The rise of robotic-assisted esophagectomy: a game-changer or just an added cost—a narrative review

Introduction

Background

Esophageal cancer remains a major global health challenge, ranking among the leading causes of cancer-related mortality worldwide (1). Esophagectomy, as an integral part of the multimodal therapy, is essential for curative treatment in resectable cases (2). Traditionally performed via open surgery, esophagectomy is associated with significant morbidity and prolonged recovery due to its complexity and the extent of surgical trauma. The procedure can be performed using either a transthoracic or transhiatal approaches. Ivor Lewis (intrathoracic anastomosis) and McKeown (cervical anastomosis) techniques are favored from the oncologic perspective for their superior mediastinal lymph node yield due direct visual guidance for dissection (3-5).

The introduction of minimally invasive esophagectomy (MIE) in the late 20th century revolutionized esophageal cancer surgery, offering reduced surgical trauma, while maintaining oncologic principles. MIE has gained widespread adoption due to its association with lower morbidity and mortality while achieving disease-free survival (DFS) and overall survival (OS) outcomes comparable to open esophagectomy (OE) (6-10). Further supporting MIE approaches, a multi-institutional study comparing MIE, hybrid esophagectomy (HE), and OE found that MIE significantly reduced postoperative complications and hospital stay compared to OE and HE (11).

Despite its advantages, MIE presents challenges, including a steep learning curve and technical limitations, particularly in lymphadenectomy within confined anatomical spaces (12). A retrospective analysis of the Society of Thoracic Surgeons (STS) National Database (2008–2011) comparing 3,780 esophagectomy cases found that while MIE and OE had similar morbidity and mortality rates, MIE was associated with longer operative times and a higher reoperation rate, likely reflecting a learning curve (13). The learning curve for MIE varies significantly, ranging from 20 to 175 cases depending on the technique (14).

Robotic-assisted esophagectomy (RAMIE) has emerged as a promising development in minimally invasive surgery, addressing some of the limitations of conventional minimally invasive esophagectomy (cMIE). Robotic platforms provide high-definition three-dimensional (3D) visualization, 10-fold magnification, and enhanced instrument dexterity through the EndoWrist system, which replicates natural wrist movements with seven degrees of freedom. Additional advantages include longer instruments and an internal fulcrum within the body cavity, reducing patient discomfort, while a 60-Hz motion filter minimizes tremor, improving surgical precision. These innovations enable more complex procedures to be performed with greater control and confidence, particularly in challenging cases (15,16). The da Vinci Surgical System, developed by Intuitive Surgical (Intuitive Surgical, Inc., Sunnyvale, CA, USA), has played a key role in advancing robotic-assisted surgery through continuous innovation since its introduction in 2000. Early versions, including the Standard and S models, provided 3D high definition (HD) visualization, wristed instruments, and tremor filtration, laying the foundation for modern robotic surgery. The da Vinci Si, introduced in 2009, featured dual-console capability and Firefly fluorescence imaging, enhancing collaboration and visualization, while the Xi system, launched in 2014, incorporated longer instrument arms, an overhead boom for multi-quadrant access, and improved imaging, expanding its applications. The Single-Port (SP) system, released in 2018, enabled single-incision surgery. The most advanced version, da Vinci 5 (DV5), introduced in 2024, integrates artificial intelligence (AI)-driven assistance, enhanced haptic feedback, next-generation vision systems with augmented reality overlays, and cloud connectivity, allowing for greater precision, decision support, and partial automation.

Rationale and knowledge gap

A pivotal study comparing RAMIE with OE found that RAMIE significantly reduced surgery-related complications (59% vs. 80%, P=0.02), blood loss (P<0.001), pulmonary (P=0.005) and cardiac complications (P=0.006), and postoperative pain (P<0.001). Functional recovery at postoperative day 14 and quality-of-life scores at discharge and 6 weeks post-discharge were superior in the RAMIE group, while oncologic outcomes at a median follow-up of 40 months remained comparable (17). A systematic review and meta-analysis of 10 studies including 1,977 patients found that RAMIE was associated with significantly lower rates of pulmonary complications, pneumonia, atrial fibrillation, and wound infections compared to OE, along with reduced blood loss and shorter hospital stays. Long-term oncologic outcomes, including OS and DFS, were comparable between RAMIE and OE (18). Further comparative studies have also demonstrated that RAMIE offers improved perioperative outcomes relative to HE. RAMIE has been associated with lower rates of anastomotic leakage, pulmonary complications, and overall morbidity. Babic et al. reported significantly fewer postoperative complications in the RAMIE group compared to HE (19). Similarly, Grimminger et al. observed reduced risks of overall morbidity, anastomotic leaks, and respiratory failure with RAMIE (20). Despite these perioperative benefits, oncologic outcomes appear similar between RAMIE and HE. Babic et al. found no significant differences in lymph node yield or R0 resection rates, and Jung et al. reported comparable radical resection rates and total lymph node harvest between hybrid laparoscopic RAMIE and fully robotic RAMIE (19,21).

These findings support RAMIE as a safe and effective alternative, reducing perioperative morbidity and enhancing recovery while maintaining equivalent oncologic efficacy. Its adoption has grown steadily, driven by evidence of improved perioperative outcomes and comparable oncologic results. Key advantages include reduced transfusion requirements, improved thoracic lymph node harvest, and similar rates of complications, anastomotic leaks, and 90-day mortality (17,22-25).

While numerous studies and reviews have examined the perioperative and oncologic outcomes of RAMIE, most have focused on direct comparisons with open or conventional minimally invasive approaches without fully contextualizing recent advances in robotic technology, surgical technique, and training models. Key developments—including AI-enhanced platforms, refined lymphadenectomy strategies, and structured learning curve optimization—have yet to be synthesized within a multidisciplinary framework. Furthermore, the economic implications and real-world feasibility of widespread RAMIE adoption in diverse healthcare settings remain underexplored. There is also a lack of integrated analysis comparing long-term survival, recurrence patterns, and cost-effectiveness relative to oncologic outcomes. By addressing these gaps, this review aims to provide a comprehensive update that informs surgical practice, enhances oncologic safety, and supports evidence-based decision-making in the adoption of robotic platforms for esophageal cancer surgery.

Objective

The objective of this review is to provide a comprehensive analysis of RAMIE for esophageal cancer, with a focus on its technical development, clinical outcomes, and comparative advantages over cMIE. Despite its growing adoption and demonstrated benefits, such as enhanced lymphadenectomy, reduced pulmonary complications, and improved ergonomics, RAMIE continues to face significant challenges, including a steep learning curve, high upfront costs, and limited accessibility. As robotic technology evolves to incorporate AI-guidance, improved haptics, and platform integration, there remains a pressing need for further research into its long-term oncologic efficacy, cost-effectiveness, and strategies for broader implementation. By consolidating current evidence and clinical insights, this review aims to evaluate the effectiveness of RAMIE, identify persistent barriers, and highlight opportunities for innovation. Emphasizing both current applications and emerging directions, the goal is to support multidisciplinary decision-making, refine surgical training, and ultimately optimize patient outcomes in esophageal cancer surgery. We present this article in accordance with the Narrative Review reporting checklist (available at https://aoe.amegroups.com/article/view/10.21037/aoe-25-10/rc).

Methods

A comprehensive literature search was conducted using electronic databases including PubMed, Scopus, Web of Science, Cochrane Library, and Google Scholar to identify peer-reviewed articles related to robotic-assisted minimally invasive esophagectomy (RAMIE). The search strategy incorporated a combination of Medical Subject Headings (MeSH) and free-text keywords such as “robotic esophagectomy”, “RAMIE”, “robot-assisted surgery”, “minimally invasive esophagectomy”, “esophageal cancer”, “learning curve”, “cost-effectiveness”, “lymphadenectomy”, and “oncologic outcomes”. Boolean operators (“AND”, “OR”) were used to maximize search sensitivity and specificity. No language restrictions were applied, although preference was given to studies published in English.

