Exploring the Potential of a Novel Iodine-Based Material as an Alternative Contrast Agent in X-ray Imaging Studies.

BACKGROUND: Contrast-enhanced mammography is one of the new emerging imaging techniques used for detecting breast tissue lesions. Optimization of imaging protocols and reconstruction techniques for this modality, however, requires the involvement of physical phantoms. Their development is related to the use of radiocontrast agents. This study assesses the X-ray properties of a novel contrast material in clinical settings. This material is intended for experimental use with physical phantoms, offering an alternative to commonly available radiocontrast agents. MATERIALS AND METHODS: The water-soluble sodium salt of the newly synthesized diiodine-substituted natural eudesmic acid, Sodium 2,6-DiIodo-3,4,5-TriMethoxyBenzoate [NaDITMB], has been investigated with respect to one of the most commonly applied radiocontrast medium in medical practice-Omnipaque®. For this purpose, simulation and experimental studies were carried out with a computational phantom and a physical counterpart, respectively. Synthetic and experimental X-ray images were subsequently produced under varying beam kilovoltage peaks (kVps), and the proposed contrast material was evaluated. RESULTS AND DISCUSSION: Simulation results revealed equivalent absorptions between the two simulated radiocontrast agents. Experimental findings supported these simulations, showing a maximum deviation of 3.7% between the image gray values of contrast materials for NaDITMB and Omnipaque solutions for a 46 kVp X-ray beam. Higher kVp X-ray beams show even smaller deviations in the mean grey values of the imaged contrast agents, with the NaDITMB solution demonstrating less than a 2% deviation compared to Omnipaque. CONCLUSION: The proposed contrast agent is a suitable candidate for use in experimental work related to contrast-enhanced imaging by utilizing phantoms. It boasts the advantages of easy synthesis and is recognized for its safety, ensuring a secure environment for both the experimenter and the environment.

Pilot Study on the Development and Integration of Anthropomorphic Models within the Dental Technician Curriculum.

The effectiveness of modern medical education largely depends on the integration and utilization of digital technologies in teaching various disciplines. In this pilot usability study, we introduced 3D printed anthropomorphic dental models, specifically designed for the elective discipline "Digital and Metal-Free Techniques in Dental Technology" from the curriculum of the Dental Technician specialty in the Medical University of Varna. The evaluation focused on dental technician students' perception of this novel learning environment, its influence on their performance, and the potential for future application of these models and related 3D technologies in their professional practice. A validated satisfaction questionnaire was distributed among 80 students, comprising the total cohort. The results indicated a high acceptance rate, with nearly 95% of participants finding the use of digitally created 3D-printed dental models beneficial. More than 90% believed that exploring digital technologies would enhance their skills. The well-trained instructor's competence in technology use convinced students of its value, with more than 98% expressing a willingness to incorporate these technologies into their future work for improved precision in dental models. However, due to the current high cost of needed equipment, only 10% of participants may practicably introduce this novel technology into their practical work. The use of anatomically accurate 3D printed models is a valuable addition to the current dental technician curriculum in medical colleges.

3D Printing, Histological, and Radiological Analysis of Nanosilicate-Polysaccharide Composite Hydrogel as a Tissue-Equivalent Material for Complex Biological Bone Phantom.

Nanosilicate-polysaccharide composite hydrogels are a well-studied class of materials in regenerative medicine that combine good 3D printability, staining, and biological properties, making them an excellent candidate material for complex bone scaffolds. The aim of this study was to develop a hydrogel suitable for 3D printing that has biological and radiological properties similar to those of the natural bone and to develop protocols for their histological and radiological analysis. We synthesized a hydrogel based on alginate, methylcellulose, and laponite, then 3D printed it into a series of complex bioscaffolds. The scaffolds were scanned with CT and CBCT scanners and exported as DICOM datasets, then cut into histological slides and stained using standard histological protocols. From the DICOM datasets, the average value of the voxels in Hounsfield Units (HU) was calculated and compared with natural trabecular bone. In the histological sections, we tested the effect of standard histological stains on the hydrogel matrix in the context of future cytological and histological analysis. The results confirmed that an alginate/methylcellulose/laponite-based composite hydrogel can be used for 3D printing of complex high fidelity three-dimensional scaffolds. This opens an avenue for the development of dynamic biological physical phantoms for bone tissue engineering and the development of new CT-based imaging algorithms for the needs of radiology and radiation therapy.

Thermoplastic 3D printing technology using a single filament for producing realistic patient-derived breast models.

Objective. This work describes an approach for producing physical anthropomorphic breast phantoms from clinical patient data using three-dimensional (3D) fused-deposition modelling (FDM) printing.Approach. The source of the anthropomorphic model was a clinical Magnetic Resonance Imaging (MRI) patient image set, which was segmented slice by slice into adipose and glandular tissues, skin and tumour formations; thus obtaining a four component computational breast model. The segmented tissues were mapped to specific Hounsfield Units (HU) values, which were derived from clinical breast Computed Tomography (CT) data. The obtained computational model was used as a template for producing a physical anthropomorphic breast phantom using 3D printing. FDM technology with only one polylactic acid filament was used. The physical breast phantom was scanned at Siemens SOMATOM Definition CT. Quantitative and qualitative evaluation were carried out to assess the clinical realism of CT slices of the physical breast phantom.Main results. The comparison between selected slices from the computational breast phantom and CT slices of the physical breast phantom shows similar visual x-ray appearance of the four breast tissue structures: adipose, glandular, tumour and skin. The results from the task-based evaluation, which involved three radiologists, showed a high degree of realistic clinical radiological appearance of the modelled breast components. Measured HU values of the printed structures are within the range of HU values used in the computational phantom. Moreover, measured physical parameters of the breast phantom, such as weight and linear dimensions, agreed very well with the corresponding ones of the computational breast model.Significance. The presented approach, based on a single FDM material, was found suitable for manufacturing of a physical breast phantom, which mimics well the 3D spatial distribution of the different breast tissues and their x-ray absorption properties. As such, it could be successfully exploited in advanced x-ray breast imaging research applications.

Development of breast lesions models database.

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.

Models of breast lesions based on three-dimensional X-ray breast images.

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.