Comparison of the da Vinci Xi and hinotori surgical robotic systems using a training model: an ex vivo study

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We used an ex vivo training model to compare task performance and subjective workload between the widely-established da Vinci Xi system and the hinotori system, which was developed in Japan. In this prospective crossover study, 16 urologists performed three standardized tasks (camera manipulation and grasping, cutting, and suturing with knot tying) under three robotic conditions: using da Vinci Xi with finger clutch, using da Vinci Xi without finger clutch, and using hinotori. Task completion time was recorded for each trial, and subjective workload was assessed after every task using the weighted NASA Task Load Index (NASA-TLX). Median task completion times tended to be longer with hinotori than with either of the da Vinci Xi conditions, although no significant differences were observed between the three systems for any of the tasks. In contrast, weighted NASA-TLX scores were significantly higher with hinotori than with the da Vinci Xi with finger clutch for the camera/grasping and suturing tasks, whereas no significant differences were detected between hinotori and the da Vinci Xi without finger clutch. In conclusion, the hinotori system demonstrated task performance comparable to the da Vinci Xi platform, while subjective workload was higher relative to the da Vinci Xi when the finger clutch function was used. Our results suggest that surgeon workload during robotic surgery may be strongly influenced by console-specific ergonomic features, particularly the presence or absence of a finger clutch function. da Vinci hinotori robotic surgery surgical training model task workload Figures Figure 1 Figure 2 Introduction Robotic-assisted surgery has become a cornerstone of contemporary urologic practice, particularly for complex oncologic procedures such as radical prostatectomy and partial nephrectomy. For more than two decades, the da Vinci surgical system (Intuitive Surgical, Sunnyvale, CA) has been the predominant robotic platform worldwide. Nevertheless, in response to concerns regarding cost, limited competition and console ergonomics, a new generation of multiport robotic systems has emerged over the past decade, and several platforms including Hugo™ RAS, Versius™, Senhance™, Saroa and the Japanese hinotori™ system have already entered clinical use in urology. Early reports suggest perioperative and short-term functional outcomes that are broadly comparable to those of established da Vinci-based procedures [ 1 – 4 ]. Among these, the hinotori surgical robot system (Medicaroid Corporation, Kobe, Japan) is the first domestically developed multiport robotic platform to be approved for clinical use in Japan. Its urologic applications have rapidly expanded to include robot-assisted radical prostatectomy, robot-assisted partial nephrectomy, robot-assisted radical nephrectomy and robot-assisted radical nephroureterectomy [ 5 – 9 ]. Various clinical studies collectively support the feasibility of hinotori as an alternative to da Vinci for major urologic procedures. However, there are also important limitations: the studies are largely retrospective, they are often single-institutional or early-experience series, and they are inherently subject to selection bias, differences in case mix and surgeon experience, and center-specific modifications of the robotic platform or surgical workflow [ 5 – 9 ]. Disentangling system-related factors from patient- or surgeon-related factors is therefore challenging when comparing clinical outcomes between robotic platforms in real-world practice. Evaluation of robotic systems in a controlled, non-clinical setting using standardized tasks on simulation or ex vivo training models offers an opportunity to minimize such confounding, thereby allowing direct comparison of psychomotor performance and console ergonomics under identical task conditions. Training tasks focusing on basic robotic skills, such as camera control, tissue handling, and cutting and suturing are thought to provide an objective framework for assessing platform-related differences. Meanwhile, the NASA Task Load Index (NASA-TLX) is a well-validated instrument for quantifying multidimensional subjective workload, including mental, physical and temporal demands, perceived performance, effort and frustration [ 10 , 11 ]. Against this background of the expansion of multi-platform robotic surgery and the caveats related to biased clinical data for hinotori, we designed the present ex vivo study. Herein, we use a standardized training model to compare task performance and subjective workload between the hinotori surgical robot system and the da Vinci Xi system (with and without the finger clutch function). We hypothesized that task completion times would be broadly comparable across platforms, whereas workload profiles, as captured by NASA-TLX, would differ and be influenced by console-specific clutch functionality. Materials and methods Study design and participants We conducted this ex vivo simulation study in a dedicated robotic skills laboratory at a single institution. Sixteen urologists voluntarily participated in the study. The participants’ certification status for robotic systems was as follows: six surgeons held console certification for both the da Vinci and hinotori systems, five held certification only for the da Vinci system, and five had not yet obtained certification for either system. The participants who held console certification for at least one of the two robotic platforms were defined as ‘attending surgeons’, whereas those without certification for either system were classified as ‘residents’. Subgroup analyses were therefore planned and conducted for these two groups. Robotic platforms and experimental conditions Three robotic conditions were evaluated: (1) the da Vinci Xi surgical system with the finger clutch function activated (da Vinci with finger clutch), (2) the da Vinci Xi system with the finger clutch function disabled (da Vinci without finger clutch), and (3) the hinotori surgical robot system. At the time this study was conducted (May 4–5, 2023), a finger clutch function was not yet available on the hinotori platform, and therefore these three conditions were selected for comparison. In all conditions, standard instrument configurations suitable for basic training tasks were used. Specifically, as described in detail below, for Tasks 1 and 3, needle drivers were mounted on both the right and left instrument arms, whereas for Task 2, monopolar curved scissors were used in the right hand and Maryland bipolar forceps in the left hand, while the third arm held ProGrasp forceps (da Vinci Xi system) or a Versatile grasper (hinotori system). Both systems were installed and maintained by experienced engineers, and the same operating table and training modules were used for all experimental conditions. Training model and tasks A dry-box type ex vivo training model was used for all experiments. Each participant completed three tasks, described below, on each robotic condition. Representative scenes of the actual task performance are shown in Fig. 1 . Task 1 comprised camera movement and grasping activities. Using bilateral needle drivers under a 0-degree endoscope, participants moved rubber bands from four rubber posts with wire tips located in the center of the field. This started at the front-right central post and the bands were to be transferred sequentially in a clockwise fashion to peripheral posts arranged in a circle. Then, again beginning at the front-right peripheral post, the bands were to be returned to the central posts in a clockwise order according to a predefined sequence. The task was intended to emphasize