The editorial examines several of the most active research fronts where AI is being tested in plastic surgery, and its conclusions are strikingly cautious. The central message is that while AI has already proven useful in non-clinical settings such as communication, accounting, feedback collection, and office management, the technology has not yet accumulated sufficient evidence to justify routine use in clinical practice. That gap between enthusiasm and proof, the author suggests, is where the specialty’s attention should now be focused.

One of the most debated applications is the computerized assessment of aesthetic outcomes. Plastic surgery has long struggled with the subjective nature of judging surgical results, and AI-driven computer vision promises to replace human impression with numbers. A study by Varghaei and colleagues assembled what is likely the largest curated paired pre- and postoperative facial image dataset to date, comprising 7,160 photographs from 1,259 patients. The team introduced a scalable, interpretable computer-vision framework designed to quantify aesthetic outcomes of facial plastic surgery using frontal photographs. On its face, this seems like a decisive step toward objectivity, but the editorial raises a fundamental objection: quantification does not guarantee objectivity.

The problem lies in how these systems learn. Current AI technology is dominated by multimodal large language models trained on human input, and the way humans train these models inevitably shapes the opinions they produce. The editorial coins the term compjective to describe this hybrid state, in which a machine’s judgment is neither fully objective nor entirely subjective. The authors of the facial analysis study themselves acknowledged that facial attractiveness, though inherently subjective, is often associated with geometric regularities such as bilateral symmetry, proportionality, and averageness. That concession raises an uncomfortable question: can computerized assessment of aesthetic outcomes ever truly be objective?

Independent evidence suggests the answer, for now, is no. A comparative evaluation by Haider and colleagues tested leading multimodal large language models, including ChatGPT-4o, GPT-4, Gemini, and Claude, on their ability to assess aesthetic features through both qualitative and quantitative analysis. The verdict was sobering. Without fine-tuning or integration with specialized computer-vision architectures, none of the models could provide a reliable aesthetic assessment. In practical terms, the general-purpose systems that most people call artificial intelligence today do not have the capacity to replace a surgeon’s trained eye and accumulated experience in evaluating an aesthetic result. The editorial’s assessment is that AI-driven computer vision has not yet proven to be a reliable resource for clinical integration and requires substantial advancement, though it may serve as a supplementary tool for quantifying treatment results in research settings.

A second frontier is continuous monitoring, where the case for machine assistance is arguably stronger. Every surgeon knows the classical signs of inflammation, calor, dolor, rubor, tumor, and functio laesa, and every training surgeon has endured the burden of watching flaps overnight with instructions as vague as calling if the color changes. A monitoring system that never gets drowsy and never loses focus could be a welcome alternative to a tired colleague. Kim and colleagues developed and tested an automated free flap monitoring system based on artificial intelligence, and the results were promising: sensitivity for detecting venous insufficiency reached 97.5 percent, while sensitivity for arterial compromise reached 92.8 percent. These figures suggest that supplemental monitoring and early warning systems could genuinely optimize patient care, but the editorial is careful to note that such technologies have yet to be evaluated in a clinical trial setting.

That trial evidence may not be far off. Several clinical studies are currently underway focusing on AI-assisted monitoring, diagnosis, and detection. Among them are WISDOM, a trial using AI within digital wound monitoring of surgical wounds to prioritize non-healing wounds for urgent review, registered as NCT06475703; AnAsToMoSIs, a study of artificial intelligence approaches to the monitoring of microvascular free-flap inpatients, registered as ISRCTN36476735; SeeWound2, a clinical evaluation of a digital wound-assessment device using AI-based image analysis, registered as NCT07211295; and an AI risk assessment model for complication prevention in plastic surgery, registered as NCT06507384. Most of these studies are observational or device precision studies, which means the field is still in the phase of establishing that the tools work as claimed, not yet proving that they improve outcomes.

