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Review

Robotic Horizons in Plastic Surgery: A Look Toward the Future

1
Department of Plastic Surgery, Cleveland Clinic, 9500 Euclid Avenue, A60, Cleveland, OH 44195, USA
2
Department of Applied Data Science, Cleveland State University, Cleveland, OH 44115, USA
3
College of Osteopathic Medicine, Pacific Western University of Health Sciences, Pomona, CA 91766, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
J. Clin. Med. 2026, 15(2), 602; https://doi.org/10.3390/jcm15020602
Submission received: 7 November 2025 / Revised: 4 January 2026 / Accepted: 8 January 2026 / Published: 12 January 2026
(This article belongs to the Special Issue Plastic Surgery: Challenges and Future Directions)

Abstract

Background/Objectives: Robotic technology has transformed several surgical specialties, offering enhanced precision, visualization, and dexterity. In plastic and reconstructive surgery, robotic systems are increasingly utilized across a range of procedures, though their applications remain in early development. Methods: A review of the literature was performed to identify studies reporting robot-assisted procedures in plastic and reconstructive surgery. The literature was synthesized thematically to characterize current procedural applications, emerging technologies, and areas of active clinical investigation. Results: Robotic systems have been reported in a broad range of plastic and reconstructive procedures, including flap harvest, microsurgery, breast reconstruction, craniofacial and head and neck reconstruction, esthetic surgery, and gender-affirming surgery. The existing studies primarily consist of case series and case reports with substantial variability in reported indications, techniques, and technological platforms. Comparative clinical outcomes and long-term data are limited. Conclusions: Robot-assisted reconstruction continues to expand across multiple procedural domains. However, current evidence remains largely descriptive, underscoring the need for standardized reporting and prospective studies to better define clinical value, safety, and appropriate indications.

1. Introduction

Robot-assisted surgery represents one of the most significant technological advancements in modern surgical practice [1]. Plastic and reconstructive surgery inherently demands exceptional precision, fine motor control, and three-dimensional spatial awareness to address intricate and variable anatomical structures. The integration of robotic systems offers an opportunity to enhance these capabilities, providing improved visual-spatial resolution, instrument dexterity, tremor reduction, and motion scaling beyond the limitations of human performance [2].
While robotic technology has been widely adopted in urologic, gynecologic, and cardiothoracic surgery, its incorporation into plastic and reconstructive surgery remains limited but is rapidly expanding [2]. Early applications, ranging from transoral reconstruction of oropharyngeal defects to muscle and perforator flap harvest, and more recent developments in microvascular anastomosis, demonstrate the feasibility of robotic approaches in procedures requiring delicate tissue handling and precise dissection within confined spaces [2,3,4].
The advantages of robotic platforms extend beyond technical precision. They enable smaller incisions, reduced blood loss, and diminished donor-site morbidity, contributing to improved recovery and esthetic outcomes [2,3]. From the surgeon’s perspective, robotic platforms may facilitate broader adoption of complex technical procedures such as super microsurgery [5], improve ergonomics through motion stabilization, reduce fatigue, and enhance performance during prolonged procedures [2]. Moreover, the integration of robotic connectivity and artificial intelligence enables opportunities for remote collaboration, telesurgery, quality benchmarking, and standardized training across institutions—advancing access to specialized care, reducing regional disparities, and promoting equity in surgical outcomes [6,7].
Despite these potential advantages, robotic applications in plastic and reconstructive surgery remain distributed across diverse procedural domains, and the existing literature is largely fragmented and predominantly composed of case reports and small case series. To date, no single publication has comprehensively synthesized the full scope of robotic applications across the specialty. This review aims to critically evaluate the current state of robotic technology in plastic and reconstructive surgery, delineate existing limitations and barriers to implementation, and propose a framework for its clinical integration and technological advancement.

2. Methods

This perspective is informed by a targeted, non-systematic review of the contemporary literature on robotic applications in plastic and reconstructive surgery. Representative publications were identified through focused searches of PubMed, Scopus, and Web of Science using combinations of the terms “robotics,” “robotic surgery,” “plastic surgery,” and “reconstructive surgery”. The final search was completed in October 2025. Publications were selected based on relevance to robotic assistance in reconstructive, esthetic, microsurgical, craniofacial, lymphatic, and gender-affirming procedures, as well as their contribution to illustrating current practice patterns and emerging technical directions. Emphasis was placed on studies that described operative techniques, workflows, or early clinical implementation of robotic platforms. The literature included comprises case reports, case series, cohort studies, feasibility studies, and early clinical trials that described robotic techniques, workflows, or applications relevant to plastic and reconstructive surgery. Purely educational or training-focused studies, studies centered on non-plastic or non-reconstructive surgical specialties, non-procedural publications (including editorials, commentaries, and opinion pieces), and animal-only or preclinical studies were excluded from analysis. Simplified PRISMA and search strategy are listed in the Supplementary Materials document.

3. Current Applications in Plastic Surgery

Robotic technology has been applied across a broad spectrum of plastic and reconstructive surgical procedures, particularly in settings where enhanced visualization, precision, and access to confined anatomical spaces may be advantageous. Reported applications include flap harvest (such as Deep Inferior Epigastric Perforator (DIEP), latissimus dorsi, rectus abdominis, and omental flaps), microsurgical and super microsurgical procedures (including free flap anastomosis, lymphaticovenular anastomosis, and nerve coaptation), implant-based breast reconstruction, craniofacial and head and neck reconstruction (notably transoral robotic surgery-assisted reconstruction), esthetic procedures, and gender-affirming surgery (including robotic-assisted vaginoplasty and peritoneal flap harvest). Across these domains, the existing majority of the literature consists of case reports and case series with only limited high-quality comparative studies, reflecting the early and evolving nature of the field.

