Augmented reality enhances spatial cognition in hepatic surgical anatomy: evidence from a randomized controlled study

Augmented reality enhances spatial cognition in hepatic surgical anatomy: evidence from a randomized controlled study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Augmented reality enhances spatial cognition in hepatic surgical anatomy: evidence from a randomized controlled study DANDAN BAO, Chenghao Zhang, Senrui Chen, Zhangwei Yang, Keqin Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9358745/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background Understanding the complex three-dimensional structure of hepatic anatomy remains challenging in traditional anatomy education. Augmented reality (AR) offers a potential solution by enabling interactive visualization of anatomical structures. Methods In this randomized controlled study, participants were assigned to either conventional teaching or AR-assisted hepatic anatomy training. The AR system provided interactive three-dimensional visualization of liver segments and vascular structures. Outcomes included anatomical knowledge assessment, spatial cognition performance, and usability evaluation. Results Participants receiving AR-assisted training demonstrated significantly improved understanding of hepatic segmental anatomy and vascular relationships compared with the control group. Spatial reasoning ability was also enhanced. Usability assessment indicated high acceptance and perceived effectiveness of the AR system. Conclusions AR-assisted training improves anatomical comprehension and spatial cognition in hepatic surgical anatomy. This approach provides an effective supplement to conventional anatomy education and may facilitate clinically relevant anatomical learning. Health sciences/Anatomy Health sciences/Medical research Augmented reality Anatomical education Liver anatomy Spatial cognition Medical education Three-dimensional visualization Figures Figure 1 Figure 2 Figure 3 Introduction Liver cancer remains a major global health burden and is among the leading causes of cancer-related death worldwide[ 1 ]. In China, liver cancer continues to account for a substantial proportion of cancer incidence and mortality, underscoring its importance as a national public health challenge[ 2 ]. Curative treatment for resectable disease relies largely on hepatectomy, which in turn requires precise knowledge of Couinaud segmentation and of the spatial relationships among the portal venous system, hepatic veins, and biliary tree[ 3 , 4 ]. For trainees, hepatic surgical anatomy is particularly difficult to master because clinically relevant structures overlap in three-dimensional space and show substantial interindividual variation[ 3 , 4 ]. Conventional teaching based on atlases, radiological images, cadaveric dissection, and apprenticeship remains fundamental in anatomy and surgical education[ 5 ]. However, these approaches often require demanding mental transformation from two-dimensional views to three-dimensional anatomy, a process that can hinder spatial understanding in learners with lower visual-spatial ability[ 6 , 7 ]. Augmented reality (AR) has emerged as a promising adjunct for anatomy and surgical education because it enables interactive visualization of complex three-dimensional structures in an immersive learning environment [ 8 , 9 ]. In anatomy learning, AR-based visualization has been reported to support spatial comprehension, particularly when conventional two-dimensional resources are insufficient for understanding anatomical relationships[ 7 , 8 ]. In hepatobiliary surgery, AR has been applied mainly to preoperative planning and intraoperative navigation, where its value lies in improving visualization of vascular and biliary anatomy and facilitating interpretation of patient-specific anatomy[ 10 , 11 ]. Despite these advances, the educational literature in liver surgery remains relatively limited, and structured evidence for anatomy-focused training interventions is still insufficient[ 12 ]. Most available hepatobiliary AR studies emphasize technical feasibility or operative guidance rather than learner-centered anatomy teaching and assessment [ 10 , 11 ]. Therefore, we developed an AR-based liver surgery training system integrating interactive holographic visualization, haptic simulation, and performance tracking, and conducted a randomized controlled study to evaluate its effectiveness in improving anatomical understanding, operative planning, and learner engagement compared with conventional teaching. Methods 2.1. Participants and study design This prospective randomized controlled study was conducted at Wenzhou People’s Hospital. Sixty third- and fourth-year medical students were recruited consecutively between August, 2023 and June, 2025. Eligible participants had not received prior formal training in hepatic anatomy and had no previous experience with hepatobiliary anatomy electives, liver surgery rotations, or augmented reality (AR)-assisted anatomy learning. Students with prior exposure to these contents were excluded in order to reduce baseline differences in anatomical knowledge. After enrolment, participants were randomly allocated in a 1:1 ratio to either the AR group (n = 30) or the conventional teaching group (n = 30). Randomization was performed using a computer-generated random sequence prepared by an independent investigator who was not involved in teaching or outcome assessment. Group allocation was concealed until the start of the intervention. Owing to the nature of the educational intervention, blinding of participants and instructors was not feasible. The study protocol was approved by the Ethics Committee of Wenzhou People’s Hospital (Approval No. KY-202509-181). Written informed consent was obtained from all participants before study entry. Participation was voluntary and had no influence on academic evaluation. All methods were performed in accordance with the relevant guidelines and regulations. 