three-dimensional camera control, depth perception and bimanual coordination. Task 2 was a cutting activity. A square sheet of paper (7×7 cm) was grasped at the midpoint of the far edge by the third arm, using a ProGrasp forceps (da Vinci Xi system) or a Versatile grasper (hinotori system). Using monopolar curved scissors in the dominant hand and a Maryland bipolar forceps in the non-dominant hand under a 0-degree endoscope, participants were instructed to cut along three wavy lines printed on the paper running from the near side toward the far side, following each line from bottom to top without deviation while preserving the structural integrity of the paper. Task 3 comprised suturing and knot tying activities. Two adjacent synthetic sponge blocks with black dots marked at 5-mm intervals were used to simulate tissue approximation. Using needle drivers in both hands under a 0-degree endoscope, participants performed a continuous running suture starting from the dot located at the most distal position and then proceeding stepwise toward the dots positioned more proximally (closer to the participant). After placing an initial interrupted stitch, an initial surgeon’s knot followed by two additional throws was tied, and then a total of five continuous stitches were placed toward the most proximal dot. Finally, the suture was tied at the end using the tail end of the thread. A 4 − 0 nylon suture with a 20-cm length was used for all trials. Study protocol Study protocol Both attending surgeons and residents were randomly allocated to one of two sequence groups (Group A or Group B) to minimize order effects ( Fig. 2 ) . At the beginning of the experiment and whenever the robotic platform was changed (i.e. at transitions from da Vinci Xi to hinotori, or from hinotori to da Vinci Xi), a standardized 5-min orientation and practice session was provided for the upcoming platform. During this time, the investigator explained console controls and allowed free practice on the training model. After each familiarization period, participants performed the three tasks sequentially on that platform. The same sequence of tasks (Task 1, Task 2, then Task 3) was used for all systems. All participants therefore completed a total of nine task trials (three tasks in each of the three robotic conditions). Outcome measures The primary quantitative performance metric was task completion time, defined as the time from the start signal to completion of each task as judged by predefined criteria. Times were recorded in seconds using a digital stopwatch by an independent observer. The secondary outcome was subjective workload, which was measured after each task using the NASA Task Load Index (NASA-TLX). Participants rated each of the six NASA-TLX subscales (mental demand, physical demand, temporal demand, performance, effort, and frustration) on a 0–100 visual analog scale. In addition, pairwise comparisons among the six subscales were performed to obtain individual weighting factors, and a weighted workload score was calculated as the weighted average of the six subscale ratings [ 12 ]. Statistical analysis Data were summarized as medians and ranges because the distributions of completion times and NASA-TLX scores were skewed. For each task, overall comparisons among the three robotic conditions were performed using the Kruskal-Wallis test. When a significant overall difference was detected, pairwise comparisons between the three robotic conditions (e.g., hinotori vs. da Vinci Xi with finger clutch, hinotori vs. da Vinci Xi without finger clutch, and da Vinci Xi with vs. without finger clutch) were conducted using the Steel-Dwass multiple comparison test. Subgroup analyses were performed for attending surgeons and residents. All statistical analyses were performed using JMP Pro 16 (SAS Institute Inc., Cary, NC, USA), and a two-sided P < 0.05 was considered statistically significant. Results Task completion times Table 1 shows the comparison of task completion times between hinotori and da Vinci Xi in (a) overall participants, (b) attending surgeons and (c) residents. Among all participants, median completion times for Task 1 were 313 sec (hinotori), 222 sec (da Vinci Xi without finger clutch) and 217 sec (da Vinci Xi with finger clutch). For Task 2, the median completion times were 464, 349 and 392 sec, respectively, and for Task 3, they were 560, 364 and 490 sec, respectively. Although task times tended to be longer with hinotori than with either of the da Vinci Xi conditions, none of the pairwise differences between robotic systems reached statistical significance for any task (Table 1a) . Similar trends were observed when analyses were restricted to attending surgeons (Table 1b) or residents (Table 1c) , and no significant differences in completion times were identified in these subgroups. NASA-TLX workload scores Comparisons of NASA-Task Load index between hinotori and da Vinci Xi for Tasks 1–3, are shown in Tables 2–4 . For Task 1, the weighted NASA-TLX score showed a significant overall difference between the three robotic conditions in the overall cohort, as well as in the attending-surgeon and resident subgroups. The hinotori yielded significantly higher weighted workload scores than the da Vinci Xi with finger clutch in all three groups, indicating greater perceived workload with hinotori for this camera and grasping task. When individual NASA-TLX subscales were analyzed, only frustration showed a significant overall difference among robotic conditions in the overall cohort and among attending surgeons. In these groups, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions, whereas no significant differences among robotic conditions were observed for the remaining subscales (Table 2) . For Task 2, the weighted NASA-TLX score did not show a significant overall difference among the three robotic conditions in the overall cohort or in the attending-surgeon and resident subgroups. However, in the analysis of individual NASA-TLX subscales, frustration was the only subscale that demonstrated a significant overall difference among robotic conditions in all three groups. In subscale-specific comparisons between robotic conditions, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions in the overall cohort and among attending surgeons. Meanwhile, in the resident subgroup, frustration was significantly higher with hinotori than with the da Vinci Xi with finger clutch alone. No significant differences among robotic conditions were observed for the remaining NASA-TLX subscales (Table 3) . For Task 3, the weighted NASA-TLX score showed a significant overall difference between the three robotic conditions in the overall cohort, but no significant overall differences were observed in the attending-surgeon or resident subgroups. In the overall cohort, analysis of the individual NASA-TLX subscales demonstrated that only frustration had a significant overall difference among robotic conditions. In subscale-specific comparisons between platforms, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions, while no significant differences among robotic conditions were observed for the remaining subscales (Table 4) . Discussion In this ex vivo simulation study, we compared surgeon performance and subjective workload between three robotic conditions: the da Vinci Xi with and without the finger clutch function, and the hinotori surgical robot system. Task completion times for all three basic tasks did not significantly differ between the robotic conditions in the overall cohort or in the attending-surgeon and resident subgroups. On the other hand, for Task 1 (camera movement and grasping) and Task 3 (suturing and knot tying), weighted NASA-TLX scores were significantly higher with hinotori than with the da Vinci Xi with finger clutch, but