3.1. Flap Harvest

Robotic platforms can assist with the precise dissection of pedicle vessels during flap harvest, potentially reducing the need for larger incisions, muscle transection, or denervation (Table 1). This is particularly relevant in procedures such as DIEP flap harvest, where open approaches may require partial transection or denervation of the rectus abdominis muscle to access the deep inferior epigastric artery [8]. The purported promise of the DIEP flap technique has been preservation of rectus abdominis function, yet the most common long-term donor site morbidity following DIEP flap harvest is abdominal bulging due to this dissection, with reported rates ranging from 2 to 33% [8,9]. Two approaches have been described for robotic harvest of the DIEP flap. The multi-port robotic transabdominal pre-peritoneal (TAPP) was first performed by Gundlapalli et al. in 2018 [10]. In the multi-port robot-assisted totally extraperitoneal (TEP) reconstruction, which was first described in a cadaver model by Manrique et al. in 2019, and performed clinically by Bishop and Schwarz, the plane of dissection is between the rectus abdominis muscle and the posterior rectus sheath [11,12]. The TEP technique allows avoidance of intra-abdominal entry, although due to the narrow working space, it might have a steeper learning curve compared with the TAPP technique [11,13]. A single-port robotic system has also been reported for DIEP flap dissection using the TEP approach in unilateral cases by Lee et al. [13]. Although no definitive advantage has been demonstrated between the TEP and TAPP approaches, the existing literature supports the feasibility of both techniques, with approach selection largely dependent on surgeon experience and comfort with robotic assistance.
Similarly, robotic assistance may be beneficial in harvesting flaps such as the latissimus dorsi or rectus abdominis muscle, where minimizing donor-site morbidity and scar burden is desirable [14,15]. Selber et al. demonstrated the feasibility of robotic latissimus dorsi flap harvesting [16]. The potential advantages of robotic harvest may apply to both muscle-only flaps and musculocutaneous flaps with a small skin paddle.
From a technical standpoint, robotic flap harvest requires careful planning of multi-port placement and instrument selection to optimize exposure while minimizing tissue trauma. For DIEP flaps, ports are typically positioned to provide a direct trajectory to the deep inferior epigastric vessels, allowing precise intramuscular dissection and perforator preservation [3,12,17]. The robotic arms facilitate gentle retraction and separation of tissue layers. Single-port techniques can be especially advantageous in confined spaces, allowing simultaneous dissection and flap mobilization without additional incisions. Additionally, the surgeon can dynamically adjust camera angles and magnification through the console, ensuring continuous visualization of critical landmarks throughout the procedure. A single port approach has shown promise, particularly in the latissimus dorsi flap harvest [18], but can also be utilized in the DIEP flap harvest [13]. Early reports suggest that robotic harvest may lead to improved postoperative outcomes, particularly in terms of pain control and reduced length of hospital stay [8,19,20].
The omental flap is a versatile reconstructive option with a wide range of applications, including lymphedema. Traditionally, harvesting this flap has required a laparotomy. More recently, both multi-port and single-port robotic approaches have been employed [21], offering enhanced visualization, reduced donor-site morbidity, and improved postoperative recovery [22].
Although the current literature remains largely limited to small case series and case reports, the number of published experiences continues to increase annually. As larger cohorts and prospective studies emerge, the true added value of robotic flap harvest—particularly with respect to outcomes such as donor-site morbidity, bulge or hernia rates, and length of hospital stay—will be more definitively characterized.
Cost remains a frequently cited barrier to the adoption of robotic techniques. While the upfront capital investment of robotic platforms is substantial, the per-case cost of robotic utilization may be more nuanced and institution-dependent. As previously discussed by Selber, the primary determinant of cost-effectiveness is not the acquisition cost of the robotic platform itself, but rather the contribution margin per case, which reflects the balance between procedural revenue and incremental costs related to disposables, staffing, and operative time [3]. In institutions where robotic infrastructure is already established and utilization is sufficient, these incremental costs may be partially offset by potential downstream benefits, including reduced length of stay, lower donor-site morbidity, and enhanced recovery. However, robust cost-effectiveness analyses specific to robotic flap harvest remain limited, and prospective comparative studies are necessary to determine whether observed clinical advantages translate into meaningful economic benefit.
Table 1. Representative studies describing robot-assisted flap harvests and reconstructions are reported in the literature.
Table 1. Representative studies describing robot-assisted flap harvests and reconstructions are reported in the literature.
S.NAuthor, YearStudy DesignLOECountryProcedure/Flap TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Selber et al., 2012 [16]Cadaveric StudyN/AUSALatissimus dorsi flap10Breast reconstructionDa Vinci SFlap harvest
2Clemens et al., 2014Retrospective chart review3USALatissimus dorsi flap146Breast reconstructionDa VinciFlap harvest
3Chung et al., 2015Case series4KoreaLatissimus dorsi flap12Breast reconstructionDa Vinci SFlap harvest
4Gundlapalli et al., 2018 [10]Case Report5USATAPP DIEP1Breast reconstructionDa VinciFlap harvest
5Benjoar et al., 2018Case Report5USATEP DIEP1Breast reconstructionDa Vinci SIFlap harvest
6Shakir et al., 2020Cohort3USATAPP DIEP3Breast reconstructionDa Vinci XIFlap harvest
7Winocour et al., 2020Cohort3USALatissimus dorsi flap25Breast reconstructionDa VinciFlap harvest
8Daar et al., 2021Case Series4USATAPP DIEP4Breast reconstructionDa Vinci XIFlap harvest
9Day et al., 2021Case Report5USAOmentum flap1Breast reconstructionDa VinciFlap harvest
10Joo et al., 2021Case report5KoreaLatissimus dorsi flap1Breast reconstructionDa Vinci SPFlap harvest
11Wittesaele and Vandervoort, 2022Case Series4BelgiumTAPP DIEP10Breast reconstructionDa VinciFlap harvest
12Bishop et al., 2022 [19]Case Series4USATAPP DIEP21Breast reconstructionDa VinciFlap harvest
13Lee et al., 2022 [13]Cohort3KoreaTEP DIEP21Breast reconstructionDa Vinci SPFlap harvest
14Cheon et al., 2022 [14]Case Series4KoreaLatissimus dorsi flap41Breast reconstructionDa Vinci Si, Da Vinci Xi, Da Vinci SPFlap harvest
15Shuck et al., 2022Cohort3USALatissimus dorsi flap15Breast reconstructionDa VinciFlap harvest
16Dayaratna et al., 2022Case Report5AustraliaTAPP DIEP1Breast reconstructionDa Vinci XiFlap harvest
17Hwang et al., 2022 [18]Case series4KoreaLatissimus dorsi flap3Breast reconstructionDa Vinci SPFlap harvest
18Jung et al. 2022Case report5KoreaTEP DIEP1Breast reconstructionDa Vinci SPFlap harvest
19Tsai et al., 2023 [20]Cohort3TaiwanTAPP DIEP13Breast reconstructionDa Vinci XIFlap harvest
20Moreira et al., 2024Cohort3USATAPP DIEP23Breast reconstructionDa Vinci X/XIFlap harvest
21Kim et al., 2024Cohort3KoreaDIEP/NSM153 (rNSM), 64 (rDIEP)Breast reconstructionDa Vinci SPFlap harvest/Mastectomy
22Phuyal et al., 2025 [8]Case Report5USATAPP DIEP1Breast reconstructionDa Vinci XiFlap harvest
23Kuo et al., 2025Cohort3TaiwanDIEP/mastectomy14Breast reconstructionDa Vinci XiFlap harvest/Mastectomy
24Bishop et al., 2025 [12]Retrospective review3USAUnilateral TEP DIEPNRBreast ReconstructionDa Vinci XiFlap harvest/mastectomy
Other Indications
1Patel et al., 2011Case report5USALatissimus dorsi flap1Shoulder reconstructionDa VinciFlap Harvest
2Patel and Pedersen, 2012Case Report and preclinical study5USARectus abdominis muscle1Lower extremity reconstructionDa VinciFlap Harvest
3Pedersen et al., 2014 [15]Cohort Study3USARectus abdominis muscle10Pelvic reconstructionDa VinciFlap Harvest
4Ciudad et al., 2016Case Report5KoreaGastroepiploic lymph node flap1LymphedemaDa VinciFlap dissection and inset
5Ozkan et al., 2019Case Report5TurkeyOmentum flap1Lower extremity reconstructionDa VinciFlap Harvest
6Moon et al., 2020Cohort Study3South KoreaLatissimus dorsi flap21Poland syndrome/chest wall reconstructionDa VinciFlap Harvest
7Fouarge et al., 2020Case series4BelgiumLatissimus dorsi flap6Upper/lower limb reconstructionDa Vinci Xi, Da Vinci SPFlap harvest
8Frey et al., 2020 [22]Case series4USAOmentum flap5Vascularized lymph node transfer for upper extremity lymphedemaDa Vinci SPFlap harvest
9Teven et al., 2021Case Report5USAVOLT1LymphedemaDa Vinci SPomental harvest
10Asaad et al., 2021Case series4USARectus abdominis flap7Pelvis reconstructionNRMuscle harvest
11Haverland et al., 2021Case series4USARectus abdominis flap6Vesicovaginal fistula, complex pelvic organ prolapses, anterior and posterior exenteration, partial and total vaginectomy, partial vulvectomy, and abdominoperineal resection.NRFlap harvest
12Armando et al., 2022Cohort Study3USARectus abdominis flap36Pelvic reconstructionDa VinciFlap harvest
13Sanchez-Rodriguez et al., 2024Case Report5SpainOmentum flap1LymphedemaDa Vinci XiOmental Dissection
14Iftekhar et al., 2025Retrospective review3USARectus abdominis flap32posterior vaginal wall reconstructionDa VinciFlap harvest
S.N—serial number; SGA—superior gluteal artery; SIEA—superficial inferior epigastric artery; SGAP—superior gluteal artery perforator; TAPP—transabdominal preperitoneal approach; TEP—totally extraperitoneal approach; DIEP—deep inferior epigastric perforator; PAP—profunda artery perforator; NSM—nipple-sparing mastectomy; rNSM—robotic nipple-sparing mastectomy; rDIEP—robotic deep inferior epigastric perforator flap; VOLT—Vascularized omentum lymphatic transplant; NR—not reported, N/A: not applicable, LOE—American Society of Plastic Surgery Level of Evidence.

