# Advancing Phantom Fabrication: Exploring 3D-Printed Solutions for Abdominal Imaging Research
## 1 Introduction  
The development of novel medical imaging technologies and treatment procedures hinges on the availability of accurate and versatile phantoms. Anthropomorphic phantoms, replicating human anatomy, offer a safe and controlled environment for evaluating these advancements [1]. Ideal phantoms possess two key characteristics: geometric fidelity that precisely mirrors human anatomy and tissue-equivalent materials that mimic the X-ray attenuation properties of real tissues across the relevant energy spectrum [2]. Traditionally, abdominal phantoms have been fabricated using materials like silicone or tissue-equivalent plastics. Hydrogels, including those combined with beeswax, offer improved tissue mimicry with adjustable mechanical properties, making them suitable for various medical applications [3, 4]. Silicone phantoms can be prohibitively expensive and time-consuming to manufacture due to complex molding processes. Tissue-equivalent plastics, while more readily available, often require specialized equipment and expertise for handling and manipulation. Additionally, both materials can exhibit limitations in their ability to replicate the full spectrum of tissue properties within the abdomen [5]. A novel and cost-effective approach for creating anthropomorphic abdominal phantoms could be to use a combination of 3D printing, beeswax, and epoxy resin for appendix analysis. Three-dimensional printing technology offers unparalleled design flexibility, enabling the creation of intricate anatomical structures with high fidelity. Beeswax, a natural product derived from honeycombs, has garnered attention for its potential applications in various fields, including biomedical engineering. Its unique composition and properties make it a promising candidate for developing tissue-mimicking materials. Chemically, beeswax is primarily composed of esters, hydrocarbons, and free acids [6]. This complex molecular structure imparts beeswax with distinctive characteristics, such as a high melting point and malleability, facilitating its processing and shaping into desired forms [7]. Epoxy resin, a versatile casting material, provides a robust matrix for embedding the 3D-printed components. Additionally, the properties of the epoxy resin can be further tailored by incorporating specific fillers to mimic the X-ray attenuation characteristics of different tissues within the phantom [8]. Furthermore, Fused Deposition Modeling (FDM) has been extensively reviewed in the context of anthropomorphic phantom creation. FDM is a popular 3D printing technique that uses thermoplastic materials to build objects layer by layer. While it offers advantages such as cost-effectiveness and ease of use, its application in creating high-fidelity phantoms is limited by the resolution and material properties achievable with current FDM printers [9]. Recent developments in medical imaging have made more use of 3D printing technology to create highly accurate anthropomorphic phantoms. These phantoms are essential tools for radiation dosage optimization, especially in complex imaging modalities like CT scans [10]. More efficient dose reduction tactics are made possible by the capacity to closely imitate the qualities of human tissue, improving patient safety without sacrificing diagnostic precision. Even with all the advancements in this industry, the choice of materials and printing methods used to create phantoms continues to have a major impact on how effective these models are. Furthermore, it is still unclear how well 3D-printed phantoms compare to solutions that are readily available on the market and patient-derived data [11]. Table 1 summarizes the key findings from this literature review, highlighting the advantages, limitations, and clinical implications of various approaches. We performed this study to investigate the development and characterization of a 3D-printed composite beeswax-epoxy abdominal phantom for a better analysis of the appendix and scanning parameter optimization.