Beneath these specific applications lies a deeper set of methodological problems that the editorial identifies as endemic to the literature. Many published AI models derive from single centers or demographically narrow datasets, which severely restricts their applicability to larger and more varied patient communities. When such models are ported to different populations, performance will likely degrade, because those populations do not resemble the original training data. There is little published work on cross-ethnicity fairness audits or performance stratification across different phenotypes, and many studies omit the detailed metadata that would make post-hoc analysis, standardization, or reproducibility possible. Patient-reported outcomes are frequently missing from pilot studies, a flaw the editorial calls major, since a patient’s understanding of a successful outcome may differ substantially from that of a computerized assessment program. Ultimately, the argument goes, AI metrics must map to patient-reported outcomes, to the surgeon’s decision-making, or to demonstrable improvements in care, and current models show signs of both selection bias and aesthetic bias.

There are, however, examples of success that point the way forward. The editorial cites work by Ravi Dhawan and colleagues reviewing FDA-approved AI-utilizing tools in the wider surgical field, which found that the devices that have cleared regulatory hurdles share common features, including necessity and efficiency. Future pioneers of AI technology in plastic and reconstructive surgery, the editorial argues, should weigh the necessity, safety, and reliability of their tools in improving patient outcomes, reducing complications, and ensuring minimum disruption to existing clinical standards and practices. A tool that is merely novel, in other words, is not enough.

To close the gap between promise and proof, the editorial lays out a set of steps for responsible integration. Reporting standards should be mandated, covering everything from methods to metadata, with proper study registration, open access data sharing, and detailed transparency as prerequisites for a reliable tool. Validation should be prospective and pre-registered, ideally multi-center, because retrospective validation is subpar for supporting the effectiveness of a new tool, even one designed only as a supplement. A patient-centered approach should govern development, with patient feedback included in assessing effectiveness and sufficient fairness audits, subgroup analyses, and stratification of performance by age, sex, ethnicity, and skin tone to avoid perpetuating aesthetic biases. Surgeon-AI workflow integration trials should investigate how AI metrics influence surgical planning, patient counseling, shared decision-making, and interrater variability, with clinician feedback loops refining the AI’s decision logic during testing. Finally, regulatory and consent frameworks need attention, since existing bodies such as the FDA and CE marking schemes do not define specific approval pathways for AI technology, and without a standardized approach governing patient consent and data protection, these tools cannot be freely deployed. The editorial’s conclusion is blunt: while the specialty is prepared for AI that optimizes care and improves outcomes, existing research does not yet provide sufficient evidence of safety for clinical integration, and future work must incorporate both patient and surgeon feedback while meeting the same methodological and reporting rigor that has become standard in clinical trials.

Subject of Research: Responsible and evidence-based integration of artificial intelligence into plastic and reconstructive surgery

Article Title: Responsible and safe integration of AI technology into clinical practice: accommodating the inevitable technological change

Article References: Sinelnikov, M. Y. (2025). Responsible and safe integration of AI technology into clinical practice: accommodating the inevitable technological change. BMC Plastic and Reconstructive Surgery, 1(1), Article 6. https://doi.org/10.1186/s44452-025-00006-4

Image Credits: AI Generated

DOI: 10.1186/s44452-025-00006-4

Keywords: artificial intelligence, plastic surgery, reconstructive surgery, computer vision, large language models, free flap monitoring, clinical trials, patient outcomes, FDA regulation, aesthetic assessment, fairness audits, surgical innovation

The scope of the series, as outlined in the editorial, is deliberately broad. It will welcome research articles examining the foundation and evolution of plastic and reconstructive surgery, including studies of the contributions of individual surgeons and patients, the historical development of surgical techniques and instrumentation, and even the field’s reflections in art and literature. That breadth reflects a central claim of the editorial: every procedure, condition, surgical algorithm and instrument in the specialty carries its own story, and those stories collectively explain how modern practice came to look the way it does.

The historical arc the editorial sketches stretches back further than most readers might expect. It opens with ancient Sanskrit texts describing Sushruta’s procedure for nasal reconstruction, a reference to one of the earliest documented operations in which tissue was deliberately transferred to repair a defect of the face. Nasal reconstruction holds a special place in the origin story of the specialty because the nose, prominently exposed and vulnerable to injury, was among the most socially and functionally devastating losses a person could suffer. Techniques for rebuilding it developed across centuries and cultures, long before the term plastic surgery existed, and the editorial treats this ancient lineage as the starting point of a continuous tradition of innovation that runs unbroken to the present day.