Studies published between 2000 and 2025 were reviewed, with inclusion criteria focusing on randomized controlled trials (RCTs), observational studies, cohort analyses, systematic reviews, meta-analyses, and expert consensus papers that discussed the technical aspects, perioperative outcomes, oncologic efficacy, learning curve, and economic considerations of RAMIE. Excluded from the analysis were non-human studies, case reports with fewer than five patients, conference abstracts without full texts, and articles not directly related to RAMIE or esophagectomy for malignant disease.

Data extracted from eligible studies included publication year, study design, patient demographics, surgical technique (fully robotic or hybrid), oncologic outcomes (R0 resection, lymph node yield, survival), perioperative outcomes (operative time, blood loss, complications), and institutional experience (volume, learning curve metrics). The findings were synthesized qualitatively to identify prevailing trends, highlight key innovations, and outline gaps in the current literature. Given the narrative nature of this review, formal quality scoring systems were not applied; however, emphasis was placed on studies with larger sample sizes, robust methodology, and relevance to contemporary surgical practice (Table 1).

Outcomes and technical considerations of RAMIE

The current literature describes three primary types of RAMIE: transhiatal [robotic-assisted transhiatal esophagectomy (RATHE)], McKeown [robotic-assisted McKeown esophagectomy (RAMKE)], and Ivor Lewis esophagectomy [robotic-assisted Ivor Lewis esophagectomy (RAILE)]. However, these procedures are often performed using hybrid approaches, making direct comparisons difficult. The degree of robotic assistance varies among institutions, with many centers integrating robotic and conventional laparoscopic or thoracoscopic techniques based on surgeon preference, patient anatomy, and institutional expertise.

Early reports of RAMKE demonstrated a morbidity rate of 29% (26). Similarly, a 3-year single-center study of RATHE reported an anastomotic leak rate of 25% and an anastomotic stricture rate of 67% (27). However, these complications decreased significantly in the latter half of the series, highlighting the impact of increasing surgical experience in RAMIE. Over time, RAMKE and RAILE have largely replaced RATHE, mirroring trends observed in cMIE. The transhiatal approach remains an option for compromised patients deemed unfit for single-lung ventilation, hostile chest due to previous operations, or an acceptable option for benign conditions, not requiring oncologic lymphadenectomy. A prospective study of 47 RAMKE cases reported an overall major morbidity rate of 46.5%, with a notable reduction in postoperative respiratory complications from 57% in OE to 33% in robotic-assisted procedures (28).

Several studies have evaluated the short-term surgical outcomes of RAMIE, assessing parameters such as operative time, blood loss, conversion rates, and postoperative complications. A study analyzing 16 robotically performed esophagectomies (8 RATHE, 5 RAILE, 3 RAMKE), found complications in 9 patients (37.5%), including anastomotic leaks (16.6%), gastric conduit complications, and cardiopulmonary events. The median hospital stay was 14 days, and while no 30-day mortality was reported, two patients died at 45 and 57 days due to complications (29). The study highlighted that robotic assistance was particularly beneficial for mediastinal dissection in transhiatal esophagectomy and that a hand-sewn robotic anastomosis in the prone position was a feasible technique for RAILE.

Another study reported a mean operative time of 267 minutes, minimal blood loss, and an average hospital stay of 10 days for RATHE. Complications occurred in 50% of cases, including anastomotic leaks (33%), thoracic duct injury, vocal cord paralysis, pleural effusion, and atrial fibrillation. No perioperative deaths were reported, and a 22-month follow-up indicated that 61% of patients remained disease-free (30).

There is currently limited data on long-term cancer survival following RAMIE. However, available evidence suggests that RAMIE achieves high rates of oncologic adequacy in terms of resection margins. Reports indicate a 97.6% R0 resection rate with hybrid RAMKE, demonstrating a high level of surgical precision (31). For RAILE, multiple studies have shown R0 resection rates ranging from 90% to 100%, comparable to or even exceeding those of conventional techniques (32-35).

A study evaluating the long-term outcomes of RAILE in 112 patients, including 76.4% after neoadjuvant chemoradiotherapy demonstrated the 30-, 60-, and 90-day mortality rates of 0.9%, 2.7%, and 3.6%, respectively. Long-term oncologic outcomes were comparable to non-robotic esophagectomy approaches, demonstrating OS of 81.4%, 60.5%, and 51.0%, while DFS was 75.3%, 42.3%, and 44.0% at 1, 3, and 5 years respectively (36). The study concluded that RAILE provides similar long-term outcomes to other esophagectomy techniques while offering the potential benefits of robotic assistance, including improved visualization and precision.

Technical refinements and learning curve

The adoption of RAMIE has led to significant advancements in surgical precision, exposure, and lymphadenectomy. However, the procedure presents a steep learning curve due to its innate complexity, necessitating structured training, iterative technical refinements, and a comprehensive understanding of perioperative risk factors to optimize outcomes. Numerous studies have examined the progressive improvements in efficiency and safety associated with RAMIE, emphasizing the critical role of surgeon experience, multidisciplinary team coordination, and case volume in achieving optimal results.

In a retrospective review of hybrid RAILE, all patients achieved R0 resection, with a median lymph node harvest of 18 and minimal blood loss. Initially, a stapled posterior and hand-sewn anterior anastomosis was used, resulting in high morbidity, including one anastomotic leak. However, a transition to a two-layer, completely hand-sewn anastomosis eliminated anastomotic leaks and major complications. There were no 30- or 90-day mortalities, demonstrating that refinements in esophageal retraction, conduit advancement, and suture techniques significantly improve patient outcomes (37).

A single-institution experience with four-arm RAMIE (17 RAILE, 4 RAMKE) further highlighted the challenges of early adoption. While R0 resection was achieved in 81% of cases and 76% of patients received neoadjuvant therapy, the median operative time of 556 minutes, decreasing to 414 minutes as surgical proficiency improved. Blood loss averaged 307 mL, and the median hospital stay was 10 days. The conversion rate to open surgery was 24%, with 24% of patients experiencing major complications, including clinically significant anastomotic leaks (14%) and gastrobronchial fistulas (9.5%). The study emphasized that while RAMIE enhances exposure and technical control, its successful implementation requires structured training, proactive complication management, and refinements in airway protection techniques (38).

A prospective study analyzing RAMIE outcomes in 52 patients found that surgical proficiency, measured by operative time, improved significantly after 20 cases (514±106 vs. 397±71.9 min, P<0.005). Notably, none of the cases required conversion to open thoracotomy, and no complications were reported in the final 10-patient cohort, illustrating substantial improvements in outcomes with increasing experience (39). Similarly, studies on fully robotic RAMIE demonstrated that significant reductions in operative time occur between 30 and 45 cases, with peak efficiency typically achieved between cases 40 and 45. Conversion rates declined from 13% in the first 50 cases to just 2% in the subsequent 50 cases, underscoring the impact of technical proficiency and team coordination (32).

The overall learning curve for RAMIE remains a subject of debate. Some studies suggest that robotic technology enables surgeons to reach proficiency in as few as 20 cases, while others report that a more extensive experience of up to 70 cases is required, particularly for fully robotic RAMIE under structured proctoring (31,39,40). The influence of prior thoracoscopic experience is particularly relevant, as demonstrated in a study evaluating 72 consecutive robotic McKeown esophagectomy cases. Surgeons experienced in thoracolaparoscopic esophagectomy required approximately 26 cases to achieve early proficiency, with significant reductions in operative and console times occurring at the 26th case. Stomach mobilization proficiency was reached after 14 cases, while thoracic and abdominal docking times improved earlier, achieving optimal efficiency after nine and 16 cases, respectively (41).

