and iodine powder in specific ratios as tissue substitutes for X-ray breast imaging. For each material, mass and linear attenuation coefficients were calculated for the X-ray energy range from 10 to 32 keV. Mixtures of epoxy resin and up to 1.8% iodine powder turn to be a suitable option for tissue substitutes. Selected materials were used in simulations of breast lesions with blurry edges.