Cherkasskaya, Marina Valeryevna

Vasilev Y.A., Akhmad E.S., Cherkasskaya M.V., Semenov D.S., Panina O.Y., Petraikin A.V.

Quantitative magnetic resonance imaging is a modern method used to detect pathological changes in the patient’s tissues. However, images with quantitative characteristics are not widely used due to the limitation in accuracy and reproducibility of the measured values. The objective of this study is to formulate the metrological problem of quantitative magnetic resonance imaging and to ensure the reliability of research based on the analysis of practical approaches to quality control of diffusion-weighted magnetic resonance imaging. The use of phantoms as means to ensure quality control of certain parameters of quantitative magnetic resonance imaging was analyzed. The importance of validation was noted, and metrics used to control the quality of quantitative magnetic resonance imaging were highlighted. In addition, examples of clinical studies using diffusion-weighted magnetic resonance imaging were provided. It was found that accurate calibration and testing of magnetic resonance imaging scanners, as well as verification of image analysis tools are necessary to enable the use of quantitative magnetic resonance imaging data in clinical practice.

Vasilev V.A., Akhmad E.S., Cherkasskaya M.V., Semenov D.S., Panina O.Y., Petraikin A.V.

Quantitative magnetic resonance imaging is a modern method for detecting pathological changes in the patient’s tissues. However, images with quantitative characteristics are not widely used due to the limitation of the accuracy and reproducibility of the measured values. The purpose of this work is to formulate the metrological problem of quantitative magnetic resonance imaging and to ensure the reliability of research based on the analysis of practical approaches to quality control of diffusion-weighted magnetic resonance imaging. As part of the work performed, an analysis was carried out of the use of phantoms as means to ensure quality control of certain parameters of quantitative magnetic resonance imaging. The importance of validation was noted, the metrics used to control the quality of quantitative magnetic resonance imaging were highlighted, an overview of examples of clinical studies using diffusion-weighted magnetic resonance imaging was presented. It was found that accurate calibration and testing of magnetic resonance imaging scanners, as well as verification of image analysis tools, are necessary for the use of quantitative magnetic resonance imaging data in clinical practice.

Cherkasskaya M.V., Petraikin A.V., Omelyanskaya O.V., Leonov D.V., Vasilev Y.A.

The use of computed tomography during diagnostic examinations makes it a source of additional radiation exposure to patients. In this regard, the development of test objects (phantoms) that simulate the X-ray properties of tissues, including for preliminary assessment of the ionizing radiation distribution, becomes relevant. These test objects play an important role in quality control and the development of new medical imaging methods in conditions where test scans of patients are not possible. Although a range of ready-made solutions is available on the market, there is a lack of prototypes with a certain set of properties to test scientific and practical hypotheses in solving specific clinical and technical problems. Finding materials for a fast and inexpensive production process and studying their properties could provide insight into the effectiveness of their use in making phantoms. The purpose of the work is to search and analyze materials for creating phantoms used in computed tomography. The article discusses materials for the production of non-anthropomorphic and anthropomorphic phantoms, including those printed on a 3D printer. The development of three-dimensional printing has facilitated the transition from simple test objects to high-precision anthropomorphic phantoms made from tissue-mimicking materials that have equivalent signals on computer tomograms. Plastics, silicones, polyvinyl chloride, resins, liquids are used for visualizations identical to soft tissues; plastics, gypsum, photopolymers, potassium hydrogen orthophosphate, calcium hydroxyapatite, plexiglass — for hard tissues. Commercial phantoms are made from materials with reproducible, stable properties, but these same materials must be retested to create test objects specific to a particular clinical task.

Cherkasskiy A.I., Cherkasskaya M.V., Artamonov A.A., Galin I.Y.