no significant differences were observed between hinotori and the da Vinci Xi without finger clutch for any of the three tasks. Over the last decade, the landscape of robotic surgery in urology has dramatically changed, with the introduction of several new multiport robotic platforms including hinotori, in addition to the da Vinci systems. Early clinical outcomes with these systems in urology have generally been reported as comparable to those with da Vinci platforms including Xi [ 1 , 13 ]. The hinotori surgical robot system is the first domestically developed multiport robotic platform to be approved for clinical use in Japan. It is characterized by several unique design features, including eight-axis robotic arms and a docking-free design that differs from that of da Vinci Xi [ 14 ]. Early clinical reports from urologic oncology have shown that hinotori is feasible and safe for robot-assisted radical prostatectomy, robot-assisted partial nephrectomy, robot-assisted radical nephrectomy and robot-assisted radical nephroureterectomy [ 5 – 9 ]. A previous propensity score–matched comparison of robot-assisted partial nephrectomy using hinotori vs. the da Vinci system reported broadly comparable perioperative outcomes between platforms [ 15 ]. Similarly, we also conducted propensity score–matched analyses of robot-assisted radical prostatectomy using two robotic platforms and showed largely comparable perioperative, oncologic and functional outcomes, despite longer operative and console times in the hinotori group [ 16 ]. However, a recent systematic review of novel multiport robotic platforms in urology, which included hinotori, emphasized that most available data are still in the developmental or early exploratory stages and that high-quality comparative evidence remains limited [ 13 ]. Importantly, patient selection bias and other confounding factors cannot be fully eliminated in clinical series [ 13 ]. To overcome these limitations, we suggest the importance of comparative evaluations using standardized training or bench models. Although Urade et al. reported on their participants’ first-touch robotic skills using hinotori and its simulator, no prior studies have directly compared hinotori with the da Vinci system in an ex vivo or bench-top setting [ 17 ]. To our knowledge, the present study is therefore the first ex vivo head-to-head comparison between the hinotori platform and the da Vinci Xi system using a standardized training model, with a specific focus on surgeon performance and subjective workload. Although overall task efficiency was comparable between the hinotori and da Vinci Xi systems, perceived workload was shown to be influenced by console-related ergonomic factors, particularly the presence or absence of a finger clutch function. In addition, at the time of this study, the hinotori platform was relatively new to many of the participating surgeons, which might have contributed to increased subjective workload. In parallel with the accumulation of clinical experience, the hinotori system has undergone iterative hardware and software refinements. Finger clutch functionality and other ergonomic enhancements are now implemented in the latest hinotori generations, so it is reasonable to expect that there will be a progressive narrowing of the gap in perceived workload compared with the da Vinci Xi with finger clutch. Moreover, multiple development projects are underway to expand the capabilities and indications of hinotori, including broadening the instrument lineup, enhancing imaging systems and electrosurgical units, and developing intraoperative navigation systems and synchronized beds. The aim is to extend its use beyond current fields such as urology, gynecology and gastrointestinal surgery into cardiovascular and thoracic surgery [ 8 ]. In addition, future-oriented initiatives involving remote surgery, increased robotic autonomy and artificial intelligence-based analysis of surgical procedures, together with plans for global deployment of the platform, suggest that the clinical utility and ergonomic performance of hinotori will continue to evolve and may ultimately approach or surpass that of existing established robotic systems. This study has several limitations. First, the sample size was relatively small and it was derived from a single institution, which may limit the generalizability of our findings. Nevertheless, the inclusion of both attending surgeons and residents, with balanced randomization between sequence groups, is thought to provide a pragmatic overview of performance across different experience levels. Second, we used a dry training model rather than animal or clinical procedures, so our results may not fully reflect the complexities of real-world surgery, including bleeding, tissue variability and intraoperative decision-making. However, the use of a standardized ex vivo model allowed us to isolate system-related differences in performance and workload while minimizing confounding by patient factors and case complexity. Third, although the tasks were designed to encompass key components of robotic surgery (camera control and grasping, precise cutting and continuous suturing), there is no universally accepted set of basic robotic tasks for cross-platform comparison. Different task designs or training curricula might yield somewhat different patterns of performance and workload. Finally, we evaluated only three relatively simple tasks in a simulated setting. Multi-step procedures and advanced reconstructive tasks might accentuate or modify the differences between systems seen here, and future studies should address more complex scenarios as well as learning-curve effects. Despite these limitations, we believe that our ex vivo study provides useful comparative data on the da Vinci Xi system and the newer hinotori platform from the perspective of surgeon performance and subjective workload. In the era of multiple available robotic systems, such benchmark comparisons can assist urologists and surgeons in other specialties in understanding platform-specific characteristics and in making informed decisions about system selection and training. In conclusion, this ex vivo comparison suggests that surgeon workload during robotic surgery may be strongly influenced by console-specific ergonomic features, particularly the presence or absence of a finger clutch function. At the same time, the overall task performance of the hinotori surgical robot system appeared broadly comparable to that of the da Vinci Xi system, indicating no major inferiority of hinotori in basic robotic skills. Abbreviations NASA-TLX = NASA Task Load Index Declarations Acknowledgements We acknowledge proofreading and editing by Benjamin Phillis, a Board-Certified Editor in the Life Sciences (BELS), at Wakayama Medical University. In addition, we used ChatGPT (OpenAI) to support part of the English translation under the supervision of the authors. Author contributions All authors significantly contributed to the present study. The conceptualization was by Shimpei Yamashita. The methodology was devised by Isao Hara and Yasuo Kohjimoto. The data collection was performed by Hiraku Yamamoto, Shimpei Yamashita, Hisanobu Tosuji, Nobuyuki Mashima, Ryusuke Deguchi, Yuya Iwahashi, Hiroki Kawabata, Satoshi Muraoka and Takahito Wakamiya. The statistical analyses were performed by Shimpei Yamashita. The original draft of the manuscript was written by Hiraku Yamamoto and Shimpei Yamashita, and it was reviewed and edited by Yasuo Kohjimoto. The study was supervised by Isao Hara and Yasuo Kohjimoto. Funding The present study did not receive any funding. Availability of data and materials The datasets analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors have no relevant financial or non-financial interests