A comparative study further analyzed the impact of prior thoracoscopic experience on RAMIE learning curves. A surgeon with over 150 video-assisted thoracic surgery (VATS) cases before transitioning to robotic surgery demonstrated a rapid reduction in recurrent laryngeal nerve (RLN) palsy rates at case 31 (32.3% to 4.2%, P<0.001) while maintaining stable lymph node retrieval rates. In contrast, a surgeon with minimal previous cMIE experience but prior assistance in 50 robotic esophagectomies exhibited a bimodal learning curve, with RLN palsy rates improving at cases 15 and 49 but experiencing fluctuations in lymph node harvest. These findings suggest that extensive thoracoscopic experience significantly shortens the learning curve for robotic esophagectomy, facilitating a more stable balance between oncologic thoroughness and RLN protection. Conversely, limited cMIE experience may initially lead to trade-offs between lymph node dissection and nerve preservation. Structured training programs integrating both thoracoscopic and robotic techniques are essential for optimizing outcomes and minimizing complications in robotic esophageal surgery (42).

The learning curve for RAILE was further analyzed in a retrospective study of 124 consecutive cases performed by a single surgeon. Risk-adjusted cumulative sum analysis identified two distinct phases: an initial learning phase (cases 1–51) and a proficiency phase (cases 52–124). Transitioning from the initial to the proficiency phase resulted in a significant reduction in major complications (37.3% to 17.8%, P=0.017), total operative time (330.9±55.6 to 267.3±39.1 min, P<0.001), and hospital length of stay {10 [interquartile range (IQR), 9–14] to 9 (IQR, 8–11 days), P=0.034}. The study demonstrated that while proficiency in the abdominal phase was reached after 39 cases, thoracic proficiency required 55 cases, blood loss stabilized after 63 cases, and lymph node yield optimization occurred at 73 cases (43). These findings highlight that the RAMIE learning curve extends beyond just operative time, underscoring the importance of complication-based learning curve assessments and structured training programs to ensure safe adoption in high-volume centers.

A propensity score-matched study compared the perioperative outcomes and learning curve of RAMKE vs. cMIE at a single center. After matching 43 patient pairs, RAMKE demonstrated significantly improved oncologic outcomes, with a higher total lymph node harvest (median 29 vs. 26, P=0.011), upper mediastinal lymph nodes (median 8 vs. 6, P<0.001), and left RLN lymph nodes (median 4 vs. 2, P=0.001). The cumulative sum (CUSUM)-based learning curve analysis revealed that surgeons required at least 20 cases to achieve proficiency, as indicated by a reduction in operative time and an increase in lymph node harvest. With increased experience, further improvements were observed, including a higher yield of upper mediastinal (median 9 vs. 6, P=0.001), left (median 5 vs. 3.5, P=0.003) and right (median 4 vs. 2, P=0.002) RLN lymph nodes, while the incidence of postoperative pneumonia significantly decreased from 25% to 4% (P=0.04) (44). These findings suggest that experienced cMIE surgeons require at least 20 RAMKE cases to reach proficiency, with potential benefits in oncologic outcomes and postoperative recovery.

A systematic review and meta-analysis across 41 studies (7,755 patients) confirmed that the pooled number of cases needed to reach proficiency was 34.6 for hybrid cMIE, 68.5 for total cMIE, 27.5 for hybrid RAMIE, and 35.9 for total RAMIE. Notably, total RAMIE had a significantly lower proficiency threshold than total cMIE [incidence rate ratio (IRR): 0.52, P=0.032], suggesting that robotic platforms facilitate a shorter learning curve. The study also emphasized the importance of standardized learning curve analysis, improved reporting of prior surgical experience, and long-term oncologic outcomes to refine training protocols in MIE (45).

A registry-based study of 3,192 RAMIE cases demonstrated increasing adoption of fully robotic techniques, stable lymph node yields, improved anastomotic leak rates, and higher textbook outcomes over time, indicating that RAMIE continues to evolve, with ongoing refinements contributing to improved perioperative efficiency and patient outcomes (46).

Cost considerations and feasibility

One of the major challenges to the widespread adoption of RAMIE is its cost. A study evaluating the impact of robotics in thoracic surgery at an academic institution found that while robotic procedures were associated with a 9% higher direct cost compared to non-robotic surgeries, the total cost difference was only 3.6%, indicating that other factors may offset the initial investment. Importantly, robotic procedures resulted in shorter hospital stays, fewer complications, and lower conversion rates, contributing to potential cost savings in the range of $1 million to $2 million when compared to traditional open or endoscopic approaches. However, the study also highlighted that robotic surgery remains financially viable only when hospitals strategically allocate resources to high-acuity inpatient procedures with a high case mix index (CMI), as outpatient robotic procedures were found to be financially unfavorable due to inadequate reimbursement (47).

A comparative study evaluating RATHE against non-robotic transhiatal esophagectomy (including open and laparoscopic approaches) found that while RATHE resulted in significantly lower blood loss (150 vs. 300 mL, P=0.0001) and fewer conversions to OE (8% vs. 46%, P=0.004), it required a significantly longer operative time (327 vs. 213 min, P=0.0001) and was associated with higher hospital charges ($197,405 vs. $159,588, P=0.31), while the median cost of care was $34,822 for robotic vs. $23,939 for non-robotic (P=0.47). Additionally, payments received were lower for RATHE ($14,365) compared to non-robotic ($28,080, P=0.35), and overall profitability was similar, with only 15% of robotic and 13% of non-robotic cases generating profit. These findings suggest that while RATHE offers distinct technical advantages, its economic viability remains uncertain, warranting further evaluation of its long-term cost-effectiveness (48).

A similar cost-effectiveness analysis comparing RAMIE and cMIE in a high-volume referral center found that although RAMIE incurred higher surgical costs ($13,370 vs. $10,864, P<0.001), total hospitalization costs ($32,951 vs. $31,214, P=0.460) and daily costs ($2,184 vs. $1,963, P=0.246) were not significantly different between the two groups. The study identified key cost drivers, including intensive care unit (ICU) readmission [hazard ratio (HR) =7.0], prolonged hospital stay (HR =13.5), anastomotic leak (HR =17.0), and postoperative pneumonia (HR =5.4), all of which were independently associated with increased costs. Despite the longer operative duration for RAMIE (421 vs. 372 min, P<0.001), oncologic outcomes, such as lymph node yield (34 vs. 32, P=0.177) and R0 resection rates (95% vs. 94%), remained comparable. Notably, RAMIE was associated with a lower incidence of postoperative pneumonia (8% vs. 25%, P=0.029) and a trend toward shorter hospital stays (15 vs. 17 days, P=0.205), suggesting that while RAMIE carries higher intraoperative costs, its potential to reduce postoperative complications and shorten hospitalization may offset overall healthcare expenditures (49). Further studies are needed to assess the long-term oncologic and economic impact of RAMIE, particularly in high-volume centers where enhanced surgical efficiency may improve cost-effectiveness.

A broader financial analysis of robotic esophagectomy, based on a prospective study of 85 patients undergoing RATHE, found no significant differences in total hospital costs between Medicare and privately insured patients ($49,186 vs. $45,763, P=0.78), variable costs ($27,098 vs. $25,149, P=0.74), fixed direct costs ($6,840 vs. $6,800, P=0.99), or hospital reimbursement ($30,872 vs. $34,181, P=0.83). However, hospitals experienced greater financial losses when treating Medicare patients (−$22,600 vs. −$13,432, P=0.07), though this did not reach statistical significance. Despite Medicare patients being older and having a higher prevalence of prior abdominal or thoracic surgeries, hospitalization costs and reimbursements were similar between groups, suggesting that robotic surgery may help mitigate historical cost disparities associated with Medicare. However, further multicenter studies are needed to validate these findings and assess the broader financial impact of RAMIE across different healthcare systems (50).