The fundamental difficulty of building an information model of a target object in social networks is that a large number of characteristics (several tens) are used in the description of objects in social networks, described by all conceivable types of data: numbers, score estimates of qualitative characteristics, texts, symbols, video and audio information. Obviously, such non-additive data types cannot be used to construct any integral criterion for the specification of the target object. To solve this problem, the article introduces the concept of “vector of target search”. The general idea for solving this problem, proposed by the authors, is to convert physical characteristics into relative dimensionless quantities with normalized values from 0 to 1. The authors have implemented modern promising ideas in the development of intelligent information technologies, such as: computer training of intelligent agents using illustrative examples from the training sample, agent-based technologies for working with Big Data, the method of wave scanning of social networks when searching for target objects. The implementation of wave scanning of social networks during agent search of targets significantly reduces the computing power required to implement the search process and reduces the amount of “noise” in agent collections. Authors developed a method of marking a single object of a social network to solve the problems of streaming classification of objects in the interests of various groups of researchers, including solving the problems of targeted attraction of applicants to a higher educational institution.

Pronicheva L., Cherkasskiy A., Cherkasskaya M.

Scientific activity is a source of new knowledge and the creation of the latest technologies to improvethe quality of life. The results of research are presented in the form of articles published in scientificjournals or collections of scientific conferences, thereby being the main channel of communication inthe scientific environment, and also characterize the state of the scientific organization and the countryin the world scientific ranking. The article analyzes the world publication activity of countries on theexample of the direction - "Robotics" based on the data of the Web of Science system. It was revealedthat the development of technologies is subject to certain laws and it is possible to build predicativemodels for the emergence of new technologies.

Cherkasskiy A., Artamonov A., Cherkasskaya M., Leonova N.

Social networks are a unique phenomenon in which a large amount of unstructured information about various users is collected. The collected data can be used to identify different groups of users for the purpose of delivering targeted information to them. The article discusses the issues of building models of thematic groups of users based on multi-criteria assessment and using agent technologies of information collection and processing. The implementation of this method expands the possibilities of social research and the formation of thematic user groups for monitoring and analyzing situations in various areas of human activity. The proposed concept has shown its effectiveness on the training and control sample of objects, which makes it possible to predict the effectiveness of the use of agent technologies for scanning information resources of social media.

Vasilev Y.A., Savkina E.F., Vladzymyrskyy A.V., Omelyanskaya O.V., Arzamasov K.M.

Background. In modern medicine, artificial intelligence algorithms are being actively introduced, for testing and training of which a large amount of labeled datasets is required. Software for labeling (annotation) of digital diagnostic images is a necessary element when creating datasets. Aim. To review the capabilities and comparative analysis of the functionality of the most common available software for annotating digital diagnostic images. Material and methods. Five free and one commercial software product for annotation of digital diagnostic images participated in the comparative analysis. When testing the marking process on medical images for several target types of pathology, the usability of the graphical user interface and functionality was evaluated. The functionality of the software products has been tested by radiologists with over 5 years of experience. In addition, a review of semi-automatic segmentation methods implemented in the studied software products was carried out. As initial medical images, datasets of computed tomography studies obtained from open sources, were used. Results. Comparison of software functionality for annotation of digital diagnostic images was made: supported formats; loading, presenting and saving original images and annotation data; the possibility of visualization of medical images; annotation tools. The algorithms underlying semi-automatic segmentation methods were studied and systematized. The requirements for the basic functionality of software for labeling digital diagnostic images have been formulated. The results obtained create a systematic basis for developing recommendations for radiologists on the choice and use of digital diagnostic image marking tools. Conclusion. The most complete functionality in the field of segmentation of digital diagnostic images among the considered free software has 3D Slicer; in the case of annotation for detection tasks, it is convenient to use the Supervisely, CVAT platforms; for automatic segmentation of some types of pathology and organs, 3D Slicer extensions and ready-made models in Medseg can be used.

Peters N., Trier Taasti V., Ackermann B., Bolsi A., Vallhagen Dahlgren C., Ellerbrock M., Fracchiolla F., Gomà C., Góra J., Cambraia Lopes P., Rinaldi I., Salvo K., Sojat Tarp I., Vai A., Bortfeld T., et. al.

Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here.The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate CT phantoms have a head- and body-sized part, with tissue-equivalent inserts in regard to X-ray and proton interactions. CT numbers are extracted from a region-of-interest covering the inner 70% of each insert in-plane and several axial CT slices in scan direction. For optimal HLUT specification, the SPR of phantom inserts is measured in a proton beam and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. Including both phantom inserts and tabulated human tissues increases HLUT stability. Piecewise linear regressions are performed between CT numbers and SPRs for four tissue groups (lung, adipose, soft tissue, and bone) and then connected with straight lines. Finally, a thorough but simple validation is performed.The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility.The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can contribute to reduce inter-centre variations in SPR prediction.

Breslin T., Paino J., Wegner M., Engels E., Fiedler S., Forrester H., Rennau H., Bustillo J., Cameron M., Häusermann D., Hall C., Krause D., Hildebrandt G., Lerch M., Schültke E.

The production of anthropomorphic phantoms generated from tissue-equivalent materials is challenging but offers an excellent copy of the typical environment encountered in typical patients. High-quality dosimetry measurements and the correlation of the measured dose with the biological effects elicited by it are a prerequisite in preparation of clinical trials with novel radiotherapy approaches. We designed and produced a partial upper arm phantom from tissue-equivalent materials for use in experimental high-dose-rate radiotherapy. The phantom was compared to original patient data using density values and Hounsfield units obtained from CT scans. Dose simulations were conducted for broad-beam irradiation and microbeam radiotherapy (MRT) and compared to values measured in a synchrotron radiation experiment. Finally, we validated the phantom in a pilot experiment with human primary melanoma cells.

Leonov D., Venidiktova D., Costa-Júnior J.F., Nasibullina A., Tarasova O., Pashinceva K., Vetsheva N., Bulgakova J., Kulberg N., Borsukov A., Saikia M.J.

The WHO reported an increasing trend in the number of new cases of breast cancer, making it the most prevalent cancer in the world. This fact necessitates the availability of highly qualified ultrasonographers, which can be achieved by the widespread implementation of training phantoms. The goal of the present work is to develop and test an inexpensive, accessible, and reproducible technology for creating an anatomical breast phantom for practicing ultrasound diagnostic skills in grayscale and elastography imaging, as well as ultrasound-guided biopsy sampling. We used FDM 3D printer and PLA plastic for printing an anatomical breast mold. We made a phantom using a mixture of polyvinyl chloride plastisol, graphite powder, and metallic glitter to simulate soft tissues and lesions. Various degrees of elasticity were imparted using plastisols of stiffness ranging from 3 to 17 on the Shore scale. The lesions were shaped by hand. The materials and methods used are easily accessible and reproducible. Using the proposed technology, we have developed and tested a basic, differential, and elastographic versions of the breast phantom. The three versions of the phantom are anatomical and intended for use in medical education: the basic version is for practicing primary hand–eye coordination skills; the differential one is for practicing the differential diagnosis skills; the elastographic version helps developing the skills needed for assessing the stiffness of tissues. The proposed technology allows the creation of breast phantoms for practicing hand–eye coordination and develop the critical skills for navigation and assessment of the shape, margins, and size of the lesion, as well as performing an ultrasound-guided biopsy. It is cost-effective, reproducible, and easily implementable, and could be instrumental in generating ultrasonographers with crucial skills for accurate diagnosis of breast cancer, especially in low-resource settings.

Ma X., Figl M., Unger E., Buschmann M., Homolka P.

