IntroductionThe development and optimization of novel diagnostic imaging prototypes heavily rely on experimental work. In radiology, this experimental work involves the use of phantoms. When testing novel techniques to demonstrate their advantages, anthropomorphic phantoms are utilized. The aim of this study was to investigate seven materials for 3D printing to replicate the radiological properties of breast lesions.MethodsTo achieve this objective, we utilized three fused filament fabrication materials, namely, polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), and polyethylene terephthalate glycol (PET-G), along with resins such as White v4 Resin, Flexible 80A v1 Resin, Model v2 Resin, and Wax40 v1 Resin, to 3D print seven irregularly shaped lesions. These lesions were used to prepare a set of seven physical phantoms, each filled with either water or liquid paraffin, and one of the printed lesions. The phantoms were then scanned using a mammography unit at 28 kVp. Additionally, six computational breast phantoms, replicating the shape of the physical phantoms, were generated. These computational models were assigned the attenuating properties of various breast tissues, including glandular tissue, adipose tissue, skin, and lesions. Mammography images were generated under the same experimental conditions as the physical scans. Both the simulated and experimental images were evaluated for their contrast-to-noise ratio (CNR) and contrast (C).DiscussionThe results indicated that the studied resins and filament-based materials are all suitable for replicating breast lesions. Among these, PLA and White v4 Resin exhibited the densest formations and can effectively approximate breast lesions that are slightly less attenuating than glandular tissue, while ABS and Flexible 80A v1 Resin were the least dense and can represent fat-containing breast lesions. The remaining materials provided good approximations for malignant lesions. These materials can be utilized for constructing phantoms for experimental work, rendering the model a valuable tool for optimizing mammography protocols, ensuring quality control of mammography X-ray equipment, and aiding in the diagnosis and assessment of breast cancer.