The regulatory landscape for hospital-based 3D printing has long been a stumbling block. Across Europe, point-of-care printing labs have proliferated, churning out patient-specific anatomical models and surgical guides that help surgeons rehearse complex operations. Yet the Medical Devices Regulation (EU) 2017/745 imposes demanding requirements on anyone who manufactures medical devices, and the complexity of the framework has left many hospital and university laboratories stuck in an experimental limbo, unable to formalize their activities without sacrificing the clinical agility that makes them valuable in the first place.

The Milan team, led by researchers from Humanitas University, IRCCS Humanitas Research Hospital and the Politecnico di Milano, set out to resolve that tension with what they call a hybrid model. Rather than choosing between a purely in-house hospital setup and a detached industrial entity, they built a single governance structure that combines clinical proximity with the quality discipline of a regulated manufacturer. The project began in December 2024 as a deliberate transformation of a university-based printing lab into a certified production environment, guided by a top-down, regulatory-driven methodology that started with a detailed reading of the MDR, its guidance documents, and the ISO 13485:2016 quality management standard.

A crucial part of the work was untangling the regulatory categories that govern personalized devices. Under Article 2(3) of the MDR, a custom-made device is manufactured according to a written prescription from an authorized healthcare professional to address the specific anatomical or pathological condition of an individual patient. Patient-matched devices, clarified in the MDCG 2021-3 guidance, are produced from patient-specific data within a predefined design and manufacturing process, while adapted devices are existing products modified after production. The distinction matters enormously: personalized geometry alone does not make a device custom-made. Qualification depends on the clinician’s role in defining patient-specific requirements and on how individualized the design workflow remains, rather than standardized.

The team evaluated several organizational alternatives, including clinical investigations, purely hospital-based in-house configurations, fully industrial manufacturing, and CE-marked devices. The in-house pathway under Article 5(5) of the MDR, which allows health institutions to manufacture devices for their own use, carries restrictions that proved incompatible with the lab’s ambitions. In-house devices cannot be transferred to another legal entity, the institution must justify why no equivalent device exists on the market, and the pathway is limited to a single site. Because the Humanitas lab intended to supply custom-made solutions to external healthcare institutions across a wider hospital network, Annex XIII of the MDR, which governs custom-made devices, emerged as the only viable operational pathway.

Building the quality management system was the heart of the project. Rather than replicating an industrial production model, the team structured the QMS to reconcile ISO 13485 requirements with a clinician-driven, case-by-case workflow. A fully digital architecture, built on the Confluence document management platform, turned compliance from a static pile of documents into a dynamic, traceable system in which procedures, records, quality objectives, reviews and improvement actions are continuously integrated. The notified body IMQ conducted a two-stage certification audit, first reviewing all QMS documentation and then verifying on site that the system was operationally implemented. The audit concluded with zero major and zero minor non-conformities and just two recommendations.

The path to certification was not frictionless. During the first months of QMS operation, the team logged 31 non-conformities and resolved 28 before the certification audit, using a structured five-phase workflow of identification, registration, root cause analysis, corrective action and verification. Representative examples reveal the granular nature of the work: a mismatch between the lot number printed on a filament spool and its cardboard box, caught during incoming material inspection, was fixed by relabeling the material and informing the supplier. Unclear sterilization instructions that mixed multiple materials and methods in one document were rewritten to ensure unambiguous, device-specific guidance.

The lab now handles roughly 20 clinical cases per month, producing two device categories with distinct risk classifications under Annex VIII of the MDR: anatomical models fall into Class I under Rule 1, while surgical guides are Class IIa under Rule 7. Risk classification is not treated as a mere label but as a driver that determines design control requirements, risk management depth, validation protocols and documentation procedures. Technical validation covers the entire chain, from imaging segmentation and CAD design to printing parameters and post-processing quality control, with predefined acceptance criteria. Supplier qualification for patient-contact materials includes verification of biocompatibility certifications according to ISO 10993. Nine formal roles, from quality manager to medical design engineer, are defined through a RACI-like governance model, and end-to-end traceability from clinical need to device release runs through a GDPR-compliant case management system.

