The research team, led by Neha Sharma of the University Hospital Basel and Duke-NUS Medical School together with colleagues at the University of Basel, Iuliu Hatieganu University of Medicine and Pharmacy in Romania, and the University Center for Dental Medicine Basel, set out to answer a deceptively simple question: what happens to the dimensional accuracy and mechanical strength of modern 3D-printed photopolymer resins when they are exposed to clinically realistic sterilization cycles? The stakes are higher than they might appear. Standard steam autoclaving runs at 121 degrees Celsius, but prion inactivation protocols demanded by infection-control authorities require an extended cycle holding a searing 134 degrees Celsius for at least 18 minutes. That thermal assault had never been systematically evaluated on the contemporary biocompatible resins now flowing through hospital 3D print labs.

To close that gap, the investigators selected four commercially available biocompatible photopolymer resins: P pro Surgical Guide Clear, ProArt Print Splint, BioMed Clear Resin, and BioMed Amber Resin. Two additive manufacturing platforms were represented, stereolithography, which cures liquid resin with a precisely steered ultraviolet laser, and digital light processing, which cures entire layers at once using a projected light pattern. The experimental design deliberately worked at two scales. First, the team printed 240 standardized ISO specimens for rigorous benchtop testing of dimensional accuracy and flexural strength, the classic three-point bending measure of how much load a material can carry before fracturing. Second, they printed 72 clinically relevant patient-specific guides representing two real surgical scenarios: cranial resection guides and oral implantology guides. This dual approach ensured the findings would speak both to materials scientists and to surgeons.

The specimens were randomly allocated to three experimental groups. A baseline group remained non-sterilized, a steam group underwent the extended prion-inactivation autoclave cycle at 134 degrees Celsius for 18 minutes, and a plasma group was treated with low-temperature hydrogen peroxide plasma sterilization at a gentle 55 degrees Celsius for 19 minutes. Dimensional accuracy was quantified using root mean square deviation analysis, a method that compares the printed object against its digital design point by point and expresses mismatch as a single deviation value in micrometers. Statistical evaluation relied on two-way analyses of variance followed by Bonferroni post-hoc testing, with the significance threshold set at 0.05.

The accuracy results told a nuanced story. Across the board, deviation was lowest for the simple ISO specimens, averaging 61 plus or minus 24 micrometers, followed by the cranial guides at 119 plus or minus 29 micrometers and the oral implantology guides at 147 plus or minus 45 micrometers. Geometry, in other words, matters: the more complex and curved the anatomy a guide must capture, the harder it is to print true. Material selection proved equally decisive. The ProArt Print Splint and P pro Surgical Guide Clear resins delivered significantly higher dimensional accuracy than the two BioMed resins across every geometry tested, with the difference reaching statistical significance at p less than 0.001. Sterilization method also significantly shifted dimensional accuracy overall, although the magnitude and direction of the change depended on the shape of the object, confirming that there is no single sterilization penalty that applies uniformly to every printed device.

The mechanical findings delivered the study’s most dramatic surprise. Counterintuitively, steam sterilization increased the flexural strength of the ISO specimens to 41 plus or minus 16 megapascals, compared with a baseline of 33 plus or minus 19 megapascals, while plasma sterilization reduced strength to 29 plus or minus 16 megapascals, a statistically significant divergence at p less than 0.001. The likely explanation lies in polymer physics: the intense heat of autoclaving drives additional post-cure crosslinking within the photopolymer network, effectively finishing a polymerization reaction that room-temperature light curing had left incomplete. Steam exposure, in effect, acts as an aggressive post-cure. But that apparent strengthening came with a catastrophic catch that standardized specimens alone could never have revealed.

When the researchers turned to the clinically relevant patient-specific guides, the picture darkened. Every single steam-sterilized guide printed from BioMed Clear and BioMed Amber resins developed visible cracks across its structure. These were not hairline cosmetic flaws; they were structural failures that rendered the devices clinically unusable, undermining exactly the geometric fidelity that makes surgical guides worth printing in the first place. The thinner, anatomically contoured walls of the guides behave differently from the stocky ISO bars, concentrating thermal stresses from rapid heating and cooling into fracture lines. The lesson is one the field is learning repeatedly as additive manufacturing enters medicine: benchtop material data cannot be extrapolated naively to real device geometries. A resin that tests beautifully in standard specimens can fail in the operating room.

Plasma sterilization told a more cautious tale. The low-temperature hydrogen peroxide treatment avoided crack formation entirely; all plasma-treated guides remained structurally intact. Yet the method exacted its own price in reduced flexural strength of the specimens, and the authors flag a further unresolved regulatory and microbiological question: hydrogen peroxide clearance, the ability of the sterilant to penetrate the device and then dissipate without leaving cytotoxic residues, has not been validated for these particular resins. The researchers therefore stop short of endorsing plasma sterilization as a default substitute for autoclaving. An intact guide is worthless if residual oxidant could compromise tissue healing, and the data simply do not yet exist to rule that risk out.