Additive manufacturing and 3D printing are widely used in medical imaging to produce phantoms for image quality optimization, imaging protocol definition, comparison of image quality between different imaging systems, dosimetry, and quality control. Anthropomorphic phantoms mimic tissues and contrasts in real patients with regard to X-ray attenuation, as well as dependence on X-ray spectra. If used with different X-ray energies, or to optimize the spectrum for a certain procedure, the energy dependence of the attenuation must replicate the corresponding energy dependence of the tissues mimicked, or at least be similar. In the latter case the materials’ Hounsfield values need to be known exactly to allow to correct contrast and contrast to noise ratios accordingly for different beam energies. Fresh bovine and porcine tissues including soft and adipose tissues, and hard tissues from soft spongious bone to cortical bone were scanned at different energies, and reference values of attenuation in Hounsfield units (HU) determined. Mathematical model equations describing CT number dependence on kV for bones of arbitrary density, and for adipose tissues are derived. These data can be used to select appropriate phantom constituents, compare CT values with arbitrary phantom materials, and calculate correction factors for phantoms consisting of materials with an energy dependence different to the tissues. Using data on a wide number of additive manufacturing and 3D printing materials, CT numbers and their energy dependence were compared to those of the tissues. Two commercially available printing filaments containing calcium carbonate powder imitate bone tissues with high accuracy at all kV values. Average adipose tissue can be duplicated by several off-the-shelf printing polymers. Since suitable printing materials typically exhibit a too high density for the desired attenuation of especially soft tissues, controlled density reduction by underfilling might improve tissue equivalence.

Partridge S.C., Steingrimsson J., Newitt D.C., Gibbs J.E., Marques H.S., Bolan P.J., Boss M.A., Chenevert T.L., Rosen M.A., Hylton N.M.

In diffusion-weighted MRI (DW-MRI), choice of b-value influences apparent diffusion coefficient (ADC) values by probing different aspects of the tissue microenvironment. As a secondary analysis of the multicenter ECOG-ACRIN A6698 trial, the purpose of this study was to investigate the impact of alternate b-value combinations on the performance and repeatability of tumor ADC as a predictive marker of breast cancer treatment response. The final analysis included 210 women who underwent standardized 4-b-value DW-MRI (b = 0/100/600/800 s/mm2) at multiple timepoints during neoadjuvant chemotherapy treatment and a subset (n = 71) who underwent test–retest scans. Centralized tumor ADC and perfusion fraction (fp) measures were performed using variable b-value combinations. Prediction of pathologic complete response (pCR) based on the mid-treatment/12-week percent change in each metric was estimated by area under the receiver operating characteristic curve (AUC). Repeatability was estimated by within-subject coefficient of variation (wCV). Results show that two-b-value ADC calculations provided non-inferior predictive value to four-b-value ADC calculations overall (AUCs = 0.60–0.61 versus AUC = 0.60) and for HR+/HER2− cancers where ADC was most predictive (AUCs = 0.75–0.78 versus AUC = 0.76), p < 0.05. Using two b-values (0/600 or 0/800 s/mm2) did not reduce ADC repeatability over the four-b-value calculation (wCVs = 4.9–5.2% versus 5.4%). The alternate metrics ADCfast (b ≤ 100 s/mm2), ADCslow (b ≥ 100 s/mm2), and fp did not improve predictive performance (AUCs = 0.54–0.60, p = 0.08–0.81), and ADCfast and fp demonstrated the lowest repeatability (wCVs = 6.71% and 12.4%, respectively). In conclusion, breast tumor ADC calculated using a simple two-b-value approach can provide comparable predictive value and repeatability to full four-b-value measurements as a marker of treatment response.

Boss M.A., Snyder B.S., Kim E., Flamini D., Englander S., Sundaram K.M., Gumpeni N., Palmer S.L., Choi H., Froemming A.T., Persigehl T., Davenport M.S., Malyarenko D., Chenevert T.L., Rosen M.A.