The long-term economic feasibility of RAMIE is also influenced by hospital reimbursement models and institutional adoption rates. While robotic surgery introduces higher initial costs, including platform acquisition, maintenance, and instrument replacement, its potential to reduce postoperative complications such as pneumonia and anastomotic leaks may help balance these costs by lowering readmission rates and ICU utilization. Additionally, as robotic technology continues to evolve, advancements such as AI-assisted surgical planning and next-generation platforms like the DV5 system are expected to enhance operative efficiency, reduce surgical time, and improve overall cost-effectiveness. Future research should explore RAMIE within value-based care models, where cost-containment strategies and optimized surgical pathways may further enhance its role in esophageal cancer treatment. A comprehensive economic assessment incorporating both short- and long-term outcomes is necessary to determine whether RAMIE represents a financially sustainable alternative to traditional esophagectomy techniques.

Comparative outcomes of robotic-assisted and cMIE

Recent studies have compared RAMIE with cMIE to assess its feasibility, safety, and effectiveness. While robotic technology offers potential advantages such as improved dexterity, greater instrument articulation, and enhanced 3D visualization, concerns remain regarding longer operative times, the learning curve, and cost-effectiveness. Research has focused on evaluating short-term outcomes, including operative time, intraoperative blood loss, complication rates, anastomotic integrity, and postoperative recovery. Additionally, oncologic outcomes such as lymph node harvest and R0 resection rates have been examined to determine whether RAMIE offers any meaningful advantage over conventional approaches. Given the increasing adoption of robotic-assisted surgery worldwide, a comprehensive analysis of the comparative benefits and limitations of RAMIE vs. cMIE is essential to guide clinical decision-making. This section synthesizes current evidence to provide insights into perioperative and postoperative outcomes, addressing whether RAMIE represents a superior alternative to cMIE in modern esophageal surgery.

Short-term outcomes and perioperative morbidity

A retrospective study by Weksler et al. comparing RAMIE with cMIE found no significant differences in operative time, blood loss, number of resected lymph nodes, postoperative complications, hospital stay, or ICU duration. While RAMIE was deemed feasible and safe, it did not demonstrate clear advantages over cMIE, underscoring the need for further investigation into its potential benefits (51).

A subsequent analysis of data from the American College of Surgeons National Surgical Quality Improvement Program reviewed 725 cases, including 100 RAMIE and 625 cMIE procedures. Mortality rates (2.3% vs. 2.2%) and overall morbidity (31% vs. 39.2%) were comparable between the two techniques. No significant differences were found in pulmonary complications, anastomotic leaks, unplanned conversion to open surgery, readmission, or reoperation rates, though RAMIE was associated with longer operative times (52).

Other studies evaluating different MIE techniques, including thoracoscopic/laparoscopic, transhiatal, and robotic-assisted Ivor Lewis approaches, reported that RAMIE had the longest operative time but resulted in lower estimated blood loss, fewer pulmonary complications, and reduced rates of anastomotic leaks (53). A single-institution study comparing RAMIE and VATS in 162 patients found that RAMIE was associated with significantly fewer complications (31.4% vs. 73.2%), including lower rates of RLN paralysis, atelectasis, pleural effusion, arrhythmia, and dysphagia. While postoperative hospital stays were slightly shorter in the RAMIE group, the difference was not statistically significant (54).

A retrospective analysis of 87 patients found that RAMIE had a significantly longer thoracic phase operative time but no significant differences in blood loss or mediastinal lymph node dissection. RAMIE patients had a lower, though not statistically significant, incidence of RLN paralysis and postoperative pneumonia. However, RAMIE was associated with significantly better postoperative swallowing function, earlier initiation of oral intake, and shorter hospital stays (55).

A nationwide review of 2,786 esophagectomy patients, 8.4% of whom underwent RAMIE, found similar pulmonary complication rates, anastomotic leak rates, and 30-day mortality between RAMIE and cMIE. However, RAMIE was associated with a lower overall morbidity rate (56). A broader analysis of esophagectomy trends in the U.S. between 2015 and 2019 reviewed 10,607 cases, of which 54.3% underwent OE, 33.2% cMIE, and 12.4% RAMIE. Over 5 years, the use of MIE and RAMIE increased, with RAMIE cases rising from 1% to 18%. Although RAMIE was associated with a higher rate of anastomotic leaks, it achieved superior R0 resection rates and lymph node harvest. A propensity-matched analysis confirmed an increased risk of anastomotic leaks in RAMIE but found no significant differences in length of stay or operative mortality (57).

Systematic reviews and meta-analyses comparing RAMIE and cMIE have confirmed key perioperative differences reported in individual studies, highlighting both advantages and limitations of robotic technology. While both approaches exhibit comparable safety and feasibility, RAMIE consistently demonstrates advantages in reducing intraoperative blood loss and pulmonary complications, particularly pneumonia with an odds ratio (OR) of 0.46 [95% confidence interval (CI): 0.35–0.61, P<0.0001] (58-66). Specifically, RAMIE results in significantly lower estimated intraoperative blood loss compared to cMIE (58,62,64,66-68). This reduction may be attributed to the robotic platform’s enhanced precision, improved instrument stability, and tremor filtration, allowing for meticulous dissection and minimized collateral tissue damage. Enhanced 3D visualization and superior hemostatic control further contribute to this benefit. Additionally, the reduction in pulmonary complications may be linked to decreased operative trauma and a lower systemic inflammatory response due to the minimally invasive nature of robotic surgery.

Across multiple analyses, there were no significant differences between RAMIE and cMIE in terms of overall short-term outcomes, including anastomotic leak rates, conversion to open surgery, RLN palsy, chyle leak, cardiac complications, infectious complications, or 30- and 90-day mortality (58,59,61-69). While some studies suggested that RAMIE patients experience shorter hospital stays (58,60), others found no statistically significant difference in length of stay between the two techniques (59,66,68,69).

Anastomotic leak remains one of the most concerning postoperative complications following esophagectomy, with reported rates ranging between 7% and 9% for both RAMIE and cMIE (58,60-62,64-66,69). Since anastomotic leaks are strongly associated with increased morbidity, prolonged hospitalization, higher mortality and even oncologic outcomes, minimizing this risk is a critical goal in surgical innovation (70,71). However, current evidence suggests that RAMIE does not confer a significant reduction in anastomotic leak rates compared to cMIE (60-62,64-66,69). While the robotic platform provides greater dexterity, particularly in facilitating precise hand-sewn anastomotic techniques, studies have not consistently demonstrated a meaningful decrease in leak rates with RAMIE. Moreover, one systematic review and meta-analysis of 18,187 patients found that anastomotic leak rates were significantly lower in cMIE compared to RAMIE [relative risk (RR) =1.23, P<0.001] (58).

RAMIE has been associated with a lower overall morbidity rate compared to cMIE, with an OR of 0.67 (95% CI: 0.58–0.79, P<0.001) (61,66-68). However, despite this reduction in morbidity, there was no significant difference in 30- and 90-day mortality rates between the two techniques, suggesting that while RAMIE may reduce perioperative complications, these benefits do not necessarily translate into improved early survival outcomes (58-62,64-66,68,69).

Despite these advantages, RAMIE is consistently associated with longer operative times than cMIE, with robotic procedures taking an average of 30–60 minutes longer (58,61-64,66). This extended duration is likely due to the steep learning curve associated with robotic surgery, as well as the additional setup and docking time required for robotic systems. While experienced robotic surgeons may be able to mitigate some of these time constraints, prolonged operative times remain a key limitation of RAMIE, particularly in high-volume surgical centers.

Oncologic outcomes and long-term survival

The oncologic efficacy of RAMIE compared to cMIE has been extensively studied, particularly concerning lymph node harvest, R0 resection rates, and long-term survival. While RAMIE appears to enhance lymphadenectomy, especially in challenging anatomic regions, its impact on oncologic outcomes, including recurrence and survival, remains inconclusive. Most comparative studies report similar overall recurrence rates between RAMIE and cMIE. However, several reports have noted a trend toward reduced locoregional (mediastinal) recurrence in RAMIE cohorts, potentially reflecting the improved visualization and dissection capabilities of the robotic platform. By contrast, rates of distant recurrence, including liver and lung metastases, appear equivalent between approaches.

