Advancing Medical Device Design with Tunable Radiopaque 3D Printing

Recent developments in 3D printing materials allow for better simulation of human anatomy, not only in shape but also in how tissues appear in medical imaging such as X-rays and CT scans. RadioMatrix, developed by Stratasys with Siemens Healthineers, offers a material option for engineers designing medical devices to create models that can be adjusted for radiopacity, providing a more detailed approach to testing and imaging.

Medical device engineers often need to test and validate prototypes in ways that closely replicate real human tissues and anatomy. Allison Harbaugh, medical business manager at Stratasys, talked with Machine Design about radiopaque 3D printing’s capability to allow for the production of physical models that more accurately represent patient-specific anatomy during imaging-based testing, calibration and training procedures.

Technical Overview of RadioMatrix Radiopacity Control 

RadioMatrix’s distinguishing feature is its ability to define radiographic density in terms of Hounsfield units (HU)—a standardized scale used in CT imaging to quantify radiodensity. Harbaugh describes the range from approximately −1,000 HU (equivalent to air) up to 1,000 HU or more (typical bone density ranges between 700-3,000). Users can specify different HU values for distinct segments of a 3D-printed model within a single build, enabling realistic replication of complex anatomical structures such as soft tissue, bone and pathological features like tumors.

The user selects these HU values via Stratasys’s GrabCAD software, which simplifies assignment within design files using an STL-based workflow. According to Harbaugh, “You can say you want anywhere from low to high Hounsfield units, and the printer will give you the required material mix to produce that density consistently.”

A Look at Material Science and Printer Mechanics

Harbaugh told Machine Design that developing RadioMatrix involved significant challenges in material science, especially related to achieving the right balance between softness to mimic human tissue and printability. The material must be soft enough to replicate the mechanical properties of native tissue—such as elasticity and compressibility—while still being compatible with the PolyJet printing process, which deposits ultra-fine resin droplets.

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She says the softness presents a technical hurdle because materials with high fluidity can clog printer nozzles, reducing reliability. Harbaugh explains how Stratasys engineering teams developed resin formulations that maintain a soft, gel-like consistency suitable for mimicking soft tissues, yet are stable enough for consistent extrusion and layering without clogging or print defects.

RadioMatrix itself is blended with other model materials during printing. On the Digital Anatomy J850 printer, for instance, up to seven different model materials can be combined in precise ratios within each voxel (3D pixel) of the printed object. This multi-material mixing allows complex internal structures to be replicated, such as varying bone porosity or the presence of tumors within soft tissue.

PolyJet Printing Technology and Digital Anatomy Platforms 

The printing platform plays a critical role in realizing these material properties into functional models. Stratasys uses PolyJet technology, which functions similarly to inkjet printing but with photopolymer resins, Harbaugh explained. Tiny droplets of resin are jetted onto the build tray, layer-by-layer, and each layer is cured rapidly by an integrated UV light source.

Harbaugh described the Digital Anatomy printers—specifically the J850 and the smaller J5—as specialized systems designed for intricate anatomical modeling. The J850 features a large build volume roughly 11 × 15 in. wide and 8 in. tall, allowing for printing of entire heads or chest cavities. The J5 has a circular build tray accommodating smaller or sectionalized body parts.

She said that each printer is equipped with advanced print heads capable of mixing multiple materials in precise proportions on the fly, guided by the digital file’s assigned settings for radiopacity and tissue properties. This enables seamless integration of RadioMatrix with existing bone matrix, vessel-like gel matrix and other proprietary resins to build heterogeneous models indistinguishable from biological tissue in both feel and radiographic response.

Print Workflow and Material Handling 

Stratasys’s GrabCAD software interfaces with the printers to manage material mixing, layer buildup and print orientation. Harbaugh points out that the software automates critical steps such as support structure generation, print bed layout optimization and print time/material estimations, which reduces manual intervention and enables operators to produce complex models efficiently.

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Material handling also includes ongoing printer maintenance. Resin tanks are dual-canister designs that automatically switch to backup supplies to avoid print interruptions. After printing, models are coated with a soft support material resembling dried gelatin, which must be removed manually through methods like soaking in cleaning tanks or water jetting. Maintenance routines require operators to clean the print beds and print heads regularly to prevent resin buildup, ensuring consistent print quality.

Applications in Phantom Production and Medical Device Testing 

Phantoms—models used to simulate human tissue for imaging and equipment calibration—have traditionally been expensive and limited in variety. Harbaugh says that printing phantoms with RadioMatrix can reduce costs and increase the variety and consistency of available models. This flexibility supports more detailed testing scenarios for medical devices and imaging technologies.

Harbaugh stresses that these 3D-printed phantoms can simulate variations in anatomy and pathology more easily than off-the-shelf models. This helps hospitals, labs and manufacturers conduct more realistic and frequent testing without the financial and logistical constraints of traditional phantoms.

Additionally, medical device manufacturers can leverage RadioMatrix to create patient-specific prototypes for testing implant fit, procedural planning or device calibration. One innovative application under discussion is the use of radioopaque "trial" implants that surgeons can verify with intraoperative imaging before final implantation.

Workflow from Patient Data to Printed Model 

Starting from patient CT or MRI scans, design engineers use segmentation software (including Siemens Healthineers tools and others like Materialize or Synopsys) to extract DICOM data and convert it into 3D-printable STL files. Harbaugh says that a scanned anatomy is typically divided into separate STL components corresponding to organs, bones or vessels. These can be assigned individual radiopacity values before being printed as a unified model.

Post-processing involves support material removal, usually by soaking the print in a cleaning tank or water-jetting to remove a gel-like support substance. Parts may also be coated to enhance durability or appearance as needed. Harbaugh notes that while some post-processing is required, models generally come off the build-plate nearly ready for use.

Practical Considerations for Design Engineers 

Patient-specific models printed with RadioMatrix can help design engineers and clinicians simulate real-world conditions with greater accuracy. Harbaugh said this can assist with device validation and surgical planning by providing radiographically accurate feedback on device placement and imaging interaction. The ability to mix multiple materials also lets design teams produce non-patient-specific components such as surgical guides, jigs or testing fixtures on the same equipment, improving facility utilization.

On cost and efficiency, she estimates a 5-10× cost reduction in phantom production compared with traditional methods, with substantial savings on time as molds and manual casting steps are eliminated.

Looking ahead, Harbaugh predicted radiopaque 3D printing materials will see broader use in medical device testing, radiology training and imaging protocol optimization. She pointed to the ability to create reproducible, customizable patient models as an advantage