to disclose. Ethical approval This study did not involve human patients or animals and was conducted exclusively using an ex vivo training model with surgeon participants. According to the policies of Wakayama Medical University, formal review and approval by the institutional review board were not required for this type of educational simulation study. The study was conducted in accordance with the principles of the Declaration of Helsinki, as applicable. Consent to participate All participating surgeons provided written informed consent prior to participation. No patients were involved in this research, so patient consent was not required. Consent for publication All participating surgeons provided written informed consent for publication of the anonymized study data and images. As no patient data were included in this research, consent for publication from patients was not required. References Salkowski M, Checcucci E, Chow AK, Rogers CC, Adbollah F, Liatsikos E, Dasgupta P, Guimaraes GC, Rassweiler J, Mottrie A, Breda A, Crivellaro S, Kaouk J, Porpiglia F, Autorino R (2023) New multiport robotic surgical systems: a comprehensive literature review of clinical outcomes in urology. 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Langenbecks Arch Surg 409(1):332. 10.1007/s00423-024-03514-6 Tables Tables 1 to 4 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files FY25096Table1editedbyBen091225.xlsx FY25096Table2editedbyBen091225.xlsx FY25096Table3editedbyBen091225.xlsx FY25096Table4editedbyBen091225.xlsx Cite Share Download PDF Status: Published Journal Publication published 12 Feb, 2026 Read the published version in Journal of Robotic Surgery → Version 1 posted Editorial decision: Revision requested 04 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviewers agreed at journal 02 Jan, 2026 Reviewers agreed at journal 30 Dec, 2025 Reviewers agreed at journal 17 Dec, 2025 Reviews received at journal 16 Dec, 2025 Reviewers agreed at journal 11 Dec, 2025 Reviewers agreed at journal 11 Dec, 2025 Reviewers agreed at journal 09 Dec, 2025 Reviewers invited by journal 09 Dec, 2025 Editor assigned by journal 09 Dec, 2025 Submission checks completed at journal 09 Dec, 2025 First submitted to journal 09 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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University","correspondingAuthor":false,"prefix":"","firstName":"Hisanobu","middleName":"","lastName":"Tosuji","suffix":""},{"id":560163169,"identity":"5abf5966-5b32-474f-b9b8-30e923f65d70","order_by":3,"name":"Nobuyuki Mashima","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Nobuyuki","middleName":"","lastName":"Mashima","suffix":""},{"id":560163173,"identity":"90985988-c586-4aec-a798-5758262ab8f7","order_by":4,"name":"Ryusuke Deguchi","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ryusuke","middleName":"","lastName":"Deguchi","suffix":""},{"id":560163174,"identity":"bb9e67ad-5ce4-4c57-bb9d-d931fe4324a4","order_by":5,"name":"Yuya Iwahashi","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuya","middleName":"","lastName":"Iwahashi","suffix":""},{"id":560163181,"identity":"b65f4a85-8dc1-4339-8390-348d1c769e48","order_by":6,"name":"Hiroki Kawabata","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hiroki","middleName":"","lastName":"Kawabata","suffix":""},{"id":560163185,"identity":"7ecbb285-53dc-418b-9bbe-699d684e3380","order_by":7,"name":"Satoshi Muraoka","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Satoshi","middleName":"","lastName":"Muraoka","suffix":""},{"id":560163186,"identity":"7896162b-369b-47a8-a567-c27510add1a3","order_by":8,"name":"Takahito Wakamiya","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Takahito","middleName":"","lastName":"Wakamiya","suffix":""},{"id":560163188,"identity":"02eb7b28-e4ad-4a40-947b-4444c28e2c5e","order_by":9,"name":"Isao Hara","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Isao","middleName":"","lastName":"Hara","suffix":""},{"id":560163190,"identity":"8d3ce239-84be-4e7b-b416-a251fa419eb5","order_by":10,"name":"Yasuo Kohjimoto","email":"","orcid":"","institution":"Wakayama Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yasuo","middleName":"","lastName":"Kohjimoto","suffix":""}],"badges":[],"createdAt":"2025-12-09 05:53:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8313500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8313500/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s11701-026-03192-0","type":"published","date":"2026-02-12T15:59:06+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":98245743,"identity":"82a87bd6-c5a1-4e65-b6c3-63dbfdf1dfce","added_by":"auto","created_at":"2025-12-15 16:18:20","extension":"tif","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5927602,"visible":true,"origin":"","legend":"","description":"","filename":"Figure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/a6a20d04756285b5e4bd9393.tif"},{"id":98245869,"identity":"40854363-4b9d-4a6f-93d9-552b2ca59320","added_by":"auto","created_at":"2025-12-15 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16:18:31","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":83328,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/65dd855b5cc65d88da9644be.html"},{"id":98245839,"identity":"7c6eed87-5acb-4a65-85ba-831bd2577156","added_by":"auto","created_at":"2025-12-15 16:18:31","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":975139,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative photographs of task performance using the hinotori surgical robot system: (a) Task 1 (camera movement and grasping), (b) Task 2 (cutting), and (c) Task 3 (suturing and knot tying).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/28e27c5a6de2f11bf20967cc.png"},{"id":98245838,"identity":"b86ce9c2-d774-42c3-9c45-30cf8ada40e5","added_by":"auto","created_at":"2025-12-15 16:18:31","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":163731,"visible":true,"origin":"","legend":"\u003cp\u003eStudy protocol showing the order of robotic conditions for Group A and Group B and the timing of the 5-minute console instruction and practice session performed before each platform.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/e1be0f33c911ee0c2042dfca.png"},{"id":102785328,"identity":"aac4eccc-e25c-419f-aec4-e8b96ab92157","added_by":"auto","created_at":"2026-02-16 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16:18:31","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":12745,"visible":true,"origin":"","legend":"","description":"","filename":"FY25096Table2editedbyBen091225.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/525d7c93581b09493304d4bd.xlsx"},{"id":98245785,"identity":"560d5f42-ded5-4a62-8150-8a6b38b7a05e","added_by":"auto","created_at":"2025-12-15 16:18:23","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":12659,"visible":true,"origin":"","legend":"","description":"","filename":"FY25096Table3editedbyBen091225.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/7cd19f02a1831bdf0731c054.xlsx"},{"id":98245877,"identity":"18bf493f-8220-432c-9be1-b16c584eb738","added_by":"auto","created_at":"2025-12-15 16:18:33","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":12644,"visible":true,"origin":"","legend":"","description":"","filename":"FY25096Table4editedbyBen091225.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8313500/v1/c71131fafa815d641a8d9a2b.