2.2. AR teaching platform The AR teaching system was developed from four anonymized biphasic CT/MRI datasets representative of normal hepatic anatomy. Image segmentation of the liver parenchyma, portal venous branches, hepatic veins, and biliary structures was performed semi-automatically using ITK-SNAP, followed by manual refinement by the study team. Anatomical accuracy of the segmented structures was reviewed by two hepatobiliary surgeons and one radiologist. Segmentation quality was quantified using the Dice similarity coefficient, with a mean value of 0.92 ± 0.03. The reconstructed three-dimensional models were imported into Unity3D and deployed on Microsoft HoloLens 2 using the Mixed Reality Toolkit. The platform enabled real-time interaction with the holographic models, including rotation, magnification, transparency adjustment, and layer-by-layer exploration of the liver parenchyma, portal venous system, hepatic venous drainage, and biliary anatomy (Fig. 1 ). 2.3. Educational intervention . Both groups received the same instructional content, covering Couinaud liver segmentation, major portal venous branches, hepatic veins, and the main biliary anatomy. Teaching was delivered by the same instructor team in order to minimize variability in instructional style. Each session lasted approximately 2 hours. In the AR group, students used the AR platform for guided exploration of the holographic liver models and completed short structured quizzes after each anatomical module. In the conventional teaching group, students received standard instruction using two-dimensional diagrams, radiological images, and cadaveric photographs presenting the same anatomical content (Fig. 2 ). Post-training assessments were completed immediately after the session in both groups, and follow-up knowledge retention was assessed 4 weeks later. 2.4. Outcome measures Primary educational outcomes were: (1) a 20-item multiple-choice test covering core hepatic anatomy, (2) a practical identification task requiring recognition of major anatomical landmarks on images and diagrams, (3) training time required to complete the session, and (4) knowledge retention 4 weeks after training. Secondary outcomes were learner engagement and usability. Secondary outcomes were learner engagement and usability. Learner engagement was assessed using a study-specific five-item survey addressing concentration, interest, motivation, perceived usefulness, and willingness to recommend the teaching approach. The full English version of this instrument is provided in Supplementary Material 1. Usability of the AR system was assessed only in the AR group using the System Usability Scale (SUS), a validated 10-item instrument scored from 0 to 100, with higher scores indicate better perceived usability. The full SUS instrument is provided in Supplementary Material 2. 2.5 Statistical analysis Statistical analyses were performed using SPSS version 27 (IBM Corp., Armonk, NY, USA). Continuous variables were tested for normality using the Shapiro–Wilk test and are presented as mean ± standard deviation (SD) or median (interquartile range), as appropriate. Categorical variables are presented as number (percentage). Between-group comparisons were performed using the independent-samples t test or Mann–Whitney U test for continuous variables and the chi-square test or Fisher’s exact test for categorical variables, as appropriate. All tests were two-sided, and p < 0.05 was considered statistically significant. Results 3.1. Participant flow Sixty medical students were enrolled and randomized, with 30 allocated to the AR group and 30 to the conventional teaching group. All participants completed the assigned teaching session and the immediate post-training assessment. Follow-up assessment at 4 weeks was completed by all participants. 3.2. Primary educational outcomes AR-assisted teaching was associated with better immediate learning outcomes than conventional instruction. Post-training test scores were significantly higher in the AR group than in the control group (4.5 ± 0.4 vs. 3.5 ± 0.6, p < 0.001). In the practical identification task, students in the AR group showed greater accuracy in recognizing portal venous branching patterns than those in the control group (92% vs. 58%, p = 0.002), indicating improved three-dimensional anatomical understanding. Training efficiency also differed between groups. The mean time required to complete the learning session was shorter in the AR group than in the conventional teaching group (3.2 ± 0.8 h vs. 5.4 ± 1.2 h, p = 0.01). At 4-week follow-up, knowledge retention remained higher in the AR group (85% vs. 62%, p = 0.03), suggesting a sustained educational benefit (Table 1 , Fig. 3 ). Table 1 Primary educational outcomes after AR-assisted and conventional teaching. Outcome AR Group Control Group p value Post- training test scores 4.5 ± 0.4 3.5 ± 0.6 < 0.001 Spatial recognition accuracy 92% 58% 0.002 Training time, h 3.2 ± 0.8 h 5.4 ± 1.2 h 0.01 Knowledge retention at 4 weeks 85% 62% 0.03 Footnote : Data are presented as mean ± SD or percentage, as appropriate. 