A study comparing RAMIE and cMIE in 105 patients (62 RAMIE, 43 cMIE) found comparable operative times (490 vs. 458 min, P=0.118) and blood loss (462.9 vs. 466.8 mL, P=0.96). Lymphadenectomy outcomes favored RAMIE, with significantly more lymph nodes harvested overall (37.3 vs. 28.7, P=0.003), particularly in the upper mediastinum (10.7 vs. 6.3, P=0.03) and abdominal region (12.2 vs. 7.8, P=0.007). Despite the increased lymph node yield, 5-year OS was similar between RAMIE (69%) and cMIE (59%, P=0.73). While locoregional recurrence was lower in the RAMIE group (12% vs. 26%), this difference was not statistically significant, suggesting that superior lymphadenectomy does not necessarily translate into improved survival outcomes (72).

A study comparing robotic-assisted and minimally invasive (robotic-assisted and laparoscopic) transhiatal esophagectomy (MTHE) found no significant differences in lymph node yield (13.9 vs. 14.3, P=0.90), R0 resection rates (94.4% in both groups), or perioperative mortality (one death in the laparoscopic group, none in the robotic group). These findings suggest that robotic-assisted transhiatal esophagectomy (THE) is oncologically noninferior to its laparoscopic counterpart, providing similar perioperative outcomes, lymph node retrieval, and margin status (73).

A propensity score-matched study comparing RAMKE and cMIE (thoraco-laparoscopic) McKeown esophagectomy in 721 patients (310 RAMKE, 411 MIMKE) found that RAMIE resulted in significantly higher retrieval of left RLN lymph nodes (2.27±0.90 vs. 2.09±0.79, P=0.01) and thoracic lymph nodes (12.60±4.22 vs. 11.83±3.12, P=0.01). However, the total number of harvested lymph nodes was comparable between groups. No significant differences were observed in OS or DFS, and recurrence rates were similar (11.7% vs. 12.9%, P=0.67). A trend toward lower mediastinal lymph node recurrence was noted in the RAMKE group (2.5% vs. 5.4%, P=0.07), suggesting a potential advantage in reducing locoregional recurrence, though its clinical significance remains uncertain (74).

Another retrospective study comparing RAMIE and cMIE reported that RAMIE yielded significantly more lymph nodes, particularly in the mediastinum, with an average of 20 harvested compared to 17 in cMIE (75).

A propensity-matched study conducted at a high-volume center over 7 years found no significant differences in OS or DFS between RAMIE and cMIE. Among 246 patients (65 RAMIE, 181 cMIE), complete resection rates were comparable (99% vs. 96%, P=0.68), with no differences in in-hospital (P=0.89), 30-day (P=0.66), or 90-day mortality (P=0.73). However, RAMIE was associated with a higher median lymph node yield (32 vs. 29, P=0.02), which may contribute to improved oncologic staging (76).

An analysis of the National Cancer Database (NCDB) from 2010 to 2017, which included 1,845 patients with stage 0–III esophageal cancer (428 RAMIE, 1,417 cMIE), found that RAMIE was associated with significantly improved OS compared to cMIE, with an HR for mortality of 1.19 (P=0.04) for cMIE relative to RAMIE. Patients treated at academic medical centers had a lower risk of mortality (HR =0.84, P<0.001). Although RAMIE patients experienced a longer delay from diagnosis to surgery, they had a higher median lymph node harvest, potentially improving oncologic outcomes. These findings suggest that RAMIE may offer superior long-term oncologic benefits, particularly when performed at high-volume centers with greater access to multidisciplinary care (77).

Large-scale systematic reviews have confirmed that both RAMIE and cMIE provide comparable oncologic outcomes, with no significant disparities in R0 resection rates or overall morbidity. Several studies have demonstrated that RAMIE is associated with a significantly higher total lymph node yield compared to cMIE, particularly in the abdominal region and along the left RLN (58-61,63,65,67). This increased lymph node retrieval may be attributed to the robotic platform’s enhanced dexterity, improved visualization, and greater precision, allowing for meticulous dissection in anatomically challenging areas. Specifically, studies utilizing propensity score-matched analyses have confirmed that RAMIE yields more thoracic lymph nodes and RLN lymph nodes compared to cMIE, potentially improving nodal staging accuracy (74). However, while RAMIE has been associated with a trend toward reduced mediastinal lymph node recurrence, overall recurrence rates remain comparable between the two techniques (59,62,63).

Despite the observed differences in lymph node harvest, meta-analyses have not consistently demonstrated a significant advantage of RAMIE over cMIE in terms of R0 resection rates. Some studies suggest that RAMIE achieves a higher rate of complete tumor resection, supporting its potential role in optimizing oncologic clearance, with Manigrasso et al. reporting a significantly higher R0 resection rate for RAMIE compared to cMIE (OR =1.420, P=0.04) (63), and Angeramo et al. further demonstrating that RAMIE had significantly greater odds of achieving an R0 resection (OR =2.84; 95% CI: 1.53–5.26; P<0.001) (66), suggesting superior oncologic clearance with the robotic approach; however, other studies indicate no significant differences between the two techniques (61,64,65,68,69). These mixed findings suggest that while robotic technology may facilitate more precise dissections, R0 resection outcomes largely depend on surgeon expertise and case complexity rather than surgical modality alone.

Long-term survival outcomes between RAMIE and cMIE remain comparable. Three-year OS rates have been found to be similar across multiple studies, while some reports indicate that RAMIE may confer a higher 3-year DFS rate (59,62). However, systematic reviews and large-scale meta-analyses have not confirmed a clear survival advantage for RAMIE, suggesting that while improved lymphadenectomy may enhance staging accuracy, it does not necessarily translate into better long-term oncologic outcomes (59,62,63,65). Further prospective data with detailed recurrence mapping are needed to clarify the true oncologic impact of robotic techniques.

RCTs comparing RAMIE and cMIE

The RAMIE trial was a multicenter randomized controlled study designed to compare RAMIE and cMIE in patients with resectable esophageal squamous cell carcinoma (SCC). Conducted across six high-volume centers in China between August 2017 and December 2019, the trial evaluated perioperative and long-term oncologic outcomes to determine whether RAMIE confers advantages over cMIE in surgical and postoperative metrics.

The findings demonstrated that RAMIE was associated with significantly shorter operative times compared to cMIE (203.8 vs. 244.9 min, P<0.001). Additionally, RAMIE achieved superior thoracic lymph node dissection, particularly in patients who had undergone neoadjuvant therapy (15 vs. 12 nodes, P=0.01). The left RLN dissection rate was also significantly higher in the RAMIE group (79.5% vs. 67.6%, P=0.001), indicating improved precision in lymphadenectomy. However, both techniques demonstrated comparable rates of R0 resection, blood loss, and conversion to open surgery, suggesting equivalent oncologic clearance.

Postoperative complication rates were similar between the two groups, with 48.6% in RAMIE vs. 41.8% in cMIE (P=0.19). There were no significant differences in major complications, anastomotic leaks, pulmonary complications, or 90-day mortality (0.6% in both groups). Although the incidence of vocal cord paralysis was slightly higher in the RAMIE group (32.6% vs. 27.1%, P=0.25), this difference was not statistically significant.

The study concluded that both RAMIE and cMIE are safe and feasible approaches for treating esophageal SCC, with RAMIE offering distinct advantages in operative efficiency and lymph node dissection, particularly in patients receiving neoadjuvant therapy. However, long-term oncologic outcomes remain to be determined, warranting extended follow-up to assess recurrence patterns and survival benefits.

Several ongoing RCTs are further investigating the comparative benefits of RAMIE and cMIE in esophageal cancer treatment. The ROBOT-2 trial is a multicenter RCT designed to compare RAMIE and cMIE in patients with resectable esophageal adenocarcinoma. The primary objective of this trial is to determine whether RAMIE results in a higher lymph node yield in both the abdominal and mediastinal regions compared to cMIE. Secondary outcomes being assessed include postoperative complications, length of hospital stay, mortality rates, pathology results, survival rates, operative time, cost-effectiveness, and surgeon fatigue. This trial is currently recruiting patients across multiple centers in Germany, the Netherlands, and Switzerland and is expected to provide critical insights into the oncologic and perioperative advantages of RAMIE over conventional approaches.