Background Uncertainty regarding the reproducibility of the apparent diffusion coefficient (ADC) hampers the use of quantitative diffusion-weighted imaging (DWI) in evaluation of the prostate with magnetic resonance imaging MRI. The quantitative imaging biomarkers alliance (QIBA) profile for quantitative DWI claims a within-subject coefficient of variation (wCV) for prostate lesion ADC of 0.17. Improved understanding of ADC reproducibility would aid the use of quantitative diffusion in prostate MRI evaluation. Purpose Evaluation of the repeatability (same-day) and reproducibility (multi-day) of whole-prostate and focal-lesion ADC assessment in a multi-site setting. Study Type Prospective multi-institutional. Subjects Twenty-nine males, ages 53 to 80 (median 63) years, following diagnosis of prostate cancer, 10 with focal lesions. Field Strength/Sequence 3T, single-shot spin-echo diffusion-weighted echo-planar sequence with four b-values. Assessment Sites qualified for the study using an ice-water phantom with known ADC. Readers performed DWI analyses at visit 1 (“V1”) and visit 2 (“V2,” 2–14 days after V1), where V2 comprised scans before (“V2pre”) and after (“V2post”) a “coffee-break” interval with subject removal and repositioning. A single reader segmented the whole prostate. Two readers separately placed region-of-interests for focal lesions. Statistical Tests Reproducibility and repeatability coefficients for whole prostate and focal lesions derived from median pixel ADC. We estimated the wCV and 95% confidence interval using a variance stabilizing transformation and assessed interreader reliability of focal lesion ADC using the intraclass correlation coefficient (ICC). Results The ADC biases from b0–b600 and b0–b800 phantom scans averaged 1.32% and 1.44%, respectively; mean b-value dependence was 0.188%. Repeatability and reproducibility of whole prostate median pixel ADC both yielded wCVs of 0.033 (N = 29). In 10 subjects with an evaluable focal lesion, the individual reader wCVs were 0.148 and 0.074 (repeatability) and 0.137 and 0.078 (reproducibility). All time points demonstrated good to excellent interreader reliability for focal lesion ADC (ICCV1 = 0.89; ICCV2pre = 0.76; ICCV2post = 0.94). Data Conclusion This study met the QIBA claim for prostate ADC. Test–retest repeatability and multi-day reproducibility were largely equivalent. Interreader reliability for focal lesion ADC was high across time points. Level of Evidence 1 Technical Efficacy Stage 2 TOC Category Pelvis

Khoruzhaya A.N., Ahkmad E.S., Semenov D.S.

Modern medical imaging methods allow for both qualitative and quantitative evaluations of tumors and issues surrounding them. Advances in computer science and big data processing are transforming any radiological study into analytic datasets, especially with the use of machine learning in medical image analysis. Among these datasets, statistically significant correlations with clinical events can then be searched for to subsequently assess their predictive value and ability to predict a particular clinical outcome. This concept, known as radiomics, was first described in 2012. It is particularly important in oncology because each type of tumor can be subdivided into many different molecular genetic subtypes, and simple visual characteristics are no longer sufficient. Moreover, as an absolutely noninvasive method, radiomics can provide a radiologist with additional information that would otherwise be unavailable without a histological examination of biopsy material. However, as with any methodology based on the use of big data, the question of the quality of the initial data becomes critical, because this can directly affect the outcome of the analysis and provide incorrect diagnostic information. In this literature review, we examine potential approaches to ensuring the quality of research at all stages, from technical control of the state of diagnostic equipment to the extraction of imaging markers in oncology and the calculation of their correlation with clinical data.

Ahmadi M., Ramezani Anarestani M., Hariri Tabrizi S., Azma Z.

