Research Challenges Accuracy of FDM 3D-Printed Medical Models

Ben Searle and Deborah Starkey, both Australian researchers from Queensland University of Technology, explore better ways to create 3D-printed medical models. Their findings are outlined in the recently published “An investigation into the effect of changing the computed tomography slice reconstruction interval on the spatial replication accuracy of three-dimensional printed anatomical models constructed by fused deposition modeling.”

As 3D printing continues to expand as an important presence in the area of medicine, doctors are becoming more reliant on 3D-printed models and a wide range of devices which aid in diagnosing, treating, educating, and planning for surgeries; in fact, 3D-printed models also play a part in the operating room, serving as guides for surgeons who may be performing procedures that are new or extremely rare. Access to cadavers, previously a main form of training, is often limited—while 3D-printed models can be made (and easily modified) on demand.

Time in the operating room can be significantly reduced, sometimes up to 20 percent. Searle and Starkey report; however, that “inaccurate anatomical representation” is still a major issue and a major flaw—especially when the results could lead to “suboptimal treatment planning.” Defects have been reported including inferior view of details like arteries, occluded foramina, and blurred sutures.

Scan‐to‐print 3D printing pipeline.

While CT scans are used for imaging, FDM 3D printing is often used for 3D-printed models due to accessibility and affordability:

“FDM printers can be operated and maintained without advanced training and can easily fit into existing workspaces,” explain the authors.

In this study, however, the researchers are concerned with the accuracy and impact of slice width and what improvements could be made:

“Slice width has a direct impact on 3D models created from an imaging data set, as higher slice widths result in lower image resolution and anatomical detail. The data from consecutive detector elements in a CT scanner can be combined to reconstruct a number of image series at a range of slice widths from the same raw scan data,” the authors write. “Due to the novel nature of the technology, there is a lack of published literature addressing the influence of reconstruction in CT scan data on the accurate reproduction of 3D‐printed anatomical models, particularly the SRI.”

Bovine coccygeal vertebrae.

European forearm phantom (Quality assurance in radiology and medicine, GmbH, Möhrendorf, Germany).

For their research, the authors used three bovine vertebrae (no animals were harmed) and an imaging phantom, separating data into slice reconstruction intervals (SRIs) of 0.1, 0.3, 0.5 and 1 mm.

Segmentation and triangulation of the bovine vertebrae in 3D slicer version 4.8 (The Slicer Community, Harvard, MA, USA), an open‐source software package for medical imaging computing.

Mesh inspection and repair in Meshmixer version 3.5 (Autodesk inc., San Rafael, CA, USA).

After creating a mesh file to import into Meshmixer, the authors exported files to a Malyan M200 (x‐y resolution of 0.011 mm, layer resolution of 0.1 mm and a nozzle width of 0.4 mm), with supports being used during 3D printing.

3D printed models produced by a Malyan M200 3D printer (Zhangzhou Changfeng Computer Equipment Co., Ltd, China).

The samples that were fabricated were deemed as “highly realistic” and “suitable for measurement and analysis.” Further, however, the researchers noted that, during the slicing process, there was loss of accuracy in the models when they used smaller SRIs than the primary limiting factor of either acquisition slice or printer spatial resolution capabilities. Using greater SRIs also resulted in less accuracy, due to the following:

• Sum of volume averaging effects
• Print error
• Processing error
• Loss of spatial resolution

The authors also noted that for even the most accurate 3D models that they produced, there was a “mean variation of approximately 0.5 mm.”

“However, the spatial resolution error of FDM printers can be significant relative to the acquisition slice width and SRI distances due to printer nozzle width limitations. This is particularly applicable in this study where the FDM printer nozzle width of 0.4 mm is similar to the acquisition slice width of 0.5 mm,” explained the authors.

“This study has successfully achieved research aims by demonstrating that changing the SRI influences the spatial replication accuracy of 3D‐printed anatomical models. It has also demonstrated that a benefit exists in using a SRI equal to or less than the primary limiting factor of either the acquisition slice width or printer capabilities by optimizing the replication accuracy of the model whilst minimizing the digital size of the data and required processing time investment. Consequently, this study can help refine 3D printing protocols in medical and tissue engineering applications and help practitioners to create accurate reproductions of anatomy for various teaching and clinical purposes.”

As 3D printed models continue to offer benefits to medical professionals especially, they are used for aid in hip surgeries, pediatric orthopedic surgeries, and studying congenital heart disease.

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