Design and evaluation of an anthropomorphic neck phantom for improved ultrasound diagnostics of thyroid gland tumors.

PURPOSE: Thyroid cancer is one of the most common cancers worldwide, with ultrasound-guided biopsy being the method of choice for its early detection. The accuracy of diagnostics directly depends on the qualifications of the ultrasonographers, whose performance can be enhanced through training with phantoms. The aim of this study is to propose a reproducible methodology for designing a neck phantom for ultrasound training and research from widely available materials and to validate its applicability. METHODS: The phantom was made using polyvinyl chloride mixed with additives to reproduce different levels of brightness on ultrasound screens. 3D printing and casting were used to create the neck model and various structures of the neck, including bones, cartilage, arteries, veins, lymph nodes, thyroid gland, and soft tissues. The small objects, such as tumor and lymph node models, were shaped manually. All the phantom's materials were carefully selected to match the ultrasonic speed and attenuation values of real soft tissues and bones. RESULTS: The thyroid gland contains models of a cancerous and cystic nodule. In the neck, there are models of carotid arteries and jugular veins filled with ultrasound-transparent gel. Additionally, there are replicas of lymph nodes and bone structures such as hyoid bone, thyroid cartilage, trachea, and vertebrae. The resulting phantom covers the entire neck area and has been positively received by practicing ultrasound specialists. CONCLUSIONS: The proposed manufacturing technology offers a reliable and cost-effective approach to produce an anthropomorphic neck phantom for ultrasound diagnosis of the thyroid gland. The realistic simulation provided by the phantom enhances the quality and accuracy of ultrasound examinations, contributing to better training for medical professionals and improved patient care. Subsequent research efforts can concentrate on refining the fabrication process and exploring additional features to enhance the phantom's capabilities.

Development of an anatomical breast phantom from polyvinyl chloride plastisol with lesions of various shape, elasticity and echogenicity for teaching ultrasound examination.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Innovative aberration correction in ultrasound diagnostics with direct phase estimation for enhanced image quality.

The paper addresses a crucial challenge in medical radiology and introduces a novel general approach, which utilises applied mathematics and information technology techniques, for aberration correction in ultrasound diagnostics. Ultrasound imaging of inhomogeneous media inherently suffers from variations in ultrasonic speed between tissue. The characteristics of aberrations are unique to each patient due to tissue morphology. This study proposes a new phase aberration correction method based on the Fourier transform and leveraging of the synthetic aperture mode. The proposed method enables correction after the emission and reception of ultrasonic wave, allowing for the estimation of aberration profiles for different parts of the sonogram. To demonstrate the method's performance, this study included the conducting of experiments using a commercially available quality control phantom, an ex-vivo temporal human bone, and specially designed distortion layers. At a frequency of 2 MHz, the experiments demonstrated an increase of two-and-three-quarters in echo signal intensity and a decrease of nearly two-fold in the width of the angular distribution compared to the pre-correction state. However, it is important to note that the implementation of the method has a limitation, as it requires an aperture synthesis mode and access to raw RF data, which restricts use in common scanners. To ensure the reproducibility of the results, this paper provides public access to an in-house C + + code for aberration correction following the proposed method, as well as the dataset used in this study.

Diagnostic Accuracy of AI for Opportunistic Screening of Abdominal Aortic Aneurysm in CT: A Systematic Review and Narrative Synthesis.

In this review, we focused on the applicability of artificial intelligence (AI) for opportunistic abdominal aortic aneurysm (AAA) detection in computed tomography (CT). We used the academic search system PubMed as the primary source for the literature search and Google Scholar as a supplementary source of evidence. We searched through 2 February 2022. All studies on automated AAA detection or segmentation in noncontrast abdominal CT were included. For bias assessment, we developed and used an adapted version of the QUADAS-2 checklist. We included eight studies with 355 cases, of which 273 (77%) contained AAA. The highest risk of bias and level of applicability concerns were observed for the "patient selection" domain, due to the 100% pathology rate in the majority (75%) of the studies. The mean sensitivity value was 95% (95% CI 100-87%), the mean specificity value was 96.6% (95% CI 100-75.7%), and the mean accuracy value was 95.2% (95% CI 100-54.5%). Half of the included studies performed diagnostic accuracy estimation, with only one study having data on all diagnostic accuracy metrics. Therefore, we conducted a narrative synthesis. Our findings indicate high study heterogeneity, requiring further research with balanced noncontrast CT datasets and adherence to reporting standards in order to validate the high sensitivity value obtained.

Design and validation of a phantom for transcranial ultrasonography.

PURPOSE: Commercial medical ultrasound phantoms are highly specific as they simulate particular clinical scenarios. This makes them expensive to use in multi-target research and training. General approaches to human tissue and organ modeling are described in the manufacturing methodology, access to which is restricted by the manufacturer's trade secret. Our aim is to propose a reproducible methodology to design a head phantom for transcranial ultrasound training and research from widely available materials and to validate its applicability. METHODS: To create an anthropomorphic phantom, we used data from real patients obtained by CT and MRI scans. We combined FDM and LCD 3D printing to achieve the desired acoustic performance and ergonomics of the phantom. We fabricated the phantom using polyvinyl chloride plastisol, photopolymer, and PLA to simulate brain tissue, temporal acoustic windows, and acoustically opaque parts of the skull, respectively. Notably, the phantom fabrication method uses only readily available materials and is easy to reproduce. RESULTS: We developed a basic one and anatomical one versions of the head phantom. The basic version contains a simplified brain: tissue-mimicking material is poured into the skull with needles inserted, which specific pattern is easy to recognize in B-mode images. The anatomical version has an anatomically correct brain dummy extracted from MRI data and contains multiple randomly distributed small metal, plastic, and bony objects ranging in size from 1 to 3 mm each. CONCLUSION: The proposed methodology allows producing head phantoms for transcranial ultrasound training and research. The anatomical accuracy of the model is proved by ultrasonography and CT studies. Both versions of the phantom comprise the skull and the brain and are intended for ultrasound imaging through the temporal bone acoustic window. Needles and small objects serve as navigation targets during the training procedure. The basic version helps learning basic navigation skills, while the anatomical one provides a realistic setting to perform the diagnostic procedure.