Another ongoing study, the REVATE trial, is a multicenter, open-label RCT being conducted in Taiwan, Shanghai and Tianjin. This trial focuses on esophageal SCC and aims to evaluate whether RAMIE improves lymph node dissection along the left RLN. The study has enrolled 212 patients, who are randomized 1:1 to either RAMIE or cMIE. The primary outcome of the REVATE trial is the rate of unsuccessful left RLN lymphadenectomy, defined as either failure to remove RLN nodes or permanent RLN palsy lasting more than 6 months. Secondary outcomes include the total number of RLN nodes retrieved, postoperative complications, hospital stay duration, 30- and 90-day mortality rates, quality of life, and long-term oncologic outcomes. If successful, this study could provide strong evidence supporting the broader adoption of RAMIE for SCC and influence future surgical practice guidelines by demonstrating its advantages in precision and oncologic effectiveness.

These trials will play a pivotal role in determining whether RAMIE offers superior oncologic and functional outcomes compared to cMIE and will guide its future integration into clinical practice for the surgical management of esophageal cancer.

Strengths and limitations

This review provides a comprehensive and up-to-date synthesis of RAMIE, incorporating recent evidence from RCTs, large-scale registry analyses, and contemporary comparative studies with cMIE. By integrating perioperative, oncologic, technical, economic, and training-related dimensions, this work offers a holistic perspective on the clinical and practical implications of RAMIE. Additionally, the review offers a detailed evaluation of the RAMIE learning curve, including complication-based proficiency assessments and the impact of prior surgical experience, thus providing a nuanced interpretation that goes beyond procedural metrics. The inclusion of structured comparisons with cMIE across multiple outcome domains further strengthens the clinical relevance of this analysis, supporting evidence-based decision-making for surgeons, trainees, and institutional stakeholders.

However, several limitations should be acknowledged. First, the narrative design of this review limits the ability to perform meta-analytic assessments or quantitative pooling of outcomes. Second, despite a comprehensive literature search, selection bias may have been introduced by prioritizing English-language publications and studies with larger sample sizes. Third, the current body of literature is heterogeneous with respect to patient selection, surgical technique (hybrid vs. fully robotic), and outcome definitions, which may affect the generalizability of findings. Finally, long-term survival and cost-effectiveness data remain limited, particularly from prospective multicenter studies, underscoring the need for future high-quality research to validate the trends and hypotheses discussed herein.

Conclusions

The evolution of MIE has transformed esophageal cancer surgery, reducing surgical trauma while maintaining oncologic outcomes. RAMIE enhances visualization, precision, and instrument articulation, overcoming limitations of conventional approaches and accelerating adoption.

A key advantage of RAMIE is improved ergonomics, reducing surgeon fatigue by enabling seated operation with superior dexterity and 3D visualization. Its intuitive controls and streamlined learning curve make training more accessible, supported by industry-driven robotic programs. The reduced physical strain also extends surgeon careers, ensuring continuity of expertise and improved patient outcomes. RAMIE may be particularly beneficial in selected clinical scenarios, including patients with obesity, dense mediastinal fibrosis, recurrent or anatomically complex disease, and tumors requiring meticulous dissection near the aortic arch or RLNs.

While RAMIE offers benefits such as improved lymph node harvest and decreased pulmonary complications, challenges remain, including cost and long-term oncologic efficacy. However, innovations like AI integration and next-generation platforms, such as the DV5 system with haptic feedback and enhanced motion scaling, promise greater efficiency. RAMIE may offer greater value in high-volume centers where structured training, team familiarity, and procedural efficiency can help mitigate its learning curve and cost implications. As technology advances, RAMIE may become the standard for MIE, but further studies are needed to confirm its long-term benefits and cost-effectiveness.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://aoe.amegroups.com/article/view/10.21037/aoe-25-10/rc

