Background: The NovoSorb® Biodegradable Temporising Matrix (BTM) is a synthetic polyurethane dermal matrix used to reconstruct complex wounds including deep dermal and full‐thickness burns, necrotising fasciitis and free flap donor site. We hope to further explore its potential applications in this series.Methods: Patients who received BTM application across four centres over an 18‐month period were included. Patients were followed up to assess BTM and graft take, the aesthetic, the return of sensation and complications.Results: A total of 27 patients with 35 wounds were identified with a range of aetiologies. Thirty‐three wounds had 100% integration of BTM at the time of sealing membrane removal. Seven wounds had partial graft loss that later healed by secondary intention. In two cases, re‐epithelialisation occurred with BTM alone without split‐skin graft.Conclusion: BTM offers a safe and reliable reconstructive option in challenging wounds that would otherwise require more complex operations.

Background/Objectives: Digital twin technology, initially developed for engineering and manufacturing, has entered healthcare. In plastic surgery, digital twins (DTs) have the potential to enhance surgical precision, personalise treatment plans, and improve patient outcomes. This systematic review aims to explore the current use of DTs in plastic surgery and evaluate their effectiveness, challenges, and future potential. Methods: A systematic review was conducted by searching PubMed, Scopus, Web of Science, and Embase databases from their infinity to October 2024. The search included terms related to digital twins and plastic surgery. Studies were included if they focused on applying DTs in reconstructive or cosmetic plastic surgery. Data extraction focused on study characteristics, technological aspects, outcomes, and limitations. Results: After 110 studies were selected for screening, 9 studies met the inclusion criteria, covering various areas of plastic surgery, such as breast reconstruction, craniofacial surgery, and microsurgery. DTs were primarily used in preoperative planning and intraoperative guidance, with reported improvements in surgical precision, complication rates, and patient satisfaction. However, challenges such as high costs, technical complexity, and the need for advanced imaging and computational tools were frequently noted. Limited research exists on using DTs in postoperative care and real-time monitoring. Conclusions: This systematic review highlights the potential of digital twins to revolutionise plastic surgery by providing personalised and precise surgical approaches. However, barriers such as cost, complexity, and ethical concerns must be addressed. Future research should focus on validating clinical outcomes through large-scale studies and developing soft tissue modelling and real-time monitoring capabilities.

Background: Dupuytren’s fibroproliferative disease affecting the hand’s palmar fascia leads to progressive finger contractures and functional limitations. Management of this condition relies heavily on the expertise of hand surgeons, who tailor interventions based on clinical assessment. With the growing interest in artificial intelligence (AI) in medical decision-making, this study aims to evaluate the feasibility of integrating AI into the clinical management of Dupuytren’s disease by comparing AI-generated recommendations with those of expert hand surgeons. Methods: This multicentric comparative study involved three experienced hand surgeons and five AI systems (ChatGPT, Gemini, Perplexity, DeepSeek, and Copilot). Twenty-two standardized clinical prompts representing various Dupuytren’s disease scenarios were used to assess decision-making. Surgeons and AI systems provided management recommendations, which were analyzed for concordance, rationale, and predicted outcomes. Key metrics included union accuracy, surgeon agreement, precision, recall, and F1 scores. The study also evaluated AI performance in unanimous versus non-unanimous cases and inter-AI agreements. Results: Gemini and ChatGPT demonstrated the highest union accuracy (86.4% and 81.8%, respectively), while Copilot showed the lowest (40.9%). Surgeon agreement was highest for Gemini (45.5%) and ChatGPT (42.4%). AI systems performed better in unanimous cases (accuracy up to 92.0%) than in non-unanimous cases (accuracy as low as 35.0%). Inter-AI agreements ranged from 75.0% (ChatGPT-Gemini) to 48.0% (DeepSeek-Copilot). Precision, recall, and F1 scores were consistently higher for ChatGPT and Gemini than for other systems. Conclusions: AI systems, particularly Gemini and ChatGPT, show promise in aligning with expert surgical recommendations, especially in straightforward cases. However, significant variability exists, particularly in complex scenarios. AI should be viewed as complementary to clinical judgment, requiring further refinement and validation for integration into clinical practice.