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of the da Vinci Xi and hinotori surgical robotic systems using a training model: an ex vivo study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRobotic-assisted surgery has become a cornerstone of contemporary urologic practice, particularly for complex oncologic procedures such as radical prostatectomy and partial nephrectomy. For more than two decades, the da Vinci surgical system (Intuitive Surgical, Sunnyvale, CA) has been the predominant robotic platform worldwide. Nevertheless, in response to concerns regarding cost, limited competition and console ergonomics, a new generation of multiport robotic systems has emerged over the past decade, and several platforms including Hugo\u0026trade; RAS, Versius\u0026trade;, Senhance\u0026trade;, Saroa and the Japanese hinotori\u0026trade; system have already entered clinical use in urology. Early reports suggest perioperative and short-term functional outcomes that are broadly comparable to those of established da Vinci-based procedures [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e Among these, the hinotori surgical robot system (Medicaroid Corporation, Kobe, Japan) is the first domestically developed multiport robotic platform to be approved for clinical use in Japan. Its urologic applications have rapidly expanded to include robot-assisted radical prostatectomy, robot-assisted partial nephrectomy, robot-assisted radical nephrectomy and robot-assisted radical nephroureterectomy [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Various clinical studies collectively support the feasibility of hinotori as an alternative to da Vinci for major urologic procedures. However, there are also important limitations: the studies are largely retrospective, they are often single-institutional or early-experience series, and they are inherently subject to selection bias, differences in case mix and surgeon experience, and center-specific modifications of the robotic platform or surgical workflow [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Disentangling system-related factors from patient- or surgeon-related factors is therefore challenging when comparing clinical outcomes between robotic platforms in real-world practice.\u003c/p\u003e\u003cp\u003eEvaluation of robotic systems in a controlled, non-clinical setting using standardized tasks on simulation or ex vivo training models offers an opportunity to minimize such confounding, thereby allowing direct comparison of psychomotor performance and console ergonomics under identical task conditions. Training tasks focusing on basic robotic skills, such as camera control, tissue handling, and cutting and suturing are thought to provide an objective framework for assessing platform-related differences. Meanwhile, the NASA Task Load Index (NASA-TLX) is a well-validated instrument for quantifying multidimensional subjective workload, including mental, physical and temporal demands, perceived performance, effort and frustration [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Against this background of the expansion of multi-platform robotic surgery and the caveats related to biased clinical data for hinotori, we designed the present ex vivo study. Herein, we use a standardized training model to compare task performance and subjective workload between the hinotori surgical robot system and the da Vinci Xi system (with and without the finger clutch function). We hypothesized that task completion times would be broadly comparable across platforms, whereas workload profiles, as captured by NASA-TLX, would differ and be influenced by console-specific clutch functionality.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and participants\u003c/h2\u003e\u003cp\u003eWe conducted this ex vivo simulation study in a dedicated robotic skills laboratory at a single institution. Sixteen urologists voluntarily participated in the study. The participants\u0026rsquo; certification status for robotic systems was as follows: six surgeons held console certification for both the da Vinci and hinotori systems, five held certification only for the da Vinci system, and five had not yet obtained certification for either system. The participants who held console certification for at least one of the two robotic platforms were defined as \u0026lsquo;attending surgeons\u0026rsquo;, whereas those without certification for either system were classified as \u0026lsquo;residents\u0026rsquo;. Subgroup analyses were therefore planned and conducted for these two groups.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRobotic platforms and experimental conditions\u003c/h3\u003e\n\u003cp\u003eThree robotic conditions were evaluated: (1) the da Vinci Xi surgical system with the finger clutch function activated (da Vinci with finger clutch), (2) the da Vinci Xi system with the finger clutch function disabled (da Vinci without finger clutch), and (3) the hinotori surgical robot system. At the time this study was conducted (May 4\u0026ndash;5, 2023), a finger clutch function was not yet available on the hinotori platform, and therefore these three conditions were selected for comparison. In all conditions, standard instrument configurations suitable for basic training tasks were used. Specifically, as described in detail below, for Tasks 1 and 3, needle drivers were mounted on both the right and left instrument arms, whereas for Task 2, monopolar curved scissors were used in the right hand and Maryland bipolar forceps in the left hand, while the third arm held ProGrasp forceps (da Vinci Xi system) or a Versatile grasper (hinotori system). Both systems were installed and maintained by experienced engineers, and the same operating table and training modules were used for all experimental conditions.\u003c/p\u003e\n\u003ch3\u003eTraining model and tasks\u003c/h3\u003e\n\u003cp\u003eA dry-box type ex vivo training model was used for all experiments. Each participant completed\u003c/p\u003e\u003cp\u003ethree tasks, described below, on each robotic condition. Representative scenes of the actual task performance are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTask 1 comprised camera movement and grasping activities. Using bilateral needle drivers under a 0-degree endoscope, participants moved rubber bands from four rubber posts with wire tips located in the center of the field. This started at the front-right central post and the bands were to be transferred sequentially in a clockwise fashion to peripheral posts arranged in a circle. Then, again beginning at the front-right peripheral post, the bands were to be returned to the central posts in a clockwise order according to a predefined sequence. The task was intended to emphasize three-dimensional camera control, depth perception and bimanual coordination.\u003c/p\u003e\u003cp\u003eTask 2 was a cutting activity. A square sheet of paper (7\u0026times;7 cm) was grasped at the midpoint of the far edge by the third arm, using a ProGrasp forceps (da Vinci Xi system) or a Versatile grasper (hinotori system). Using monopolar curved scissors in the dominant hand and a Maryland bipolar forceps in the non-dominant hand under a 0-degree endoscope, participants were instructed to cut along three wavy lines printed on the paper running from the near side toward the far side, following each line from bottom to top without deviation while preserving the structural integrity of the paper.\u003c/p\u003e\u003cp\u003eTask 3 comprised suturing and knot tying activities. Two adjacent synthetic sponge blocks with black dots marked at 5-mm intervals were used to simulate tissue approximation. Using needle drivers in both hands under a 0-degree endoscope, participants performed a continuous running suture starting from the dot located at the most distal position and then proceeding stepwise toward the dots positioned more proximally (closer to the participant). After placing an initial interrupted stitch, an initial surgeon\u0026rsquo;s knot followed by two additional throws was tied, and then a total of five continuous stitches were placed toward the most proximal dot. Finally, the suture was tied at the end using the tail end of the thread. A 4\u0026thinsp;\u0026minus;\u0026thinsp;0 nylon suture with a 20-cm length was used for all trials.