3.3. Learner engagement and usability Learner engagement was greater in the AR group. Self-reported interest scores were significantly higher after AR-assisted teaching than after conventional instruction (4.6 ± 0.3 vs. 2.9 ± 0.7, p < 0.001). In addition, AR sessions were associated with a higher level of active participation, reflected by a greater number of student-initiated questions during training. Usability of the AR platform was assessed in the AR group using the System Usability Scale. The mean SUS score was 82 ± 6, indicating high perceived usability. Furthermore, 94% of participants in the AR group reported that they preferred AR-assisted learning to textbook-based study when learning complex hepatic anatomy (Table 2 ). Table 2 Learner engagement and usability outcomes. Outcome AR Group Control Group p value Interest score (5-point Likert scale) 4.6 ± 0.3 2.9 ± 0.7 < 0.001 System Usability Scale 82 ± 6 N/A N/A Preference for AR over textbooks 94% N/A N/A Footnote : Usability and preference were assessed only in the AR group. 3.4. Summary of findings Taken together, these findings indicate that AR-assisted hepatic anatomy teaching improved anatomical test performance, spatial recognition, learning efficiency, and short-term knowledge retention, while also achieving high learner engagement and favorable usability ratings. Discussion This randomized controlled study showed that AR-assisted teaching improved several key aspects of hepatic anatomy learning. Compared with conventional instruction, AR-based teaching was associated with better immediate test performance, improved spatial recognition of anatomically relevant structures, shorter training time, and better knowledge retention at 4 weeks. Taken together, these findings support the educational value of immersive three-dimensional visualization for anatomically complex hepatobiliary relationships that are difficult to fully appreciate using two-dimensional teaching materials alone[ 9 , 13 ]. From the perspective of anatomy education, the principal strength of AR in the present study appears to lie in its support for spatial understanding. Hepatic anatomy requires learners to integrate Couinaud segmentation with the three-dimensional arrangement of the portal venous system, hepatic veins, and biliary structures, which is a well-recognized source of difficulty in anatomical training[ 14 ]. Conventional atlases and sectional images require substantial mental transformation from two-dimensional representations into three-dimensional structures, increasing cognitive load for novice learners [ 15 ]. By allowing users to rotate, magnify, and selectively visualize anatomical layers, AR-based platforms may reduce this cognitive burden and facilitate the construction of accurate mental models of anatomical relationships[ 16 , 17 ]. The present findings are also relevant to the teaching of clinically applied anatomy. In hepatobiliary surgery, anatomical understanding requires not only identification of structures but also interpretation of their spatial relationships in a manner relevant to surgical planning and intraoperative orientation[ 18 ]. Imaging-derived three-dimensional reconstructions have increasingly been used to bridge this gap between anatomical education and clinical application, particularly in liver surgery, where anatomical variability is common and clinically significant [ 19 , 20 ]. In this context, AR-based visualization may enhance the integration of anatomical knowledge with clinically meaningful interpretation. Another notable finding was the higher learner engagement observed in the AR group. Although engagement is not a direct measure of learning outcome, active interaction with educational content has been associated with improved attention and knowledge retention in medical education[ 21 ]. Interactive visualization tools may promote repeated exploration of complex anatomical structures and encourage self-directed learning, which may partially explain the improved short-term retention observed in the present study[ 22 ]. These findings should also be interpreted in the context of the limitations of traditional anatomy teaching resources. Cadaveric dissection remains the gold standard for anatomical education; however, access to cadaveric material is limited in many institutions, and available specimens may not adequately represent the spectrum of anatomical variation encountered in clinical practice[ 23 , 24 ]. Digital and imaging-based models provide an opportunity for repeated, standardized exposure to anatomical structures and may serve as an effective adjunct to conventional teaching methods, particularly in spatially complex regions such as the liver[ 25 ] Several limitations should be acknowledged. First, this was a single-center study with a relatively small sample size, which may limit generalizability. Second, the participants were medical students rather than surgical residents or practicing trainees, and the findings therefore primarily reflect early-stage anatomy learning rather than technical or intraoperative performance. Third, learner engagement was assessed using a project-specific questionnaire that has face validity but lacks the broader external validation of established educational instruments. Fourth, the duration of follow-up was limited, and it remains