3.2. Robotic Breast Reconstruction with Prosthesis

Although the clinical utility and effectiveness of robot-assisted mastectomy and breast reconstruction remain subjects of ongoing debate, several reports describing these techniques have been published (Table 2) [23,24]. Prosthesis-based robot-assisted breast reconstruction has been reported with the use of small lateral incisions, offering the potential for reduced visible scarring. Both Da Vinci SP and XI robots have been utilized for this purpose [24]. It has been hypothesized that carbon dioxide insufflation during robotic dissection, particularly with single-port systems, may be less traumatic to mastectomy skin flaps than manual retraction, potentially reducing the risk of flap ischemia or necrosis. This potential benefit was suggested by Kim et al. in a cohort study; however, further comparative studies are required to substantiate these findings [24].
Although prosthesis reconstructions are technically feasible, careful attention must be paid to the preservation of key esthetic landmarks during reconstruction. In particular, maintaining the integrity of the inframammary fold may be challenging in the robotic setting, where tactile feedback and traditional visual cues are altered. Additionally, deliberate efforts are required to preserve the midline to avoid inadvertent obliteration, which may predispose to symmastia.

3.3. Robotic Microscope

There are several technologies available for surgical field magnification, including surgical loupes, operative microscopes, and exoscopes. Although the operative microscope remains the most widely used tool, it can be cumbersome, requiring repeated manual adjustments, and it can be ergonomically challenging during prolonged procedures. In response to these limitations, robotic digital microscopes-such as the RoboticScope (BHS Technologies, Innsbruck, Austria), were introduced, integrating high-resolution three-dimensional visualization with virtual reality (VR) interfaces (Table 3) [25,26]. These platforms enable hands-free, head gesture-controlled navigation of the surgical camera, allowing surgeons to adjust the operative view without breaking sterility or disrupting workflow. While early experience suggests potential ergonomic advantages compared with conventional microscopes, further objective evaluation is needed to determine their impact on surgeon fatigue, efficiency, and clinical outcomes.
Moreover, the combination of image stabilization with magnified three-dimensional visualization may be particularly relevant for technically demanding microsurgical tasks, including vascular anastomosis, free flap dissection, and lymphaticovenular anastomosis. As these technologies continue to evolve, robotic digital visualization systems may also play a role in surgical education and tele-mentoring by enabling real-time, shared, virtual reality-based operative views, although their broader clinical and educational impact remains to be defined [25,26].