From that ancient beginning, the editorial traces a path to the other end of the technological spectrum: modern robot-assisted surgery. The contrast is striking, but the authors’ point is that the two are connected by more than chronology. The principles that govern reconstruction today, such as careful wound closure, respect for tissue planes and the strategic transfer of tissue from one part of the body to another, were established through accumulated experience rather than invented overnight. Knowledge of this history, the editorial argues, is an important resource for understanding and respecting the sacrifices and contributions of the surgeons and patients whose experiences defined the techniques, principles and standards that define practice today.

A central and sobering theme of the editorial is the role of war. For the most part, the modern techniques used in plastic surgery took root in field army hospitals and were first performed by military surgeons, who were tasked with wound closures of varying complexity, extremity reattachments, burn treatments and other consequences of armed conflict. The scale and complexity of injury seen in the First and Second World Wars necessitated rapid surgical innovation, producing novel techniques in wound closure, reconstruction and microsurgery. Battlefield conditions, in this telling, functioned as an brutal forcing function: mass casualties with unprecedented combinations of injuries demanded solutions that civilian practice had never been required to develop at speed.

The editorial names a remarkable roster of contributors from the first half of the twentieth century, a period when the specialty crystallized into a distinct discipline. Among those listed are Sir Harold Gillies, Sir Robert Jones, Henry Pickerill, Hippolyte Morestin, Erich Lexer, Jaques Joseph, Otto Lanz, Johannes Esser, Vladimir Petrovich Filatov, Archibald McIndoe, Luke Voyno-Yasenetsky, Vincenz Czerny and Suzanne Noël. The list spans multiple countries and national traditions, underscoring that the birth of modern plastic surgery was an international enterprise rather than the achievement of a single school. Several of these names remain familiar to surgeons today through eponymous flaps, instruments and techniques that are still taught in training programs around the world.

What distinguishes this editorial from a conventional celebration of surgical pioneers is its insistence on remembering the other half of the partnership: the patients. It is equally important, the authors write, to remember the soldiers and civilians whose injuries compelled the marvelous surgical progress from which patients continue to benefit today. Their suffering and sacrifice are often overshadowed by the focus on the surgeon or the technique, but their experiences are a reminder that the history of surgery carries a tremendous human cost that must never be forgotten. This reframing is significant for how the series is likely to approach its subject. Rather than treating historical patients as passive material upon which progress was made, the editorial positions them as contributors whose injuries, endurance and outcomes shaped the establishment and evolution of surgical practice.

The announcement also arrives at a meaningful moment for the journal itself. BMC Plastic and Reconstructive Surgery is a new open access title, and the history series appears in its first volume, as article number nine. Launching a focus series on the field’s origins in a journal’s inaugural year is a deliberate statement of editorial identity: the journal is positioning historical scholarship not as a peripheral curiosity but as a core strand of the specialty’s literature. The open access model matters here too, since making historical research freely available allows surgeons, students, historians and the public to engage with the field’s past without paywall barriers.

For working surgeons, the editorial suggests that historical knowledge has practical value beyond commemoration. Understanding why a particular flap design, fixation method or reconstructive algorithm emerged, and under what constraints it was first tested, can deepen technical judgment and clarify which elements of current practice are fundamental principles and which are contingent solutions to problems that may no longer exist in the same form. For patients, the history is a reminder that every contemporary standard of care, from burn reconstruction to microsurgical reattachment, was earned through the experiences of people who underwent surgery in eras without modern anesthesia, antibiotics or imaging.

The series now open for submissions invites researchers to document and analyze this heritage in detail, whether through studies of individual surgeons and patients, the evolution of specific techniques and instruments, or the field’s portrayal in art and literature. As the editorial makes clear, the history of plastic and reconstructive surgery is extensive, complex and remarkable in its depth, and the journal intends to ensure that this record, with all of its innovation and all of its human cost, is preserved, examined and made freely available to everyone the specialty serves.