\u003c/p\u003e\n\u003ch3\u003eStudy protocol\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eStudy protocol\u003c/div\u003e\u003cp\u003eBoth attending surgeons and residents were randomly allocated to one of two sequence groups (Group A or Group B) to minimize order effects \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. At the beginning of the experiment and whenever the robotic platform was changed (i.e. at transitions from da Vinci Xi to hinotori, or from hinotori to da Vinci Xi), a standardized 5-min orientation and practice session was provided for the upcoming platform. During this time, the investigator explained console controls and allowed free practice on the training model. After each familiarization period, participants performed the three tasks sequentially on that platform. The same sequence of tasks (Task 1, Task 2, then Task 3) was used for all systems. All participants therefore completed a total of nine task trials (three tasks in each of the three robotic conditions).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eOutcome measures\u003c/h3\u003e\n\u003cp\u003eThe primary quantitative performance metric was task completion time, defined as the time from the start signal to completion of each task as judged by predefined criteria. Times were recorded in seconds using a digital stopwatch by an independent observer. The secondary outcome was subjective workload, which was measured after each task using the NASA Task Load Index (NASA-TLX). Participants rated each of the six NASA-TLX subscales (mental demand, physical demand, temporal demand, performance, effort, and frustration) on a 0\u0026ndash;100 visual analog scale. In addition, pairwise comparisons among the six subscales were performed to obtain individual weighting factors, and a weighted workload score was calculated as the weighted average of the six subscale ratings [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData were summarized as medians and ranges because the distributions of completion times and NASA-TLX scores were skewed. For each task, overall comparisons among the three robotic conditions were performed using the Kruskal-Wallis test. When a significant overall difference was detected, pairwise comparisons between the three robotic conditions (e.g., hinotori vs. da Vinci Xi with finger clutch, hinotori vs. da Vinci Xi without finger clutch, and da Vinci Xi with vs. without finger clutch) were conducted using the Steel-Dwass multiple comparison test. Subgroup analyses were performed for attending surgeons and residents. All statistical analyses were performed using JMP Pro 16 (SAS Institute Inc., Cary, NC, USA), and a two-sided \u003cem\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/em\u003e was considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eTask completion times\u003c/h2\u003e\u003cp\u003e\u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e shows the comparison of task completion times between hinotori and da Vinci Xi in (a) overall participants, (b) attending surgeons and (c) residents. Among all participants, median completion times for Task 1 were 313 sec (hinotori), 222 sec (da Vinci Xi without finger clutch) and 217 sec (da Vinci Xi with finger clutch). For Task 2, the median completion times were 464, 349 and 392 sec, respectively, and for Task 3, they were 560, 364 and 490 sec, respectively. Although task times tended to be longer with hinotori than with either of the da Vinci Xi conditions, none of the pairwise differences between robotic systems reached statistical significance for any task \u003cb\u003e(Table\u0026nbsp;1a)\u003c/b\u003e. Similar trends were observed when analyses were restricted to attending surgeons \u003cb\u003e(Table\u0026nbsp;1b)\u003c/b\u003e or residents \u003cb\u003e(Table\u0026nbsp;1c)\u003c/b\u003e, and no significant differences in completion times were identified in these subgroups.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eNASA-TLX workload scores\u003c/h2\u003e\u003cp\u003eComparisons of NASA-Task Load index between hinotori and da Vinci Xi for Tasks 1\u0026ndash;3, are shown in \u003cb\u003eTables\u0026nbsp;2\u0026ndash;4\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eFor Task 1, the weighted NASA-TLX score showed a significant overall difference between the three robotic conditions in the overall cohort, as well as in the attending-surgeon and resident subgroups. The hinotori yielded significantly higher weighted workload scores than the da Vinci Xi with finger clutch in all three groups, indicating greater perceived workload with hinotori for this camera and grasping task. When individual NASA-TLX subscales were analyzed, only frustration showed a significant overall difference among robotic conditions in the overall cohort and among attending surgeons. In these groups, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions, whereas no significant differences among robotic conditions were observed for the remaining subscales \u003cb\u003e(Table\u0026nbsp;2)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eFor Task 2, the weighted NASA-TLX score did not show a significant overall difference among the three robotic conditions in the overall cohort or in the attending-surgeon and resident subgroups. However, in the analysis of individual NASA-TLX subscales, frustration was the only subscale that demonstrated a significant overall difference among robotic conditions in all three groups. In subscale-specific comparisons between robotic conditions, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions in the overall cohort and among attending surgeons. Meanwhile, in the resident subgroup, frustration was significantly higher with hinotori than with the da Vinci Xi with finger clutch alone. No significant differences among robotic conditions were observed for the remaining NASA-TLX subscales \u003cb\u003e(Table\u0026nbsp;3)\u003c/b\u003e.\u003c/p\u003e\u003cp\u003eFor Task 3, the weighted NASA-TLX score showed a significant overall difference between the three robotic conditions in the overall cohort, but no significant overall differences were observed in the attending-surgeon or resident subgroups. In the overall cohort, analysis of the individual NASA-TLX subscales demonstrated that only frustration had a significant overall difference among robotic conditions. In subscale-specific comparisons between platforms, frustration scores were significantly higher with hinotori than with either of the da Vinci Xi conditions, while no significant differences among robotic conditions were observed for the remaining subscales \u003cb\u003e(Table\u0026nbsp;4)\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this ex vivo simulation study, we compared surgeon performance and subjective workload between three robotic conditions: the da Vinci Xi with and without the finger clutch function, and the hinotori surgical robot system. Task completion times for all three basic tasks did not significantly differ between the robotic conditions in the overall cohort or in the attending-surgeon and resident subgroups. On the other hand, for Task 1 (camera movement and grasping) and Task 3 (suturing and knot tying), weighted NASA-TLX scores were significantly higher with hinotori than with the da Vinci Xi with finger clutch, but no significant differences were observed between hinotori and the da Vinci Xi without finger clutch for any of the three tasks.