Clinical feedback suggests the model delivers real value. Questionnaires returned by seven surgeons for surgical guides and nine for anatomical models showed high satisfaction across communication, perceived improvement in surgical outcomes and overall surgery execution, with slightly lower, though still positive, scores for time saved in the operating room, a pattern the authors attribute to the exceptional complexity of the cases treated. Preliminary internal data from orthopedics indicate that custom-made 3D models showed about 30 percent higher agreement with intraoperative findings compared with conventional imaging, though the researchers caution that this comes from a single-center thesis study and requires further validation. Case examples illustrate the reach of the approach: a liver surgery guide tested on a 3D-printed phantom achieved 99.97 percent volumetric agreement between simulated and planned resection, a custom-made model enabled surgical rehearsal in a cadaveric cardiac oncology case that supported a successful intervention in an otherwise inoperable patient, and 3D reconstruction of a giant abdominal sarcoma contributed to a limb-preserving and organ-preserving outcome.

The economic logic of the hybrid model is equally significant. Both the in-house and custom-made pathways demand substantial investment in quality systems, validated procedures, personnel training and regulatory oversight. But while Article 5(5) restricts devices to the manufacturing institution, the Annex XIII framework opens the door to supplying third-party healthcare institutions and generating revenue streams that partially offset the initial costs. The authors argue that the model achieves a CE-ready level of regulatory preparedness, positioning the lab for possible future CE-marking pathways and even implantable product categories, while retaining the bedside agility that industrial manufacturers often lack. Replicability, they stress, is realistic but conditional: it requires a mature ISO 13485 system, stable clinician-engineer integration and a clear regulatory strategy. Without those prerequisites, institutions risk copying only the visible part of the model, the 3D printing lab itself, without the governance structure that actually makes it compliant and scalable. As point-of-care manufacturing expands worldwide, and as regulators in the United States continue to debate how healthcare institutions should be overseen when they act as manufacturers, the Milan experience offers a concrete demonstration that clinical integration and regulatory rigor need not be enemies.

Subject of Research: A hybrid organizational and regulatory model enabling a university-based 3D printing laboratory to manufacture custom-made medical devices in compliance with the EU Medical Devices Regulation

Article Title: Bridging clinical integration and regulatory compliance in 3D printing: a hybrid model for university-based manufacturing of custom-made medical devices

Article References: Oliva, P., Cereda, E., Robles, E., Cappelli, C., Micalizzi, S., Bevilacqua, A., Rescalli, A., & Mansour, N. K. (2026). Bridging clinical integration and regulatory compliance in 3D printing: a hybrid model for university-based manufacturing of custom-made medical devices. Frontiers in Medical Engineering, 4, Article 1869701. https://doi.org/10.3389/fmede.2026.1869701

Image Credits: AI Generated

DOI: 10.3389/fmede.2026.1869701

Keywords: 3D printing, custom-made medical devices, EU MDR, ISO 13485, quality management system, point-of-care manufacturing, personalized medicine, surgical guides, anatomical models, regulatory compliance, university-based manufacturing, risk management

The commentary responds to a recent report by Guerino-Cunha and colleagues documenting Brazil’s efforts to establish a national CAR T-cell program. CAR T-cell therapy, which involves reprogramming a patient’s own T lymphocytes to recognize and destroy CD19-positive cancer cells, has transformed outcomes in relapsed and refractory B-cell acute lymphoblastic leukemia since the landmark tisagenlecleucel trials. Yet the commercial products remain extraordinarily expensive, with costs estimated to reach as much as 500,000 US dollars per patient. Uruguay, despite being classified as a high-income country, found that its national health budget simply could not absorb those prices, a predicament shared by Brazil and other neighboring nations.

Before the new program existed, only one Uruguayan child had ever received CAR T-cell therapy, and that single treatment required referral to a center abroad. Access, the authors note, mirrored the difficult scenario described in Brazil: judicial litigation, bureaucratic delays, and private fundraising campaigns to cover overseas costs. The contrast between the two countries is stark in scale. Brazil is the largest and most populous nation in South America, while Uruguay is the second smallest, with a highly centralized population. That geography, it turns out, became an unexpected asset.

Where Brazil’s CAR T-cell infrastructure has developed primarily through a top-down model promoted by national authorities and major international collaborations, Uruguay took the opposite route. The clinical need was identified directly by frontline pediatric oncologists and patient advocates, who mobilized charitable funding to support an autonomous point-of-care manufacturing strategy. The program was built from fundraising, without direct initial funding from national authorities, and relies on the automated cliniMACS Prodigy platform installed inside a certified Good Manufacturing Practice facility on the foundation’s own premises.

The product itself is a second-generation anti-CD19 CAR T-cell construct generated with a Miltenyi lentiviral vector and incorporating a 4-1BB costimulatory domain, the same architectural principle underlying approved commercial therapies. Comprehensive technical transfer and training of clinical and laboratory personnel were secured through academic collaboration with Hospital Sant Joan de Déu and Hospital Clínic in Barcelona. Uruguay also brought solid baseline infrastructure to the challenge, including established experience in hematopoietic stem cell transplantation, apheresis, advanced cell processing, and highly specialized supportive care, with immediate access to a referral pediatric intensive care unit.