Peer Review File: Available at https://aoe.amegroups.com/article/view/10.21037/aoe-25-10/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://aoe.amegroups.com/article/view/10.21037/aoe-25-10/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Siegel RL, Giaquinto AN, Jemal A. Cancer statistics, 2024. CA Cancer J Clin 2024;74:12-49. [Crossref] [PubMed]
2. Iriarte F, Su S, Petrov RV, et al. Surgical Management of Early Esophageal Cancer. Surg Clin North Am 2021;101:427-41. [Crossref] [PubMed]
3. Mertens AC, Kalff MC, Eshuis WJ, et al. Transthoracic Versus Transhiatal Esophagectomy for Esophageal Cancer: A Nationwide Propensity Score-Matched Cohort Analysis. Ann Surg Oncol 2021;28:175-83. [Crossref] [PubMed]
4. Witek TD, Melvin TJ, Luketich JD, et al. Open, Minimally Invasive, and Robotic Approaches for Esophagectomy: What Is the Approach Algorithm? Thorac Surg Clin 2020;30:269-77. [Crossref] [PubMed]
5. Fajardo R, Abbas AE, Petrov RV, et al. Salvage Esophagectomy. Surg Clin North Am 2021;101:467-82. [Crossref] [PubMed]
6. Biere SS, van Berge Henegouwen MI, Maas KW, et al. Minimally invasive versus open oesophagectomy for patients with oesophageal cancer: a multicentre, open-label, randomised controlled trial. Lancet 2012;379:1887-92. [Crossref] [PubMed]
7. Luketich JD, Pennathur A, Awais O, et al. Outcomes after minimally invasive esophagectomy: review of over 1000 patients. Ann Surg 2012;256:95-103. [Crossref] [PubMed]
8. Luketich JD, Pennathur A, Franchetti Y, et al. Minimally invasive esophagectomy: results of a prospective phase II multicenter trial-the eastern cooperative oncology group (E2202) study. Ann Surg 2015;261:702-7. [Crossref] [PubMed]
9. Straatman J, van der Wielen N, Cuesta MA, et al. Minimally Invasive Versus Open Esophageal Resection: Three-year Follow-up of the Previously Reported Randomized Controlled Trial: the TIME Trial. Ann Surg 2017;266:232-6. [Crossref] [PubMed]
10. Mariette C, Markar S, Dabakuyo-Yonli TS, et al. Health-related Quality of Life Following Hybrid Minimally Invasive Versus Open Esophagectomy for Patients With Esophageal Cancer, Analysis of a Multicenter, Open-label, Randomized Phase III Controlled Trial: The MIRO Trial. Ann Surg 2020;271:1023-9. [Crossref] [PubMed]
11. van der Sluis PC, Babic B, Uzun E, et al. Robot-assisted and conventional minimally invasive esophagectomy are associated with better postoperative results compared to hybrid and open transthoracic esophagectomy. Eur J Surg Oncol 2022;48:776-82. [Crossref] [PubMed]
12. van Workum F, Stenstra MHBC, Berkelmans GHK, et al. Learning Curve and Associated Morbidity of Minimally Invasive Esophagectomy: A Retrospective Multicenter Study. Ann Surg 2019;269:88-94. [Crossref] [PubMed]
13. Sihag S, Kosinski AS, Gaissert HA, et al. Minimally Invasive Versus Open Esophagectomy for Esophageal Cancer: A Comparison of Early Surgical Outcomes From The Society of Thoracic Surgeons National Database. Ann Thorac Surg 2016;101:1281-8; discussion 1288-9. [Crossref] [PubMed]
14. Claassen L, van Workum F, Rosman C. Learning curve and postoperative outcomes of minimally invasive esophagectomy. J Thorac Dis 2019;11:S777-85. [Crossref] [PubMed]
15. van der Sluis PC, Tagkalos E, Hadzijusufovic E, et al. Robot-Assisted Minimally Invasive Esophagectomy with Intrathoracic Anastomosis (Ivor Lewis): Promising Results in 100 Consecutive Patients (the European Experience). J Gastrointest Surg 2021;25:1-8. [Crossref] [PubMed]
16. Watson J, Reddy RM. Robot-Assisted-Minimally Invasive-Transhiatal Esophagectomy (RAMI-THE). Surg Oncol Clin N Am 2024;33:497-508. [Crossref] [PubMed]
17. van der Sluis PC, van der Horst S, May AM, et al. Robot-assisted Minimally Invasive Thoracolaparoscopic Esophagectomy Versus Open Transthoracic Esophagectomy for Resectable Esophageal Cancer: A Randomized Controlled Trial. Ann Surg 2019;269:621-30. [Crossref] [PubMed]
18. Esagian SM, Ziogas IA, Skarentzos K, et al. Robot-Assisted Minimally Invasive Esophagectomy versus Open Esophagectomy for Esophageal Cancer: A Systematic Review and Meta-Analysis. Cancers (Basel) 2022;14:3177. [Crossref] [PubMed]
19. Babic B, Müller DT, Jung JO, et al. Robot-assisted minimally invasive esophagectomy (RAMIE) vs. hybrid minimally invasive esophagectomy: propensity score matched short-term outcome analysis of a European high-volume center. Surg Endosc 2022;36:7747-55. [Crossref] [PubMed]
20. Grimminger PP, Staubitz JI, Perez D, et al. Multicenter Experience in Robot-Assisted Minimally Invasive Esophagectomy - a Comparison of Hybrid and Totally Robot-Assisted Techniques. J Gastrointest Surg 2021;25:2463-9. [Crossref] [PubMed]
21. Jung JO, de Groot EM, Kingma BF, et al. Hybrid laparoscopic versus fully robot-assisted minimally invasive esophagectomy: an international propensity-score matched analysis of perioperative outcome. Surg Endosc 2023;37:4466-77. [Crossref] [PubMed]
22. de Groot EM, van der Horst S, Kingma BF, et al. Robot-assisted minimally invasive thoracolaparoscopic esophagectomy versus open esophagectomy: long-term follow-up of a randomized clinical trial. Dis Esophagus 2020;33:doaa079. [Crossref] [PubMed]
23. Na KJ, Kang CH, Park S, et al. Robotic esophagectomy versus open esophagectomy in esophageal squamous cell carcinoma: a propensity-score matched analysis. J Robot Surg 2022;16:841-8. [Crossref] [PubMed]
24. Sarkaria IS, Rizk NP, Goldman DA, et al. Early Quality of Life Outcomes After Robotic-Assisted Minimally Invasive and Open Esophagectomy. Ann Thorac Surg 2019;108:920-8. [Crossref] [PubMed]
25. Weindelmayer J, De Pasqual CA, Turolo C, et al. Robotic versus open Ivor-Lewis esophagectomy: A more accurate lymph node dissection without burdening the leak rate. J Surg Oncol 2023;127:1109-15. [Crossref] [PubMed]
26. Kernstine KH, DeArmond DT, Shamoun DM, et al. The first series of completely robotic esophagectomies with three-field lymphadenectomy: initial experience. Surg Endosc 2007;21:2285-92. [Crossref] [PubMed]
27. Dunn DH, Johnson EM, Morphew JA, et al. Robot-assisted transhiatal esophagectomy: a 3-year single-center experience. Dis Esophagus 2013;26:159-66. [Crossref] [PubMed]
28. Boone J, Schipper ME, Moojen WA, et al. Robot-assisted thoracoscopic oesophagectomy for cancer. Br J Surg 2009;96:878-86. [Crossref] [PubMed]
29. Diez Del Val I, Loureiro Gonzalez C, Larburu Etxaniz S, et al. Contribution of robotics to minimally invasive esophagectomy. J Robot Surg 2013;7:325-32. [Crossref] [PubMed]
30. Galvani CA, Gorodner MV, Moser F, et al. Robotically assisted laparoscopic transhiatal esophagectomy. Surg Endosc 2008;22:188-95. [Crossref] [PubMed]
31. Puntambekar S, Kenawadekar R, Kumar S, et al. Robotic transthoracic esophagectomy. BMC Surg 2015;15:47. [Crossref] [PubMed]
32. Sarkaria IS, Rizk NP, Grosser R, et al. Attaining Proficiency in Robotic-Assisted Minimally Invasive Esophagectomy While Maximizing Safety During Procedure Development. Innovations (Phila) 2016;11:268-73. [Crossref] [PubMed]
33. Sarkaria IS, Rizk NP. Robotic-assisted minimally invasive esophagectomy: the Ivor Lewis approach. Thorac Surg Clin 2014;24:211-22. vii. [Crossref] [PubMed]
34. Okusanya OT, Sarkaria IS, Hess NR, et al. Robotic assisted minimally invasive esophagectomy (RAMIE): the University of Pittsburgh Medical Center initial experience. Ann Cardiothorac Surg 2017;6:179-85. [Crossref] [PubMed]
35. Hodari A, Park KU, Lace B, et al. Robot-Assisted Minimally Invasive Ivor Lewis Esophagectomy With Real-Time Perfusion Assessment. Ann Thorac Surg 2015;100:947-52. [Crossref] [PubMed]
36. Kandagatla P, Ghandour AH, Amro A, et al. Long-term outcomes after robotic-assisted Ivor Lewis esophagectomy. J Robot Surg 2022;16:119-25. [Crossref] [PubMed]
37. Cerfolio RJ, Bryant AS, Hawn MT. Technical aspects and early results of robotic esophagectomy with chest anastomosis. J Thorac Cardiovasc Surg 2013;145:90-6. [Crossref] [PubMed]
38. Sarkaria IS, Rizk NP, Finley DJ, et al. Combined thoracoscopic and laparoscopic robotic-assisted minimally invasive esophagectomy using a four-arm platform: experience, technique and cautions during early procedure development. Eur J Cardiothorac Surg 2013;43:e107-15. [Crossref] [PubMed]