Subject of Research: The history and evolution of plastic and reconstructive surgery from ancient times through modern military-driven innovation

Article Title: History of plastic surgery: introducing a BMC Plastic and Reconstructive Surgery focus series

Article References: Sinelnikov, M. Y. (2025). History of plastic surgery: introducing a BMC Plastic and Reconstructive Surgery focus series. BMC Plastic and Reconstructive Surgery, 1(1), Article 9. https://doi.org/10.1186/s44452-025-00009-1

Image Credits: AI Generated

DOI: 10.1186/s44452-025-00009-1

Keywords: plastic surgery, reconstructive surgery, history of medicine, military surgery, Sushruta, Harold Gillies, Archibald McIndoe, microsurgery, world wars, surgical innovation, open access, BMC Plastic and Reconstructive Surgery

The conceptual foundations were laid long before the first camera entered an abdomen. Surgeons such as Kajitani, Okajima, and Maruyama validated D2 lymphadenectomy, the systematic removal of the lymph node stations around the stomach, establishing both the oncologic logic and the therapeutic value of extended nodal dissection. Then came a crucial corrective. Sasako’s landmark randomized trial demonstrated that adding prophylactic para-aortic nodal dissection to D2 surgery did not improve patient survival, a result that shifted the field’s focus toward survival balanced with quality of life and laid the groundwork for the modern, evidence-based approach to deciding how much surgery is enough. That principle, that more extensive is not universally better, now underpins nearly every innovation in the field.

The minimally invasive era began in earnest in 1994, when Kitano reported the first laparoscopic gastrectomy for gastric cancer. Skepticism was intense. Critics questioned whether a two-dimensional video view could ever match the tactile feedback and direct exposure of open surgery, particularly for a cancer operation requiring meticulous lymph node dissection. In 2002, Hashizume performed the first robotic gastrectomy, opening a second technological front. What followed was a systematic, two-decade process of evaluation, refinement, and gradual integration, driven primarily by high-volume centers in Japan, Korea, and China. A single-center pilot study of 164 patients demonstrated the safety of laparoscopic gastrectomy for early gastric cancer and revealed unexpected improvements in postoperative quality of life. A subsequent multicenter phase 2 trial across eight centers extended the approach to more advanced disease, creating the foundation for the definitive randomized trials that would follow.

Those trials have transformed practice. Korea’s KLASS-01 study showed in 2019 that laparoscopic distal gastrectomy was noninferior to open surgery for early gastric cancer in five-year disease-free survival. KLASS-02 extended the finding to locally advanced disease, confirming comparable relapse-free survival with laparoscopic D2 lymphadenectomy and fewer complications. Japan’s JCOG0912 trial established noninferiority for laparoscopy-assisted distal gastrectomy in stage I disease, and the JLSSG0901 trial replicated the result for advanced cancer in 2023. China’s CLASS-01 and CLASS-02 trials contributed complementary evidence for distal and total gastrectomy. Taken together, these studies converted laparoscopic gastrectomy from an experimental technique into an evidence-based standard. Robotic surgery, by contrast, remains at an earlier stage of proof. Comparative studies show the robot is feasible, with reduced blood loss and similar lymph node harvests, but large-scale randomized evidence is still limited, and ongoing East Asian trials are expected to clarify its place in treatment guidelines.

Behind the trial results lies a distinctive culture of collaboration and knowledge sharing. Japanese, Korean, and Chinese surgical groups have long exchanged operative videos, built consensus documents, and performed live demonstration surgeries for international audiences. When Uyama shared detailed videos of laparoscopic D2 dissections, the clarity and sophistication of the technique astonished viewers and accelerated global understanding of what minimally invasive cancer surgery could achieve. International teleconferences and live surgical transmissions, including real-time dialogue between operating surgeons and remote experts, have proven educational even for highly experienced operators. The review argues that this openness is not incidental but essential: meaningful innovation in surgery depends on institutions and countries actively sharing what works, what fails, and how standards can be harmonized across centers with very different case volumes and resources.