uncertain whether the observed educational benefit is maintained over longer periods or transferred to more clinically authentic tasks. Future studies should evaluate AR-assisted anatomy teaching across different learner populations, include longer follow-up, and compare immersive visualization not only with conventional instruction but also with other three-dimensional teaching modalities[ 13 , 16 ]. Overall, the present study suggests that AR-assisted teaching may be a useful adjunct in hepatic anatomy education, particularly for learning anatomically complex spatial relationships. Its contribution appears to be most relevant in supporting three-dimensional understanding and in linking anatomical knowledge with clinically applied interpretation. Conclusion AR-assisted teaching improved anatomical comprehension, spatial recognition, learning efficiency, and short-term retention in hepatic anatomy education. As an adjunct to conventional teaching, it may be particularly useful for anatomically complex and clinically applied subject areas in which spatial understanding is essential. AR-based visualization may therefore broaden access to structured hepatic anatomy learning, especially in settings where cadaveric resources are limited. Declarations Consent for publication This study does not contain identifying images or personal details that would compromise participant anonymity; therefore, consent for publication was not required. Data availability The datasets used and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Authors’ contributions DB and CZ designed the study. SC, ZY, KL, PW, and YL performed data collection. YH supervised the study and revised the manuscript. All authors read and approved the final manuscript. Acknowledgements We thank all participants for their involvement in this study. Funding This study was supported by Shangda Translational Medicine Fund of the Shanghai University Wenzhou Research Institute（Grant No. SDTMF2023EP05） and Wenzhou Municipal Science and Technology Bureau Project（Grant No.2022Y1645）. Clinical trial registration : not applicable. 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Acta Med Acad, 54(2): pp. 164–171.dol: (2025). 10.5644/ama2006-124.481 Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1.docx SupplementaryMaterial2.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 12 May, 2026 Reviewers invited by journal 04 May, 2026 Editor assigned by journal 04 May, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 13 Apr, 2026 First submitted to journal 13 Apr, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9358745","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":635382541,"identity":"5ce4e686-d756-45a6-b424-7b3e97c44f07","order_by":0,"name":"DANDAN BAO","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACAyCWYGBgBlLMBw58+EGaFrbEgzN7SNPCY3yYg40ILebshw/e+LnDWt6c/8yHwww8DPL8Ygfwa7HsSUu27D2TbrhzRu6GwwUWDIYzZycQcNiBHDMJ3rbDjBtu8G44PIOHIcHgNiEt59+YSf5tO2y/4fyZB4d52IjRciPHTBpoS+KGAzkMxGmxnPEs2Vq2LT15w400A2AgSxD2izl/8sGbb9usbTecP/z4w4cfNvL80gS0oAMJ0pSPglEwCkbBKMAOAIeVST+yIJcoAAAAAElFTkSuQmCC","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":true,"prefix":"","firstName":"DANDAN","middleName":"","lastName":"BAO","suffix":""},{"id":635382551,"identity":"b9e81ebb-61b6-452d-9aa5-a7c0cec612e0","order_by":1,"name":"Chenghao Zhang","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chenghao","middleName":"","lastName":"Zhang","suffix":""},{"id":635382553,"identity":"064094e0-a4cf-4d4b-befa-2775791fc000","order_by":2,"name":"Senrui Chen","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Senrui","middleName":"","lastName":"Chen","suffix":""},{"id":635382554,"identity":"ad820047-ff0d-4ba5-8ba7-537ea05ba405","order_by":3,"name":"Zhangwei Yang","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhangwei","middleName":"","lastName":"Yang","suffix":""},{"id":635382557,"identity":"cf482320-10d1-43c8-88fa-71056e7725bf","order_by":4,"name":"Keqin Li","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Keqin","middleName":"","lastName":"Li","suffix":""},{"id":635382558,"identity":"e17bb7ab-7ff1-45da-adeb-1b2bf35c95d6","order_by":5,"name":"Pengwei Wang","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Pengwei","middleName":"","lastName":"Wang","suffix":""},{"id":635382560,"identity":"060ef28d-8874-4a76-b19f-b7f07e592da3","order_by":6,"name":"Yuncheng Luo","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuncheng","middleName":"","lastName":"Luo","suffix":""},{"id":635382563,"identity":"41a96220-1f69-4721-a526-8aece8977680","order_by":7,"name":"Yiren Hu","email":"","orcid":"","institution":"Wenzhou City People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yiren","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2026-04-08 15:10:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9358745/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9358745/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109101601,"identity":"16e727ae-2ce8-4b7b-86fd-880a32362dfa","added_by":"auto","created_at":"2026-05-12 14:29:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":766460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAR-based hepatic anatomy teaching platform.\u003c/strong\u003e Representative holographic models show the liver parenchyma, portal venous branches, hepatic veins, and biliary structures. The platform allows rotation, magnification, transparency adjustment, and layer-by-layer exploration of anatomical relationships.