A new multi-purpose Iranian head and neck (MIHAN) anthropomorphic phantom was designed and manufactured to be used in diagnostic and therapeutic applications. Geometry of MIHAN phantom was determined based on the average dimensions acquired by CT scans of twenty patients without any medical problems in their head and neck site. Because the phantom was expected to be used with different modalities with a wide range of photon energies, attenuation coefficients of some selected materials were determined using Monte Carlo simulation. Based on analytical and simulation results, acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) were found suitable choices for soft and bony tissues, respectively. They were used in the 3D printer to build the phantom. The suitability of the materials was checked by CT number value comparison between the organs included in the phantom and the corresponding body tissues and also film dosimetry of a typical intensity-modulated radiation therapy (IMRT) plan.. Hounsfield Unit agreement and 95% ± 2% pass rate for the IMRT plan verification proved the suitability of material selection. Also, the film dosimetry showed feasibility of using MIHAN in radiotherapy plan verification workflow. In addition, PLA was introduced as a spongy bone tissue substitute for the first time.

Cashmore M.T., McCann A.J., Wastling S.J., McGrath C., Thornton J., Hall M.G.

MRI has been an essential diagnostic tool in healthcare for several decades. It offers unique insights into most tissues without the need for ionising radiation. Historically, MRI has been predominantly used qualitatively, images are formed to allow visual discrimination of tissues types and pathologies, rather than providing quantitative measurements. Increasingly, quantitative MRI (qMRI) is also finding clinical application, where images provide the basis for physical measurements of, e.g. tissue volume measures and represent aspects of tissue composition and microstructure. This article reviews some common current research and clinical applications of qMRI from the perspective of measurement science. qMRI not only offers additional information for radiologists, but also the opportunity for improved harmonisation and calibration between scanners and as such it is well-suited to large-scale investigations such as clinical trials and longitudinal studies. Realising these benefits, however, presents a new kind of technical challenge to MRI practioners. When measuring a parameter quantitatively, it is crucial that the reliability and reproducibility of the technique are well understood. Strictly speaking, a numerical result of a measurement is meaningless unless it is accompanied by a description of the associated measurement uncertainty. It is therefore necessary to produce not just estimates of physical properties in a quantitative image, but also their associated uncertainties. As the process of determining a physical property from the raw MR signal is complicated and multistep, estimation of uncertainty is challenging and there are many aspects of the MRI process that require validation. With the clinical implementation of qMRI techniques and its continued expansion, there is a clear and urgent need for metrology in this field.

Shur J., Blackledge M., D’Arcy J., Collins D.J., Bali M., O’Leach M., Koh D.

To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. Separate water and tissue phantoms were imaged twice with the same protocol in a test-retest experiment using a 1.5-T scanner. Protocols were acquired to favour signal-to-noise ratio and resolution. Forty-six features including first order statistics and second-order texture features were extracted, and repeatability was assessed by calculating the concordance correlation coefficient. Separately, base image noise and resolution were manipulated in an in silico experiment, and robustness of features was calculated by assessing percentage coefficient of variation and linear correlation of features with noise and resolution. These simulation data were compared with the acquired data. Features were classified by their degree (high, intermediate, or low) of robustness and repeatability. Eighty percent of the MRI features were repeatable (concordance correlation coefficient > 0.9) in the phantom test-retest experiment. The majority (approximately 90%) demonstrated a strong or intermediate correlation with image acquisition parameter, and 19/46 (41%) and 13/46 (28%) of features were highly robust to noise and resolution, respectively (coefficient of variation < 5%). Agreement between the acquired and simulation data varied, with the range of agreement within feature classes between 11 and 92%. Most MRI features were repeatable in a phantom test-retest study. This phantom data may serve as a lower limit of feature MRI repeatability. Robustness of features varies with acquisition parameter, and appropriate features can be selected for clinical validation studies.

Whisenant J.G., Romanoff J., Rahbar H., Kitsch A.E., Harvey S.M., Moy L., DeMartini W.B., Dogan B.E., Yang W.T., Wang L.C., Joe B.N., Wilmes L.J., Hylton N.M., Oh K.Y., Tudorica L.A., et. al.