The study’s central conclusion is a shift in how surgical 3D printing workflows should be conceived. Material and sterilization method, the authors argue, must be selected and validated as a pair, matched both to the specific sterilization cycle available at the point of care and to the mechanical and accuracy demands of the intended procedure. A high-accuracy resin paired with an incompatible sterilization cycle is not a workflow; it is a latent failure waiting to reach the operating theater. For hospital print labs producing guides under time pressure, the practical message is to consult validated material-sterilization combinations before a case, not after a guide emerges from the autoclave visibly fractured on the morning of surgery.

Beyond the immediate clinical implications, the work resonates with a broader trend in biomedical additive manufacturing. As regulators, including those administering the European Union Medical Device Regulation, scrutinize hospital-produced devices ever more closely, standardized evidence of how fabrication variables interact with post-processing steps becomes essential. This study provides exactly that kind of evidence for the prion-inactivation steam cycle, an extreme but legally mandated condition that most prior research ignored. It also highlights the enduring value of testing devices and specimens side by side. The 61 micrometer accuracy of an ISO bar, the 147 micrometer deviation of an implantology guide, the crosslinking that strengthens a specimen while splitting a guide apart: these are the granular, quantitative facts on which the safety of point-of-care 3D printing will ultimately rest. As hospital printers multiply from Basel to Bangkok, the pairing of resin and sterilization cycle may prove to be one of the most consequential choices a surgical team never knew it was making.

Subject of Research: Effects of steam and plasma sterilization on the accuracy and strength of 3D-printed surgical guide resins

Article Title: Dimensional accuracy and flexural strength of 3D-printed photopolymer resins for point-of-care surgical guides after steam and plasma sterilization: an in-vitro comparative study

Article References: Sharma, N., Burde, A. V., Manea, A., Fischer, J., Thieringer, F. M., & Rohr, N. (2026). Dimensional accuracy and flexural strength of 3D-printed photopolymer resins for point-of-care surgical guides after steam and plasma sterilization: an in-vitro comparative study. 3D Printing in Medicine. https://doi.org/10.1186/s41205-026-00352-8

Image Credits: AI Generated

DOI: 10.1186/s41205-026-00352-8

Keywords: 3D printing, surgical guides, sterilization, photopolymer resins, dimensional accuracy, flexural strength, steam sterilization, plasma sterilization, craniomaxillofacial surgery, dental implants, point-of-care manufacturing, biomaterials

The research, led by Mauranne Lievens of the Department of Oral & Maxillofacial Surgery at Ghent University Hospital, together with Wim Van Paepegem, Tom Goffin, Geert Villeirs and Renaat Coopman, addresses a long-standing gap in the validation of hospital 3D printing programs. Earlier validation studies typically relied on geometric calibration artifacts, standardized test shapes, or simplified phantom objects—objects that behave well on a build plate but share little with the irregular, thin-walled, undercut-rich anatomy of a human skull. The Ghent team instead designed the study around highly accurate anatomical models, deliberately mimicking the actual workflow a hospital follows when a surgeon requests a patient-specific replica for preoperative planning, implant shaping, or patient counseling.

Accuracy in this context is not a single number but a composite of two distinct properties. The first is trueness, which measures how closely a printed model matches the digital reference design—the deviation between the physical object and the source file that clinicians use. The second is precision, which captures reproducibility: how consistent a printer is when producing the same model repeatedly within a single build (intra-build variability), and how consistent it is across separate print jobs run at different times (inter-build variability). Both dimensions matter clinically. A printer that faithfully reproduces anatomy once but drifts between builds is as problematic as one that is consistently wrong. The team quantified both using root mean square (RMS) error, a standard metric that aggregates surface deviation across the entire model rather than relying on a handful of caliper measurements at convenient points.

The statistical design of the study is one of its most notable contributions. Because the dataset comprised repeated prints of multiple anatomical models at multiple timepoints, the observations were inherently clustered—prints from the same build and models from the same printer are not independent of one another. Conventional statistical tests that ignore this structure can overstate significance. To handle the complexity, the researchers employed a Linear Mixed Model (LMM), a framework widely used in agriculture, ecology and clinical trials but, according to the authors, never before applied in 3D printing accuracy research. The mixed model allowed the team to evaluate fixed effects—printer type, anatomical model, and comparison type—while correctly accounting for the internal clustering of repeated measurements, yielding a statistically robust picture of where true differences lie.

