Fabrication and evaluation of breast tissue equivalent phantoms for image quality assessment in ultrasound imaging

Introduction: Phantom materials with tissue-equivalent physical properties that require regular evaluation using patented phantoms are essential for medical device quality assurance programs. This study evaluated phantom materials for tissue equivalence and their use in image quality assessment for breast ultrasound scanner performance testing using two custom-made phantoms. Methods: Two types of phantoms were developed: phantoms A and B. Phantom A was made from a base material consisting of polyvinyl chloride-plastisol with the addition of glycerol, whereas phantom B consisted of polyvinyl chloride-plastisol with the addition of graphite. Each phantom had a stiff and soft lesion shaped like a sphere, with a diameter of 1.4 cm. The phantoms were cuboids with dimensions of 10 x 10 cm(2) and a thickness of 5 cm. A series of phantom evaluations was performed, consisting of density, elasticity, acoustic properties, B-mode ultrasound images, and strain ratio. Results: The characterisation results show that background A closely resembles fibroglandular tissue in terms of density and acoustic properties (<5% variation); background B only resembles fibroglandular tissue in terms of density (-1.8% variation). In terms of elasticity, both backgrounds were close to the minimum value of fibroglandular tissue elasticity. The soft lesion on the phantom had a slightly lower density and elasticity than the carcinoma, whereas its acoustic properties (speed of sound and attenuation coefficient) were slightly higher than those of the reference carcinoma. Both phantoms were consistent with the literature in terms of strain ratio, geometric accuracy, lesion detection, and mean pixel value and showed good potential stability over one year. Conclusion: This study successfully described the fabrication and evaluation sequence of a phantom equivalent to breast fibroglandular tissue and its evaluation via ultrasound imaging. (c) 2024 The College of Radiographers. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.