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/e419aa0d3b3feb03b1ea2f48.png"},{"id":109101669,"identity":"a03564c7-05d8-48a1-aa66-612865940f0d","added_by":"auto","created_at":"2026-05-12 14:29:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":443608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConceptual framework of AR-assisted anatomy learning.\u003c/strong\u003e This schematic illustrates the mechanisms by which augmented reality (AR) enhances the learning of hepatic anatomy. Compared with conventional two-dimensional teaching, AR provides interactive three-dimensional visualization, which reduces cognitive load and facilitates spatial cognition. These mechanisms promote active learner engagement and ultimately lead to improved learning outcomes, including enhanced test performance, better spatial recognition, shorter training time, and improved knowledge retention at 4 weeks (Solid arrows indicate observed or supported associations, whereas dashed arrows indicate proposed mechanisms not directly measured in this study).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/39d3454ef0e42ae98d8e61fb.png"},{"id":109101635,"identity":"1835332f-2b59-49c1-9283-411a3d27fc16","added_by":"auto","created_at":"2026-05-12 14:29:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":917289,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of learning outcomes between AR-assisted and conventional teaching groups.\u003c/strong\u003e Bar graphs show immediate post-training knowledge test scores, training time and 4-week knowledge retention in 30 participants per group.\u003c/p\u003e\n\u003cp\u003eThe AR-assisted group demonstrated significantly higher scores compared with the conventional teaching group in all measured outcomes. Data are presented as mean ± SD; \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 (independent-samples t-test). Error bars represent standard deviation.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/3c0f9d34ce05aac1404a9258.png"},{"id":109296068,"identity":"2cacc977-8ac1-451c-81b4-24565ea4021a","added_by":"auto","created_at":"2026-05-15 08:45:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2570276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/49528cf2-d9a7-4712-978a-c480fddd2b8d.pdf"},{"id":109101670,"identity":"aa998af1-5dcf-4345-94fd-18fbfca5b495","added_by":"auto","created_at":"2026-05-12 14:29:34","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":29778,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/4a303c6e752c1b98af2235c3.docx"},{"id":109101662,"identity":"f268edcb-eee5-4d97-a41f-03c147c1a509","added_by":"auto","created_at":"2026-05-12 14:29:30","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":168314,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9358745/v1/9857e775796e0486fb1ac69b.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Augmented reality enhances spatial cognition in hepatic surgical anatomy: evidence from a randomized controlled study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLiver cancer remains a major global health burden and is among the leading causes of cancer-related death worldwide[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In China, liver cancer continues to account for a substantial proportion of cancer incidence and mortality, underscoring its importance as a national public health challenge[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Curative treatment for resectable disease relies largely on hepatectomy, which in turn requires precise knowledge of Couinaud segmentation and of the spatial relationships among the portal venous system, hepatic veins, and biliary tree[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor trainees, hepatic surgical anatomy is particularly difficult to master because clinically relevant structures overlap in three-dimensional space and show substantial interindividual variation[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Conventional teaching based on atlases, radiological images, cadaveric dissection, and apprenticeship remains fundamental in anatomy and surgical education[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, these approaches often require demanding mental transformation from two-dimensional views to three-dimensional anatomy, a process that can hinder spatial understanding in learners with lower visual-spatial ability[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAugmented reality (AR) has emerged as a promising adjunct for anatomy and surgical education because it enables interactive visualization of complex three-dimensional structures in an immersive learning environment [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In anatomy learning, AR-based visualization has been reported to support spatial comprehension, particularly when conventional two-dimensional resources are insufficient for understanding anatomical relationships[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In hepatobiliary surgery, AR has been applied mainly to preoperative planning and intraoperative navigation, where its value lies in improving visualization of vascular and biliary anatomy and facilitating interpretation of patient-specific anatomy[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite these advances, the educational literature in liver surgery remains relatively limited, and structured evidence for anatomy-focused training interventions is still insufficient[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Most available hepatobiliary AR studies emphasize technical feasibility or operative guidance rather than learner-centered anatomy teaching and assessment [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, we developed an AR-based liver surgery training system integrating interactive holographic visualization, haptic simulation, and performance tracking, and conducted a randomized controlled study to evaluate its effectiveness in improving anatomical understanding, operative planning, and learner engagement compared with conventional teaching.