3.4. Microsurgery

Robotic systems such as MUSA (Microsure, Eindhoven, The Netherlands) and Symani (MMI, Pisa, Italy) have been developed to facilitate high-precision microsurgical procedures (Table 4) [4,27]. Reported applications include lymphovenous anastomosis, free flap microvascular anastomosis, and nerve coaptation [4,27]. The platforms are teleoperated, with the surgeon seated and viewing the operative field through an exoscope or robotic digital microscope rather than a conventional microscope [4]. The surgeon’s movements are translated to wristed microinstruments (Symani, MMI, Pisa, Italy) with multiple degrees of freedom, enabling fine manipulation at a submillimeter scale. While this configuration may reduce physical strain, its impact on operative efficiency and outcomes remains under evaluation [4].
Micro-robotic systems may be particularly relevant in super microsurgery, where vessel diameters are often less than 0.8 mm and technical precision approaches the limits of human dexterity [4,27]. These systems incorporate motion scaling, tremor filtration, and console-based operation, which may assist surgeons when working with delicate structures. These technologies also hold promise for extending the operative careers of microsurgeons by reducing physical strain, improving posture, and mitigating the effects of age-related physiologic tremor. In addition, microneural surgery-including procedures on the brachial plexus-has emerged as another promising field for robotic assistance, offering improved visualization and fine motor control during intricate nerve repairs.
Comparative studies have suggested that robotic assistance with platforms such as Symani may reduce vessel edge trauma during anastomosis compared with conventional techniques [28,29,30]. Surgeons also reported improved scores in intraoperative tremor suppression, reduced muscle fatigue, enhanced optical detail, greater operative comfort, and superior depth and 3D structural visualization when using robotic systems. However, Jeong et al. reported longer anastomotic times and steep learning curves with the Symani. High rates of intraoperative anastomosis patency (>90%) were reported but remain to be evaluated in head-to-head comparisons with conventional methods [28]. Furthermore, the performance of manual super microsurgery engenders limited haptic feedback at baseline, making its absence relatively inconsequential for surgeons who routinely perform these procedures [28,29,30].
From a practical standpoint, the clinical introduction of microrobotic systems such as MUSA and Symani requires adjustments in operative workflow and training. Although setup is generally achievable within minutes, it requires appropriate preoperative planning and team familiarity. Current platforms are compatible with standard operating rooms and utilize compact robotic arms positioned on either side of the patient. Surgeons typically undergo dedicated training sessions, including dry-lab simulations on synthetic vessels and animal models, before progressing to clinical cases. Early experience suggests that the learning curve for most microsurgeons adapting to motion scaling and wristed microinstruments occurs within 10–20 practice cases [28]. As clinical experience expands, broader adoption of micro-robotic systems will depend on practical considerations such as cost, availability of instruments, training requirements, and seamless integration with visualization platforms. Further comparative and long-term studies will be necessary to clarify whether these technologies translate into consistent clinical or ergonomic advantages over conventional microsurgical techniques.
Table 4. Representative studies describing robot-assisted microsurgery and free flap reconstruction in plastic and reconstructive surgery. LOE: American Society of Plastic Surgery Level of Evidence.
Table 4. Representative studies describing robot-assisted microsurgery and free flap reconstruction in plastic and reconstructive surgery. LOE: American Society of Plastic Surgery Level of Evidence.
S.NAuthor, YearStudy DesignLOECountryProcedure/Flap TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Boyd et al., 2006Case series4USAMuscle-sparing TRAM flap (11), SGA flap (6), SIEA flap (4), and SGAP flap (1)20Breast reconstructionAesopInternal Mamary Artery Dissection
2Barbon et al., 2022Case Series4SwitzerlandPAP, gracilis neurovascular flap, SCIP22Lymphatic reconstructive surgery (18), free flap reconstruction (3), nerve coaptation (1)SymaniRobot-assisted anastomosis
3van Mulken et al., 2022Cohort Study3The NetherlandsLVA8LymphedemaMicroSure MUSARobot-assisted anastomosis
4Lindenblatt et al., 2022Cohort Study3SwitzerlandLVA/free vascularized lymph node transfer5LymphedemaSymaniRobot-assisted anastomosis
5Beier et al., 2023Case Series4GermanyRadial forearm flap (11), ALT-flap (7), fibular flap (4), and anterior serrate muscle flap (1)23Free flap reconstruction (various)SymaniRobot-assisted anastomosis
6Besmens et al., 2023Case Series4Switzerlandmedial femoral condyle free flap (2), ALT free flap (1), lateral arm free flap (1), nerve grafting with nerve allograft (2)6Arterial anastomoses (4), nerve grafting (2)SymaniRobot-assisted anastomosis
7Schafer et al., 2023Case report5GermanyNerve transfer/Intercostal nerves to long thoracic and thoracodorsal nerve1Brachial Plexus PalsySymaniNerve transfer
8Grunherz et al., 2023Case report5SwitzerlandCentral lymphatic reconstruction1Central lymphatic dilationSymaniMicrosurgical anastomoses
9Innocenti et al., 2023Case report5ItalyALT1Post traumaticSymaniMicrosurgical anastomoses
10Martin et al., 2024Case Series4GermanyPeripheral nerve surgery19Nerve transfer, muscle reinnervation, neurotized free flaps, autologous nerve graftsSymaniNerve coaptation
11Reibnitz et al., 2024Cohort Study3SwitzerlandLTT/LVA/LLA67LymphedemaSymaniRobot-assisted anastomosis
12Tolksdorf et al., 2024Cohort Study3GermanyRadial forearm, fibula, latissimus dorsi, scapula30Cranio- and maxillofacial surgerySymaniRobot-assisted anastomosis
13Struebing et al., 2024Cohort Study3GermanyFree flap (ALT, latissimis dorsi, DIEP, etc.), Nerve surgery, LVA (Various)100VariousSymaniVarious
14Struebing et al., 2024Cohort Study3GermanyALT, medial femoral condyle, latissimus dorsi16Upper extremity defectsSymaniRobot-assisted anastomosis
15Dastagir et al., 2024Retrospective chart review3GermanyFinger replantation (8), finger blood vessel injury (13)21Hand reconstructionSymaniRobot-assisted anastomosis
16Reilly et al., 2024 [29]Cohort Study3SwedenLVA12LymphedemaMUSA-2Robot-assisted anastomosis
17Mori et al., 2024Cohort Study3ItalyALT (5), medial plantar (1), SCIP (1), latissimus dorsi (2), serratus anterior (1), medical femoral condyle (1), free fibular (3), free toe pulp (1), sensate free-style perforator flap from ulnar artery (1)16VariousSymaniRobot-assisted anastomosis
18Lilja, et al., 2024Case Report5DenmarkLVA/lymphocele excision1LymphoceleSymaniRobot-assisted anastomosis, excision
19Gorji et al., 2024Retrospective review3GermanyDIEP (10), ALT (4), gracilis (4), SCIP (2), PAP (2), latissimus dorsi (1)23Cancer, posttraumaticSymani robot, RoboticScope microscopeMicrosurgical anastomoses
20Vollbach et al., 2024Case Report5GermanyDIEP1Breast ReconstructionSymaniRobot-assisted anastomosis
21Watson et al., 2025Cohort Study5SwitzerlandFree ALT or latissimus dorsi to scalp/facial artery and vein6Free tissue transfers for defects of the scalpSymaniRobot-assisted anastomosis
22Chen et al., 2025 [17]Case Series4USALymph node-to-vein anastomosis20LymphedemaSymaniRobot-assisted anastomosis
23Spille et al., 2025Cohort Study3GermanyRadial forearm flap, ulnar forearm, fibula93Head and neck reconstructionSymaniRobot-assisted anastomosis
24Sorensen et al., 2025Cohort Study3DenmarkALT, DIEP, fibular, helical and LVA12VariousSymanirobot-assisted anastomosis
25Paternoster et al., 2025Case report5UKDIEP1Chest wall reconstructionSymanirobot-assisted anastomosis
26Kukreja-Pandey et al., 2025Case report5USALVB1Breast lymphedemaSymaniLVB
27Konneker et al., 2025Cohort Study3SwitzerlandSCIP (2), ALT (6)8Upper and lower extremity reconstructionSymaniRobot-assisted anastomosis
S.N—serial number; TRAM—transverse rectus abdominis musculocutaneous; SGA—superior gluteal artery; SIEA—superficial inferior epigastric artery; SGAP—superior gluteal artery perforator; PAP—profunda artery perforator; ALT—anterolateral thigh; DIEP—deep inferior epigastric perforator; LVA—lymphaticovenular anastomosis; LTT—lymphatic transfer; LLA—lymphatic-lymphatic anastomosis; SCIP—superficial circumflex iliac artery perforator; LVB—lymphatic-venous bypass; LOE—American Society of Plastic Surgery Level of Evidence. Numbers in brackets indicate the total number of flaps for each procedure.