\u003c/p\u003e\u003cp\u003eOver the last decade, the landscape of robotic surgery in urology has dramatically changed, with the introduction of several new multiport robotic platforms including hinotori, in addition to the da Vinci systems. Early clinical outcomes with these systems in urology have generally been reported as comparable to those with da Vinci platforms including Xi [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The hinotori surgical robot system is the first domestically developed multiport robotic platform to be approved for clinical use in Japan. It is characterized by several unique design features, including eight-axis robotic arms and a docking-free design that differs from that of da Vinci Xi [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Early clinical reports from urologic oncology have shown that hinotori is feasible and safe for robot-assisted radical prostatectomy, robot-assisted partial nephrectomy, robot-assisted radical nephrectomy and robot-assisted radical nephroureterectomy [\u003cspan additionalcitationids=\"CR6 CR7 CR8\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. A previous propensity score\u0026ndash;matched comparison of robot-assisted partial nephrectomy using hinotori vs. the da Vinci system reported broadly comparable perioperative outcomes between platforms [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Similarly, we also conducted propensity score\u0026ndash;matched analyses of robot-assisted radical prostatectomy using two robotic platforms and showed largely comparable perioperative, oncologic and functional outcomes, despite longer operative and console times in the hinotori group [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, a recent systematic review of novel multiport robotic platforms in urology, which included hinotori, emphasized that most available data are still in the developmental or early exploratory stages and that high-quality comparative evidence remains limited [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Importantly, patient selection bias and other confounding factors cannot be fully eliminated in clinical series [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. To overcome these limitations, we suggest the importance of comparative evaluations using standardized training or bench models. Although Urade et al. reported on their participants\u0026rsquo; first-touch robotic skills using hinotori and its simulator, no prior studies have directly compared hinotori with the da Vinci system in an ex vivo or bench-top setting [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. To our knowledge, the present study is therefore the first ex vivo head-to-head comparison between the hinotori platform and the da Vinci Xi system using a standardized training model, with a specific focus on surgeon performance and subjective workload.\u003c/p\u003e\u003cp\u003eAlthough overall task efficiency was comparable between the hinotori and da Vinci Xi systems, perceived workload was shown to be influenced by console-related ergonomic factors, particularly the presence or absence of a finger clutch function. In addition, at the time of this study, the hinotori platform was relatively new to many of the participating surgeons, which might have contributed to increased subjective workload. In parallel with the accumulation of clinical experience, the hinotori system has undergone iterative hardware and software refinements. Finger clutch functionality and other ergonomic enhancements are now implemented in the latest hinotori generations, so it is reasonable to expect that there will be a progressive narrowing of the gap in perceived workload compared with the da Vinci Xi with finger clutch. Moreover, multiple development projects are underway to expand the capabilities and indications of hinotori, including broadening the instrument lineup, enhancing imaging systems and electrosurgical units, and developing intraoperative navigation systems and synchronized beds. The aim is to extend its use beyond current fields such as urology, gynecology and gastrointestinal surgery into cardiovascular and thoracic surgery [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, future-oriented initiatives involving remote surgery, increased robotic autonomy and artificial intelligence-based analysis of surgical procedures, together with plans for global deployment of the platform, suggest that the clinical utility and ergonomic performance of hinotori will continue to evolve and may ultimately approach or surpass that of existing established robotic systems.\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the sample size was relatively small and it was derived from a single institution, which may limit the generalizability of our findings. Nevertheless, the inclusion of both attending surgeons and residents, with balanced randomization between sequence groups, is thought to provide a pragmatic overview of performance across different experience levels. Second, we used a dry training model rather than animal or clinical procedures, so our results may not fully reflect the complexities of real-world surgery, including bleeding, tissue variability and intraoperative decision-making. However, the use of a standardized ex vivo model allowed us to isolate system-related differences in performance and workload while minimizing confounding by patient factors and case complexity. Third, although the tasks were designed to encompass key components of robotic surgery (camera control and grasping, precise cutting and continuous suturing), there is no universally accepted set of basic robotic tasks for cross-platform comparison. Different task designs or training curricula might yield somewhat different patterns of performance and workload. Finally, we evaluated only three relatively simple tasks in a simulated setting. Multi-step procedures and advanced reconstructive tasks might accentuate or modify the differences between systems seen here, and future studies should address more complex scenarios as well as learning-curve effects. Despite these limitations, we believe that our ex vivo study provides useful comparative data on the da Vinci Xi system and the newer hinotori platform from the perspective of surgeon performance and subjective workload. In the era of multiple available robotic systems, such benchmark comparisons can assist urologists and surgeons in other specialties in understanding platform-specific characteristics and in making informed decisions about system selection and training.\u003c/p\u003e\u003cp\u003eIn conclusion, this ex vivo comparison suggests that surgeon workload during robotic surgery may be strongly influenced by console-specific ergonomic features, particularly the presence or absence of a finger clutch function. At the same time, the overall task performance of the hinotori surgical robot system appeared broadly comparable to that of the da Vinci Xi system, indicating no major inferiority of hinotori in basic robotic skills.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eNASA-TLX = NASA Task Load Index\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge proofreading and editing by Benjamin Phillis, a Board-Certified Editor in the Life Sciences (BELS), at Wakayama Medical University. In addition, we used ChatGPT (OpenAI) to support part of the English translation under the supervision of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors significantly contributed to the present study. The conceptualization was by Shimpei Yamashita. The methodology was devised by Isao Hara and Yasuo Kohjimoto. The data collection was performed by Hiraku Yamamoto, Shimpei Yamashita, Hisanobu Tosuji, Nobuyuki Mashima, Ryusuke Deguchi, Yuya Iwahashi, Hiroki Kawabata, Satoshi Muraoka and Takahito Wakamiya. The statistical analyses were performed by Shimpei Yamashita. The original draft of the manuscript was written by Hiraku Yamamoto and Shimpei Yamashita, and it was reviewed and edited by Yasuo Kohjimoto. The study was supervised by Isao Hara and Yasuo Kohjimoto.