Novosorb^® Biodegradable Temporising Matrix (BTM) is an entirely synthetic dermal matrix that is gaining popularity in the management of challenging wounds. Not only does it provide a framework in which to grow an organised neodermis, it is also especially resistant to infection. Today, the matrix is available as a 2 mm thick open cell polyurethane foam with a non-degrading sealing membrane. Its current form is the result of numerous in vitro and in vivo experiments that examined its shape, biodegradation, inflammatory response, and cytotoxicity. Clinical data on the use of BTM in a variety of cases is novel and presents early insights into its ability to foster wound healing where otherwise improbable. This review presents the history and development of Novosorb^® BTM as well as all the currently available clinical data on its efficacy in difficult wounds such as: major burns, necrotising soft tissue infection, chronic wounds and in non graftable wound beds.

Background: Robotic surgical systems offer enhanced precision, motion scaling, tremor filtration, and visualization, making them highly suitable for the complex anatomical demands of plastic and reconstructive surgery. While widely implemented in other specialties, their integration in plastic surgery remains limited. This systematic review evaluates the clinical applications, outcomes, and limitations of robotic-assisted techniques in plastic and reconstructive procedures. Methods: Following PRISMA guidelines, a systematic search was conducted across PubMed, Embase, Scopus, and Web of Science for studies published between January 1980 and March 2025. Clinical studies reporting robotic applications in plastic surgery were included, while cadaveric, animal, and non-English studies were excluded. Data extraction and quality assessment were performed using Covidence and validated tools including the CARE checklist, NOS, GRADE, and SYRCLE. A total of 1428 studies were screened, and 31 met the inclusion criteria. Results: Robotic systems were primarily applied in microsurgery (n = 16), breast reconstruction (n = 8), and craniofacial/aesthetic surgery (n = 7). Common platforms included the Symani Surgical System, Da Vinci systems, and ARTAS. Robotic-assisted approaches improved precision, aesthetic outcomes, flap survival, and patient satisfaction, particularly in procedures involving lymphaticovenous anastomosis and nipple-sparing mastectomy. However, challenges included steep learning curves, longer operative times, high equipment costs, and the lack of haptic feedback. Quality assessment rated all studies as moderate. Conclusions: Robotic-assisted surgery demonstrates considerable potential in enhancing plastic and reconstructive outcomes. As systems become more compact, cost-effective, and integrated with AI and biomimetic technologies, their broader adoption is anticipated. Further high-quality studies are needed to optimize these systems and support widespread clinical implementation.

Background: Lymphedema can significantly affect patients’ health-related quality of life (HRQoL). Various quality of life scales have been developed to assess the extent of the disease burden. The purpose of this study is to review various HRQoL instruments that have been used in lymphedema studies and compare their qualities against the COSMIN checklist. Methods: A systematic literature review search was conducted for clinical lymphedema studies published between January 1, 1984, and February 1, 2020, using Pubmed database. All clinical lymphedema studies which used HRQoL instruments as outcome measures were identified. Results: One thousand seventy-six studies were screened—of which, 288 studies were individually assessed. Thirty-nine HRQoL instruments were identified in these clinical lymphedema studies. Of these, there are eight lymphedema-specific questionnaires that cover all HRQoL domains, all of which have been validated for use in lymphedema. We contrasted the two most popular questionnaires [LYMQOL and Upper Limb Lymphedema (ULL)-27] and compared their features. Conclusion: There is currently no ideal lymphedema HRQoL measurement tool available based on the COSMIN criteria. However, our review suggested that LYMQOL and ULL-27 are the most used and most validated instruments at present, but each has their own limitations. We recommend the use of LYMQOL and ULL-27 for future studies to allow direct HRQoL comparison to current literature. Further research is required to develop an optimal HRQoL questionnaire that can ultimately become the gold standard HRQoL instrument for lymphedema.