3.5. Head and Neck/Craniofacial Reconstruction

Before the introduction of Trans-Oral Robotic Surgery (TORS), surgical management of oropharyngeal and hypopharyngeal tumors often required highly morbid open approaches, such as mandibulotomy or lip-splitting incisions, which carried substantial risks of cosmetic deformity, prolonged recovery, and impaired swallowing and speech. Even with transoral laser microsurgery, visualization and maneuverability in deep anatomical corridors remained limited. The advent of robotic surgery addressed some of these challenges by enabling access to narrow spaces through natural orifices, improving visualization, and enhancing surgeon ergonomics, thereby facilitating minimally invasive tumor resection.
TORS was pioneered in the mid-2000s by Drs. Bert O’Malley Jr. and Gregory Weinstein at the University of Pennsylvania, who demonstrated its clinical benefits with minimally invasive approaches to oropharyngeal lesions—first in preclinical models and later in patients—with the term officially entering the surgical field in 2005 [31]. Following early clinical experience, the U.S. Food and Drug Administration approved the Da Vinci system to perform TORS on benign and early-stage malignant head and neck tumors in December 2009 (Table 5). Since then, TORS has been increasingly adopted for appropriately selected cases, supported by its ability to provide three-dimensional visualization, wristed instrumentation, tremor reduction, and precise access to confined anatomical spaces.
Beyond its initial application in tonsillar and base-of-tongue tumors, TORS has been extended to lesions of the hypopharynx, parapharyngeal space, supraglottic larynx, and carcinoma of unknown primary, where enhanced visualization may facilitate identification of occult disease in accordance with current guidelines. TORS has also been explored in the management of obstructive sleep apnea in patients resistant to conventional therapies [35].
More recently, robotic platforms have been applied in reconstructive and craniofacial surgery, including TORS-assisted flap inset, selected free flap reconstructions, and investigational applications in hemifacial microsomia, genioplasty, Le Fort osteotomies, and mandibular contouring (Table 5) [32,33,34]. Overall, robotic use in craniofacial surgery spans oncologic resection, flap inset, cleft palate repair, and osteotomy. However, broader adoption remains limited by the paucity of high-quality evidence, as most published data consist of cohort studies, case reports, and small case series.

3.6. Esthetic Procedures

Robotic technology is in its early stages within facial rejuvenation but shows considerable promise [36]. Surgical robots have been reported to enhance precision in the dissection and visualization of delicate facial structures, offering up to twenty times magnification and tremor-free movement [36]. The Da Vinci system has been explored for esthetic face and neck procedures, rectus diastasis repair with abdominal body contouring, although early experiences required innovative docking strategies to accommodate the constraints of the robotic arms [36].
Hair restoration is currently the most developed use of robotics in esthetics. Robotic follicular unit extraction systems like ARTAS (Venus Concept, Toronto, ON, Canada) and NeoGraft (Venus Concept, Toronto, ON, Canada) have been in use for over a decade [37,38]. ARTAS, FDA-approved in 2011, uses image-guided algorithms to identify and harvest follicular units with precision. Advantages include consistent graft quality, reduced surgeon fatigue, and precise targeting, although limitations include cost, slower speed compared to skilled manual teams, and reduced accuracy with certain hair types.
Robotic assistance is slowly expanding beyond hair and facial applications into other fields of esthetic surgery (Table 6). Uptake is slower than in other specialties due to the artistic and individualized nature of cosmetic work [39]. Continued refinement in artificial intelligence (AI) guidance, force feedback, and specialized instruments may allow robots to enhance surgical artistry while maintaining safety and patient confidence.