The review also emphasizes that surgeons themselves should drive the technology, not merely adopt it. The author describes identifying the limitations of conventional two-dimensional endoscopic visualization, particularly in depth perception and structural recognition, and then collaborating with engineering teams to develop three-dimensional laparoscopic endoscopes that improved precision in dissection and reconstruction. This surgeon-inventor model, the argument goes, should be cultivated from the earliest stages of surgical education, because only clinicians embedded in daily operative reality can identify the design flaws that matter for safety and outcomes. The same philosophy extends to how new techniques spread. Simple publication is not enough. The safest dissemination strategy embeds innovation within clinical trials that include structured quality assurance: objective assessment of surgical proficiency, standardized operative guidelines, procedure manuals, educational videos, and validated evaluation forms.

As standard procedures mature, attention has turned to optimization and personalization. Reconstruction after proximal gastrectomy has become a fertile arena for innovation. The SPADE technique uses double-suture anchoring between the posterior wall of the esophagus and the anterior wall of the stomach to create a flap and pseudo-fornix, improving anti-reflux function and reducing complications. The OFFROAD technique reinforces anastomoses and dissected areas with remaining omental tissue, and preliminary studies suggest it does not significantly increase operative time or complication rates while potentially mitigating the severity of leaks. The ongoing ADDICT trial is asking a more fundamental question: whether D1+ or D2 dissection is the appropriate extent for advanced gastric cancer. Meanwhile, function-preserving approaches are challenging the assumption that every early cancer needs the same resection as advanced disease. Middle segmental gastrectomy, an evolution of pylorus-preserving gastrectomy, aims to maintain gastric function for tumors in the middle third of the stomach, and sentinel node navigation surgery, inspired by melanoma trials and refined by the SENORITA group, may allow less extensive resections in carefully selected patients based on biologic information from mapped lymphatic basins.

Optimization now begins well before the operating room. The review highlights anemia as one of the most important modifiable preoperative factors, since suboptimal hemoglobin worsens recovery, raises complication rates, and harms long-term outcomes. A seven-year multicenter trial demonstrated that intravenous ferric carboxymaltose significantly improves hemoglobin levels and reduces transfusion needs in surgical patients. In parallel, patient blood management, endorsed by the World Health Organization, promotes evidence-based transfusion thresholds, meticulous intraoperative hemostasis, and preservation of the patient’s own blood, with benefits including faster recovery, shorter hospital stays, and fewer transfusion-related risks. These strategies reflect a broader shift toward holistic, patient-centered care in which surgical technique, perioperative medicine, and long-term survivorship are planned together rather than treated as separate phases.

The most consequential frontier, however, is artificial intelligence. Deep-learning systems for endoscopy have already demonstrated improved detection rates of early gastric cancer lesions, reducing operator-dependent variability and potentially enabling earlier diagnosis. Computer vision models are being trained to recognize surgical phases, identify critical structures such as lymph node stations, major vessels, and dissection planes, and provide real-time feedback during laparoscopic and robotic gastrectomy. Machine learning algorithms integrating clinical, laboratory, and imaging data show promise for predicting survival and postoperative complications, supporting individualized prehabilitation and risk stratification. Yet the review is candid about the obstacles. Many AI applications rest on small, single-center datasets with limited external validation, and concerns about data privacy, algorithmic interpretability, medico-legal responsibility, and workflow integration remain unresolved. Autonomous robotic systems, despite demonstrating remarkable precision in experimental tasks, remain far from safe independent deployment in complex oncologic surgery, where judgment and ethical responsibility remain fundamentally human.

The future envisioned is collaborative rather than substitutive. Flexible robotic platforms such as K-Flex, holographic and three-dimensional printed preoperative modeling, and the coming flood of genomic, proteomic, and radiomic data will give surgeons tools of unprecedented power, but translating that data into actionable treatment decisions, from the choice and extent of surgery to perioperative therapy and surveillance, will require clinicians who are curious, data-driven, and committed to patient safety. In the model the review proposes, AI assists with case selection, operative planning, intraoperative guidance, and postoperative monitoring, while surgeons interpret the unexpected, weigh patient values, and take responsibility for nuanced decisions. Global capacity-building through tele-mentoring, simulation, and structured fellowships is meant to ensure these advances reach patients far beyond the high-volume East Asian centers where they were born. The transformation of gastric cancer surgery, from Billroth’s open incisions to intelligent operating rooms, is ultimately a story about surgeons who refused to stop asking whether the operation could be done better, and who built the evidence, the tools, and the networks to find out.