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe present study did not receive any funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study did not involve human patients or animals and was conducted exclusively using an ex vivo training model with surgeon participants. According to the policies of Wakayama Medical University, formal review and approval by the institutional review board were not required for this type of educational simulation study. The study was conducted in accordance with the principles of the Declaration of Helsinki, as applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participating surgeons provided written informed consent prior to participation. No patients were involved in this research, so patient consent was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participating surgeons provided written informed consent for publication of the anonymized study data and images. As no patient data were included in this research, consent for publication from patients was not required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSalkowski M, Checcucci E, Chow AK, Rogers CC, Adbollah F, Liatsikos E, Dasgupta P, Guimaraes GC, Rassweiler J, Mottrie A, Breda A, Crivellaro S, Kaouk J, Porpiglia F, Autorino R (2023) New multiport robotic surgical systems: a comprehensive literature review of clinical outcomes in urology. 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Int J Urol 29(10):1213\u0026ndash;1220. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/iju.14973\u003c/span\u003e\u003cspan address=\"10.1111/iju.14973\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMotoyama D, Matsushita Y, Watanabe H, Tamura K, Otsuka A, Fujisawa M, Miyake H (2023) Perioperative outcomes of robot-assisted partial nephrectomy using hinotori versus da Vinci surgical robot system: a propensity score-matched analysis. J Robot Surg 17(5):2435\u0026ndash;2440. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11701-023-01614-x\u003c/span\u003e\u003cspan address=\"10.1007/s11701-023-01614-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKohjimoto Y, Yamashita S, Iwagami S, Muraoka S, Wakamiya T, Hara I (2024) hinotori(TM) vs. da Vinci(\u0026reg;): propensity score-matched analysis of surgical outcomes of robot-assisted radical prostatectomy. J Robot Surg 18(1):130. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11701-024-01877-y\u003c/span\u003e\u003cspan address=\"10.1007/s11701-024-01877-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eUrade T, Yamasaki N, Uemura M, Hirata J, Okamura Y, Mitani Y, Hattori T, Nanchi K, Ozawa S, Chihara Y, Chinzei K, Fujisawa M, Fukumoto T (2024) Assessment of first-touch skills in robotic surgical training using hi-Sim and the hinotori surgical robot system among surgeons and novices. Langenbecks Arch Surg 409(1):332. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00423-024-03514-6\u003c/span\u003e\u003cspan address=\"10.1007/s00423-024-03514-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-robotic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jors","sideBox":"Learn more about [Journal of Robotic Surgery](http://link.springer.com/journal/11701)","snPcode":"11701","submissionUrl":"https://submission.nature.com/new-submission/11701/3","title":"Journal of Robotic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"da Vinci, hinotori, robotic surgery, surgical training model, task workload","lastPublishedDoi":"10.21203/rs.3.rs-8313500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8313500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRobotic-assisted surgery is widely adopted in urology, but there is little comparative data between established and newly introduced platforms. We used an ex vivo training model to compare task performance and subjective workload between the widely-established da Vinci Xi system and the hinotori system, which was developed in Japan. In this prospective crossover study, 16 urologists performed three standardized tasks (camera manipulation and grasping, cutting, and suturing with knot tying) under three robotic conditions: using da Vinci Xi with finger clutch, using da Vinci Xi without finger clutch, and using hinotori. Task completion time was recorded for each trial, and subjective workload was assessed after every task using the weighted NASA Task Load Index (NASA-TLX). Median task completion times tended to be longer with hinotori than with either of the da Vinci Xi conditions, although no significant differences were observed between the three systems for any of the tasks. In contrast, weighted NASA-TLX scores were significantly higher with hinotori than with the da Vinci Xi with finger clutch for the camera/grasping and suturing tasks, whereas no significant differences were detected between hinotori and the da Vinci Xi without finger clutch. In conclusion, the hinotori system demonstrated task performance comparable to the da Vinci Xi platform, while subjective workload was higher relative to the da Vinci Xi when the finger clutch function was used. Our results suggest that surgeon workload during robotic surgery may be strongly influenced by console-specific ergonomic features, particularly the presence or absence of a finger clutch function.\u003c/p\u003e","manuscriptTitle":"Comparison of the da Vinci Xi and hinotori surgical robotic systems using a training model: an ex vivo study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 16:12:30","doi":"10.21203/rs.3.rs-8313500/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-04T20:51:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T20:42:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"189352130246723377102220958772265197916","date":"2026-01-02T15:12:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"12299108125132853004022136537698449607","date":"2025-12-30T15:26:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21560617174521493132689245468735760355","date":"2025-12-17T17:11:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-16T22:33:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201437917469698805496198900866710599995","date":"2025-12-12T01:28:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317874604993941595492222854730449164629","date":"2025-12-12T00:03:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172470412136947365155103901497761086617","date":"2025-12-10T02:34:36+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-09T21:30:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-09T21:26:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-09T13:08:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Robotic Surgery","date":"2025-12-09T05:43:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-robotic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jors","sideBox":"Learn more about [Journal of Robotic Surgery](http://link.springer.com/journal/11701)","snPcode":"11701","submissionUrl":"https://submission.nature.com/new-submission/11701/3","title":"Journal of Robotic Surgery","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3a69c0c5-c40c-4e01-8919-885a114f4abb","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:02:20+00:00","versionOfRecord":{"articleIdentity":"rs-8313500","link":"https://doi.org/10.1007/s11701-026-03192-0","journal":{"identity":"journal-of-robotic-surgery","isVorOnly":false,"title":"Journal of Robotic Surgery"},"publishedOn":"2026-02-12 15:59:06","publishedOnDateReadable":"February 12th, 2026"},"versionCreatedAt":"2025-12-15 16:12:30","video":"","vorDoi":"10.1007/s11701-026-03192-0","vorDoiUrl":"https://doi.org/10.1007/s11701-026-03192-0","workflowStages":[]},"version":"v1","identity":"rs-8313500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8313500","identity":"rs-8313500","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}