3.7. Gender-Affirming Surgery

Robot-assisted vaginoplasty has evolved rapidly over the past decade, transitioning from isolated case reports to large multi-institutional series (Table 7). Early reports, such as Boztosun and Olgan (2016) [40], described the use of the Da Vinci Xi system for sigmoid vaginoplasty in Mayer–Rokitansky–Küster–Hauser syndrome, while subsequent studies demonstrated its application in gender-affirming surgery for flap dissection, harvest, and inset [40,41]. Between 2019 and 2025, multiple case series have documented increasing procedural volume and refinement, with sample sizes expanding from small case reports to 500-patient cohorts [41]. Across studies, robotic platforms (Da Vinci Xi and SP) have enabled precise peritoneal flap harvest, vaginal canal creation, and improved visualization of pelvic structures. Collectively, the literature suggests that robotic assistance has become an integral adjunct in contemporary gender-affirming vaginoplasty; however, most available evidence remains observational, underscoring the need for standardized outcome reporting and higher-quality comparative studies.

3.8. The Promise of AI in Robotic Surgery

Recent advances in artificial intelligence (AI) have expanded the role of surgical robots beyond simply replicating the surgeon’s hand movements. Modern systems can learn, adapt, and provide real-time assistance during operations. As these technologies mature, robotic platforms may evolve toward more collaborative roles by integrating visual, tactile, and kinematic inputs with patient-specific data. However, the extent to which such systems can reliably anticipate complications, reduce errors, or meaningfully augment surgical capability remains an area of active investigation and will require careful validation before broader clinical integration [42,43].
AI has the potential to merge computational power with human expertise. These capabilities can enhance preoperative planning, improve surgical precision, and provide real-time intraoperative decision support. Applications include simulation-based training, quality monitoring, benchmarking to support key performance indicators, continuous learning and improvement, event and outcome prediction, complication management, and even surgeon credentialing [44].

3.9. Path Toward Autonomous Surgical Robotics

The convergence of AI and robotic surgery paves the way for autonomous completion of advanced procedures. This requires accurate perception of the surgical situation through synthesis of computer vision and sensorized data, ultimately advancing to adaptive, intelligent decision-making [45].

3.10. Training and the Learning Curve

Training in robot-assisted surgery is typically supported through a combination of structured courses, virtual reality-based simulators, and supervised clinical experience. Emerging applications of machine learning and video-based feedback have been proposed as adjuncts to surgical education and may help facilitate skill acquisition, although their effectiveness continues to be evaluated.
A fundamental distinction between open and robot-assisted surgery is the absence of direct tactile feedback. Replicating meaningful haptic sensation requires the integration of high-resolution sensors, robust algorithms to interpret tactile data, and reliable control systems capable of approximating the human sensorimotor loop. While progress has been made, with some platforms incorporating elements of real-time tactile perception to assist with grasp control and instrument handling, these technologies remain under active development and have yet to be fully validated in routine clinical practice [46,47].

3.11. Soft Robotics and Future Directions

Soft robotics, which uses materials such as fluids, gels, and elastomers that are functionally closer to humans, offers exciting possibilities. These systems are safer for clinical application, reduce mechanical complexity, and adapt to complex working environments. Soft continuum robots—small, flexible, and strong—can navigate curved pathways to reach difficult-to-access surgical sites, performing tasks with exceptional dexterity [48,49]. Of note to our knowledge, soft robotic technologies have not yet achieved routine clinical implementation; however, they represent a rapidly evolving area of research with substantial technological progress.
Looking ahead, the integration of soft robotics into surgical practice has the potential to revolutionize minimally invasive techniques by combining the safety of compliant structures with the precision of robotic control. Emerging advances include hybrid systems, where rigid robotic arms provide stability while soft, continuum segments perform fine manipulations in delicate regions such as the oropharynx, skull base, or around critical neurovascular structures. Additionally, developments in smart materials and embedded sensing technologies may allow soft robotic instruments to provide real-time haptic feedback, enabling surgeons to “feel” tissue interactions remotely—an element largely missing in current robotic platforms. These innovations hold promise not only for expanding the indications of transoral and craniofacial surgery but also for improving patient outcomes through shorter operative times, reduced adjacent tissue trauma, and enhanced functional recovery.

4. Current Limitations and Challenges

Although robotic platforms are designed to facilitate complex surgical tasks, their adoption is associated with a learning curve that may initially affect operative efficiency. Early experiences have reported longer operative times compared with conventional approaches, particularly during the adoption phase. While published studies reflect growing interest in robotic surgery, the available evidence remains mostly low-level evidence as per ASPS grading. The majority of published studies consist of case reports, small case series, and retrospective cohort studies (ASPS Levels III–V), with relatively few comparative analyses and a near absence of randomized or prospective trials. As a result, conclusions regarding the clinical benefit, safety, and cost-effectiveness of robotic assistance must be interpreted with caution. The heterogeneity in study design, patient selection, procedural indications, and outcome reporting further limits the ability to draw definitive comparisons across techniques or platforms.
Current limitations include technological constraints, particularly in complex surgical cases, where current robotic systems may not yet match the adaptability and versatility of conventional techniques [21,23,24]. For example, the absence of tactile feedback may lead to excessive force on delicate structures, thereby increasing the risk of injury. Furthermore, it limits the concomitant two-team approach in complex multisite surgery, which may add operating time to the surgery and decrease the workflow in the operating room. In addition, while robotic-assisted procedures are currently associated with higher upfront costs compared with traditional techniques, their true economic impact remains incompletely defined. Well-designed studies with larger sample sizes and extended follow-up are needed to evaluate potential downstream cost benefits, particularly those related to reductions in postoperative abdominal wall morbidity, such as hernia formation and muscle dysfunction, which may otherwise necessitate additional interventions.
Looking ahead, overcoming these challenges will require collaboration among surgeons, engineers, industry leaders, and policymakers. Technical solutions such as enhanced haptic feedback, smaller and more flexible robotic instruments, and integration of artificial intelligence are under development, but their safe clinical adoption will demand rigorous validation through high-quality multicenter trials. From a systems perspective, addressing cost-effectiveness and equitable access will be critical if robotic surgery is to move beyond high-resource centers and benefit patients globally. Finally, standardized training curricula and credentialing pathways must be established to ensure surgeons worldwide can adopt robotic techniques safely and efficiently, ultimately maximizing the impact of this rapidly advancing technology.
Given the narrative design of this study, it relies on the authors’ interpretation and synthesis of the available evidence. To maintain a clinical and procedural focus, educational- and training-focused studies were excluded, which may limit representation of the broader robotic learning ecosystem. Comparative evaluation of clinical outcomes should be better addressed through procedure-specific systematic reviews with standardized outcome reporting.