The headline result is that every technology tested achieved accuracy within clinically acceptable limits, an encouraging finding for hospitals that have invested in lower-cost equipment. But the ranking was clear and statistically significant. Material Jetting, which builds objects by jetting tiny droplets of photopolymer in extremely thin layers, achieved a mean RMS error of 67 micrometers—the finest accuracy in the study. Stereolithography, which cures liquid resin layer by layer with a light source, followed at 109 micrometers. Fused Filament Fabrication, the thermoplastic extrusion process behind most affordable desktop printers, came in at 130 micrometers. In practical terms, these differences span roughly the width of one to two human hairs, yet in surgery that margin can matter: when a model is used to pre-bend titanium plates or rehearse the osteotomy of a complex orbital or mandibular reconstruction, sub-millimeter deviations propagate directly to the operating table.

Just as important as the ranking was what the Linear Mixed Model revealed about the drivers of error. Printer type was a significant fixed effect, confirming that the technology choice itself—not random variation—explains much of the accuracy difference. But anatomical complexity also exerted a significant influence, meaning that the shape being printed matters nearly as much as the machine printing it. Models with delicate facial structures, thin bony walls and deep undercuts stressed each technology differently: resin- and jetting-based photopolymer processes handled fine detail more gracefully, while extrusion-based FFF showed characteristic stair-stepping and filament-path limitations on curved, intricate surfaces. This interaction underscores why calibration artifacts alone cannot predict clinical performance; a flat test coupon tells a hospital little about how a printer will cope with a zygomatic arch or a thin orbital floor.

The study’s framing around the Medical Device Regulation gives it particular weight for European hospitals. MDR 2017/745 classifies many in-house manufactured products as devices and requires health institutions to demonstrate that their production, under the responsibility of a single legal manufacturer, meets safety and performance expectations—including verification of accuracy appropriate to the intended clinical use. Point-of-care 3D printing has often grown organically inside surgical departments, with validation practices varying wildly from one hospital to the next. By defining accuracy through trueness and precision, quantifying it with RMS error against digital references, and analyzing it with a defensible statistical model, the Ghent team has effectively published a template for the kind of documented, reproducible validation that regulators and hospital quality officers can build upon.

For hospital administrators weighing procurement decisions, the results offer a nuanced cost-benefit picture. Material Jetting’s superior fidelity comes with higher machine and material costs, and photopolymer processes require resin handling and post-processing protocols. FFF remains the most affordable and accessible option, and the study confirms its output is still clinically acceptable—suggesting it can retain a role for models where extreme fidelity is not essential, such as patient education or approximate planning. SLA sits between the two, offering strong performance at moderate cost. The finding that all three cleared the clinical acceptability bar means the choice can legitimately be driven by the intended application, budget and workflow, rather than by fear that cheaper technology is automatically unsafe. For applications demanding the highest anatomical fidelity within the MDR framework, however, the evidence now points decisively toward Material Jetting.

The research also carries implications well beyond craniomaxillofacial surgery. In-house and point-of-care 3D printing is expanding rapidly into orthopedics, cardiothoracic surgery, dental applications and surgical training, and virtually every one of those programs faces the same questions: how accurate is our printer, how repeatable is it, and can we prove it? The study’s methodological chain—realistic anatomical models, digitized reference comparisons, RMS-based quantification of trueness and precision, and mixed-model statistics that respect the structure of repeated manufacturing data—offers a portable blueprint for any institution seeking to validate its own fleet. The authors note it is the first application of a Linear Mixed Model in this field, and if the approach is adopted broadly, it could standardize how hospitals across jurisdictions demonstrate regulatory compliance. Published open access in the journal 3D Printing in Medicine, with no specific external funding and no declared competing interests, the study was reviewed with the involvement of the Ghent University Hospital Medical Ethics Committee, receiving official approval on July 2, 2024, and received on 16 September 2025, accepted on 16 August 2026, and published on 11 September 2026.

Subject of Research: Comparative accuracy of FFF, SLA and Material Jetting 3D printing for in-house anatomical models in craniomaxillofacial surgery

Article Title: Clinical relevance of accuracy in in-house 3D printing in craniomaxillofacial surgery: a comparative study of FFF, SLA, and MJ technologies

Article References: Lievens, M., Van Paepegem, W., Goffin, T., Villeirs, G., & Coopman, R. (2026). Clinical relevance of accuracy in in-house 3D printing in craniomaxillofacial surgery: a comparative study of FFF, SLA, and MJ technologies. 3D Printing in Medicine. https://doi.org/10.1186/s41205-026-00344-8

Image Credits: AI Generated

DOI: 10.1186/s41205-026-00344-8

Keywords: 3D printing, craniomaxillofacial surgery, anatomical models, FFF, SLA, Material Jetting, Medical Device Regulation, accuracy validation, Linear Mixed Model, point-of-care manufacturing, Clinical, relevance