Subject of Research: Evolution and future of minimally invasive gastric cancer surgery, including randomized trial evidence, surgical innovation, and artificial intelligence applications

Article Title: Innovations in Gastric Cancer Surgery During Early Minimally Invasive Era and Future Perspectives

Article References: El‐On, R., & Kim, Y.-W. (2026). Innovations in Gastric Cancer Surgery During Early Minimally Invasive Era and Future Perspectives. Annals of Gastroenterological Surgery, 10(5), 1382-1387. https://doi.org/10.1002/ags3.70234

Image Credits: AI Generated

DOI: 10.1002/ags3.70234

Keywords: gastric cancer, laparoscopic gastrectomy, D2 lymphadenectomy, robotic surgery, randomized controlled trials, artificial intelligence, sentinel node navigation, function-preserving surgery, patient blood management, surgical innovation, minimally invasive surgery, East Asia

The appeal of the approach lies in its simplicity and accessibility. Previous attempts to bring three-dimensional printing into breast reconstruction have generally depended on computed tomographic angiography data or dedicated surface-imaging platforms, both of which carry substantial costs and infrastructure requirements. CT-based workflows also expose patients to additional radiation when imaging has not already been obtained for surgical planning, and image segmentation demands specialized expertise that many centers cannot easily mobilize at the point of care. By contrast, the new technique uses the structured-light TrueDepth camera already built into an iPhone, capturing surface geometry through the ScandyPro application in a matter of minutes during an ordinary outpatient appointment.

Before applying the method to patients, the research team validated the accuracy of smartphone scanning against a professional-grade alternative. They fabricated a physical breast phantom from an open-source digital model using fused deposition modeling, then scanned it with two protocols. The smartphone protocol used ScandyPro on an iPhone 12, which reconstructs surfaces from the infrared depth data of the front-facing camera. The comparison protocol used a Canon digital single-lens reflex camera with a 24 millimeter lens, acquiring 100 to 150 photographs in circular passes at varying elevation angles and reconstructing them through photogrammetry in Agisoft Metashape. Fiducial markers provided correspondence points and a calibration bar of known length fixed the absolute scale, since structure-from-motion reconstructions are otherwise ambiguous in size.

The geometric comparison was carried out in CloudCompare using a two-stage registration procedure. A coarse alignment was first computed by manually selecting corresponding fiducial points, followed by fine registration with the Iterative Closest Point algorithm restricted to rigid-body motion, so that genuine geometric deviation was preserved rather than absorbed by the fit. The results were striking: smartphone scans showed a mean deviation of just 0.033 millimeters and a root-mean-square error of 0.697 millimeters, with individual scans ranging from 0.456 to 0.878 millimeters. Every smartphone scan outperformed the DSLR photogrammetry reconstruction, which recorded an RMSE of 0.954 millimeters. Both methods achieved sub-millimeter accuracy with negligible systematic bias, but the phone, remarkably, edged out the professional camera setup on this rigid test object.

With accuracy established, the team enrolled three patients prospectively, each of whom had previously undergone a unilateral mastectomy and was planned for autologous reconstruction. During a preoperative clinic visit, each patient’s native breast was scanned in the upright position with the smartphone application. The resulting surface model was exported in standard tessellation language and mirrored across the midline to represent the contralateral, pre-mastectomy breast. The investigators caution that because breast tissue is deformable and position-dependent, the mirrored upright scan serves as a patient-specific shaping reference rather than an exact replica of the supine anatomy the surgeon encounters in the operating room, but it provides a tangible target that visual estimation alone cannot.