5. Conclusions

Robot-assisted reconstructive surgery has advanced from a novel concept to a rapidly growing field defined by innovation and precision. Multi-port and single-port systems have enabled the first wave of robotic plastic surgery applications. Early-generation microsurgical robotic platforms are experiencing growing clinical adoption. Continued collaboration and accumulation of real-world data will further refine indications, techniques, and outcomes. Robotic reconstruction is in its early phase yet firmly positioned as a lasting component of modern reconstructive surgery.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm15020602/s1, Figure S1: Flow diagram illustrating the literature identification and selection process for this narrative review.

Author Contributions

Conceptualization, A.F., G.S.S., R.D., S.N.B. and D.P.; methodology, D.P.; data collection, G.B., J.T. and D.P.; formal analysis, D.P.; writing—original draft preparation, A.F., N.N., G.M., D.P., J.T. and G.B.; writing—review and editing, D.P. and G.S.S.; visualization, D.P.; supervision, G.S.S., R.D. and S.N.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Can be provided on request to the corresponding authors.

Conflicts of Interest

Sarah N Bishop: Consultant for RTI Surgical and Integra and Speaker for MMI. Graham S Schwarz: Consultant for RTI and MMI. Risal Djohan: Consultant for MMI. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Abbreviations

AIArtificial Intelligence
ALTAnterolateral Thigh
DIEPDeep Inferior Epigastric Perforator
FUEFollicular Unit Extraction
LVALymphaticovenular Anastomosis
NSMNipple-Sparing Mastectomy
OSAObstructive Sleep Apnea
SPSingle-Port
TEPTotally Extraperitoneal
TORSTrans-Oral Robotic Surgery
VRVirtual Reality