Abstract Objective The A6702 multisite trial confirmed that apparent diffusion coefficient (ADC) measures can improve breast MRI accuracy and reduce unnecessary biopsies, but also found that technical issues rendered many lesions non-evaluable on diffusion-weighted imaging (DWI). This secondary analysis investigated factors affecting lesion evaluability and impact on diagnostic performance. Methods The A6702 protocol was IRB-approved at 10 institutions; participants provided informed consent. In total, 103 women with 142 MRI-detected breast lesions (BI-RADS assessment category 3, 4, or 5) completed the study. DWI was acquired at 1.5T and 3T using a four b-value, echo-planar imaging sequence. Scans were reviewed for multiple quality factors (artifacts, signal-to-noise, misregistration, and fat suppression); lesions were considered non-evaluable if there was low confidence in ADC measurement. Associations of lesion evaluability with imaging and lesion characteristics were determined. Areas under the receiver operating characteristic curves (AUCs) were compared using bootstrapping. Results Thirty percent (42/142) of lesions were non-evaluable on DWI; 23% (32/142) with image quality issues, 7% (10/142) with conspicuity and/or localization issues. Misregistration was the only factor associated with non-evaluability (P = 0.001). Smaller (≤10 mm) lesions were more commonly non-evaluable than larger lesions (p &lt;0.03), though not significant after multiplicity correction. The AUC for differentiating benign and malignant lesions increased after excluding non-evaluable lesions, from 0.61 (95% CI: 0.50–0.71) to 0.75 (95% CI: 0.65–0.84). Conclusion Image quality remains a technical challenge in breast DWI, particularly for smaller lesions. Protocol optimization and advanced acquisition and post-processing techniques would help to improve clinical utility.

Onykiy B., Antonov E., Artamonov A., Tretyakov E.

Vasilev Y.A., Semenov D.S., Akhmad E.S., Panina O.Y., Sergunova K.A., Petraikin A.V.

The effect of metal artifact reduction algorithms on CT image quality was considered. The mean signal intensities and noise levels were compared for objects with different X-ray densities and spatial positions using phantom modeling. It was shown that, despite an improvement in the visual characteristics of the images, their quantitative characteristics may deteriorate: the change in the mean density reached in some cases 15%; the increase in noise, 30%.

Mille M.M., Griffin K.T., Maass‐Moreno R., Lee C.

To demonstrate an on-demand and nearly automatic method for fabricating tissue-equivalent physical anthropomorphic phantoms for imaging and dosimetry applications using a dual nozzle thermoplastic three-dimensional (3D) printer and two types of plastic.Two 3D printing plastics were investigated: (a) Normal polylactic acid (PLA) as a soft tissue simulant and (b) Iron PLA (PLA-Fe), a composite of PLA and iron powder, as a bone simulant. The plastics and geometry of a 1-yr-old computational phantom were combined with a dual extrusion 3D printer to fabricate an anthropomorphic imaging phantom. The volumetric fill density of the 3D-printed parts was varied to approximate tissues of different radiographic density using a calibration curve relating the printer infill density setting to measured CT number. As a demonstration of our method we printed a 10 cm axial cross-section of the computational phantom's torso at full scale. We imaged the phantom on a CT scanner and compared HU values to those of a 1-yr-old patient and a commercial 5-yr-old physical phantom.The phantom was printed in six parts over the course of a week. The printed phantom included 30 separate anatomical regions including soft tissue remainder, lungs (left and right), heart, esophagus, rib cage (left and right ribs 1 to 10), clavicles (left and right), scapulae (left and right), thoracic vertebrae (one solid object defining thoracic vertebrae T1 to T9). CT scanning of the phantom showed five distinct radiographic regions (heart, lung, soft tissue remainder, bone, and air cavity) despite using only two types of plastic. The 3D-printed phantom demonstrated excellent similarity to commercially available phantoms, although key limitations in the printer and printing materials leave opportunity for improvement.Patient-specific anthropomorphic phantoms can be 3D printed and assembled in sections for imaging and dosimetry applications. Such phantoms will be useful for dose verification purposes when commercial phantoms are unavailable for purchase in the specific anatomies of interest.