The program launched in August 2025 with the infusion of its first pediatric patient. Offered as an academic research study, the clinical protocol was approved by the Hospital Pereira Rossell Ethical Committee and national regulatory offices, and therapy is provided free of charge regardless of whether families hold public or private insurance. Between August 2025 and May 2026, five patients were treated: four children and one young adult who had relapsed with acute lymphoblastic leukemia originally diagnosed during adolescence. Four had ALL and one had non-Hodgkin lymphoma. All received a standardized lymphodepletion regimen of cyclophosphamide and fludarabine, followed by infusion of fresh, non-cryopreserved CAR T-cells at a target dose of 3 million cells per kilogram.

The early safety profile was demanding but manageable. Four patients developed grade 3 cytokine release syndrome, the systemic inflammatory reaction that occurs when engineered T-cells activate en masse, requiring tocilizumab and temporary admission to the pediatric intensive care unit. Three patients developed immune effector cell-associated neurotoxicity syndrome, another well-recognized toxicity of CAR T-cell therapy. In every case the toxicities resolved without residual neurological or systemic sequelae. More striking are the efficacy signals: at the time of the report, all five patients remain in complete clinical remission and are negative for measurable residual disease by flow cytometry, showing the persistent B-cell aplasia that indicates the engineered cells remain biologically active. The authors caution that these outcomes are preliminary given the tiny sample size and short follow-up.

One of the most consequential technical advantages lies in logistics. Because the cells are manufactured on-site and infused fresh rather than cryopreserved, the program achieved a vein-to-vein time, the interval from leukapheresis to infusion, of less than 12 days. Commercial products, which must be shipped internationally and frozen, still average 100 to 150 days between collection and infusion. For patients with aggressive relapsed disease, that difference can be decisive. The centralized pediatric cancer care system, funneled through a single institutional partnership between the Pérez Scremini Foundation and Hospital Pereira Rossell, eliminates the bottlenecks of long-distance cell transport and allows seamless referral to a single manufacturing center.

The path from concept to clinic was far slower than anticipated, however. Although the program was conceived in 2021, the first patient was not infused until 2025, a four-year delay caused by barriers strikingly similar to those described in Brazil: bureaucratic hurdles in importing specialized equipment, lengthy national regulatory approvals for cell therapy products, complex global procurement of viral vectors, and the meticulous validation required for a local GMP facility operating under strict international standards. Maintaining a decentralized point-of-care framework also demands a robust, continuous quality management system to satisfy both international cellular therapy standards and evolving local regulations.

Scalability and sustainability remain open questions. Current manufacturing capacity covers national pediatric demand, estimated at roughly three to five candidates per year based on standard clinical indications, but expanding to adult indications or other hematological malignancies would introduce substantial challenges. The entire operational model depends on imported specialized reagents, disposables, and viral vectors, leaving it exposed to global market bottlenecks and customs delays, and formal long-term financial sustainability has not yet been achieved, with reimbursement mechanisms from national authorities still under negotiation. The authors also acknowledge that their model’s favorable conditions, small patient volume, short travel distances, and a single centralized referral center, limit its direct generalizability to larger or geographically dispersed health systems. Even so, the Uruguayan experience demonstrates that a public-private and charitable partnership can implement an efficient, academic, point-of-care CAR T-cell program in Latin America, offering a bottom-up blueprint for countries where commercial pricing puts these life-saving therapies out of reach.

Subject of Research: Academic point-of-care CAR T-cell therapy access for pediatric leukemia and lymphoma in Uruguay

Article Title: Commentary: “Bridging innovation and equity: the evolving landscape of CAR T-cell therapy access in Brazil” The Uruguayan pediatric experience

Article References: Pereira, M. I., Barrios, M., D’ Andrea, L., Ibarra, M., Rives, S., & Castillo, L. (2026). Commentary: “Bridging innovation and equity: the evolving landscape of CAR T-cell therapy access in Brazil” The Uruguayan pediatric experience. Frontiers in Hematology, 5, Article 1891877. https://doi.org/10.3389/frhem.2026.1891877

Image Credits: AI Generated

DOI: 10.3389/frhem.2026.1891877

Keywords: CAR T-cell therapy, pediatric oncology, acute lymphoblastic leukemia, point-of-care manufacturing, Uruguay, Latin America, health equity, cell therapy, lymphoma, cytokine release syndrome, GMP facility, health economics

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