The models were printed at Duke University’s Innovation Co-Lab on a Form 3B+ stereolithography printer using Elastic 50A resin, a flexible, semi-translucent material chosen for its malleability and its ability to let surgeons partially see through the template intraoperatively. Each print was oriented with its concave inner surface facing the build platform to avoid the cupping effect inherent to bottom-up stereolithography and to keep support material away from the functional outer surface. After support removal, the prints were washed in isopropyl alcohol, post-cured under ultraviolet light, and sterilized using the institution’s standard operating-room autoclave protocol, making them fully surgical instruments.

In the operating room, the templates served as physical guides for flap shaping. Two of the patients underwent unilateral reconstruction with bipedicled deep inferior epigastric perforator flaps, in which the entire abdominal flap was folded ninety degrees so that lateral tissue formed the superior breast border while contralateral tissue was de-epithelialized and folded beneath to provide lower-pole projection. The third patient underwent prophylactic mastectomy of the remaining breast followed by bilateral reconstruction with profunda artery perforator flaps, each shaped into a cone to maximize projection. In every case, the sterilized template was placed over the shaped flap to approximate symmetry with the native breast and to help the surgeon visualize the breast footprint and overall contour.

One particularly notable case demonstrated a capability that earlier single-use molds lacked: reusability. In a patient whose flap provided less tissue than the template represented, the mold still guided shaping despite the limited volume, and after the initial operation the same template was re-sterilized and used during a revision procedure to guide implant placement beneath the flap and improve projection. This adaptability addresses a recognized limitation of prior rigid, single-use molds and suggests the templates can follow a patient across the full reconstructive course. The authors note that when available tissue falls short of the template, the approach can be adapted through stacked flaps or hybrid techniques combining autologous tissue with implants, and that superficial wound-healing complications observed in one case were considered unrelated to the template workflow.

The researchers are careful to frame the study as a demonstration of technical feasibility rather than proven clinical benefit. With only three patients, the series cannot establish improvements in operative efficiency, symmetry, or patient-reported outcomes, and results were limited to subjective surgeon and patient satisfaction. The authors call for larger prospective studies incorporating blinded assessment against conventional visual judgment, operative and flap-shaping time, objective measurements of breast volume, shape, footprint, and postoperative symmetry, and validated patient-reported measures such as BREAST-Q scores. They also acknowledge that while smartphone capture eliminates the cost and radiation of CT-based workflows, the printing infrastructure itself remains an institutional investment, and the collection and storage of patient surface images raises privacy and regulatory considerations that must be managed within appropriate legal safeguards.

Nevertheless, the study points toward a democratization of surgical planning technology that could extend well beyond breast reconstruction. Three-dimensional printing has already transformed craniomaxillofacial surgery, prosthetics, surgical training, and patient education, and the authors anticipate a parallel emergence of soft-tissue applications as the technology matures. If subsequent studies confirm that a device carried in millions of pockets can capture anatomy with sub-millimeter fidelity and translate it into a sterilized operating-room tool at minimal incremental cost, the print-to-patient paradigm could reshape how reconstructive surgeons plan, practice, and personalize some of the most intricate operations in medicine, turning an everyday smartphone into an instrument of surgical precision.

Subject of Research: A smartphone-based 3D printing workflow for creating patient-specific intraoperative templates in autologous breast reconstruction.

Article Title: Print-to-patient: a novel 3D printing technique for autologous breast reconstruction

Article References: Morris, M. X., Barrow, B. E., Park, H. S., Rames, J., Haider, M., Feaster, J., Sekhar, S., Rattey, I., & Phillips, B. T. (2026). Print-to-patient: a novel 3D printing technique for autologous breast reconstruction. BMC Plastic and Reconstructive Surgery, 2(1), Article 25. https://doi.org/10.1186/s44452-026-00037-5

Image Credits: AI Generated

DOI: 10.1186/s44452-026-00037-5

Keywords: 3D printing, breast reconstruction, autologous reconstruction, DIEP flap, smartphone 3D scanning, surgical templates, plastic surgery, microsurgery, 3D imaging, surgical innovation, patient-specific modeling, reconstructive surgery