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Table 2. Representative studies describing robotic-prosthesis-based breast reconstruction.
Table 2. Representative studies describing robotic-prosthesis-based breast reconstruction.
S.NAuthor, YearStudy DesignLOECountryProcedure TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Lai et al., 2020Case–control3TaiwanNSM with immediate implant-based reconstruction40Breast ReconstructionDa VinciDissection/mastectomy + IPBR
2Jeon et al., 2021Case series4KoreaMastectomy, direct-to-implant reconstruction16Breast reconstructionDa Vinci XiMastectomy + IPBR
3Joo et al., 2021Case series4KoreaMastectomy, direct-to-implant reconstruction2Breast ReconstructionDa Vinci SPMastectomy + IPBR
4Kijima et al., 2025Case report5JapanNSM with implant-based reconstruction1Breast ReconstructionDa VinciNSM + IPBR
5Kim et al., 2025 [24]Cohort Study3KoreaImplant based breast reconstruction49Breast reconstructionDa Vinci Xi and SPImplant based breast reconstruction
S.N—serial number; NSM—nipple-sparing mastectomy; IPBR—immediate prosthetic breast reconstruction; SP—single-port; Xi—multi-port system; LOE—American Society of Plastic Surgery Level of Evidence.
Table 3. Representative studies describing the use of the Robotic microscope.
Table 3. Representative studies describing the use of the Robotic microscope.
S.NAuthor, YearStudy DesignLOECountryProcedure/Flap TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Dermietzel et al., 2022 [25]Cohort3GermanyPAP flap, DIEP 5Breast reconstructionRoboticScopeVisualizing anastomosis
2Chung et al., 2023 [26]Case Report 5KoreaLVA1LymphedemaRoboticScopeVisualizing anastomosis
3De Virgilio et al., 2024Case Report 5ItalyFree fibula flap 1Oral squamous cell carcinomaRoboticScopeVisualizing anastomosis
4Mokhtar et al., 2025Cohort3United Arab EmiratesPalatoplasty 4Cleft palate/lipRoboticScopeDissection and visualization
S.N—serial number, PAP—profunda artery perforator flap; DIEP—deep inferior epigastric perforator; LVA—lymphaticovenular anastomosis; LOE—American Society of Plastic Surgery Level of Evidence.
Table 5. Representative studies reporting robotic applications in craniofacial and head and neck reconstructive surgery.
Table 5. Representative studies reporting robotic applications in craniofacial and head and neck reconstructive surgery.
S.NAuthor, YearStudy DesignLOECountryProcedure TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Garfein et al., 2011 [32]Case report5USARFFF 1Squamous cell carcinoma of base of tongueDa VinciFlap inset
2Bonawitz and Duvvuri, 2012Case Report5USAALT flap (2), RFFF (2)4TORS for malignant tumorNROral reconstruction, vessel anastomosis
3Song et al., 2013Cohort Study3KoreaTORS with RFFF, ALT5Head and neck reconstructionDa Vinci STORS tumor dissection, flap inset
4Bonawitz and Duvvuri, 2013Case series4USAFAMM flap5TORS for malignant tumorNRTumor resection
5Duvvuri et al., 2013Retrospective review3USATORS/Base of Tongue with epiglottoplasty12Malignant neoplasm, post-surgical VPI, velopharyngeal stenosisNRFlap harvest
6Hans et al., 2013Case report5FranceTORS2hypopharyngeal carcinomaDa VinciFlap harvest
7Lin et al., 2016Feasibility StudyN/AChinaMandibular angle split osteotomy5Prominent mandibular angleUnnamed, surgical robotic arm and AR systemPositioning
8Kayhan et al., 2016 [33]Cohort3TurkeyTORS/base of tongue with epiglottoplasty25OSADa VinciBase of tongue reduction, epiglottoplasty
9Nadjmi, 2016Case Series4IranTORS10Cleft PalateDa VinciPalate muscle dissection
10Biron et al., 2017Case series4CanadaRFFF18TORS for oropharyngeal squamous cell carcinomaDa Vinci STumor resection
11Lin et al., 2021Case series4ChinaGenioplasty6Asymmetry, dysplasia, overdevelopmentCPSR-I systemPositioning and surgeon force perception
12Lin et al., 2021Randomized Controlled Trial2ChinaGenioplasty, mandibular angle osteotomy15Craniofacial diseaseUnnamedOsteotomy navigation
13Zhang et al. 2023 [34]Clinical study2ChinaMDO4HFMAurora V3, NDIDistraction Osteogenesis/Intraoperative Guidance
14Ebeling et al., 2023Case Report5USALe Fort I osteotomy1Skeletal class III malocclusionCARLOLinear laser osteotomy
15Porcuna et al., 2023Cohort Study3SpainTORS/tracheostomy and resection with free flap reconstruction (ALT/RFFF)15Oropharyngeal squamous cell carcinomaDa Vinci XiDissection, vessel exposure, flap inset
16Li et al., 2025Cohort3ChinaMandibular osteotomy42Cosmetic, hemifacial microsomiaNRMandibular osteotomy, distraction osteogenesis
S.N: Serial Number; ALT—anterolateral thigh flap; RFFF—radial forearm free flap; TORS—transoral robotic surgery; FAMM—facial artery musculomucosal flap; MDO—mandibular distraction osteogenesis; AR—augmented reality; CPSR-I—craniofacial-plastic surgical robot, version i; CARLO—cold ablation robot-guided laser osteotome; HFM—hemifacial microsomia; OSA—obstructive sleep apnea; VPI—velopharyngeal insufficiency; LOE—level of evidence; NR—not reported; NA: not applicable. Numbers in brackets indicate the total number of flaps for each procedure.
Table 6. Representative studies describing robot-assisted esthetic procedures. LOE: American Society of Plastic Surgery Level of Evidence.
Table 6. Representative studies describing robot-assisted esthetic procedures. LOE: American Society of Plastic Surgery Level of Evidence.
S.NYearAuthor, YearStudy DesignLOECountryProcedure TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
12016Bernstein et al., 2016 [37]Case Series4USAFUE hair transplant24Follicular unit graft selectionARTASGraft harvest
22021Kanayama et al., 2021 [38]Cohort3JapanFUE hair transplant31AlopeciaARTASFollicular harvest
32023Rybakin et al., 2023Cohort3RussiaRhytidectomy5Facial RejuvenationDa Vinci SiDissection
42024Borisenko et al., 2024 [39]Case Report5RussiaEsthetic lipoabdominoplasty, cholecystectomy 1Diastasis of the rectus abdominis muscles, cholelithiasis, calculous cholecystitsNRDissection, cholecystectomy
S.N—serial number; FUE—follicular unit extraction; NR—not reported. LOE—American Society of Plastic Surgery Level of Evidence.
Table 7. Representative studies describing robot-assisted gender-affirming genital surgery.
Table 7. Representative studies describing robot-assisted gender-affirming genital surgery.
S.NAuthor, YearStudy DesignLOECountryProcedure TypeNumber of PatientsIndicationRobot UsedApplication/Role of Robot
1Boztosun and Olgan, 2016 [40]Case Report5TurkeySigmoid vaginoplasty 1Mayer-Rokitansky-Kuster-Hauser SyndromeDa Vinci XiDissection of sigmoid colon graft
2Jacaby et al., 2019Retrospective review3USAVaginoplasty41Gender-affirming surgeryDa VinciFlap dissection
3Acar et al. 2020 Case series4USAVaginoplasty11Gender-affirming surgeryDa Vinci Xi, Da Vinci SPPeritoneal flap harvest and suturing
4Oriana et al., 2020Case Report5USAVaginectomy16Gender-affirming surgeryNRRobotic asissted vaginectomy and muscle harvest
5Dy et al., 2021Retrospective review3USAPeritoneal flap revision vaginoplasty24Gender-affirming surgeryDa Vinci Xi, Da Vinci SPFlap harvest and inset
6Jun et al., 2021Retrospective review3USAVaginectomy 42Gender-affirming surgeryDa Vinci Xi, Da Vinci SPFlap dissection
7Dy et al., 2022Retrospective review3USAPeritoneal flap vaginoplasty145Gender-affirming surgeryDa Vinci Xi, Da Vinci SPFlap harvest and inset
8Blasdel et al., 2023Case series4USA Vaginoplasty43Gender-affirming surgeryDa Vinci SPVaginal canal dissection and peritoneal flap creation
9Corral et al., 2024Case series4USAVaginoplasty6Gender-affirming surgeryNRFlap harvest
10Blasdel et al., 2025 [41]Case series4USAVaginoplasty500Gender-affirming surgeryDa Vinci Xi, Da Vinci SPNR
S.N—serial number; NR—Not Reported; LOE—American Society of Plastic Surgery Level of Evidence.
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MDPI and ACS Style

Foroutan, A.; Phuyal, D.; Babb, G.; Ting, J.; Mashhadiagha, G.; Najafi, N.; Djohan, R.; Bishop, S.N.; Schwarz, G.S. Robotic Horizons in Plastic Surgery: A Look Toward the Future. J. Clin. Med. 2026, 15, 602. https://doi.org/10.3390/jcm15020602

AMA Style

Foroutan A, Phuyal D, Babb G, Ting J, Mashhadiagha G, Najafi N, Djohan R, Bishop SN, Schwarz GS. Robotic Horizons in Plastic Surgery: A Look Toward the Future. Journal of Clinical Medicine. 2026; 15(2):602. https://doi.org/10.3390/jcm15020602

Chicago/Turabian Style

Foroutan, Ali, Diwakar Phuyal, Georgia Babb, Julia Ting, Ghazal Mashhadiagha, Niayesh Najafi, Risal Djohan, Sarah N. Bishop, and Graham S. Schwarz. 2026. "Robotic Horizons in Plastic Surgery: A Look Toward the Future" Journal of Clinical Medicine 15, no. 2: 602. https://doi.org/10.3390/jcm15020602

APA Style

Foroutan, A., Phuyal, D., Babb, G., Ting, J., Mashhadiagha, G., Najafi, N., Djohan, R., Bishop, S. N., & Schwarz, G. S. (2026). Robotic Horizons in Plastic Surgery: A Look Toward the Future. Journal of Clinical Medicine, 15(2), 602. https://doi.org/10.3390/jcm15020602

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