39. Hernandez JM, Dimou F, Weber J, et al. Defining the learning curve for robotic-assisted esophagogastrectomy. J Gastrointest Surg 2013;17:1346-51. [Crossref] [PubMed]
40. van der Sluis PC, Ruurda JP, van der Horst S, et al. Learning Curve for Robot-Assisted Minimally Invasive Thoracoscopic Esophagectomy: Results From 312 Cases. Ann Thorac Surg 2018;106:264-71. [Crossref] [PubMed]
41. Zhang H, Chen L, Wang Z, et al. The Learning Curve for Robotic McKeown Esophagectomy in Patients With Esophageal Cancer. Ann Thorac Surg 2018;105:1024-30. [Crossref] [PubMed]
42. Hsieh MJ, Park SY, Wen YW, et al. Impact of prior thoracoscopic experience on the learning curve of robotic McKeown esophagectomy: a multidimensional analysis. Surg Endosc 2022;36:5635-43. [Crossref] [PubMed]
43. Han Y, Zhang Y, Zhang W, et al. Learning curve for robot-assisted Ivor Lewis esophagectomy. Dis Esophagus 2022;35:doab026. [Crossref] [PubMed]
44. Sun HB, Jiang D, Liu XB, et al. Perioperative Outcomes and Learning Curve of Robot-Assisted McKeown Esophagectomy. J Gastrointest Surg 2023;27:17-26. [Crossref] [PubMed]
45. Chan KS, Oo AM. Exploring the learning curve in minimally invasive esophagectomy: a systematic review. Dis Esophagus 2023;36:doad008. [Crossref] [PubMed]
46. Kooij CD, de Jongh C, Kingma BF, et al. ASO Visual Abstract: The Current State of Robot-Assisted Minimally Invasive Esophagectomy (RAMIE)—Outcomes from the Upper GI International Robotic Association (UGIRA) Esophageal Registry. Ann Surg Oncol 2025;32:892-3. [Crossref]
47. Abbas A, Bakhos C, Petrov R, et al. Financial impact of adapting robotics to a thoracic practice in an academic institution. J Thorac Dis 2020;12:89-96. [Crossref] [PubMed]
48. Ross SB, Rayman S, Thomas J, et al. Evaluating the Cost for Robotic vs "Non-Robotic" Transhiatal Esophagectomy. Am Surg 2022;88:389-93. [Crossref] [PubMed]
49. Knitter S, Maurer MM, Winter A, et al. Robotic-Assisted Ivor Lewis Esophagectomy Is Safe and Cost Equivalent Compared to Minimally Invasive Esophagectomy in a Tertiary Referral Center. Cancers (Basel) 2023;16:112. [Crossref] [PubMed]
50. Dugan MM, Ross SB, Sucandy I, et al. Cost comparison between medicare and private insurance for robotic transhiatal esophagectomy. J Robot Surg 2024;18:30. [Crossref] [PubMed]
51. Weksler B, Sharma P, Moudgill N, et al. Robot-assisted minimally invasive esophagectomy is equivalent to thoracoscopic minimally invasive esophagectomy. Dis Esophagus 2012;25:403-9. [Crossref] [PubMed]
52. Harbison GJ, Vossler JD, Yim NH, et al. Outcomes of robotic versus non-robotic minimally-invasive esophagectomy for esophageal cancer: An American College of Surgeons NSQIP database analysis. Am J Surg 2019;218:1223-8. [Crossref] [PubMed]
53. Meredith K, Blinn P, Maramara T, et al. Comparative outcomes of minimally invasive and robotic-assisted esophagectomy. Surg Endosc 2020;34:814-20. [Crossref] [PubMed]
54. Booka E, Kikuchi H, Haneda R, et al. Short-term Outcomes of Robot-assisted Minimally Invasive Esophagectomy Compared With Thoracoscopic or Transthoracic Esophagectomy. Anticancer Res 2021;41:4455-62. [Crossref] [PubMed]
55. Morimoto Y, Kawakubo H, Ishikawa A, et al. Short-term outcomes of robot-assisted minimally invasive esophagectomy with extended lymphadenectomy for esophageal cancer compared with video-assisted minimally invasive esophagectomy: A single-center retrospective study. Asian J Endosc Surg 2022;15:270-8. [Crossref] [PubMed]
56. Turner KM, Delman AM, Johnson K, et al. Robotic-Assisted Minimally Invasive Esophagectomy: Postoperative Outcomes in a Nationwide Cohort. J Surg Res 2023;283:152-60. [Crossref] [PubMed]
57. Khaitan PG, Vekstein AM, Thibault D, et al. Robotic Esophagectomy Trends and Early Surgical Outcomes: The US Experience. Ann Thorac Surg 2023;115:710-7. [Crossref] [PubMed]
58. Perry R, Barbosa JP, Perry I, et al. Short-term outcomes of robot-assisted versus conventional minimally invasive esophagectomy for esophageal cancer: a systematic review and meta-analysis of 18,187 patients. J Robot Surg 2024;18:125. [Crossref] [PubMed]
59. Zhang Y, Dong D, Cao Y, et al. Robotic Versus Conventional Minimally Invasive Esophagectomy for Esophageal Cancer: A Meta-analysis. Ann Surg 2023;278:39-50. [Crossref] [PubMed]
60. Zhou J, Xu J, Chen L, et al. McKeown esophagectomy: robot-assisted versus conventional minimally invasive technique-systematic review and meta-analysis. Dis Esophagus 2022;35:doac011. [Crossref] [PubMed]
61. Zheng C, Li XK, Zhang C, et al. Comparison of short-term clinical outcomes between robot-assisted minimally invasive esophagectomy and video-assisted minimally invasive esophagectomy: a systematic review and meta-analysis. J Thorac Dis 2021;13:708-19. [Crossref] [PubMed]
62. Mederos MA, de Virgilio MJ, Shenoy R, et al. Comparison of Clinical Outcomes of Robot-Assisted, Video-Assisted, and Open Esophagectomy for Esophageal Cancer: A Systematic Review and Meta-analysis. JAMA Netw Open 2021;4:e2129228. [Crossref] [PubMed]
63. Manigrasso M, Vertaldi S, Marello A, et al. Robotic Esophagectomy. A Systematic Review with Meta-Analysis of Clinical Outcomes. J Pers Med 2021;11:640. [Crossref] [PubMed]
64. Huang Y, Zhao YL, Song JD. Early outcomes with robot-assisted vs. minimally invasive esophagectomy for esophageal cancer: a systematic review and meta-analysis of matched studies. Eur Rev Med Pharmacol Sci 2021;25:7887-97. [PubMed]
65. Chen H, Liu Y, Peng H, et al. Robot-assisted minimally invasive esophagectomy versus video-assisted minimally invasive esophagectomy: a systematic review and meta-analysis. Transl Cancer Res 2021;10:4601-16. [Crossref] [PubMed]
66. Angeramo CA, Bras Harriott C, Casas MA, et al. Minimally invasive Ivor Lewis esophagectomy: Robot-assisted versus laparoscopic-thoracoscopic technique. Systematic review and meta-analysis. Surgery 2021;170:1692-701. [Crossref] [PubMed]
67. Li XK, Xu Y, Zhou H, et al. Does robot-assisted minimally invasive oesophagectomy have superiority over thoraco-laparoscopic minimally invasive oesophagectomy in lymph node dissection? Dis Esophagus 2021;34:doaa050. [Crossref] [PubMed]
68. Jin D, Yao L, Yu J, et al. Robotic-assisted minimally invasive esophagectomy versus the conventional minimally invasive one: A meta-analysis and systematic review. Int J Med Robot 2019;15:e1988. [Crossref] [PubMed]
69. Magouliotis DE, Zotos PA, Fergadi MP, et al. Meta-analysis of robot-assisted versus video-assisted McKeown esophagectomy for esophageal cancer. Updates Surg 2022;74:1501-10. [Crossref] [PubMed]
70. Fransen LFC, Berkelmans GHK, Asti E, et al. The Effect of Postoperative Complications After Minimally Invasive Esophagectomy on Long-term Survival: An International Multicenter Cohort Study. Ann Surg 2021;274:e1129-37. [Crossref] [PubMed]
71. Markar S, Gronnier C, Duhamel A, et al. Pattern of Postoperative Mortality After Esophageal Cancer Resection According to Center Volume: Results from a Large European Multicenter Study. Ann Surg Oncol 2015;22:2615-23. [Crossref] [PubMed]
72. Park S, Hwang Y, Lee HJ, et al. Comparison of robot-assisted esophagectomy and thoracoscopic esophagectomy in esophageal squamous cell carcinoma. J Thorac Dis 2016;8:2853-61. [Crossref] [PubMed]
73. Washington K, Watkins JR, Jay J, et al. Oncologic Resection in Laparoscopic Versus Robotic Transhiatal Esophagectomy. JSLS 2019;23:e2019.00017.
74. Xu Y, Li XK, Cong ZZ, et al. Long-term outcomes of robotic-assisted versus thoraco-laparoscopic McKeown esophagectomy for esophageal cancer: a propensity score-matched study. Dis Esophagus 2021;34:doaa114. [Crossref] [PubMed]
75. Trung LV, Loc NVV, Tien TPD, et al. Robot-Assisted Versus Thoraco-laparoscopic McKeown Esophagectomy for Esophageal Cancer: a Propensity Score-Matched Study. J Gastrointest Surg 2022;26:1093-6. [Crossref] [PubMed]
76. Ekeke CN, Kuiper GM, Luketich JD, et al. Comparison of robotic-assisted minimally invasive esophagectomy versus minimally invasive esophagectomy: A propensity-matched study from a single high-volume institution. J Thorac Cardiovasc Surg 2023;166:374-382.e1. [Crossref] [PubMed]
77. Byiringiro I, Aurit SJ, Nandipati KC. Long-term survival outcomes associated with robotic-assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer. Surg Endosc 2023;37:4018-27. [Crossref] [PubMed]