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Participants and study design\u003c/h2\u003e \u003cp\u003eThis prospective randomized controlled study was conducted at Wenzhou People\u0026rsquo;s Hospital. Sixty third- and fourth-year medical students were recruited consecutively between August, 2023 and June, 2025. Eligible participants had not received prior formal training in hepatic anatomy and had no previous experience with hepatobiliary anatomy electives, liver surgery rotations, or augmented reality (AR)-assisted anatomy learning. Students with prior exposure to these contents were excluded in order to reduce baseline differences in anatomical knowledge.\u003c/p\u003e \u003cp\u003eAfter enrolment, participants were randomly allocated in a 1:1 ratio to either the AR group (n\u0026thinsp;=\u0026thinsp;30) or the conventional teaching group (n\u0026thinsp;=\u0026thinsp;30). Randomization was performed using a computer-generated random sequence prepared by an independent investigator who was not involved in teaching or outcome assessment. Group allocation was concealed until the start of the intervention. Owing to the nature of the educational intervention, blinding of participants and instructors was not feasible.\u003c/p\u003e \u003cp\u003eThe study protocol was approved by the Ethics Committee of Wenzhou People\u0026rsquo;s Hospital (Approval No. KY-202509-181). Written informed consent was obtained from all participants before study entry. Participation was voluntary and had no influence on academic evaluation. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. AR teaching platform\u003c/h2\u003e \u003cp\u003eThe AR teaching system was developed from four anonymized biphasic CT/MRI datasets representative of normal hepatic anatomy. Image segmentation of the liver parenchyma, portal venous branches, hepatic veins, and biliary structures was performed semi-automatically using ITK-SNAP, followed by manual refinement by the study team. Anatomical accuracy of the segmented structures was reviewed by two hepatobiliary surgeons and one radiologist. Segmentation quality was quantified using the Dice similarity coefficient, with a mean value of 0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03.\u003c/p\u003e \u003cp\u003eThe reconstructed three-dimensional models were imported into Unity3D and deployed on Microsoft HoloLens 2 using the Mixed Reality Toolkit. The platform enabled real-time interaction with the holographic models, including rotation, magnification, transparency adjustment, and layer-by-layer exploration of the liver parenchyma, portal venous system, hepatic venous drainage, and biliary anatomy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e2.3. Educational intervention\u003c/b\u003e.\u003c/h2\u003e \u003cp\u003eBoth groups received the same instructional content, covering Couinaud liver segmentation, major portal venous branches, hepatic veins, and the main biliary anatomy. Teaching was delivered by the same instructor team in order to minimize variability in instructional style.\u003c/p\u003e \u003cp\u003eEach session lasted approximately 2 hours. In the AR group, students used the AR platform for guided exploration of the holographic liver models and completed short structured quizzes after each anatomical module. In the conventional teaching group, students received standard instruction using two-dimensional diagrams, radiological images, and cadaveric photographs presenting the same anatomical content (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Post-training assessments were completed immediately after the session in both groups, and follow-up knowledge retention was assessed 4 weeks later.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Outcome measures\u003c/h2\u003e \u003cp\u003ePrimary educational outcomes were: (1) a 20-item multiple-choice test covering core hepatic anatomy, (2) a practical identification task requiring recognition of major anatomical landmarks on images and diagrams, (3) training time required to complete the session, and (4) knowledge retention 4 weeks after training. Secondary outcomes were learner engagement and usability.\u003c/p\u003e \u003cp\u003eSecondary outcomes were learner engagement and usability. Learner engagement was assessed using a study-specific five-item survey addressing concentration, interest, motivation, perceived usefulness, and willingness to recommend the teaching approach. The full English version of this instrument is provided in Supplementary Material 1.\u003c/p\u003e \u003cp\u003eUsability of the AR system was assessed only in the AR group using the System Usability Scale (SUS), a validated 10-item instrument scored from 0 to 100, with higher scores indicate better perceived usability. The full SUS instrument is provided in Supplementary Material 2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS version 27 (IBM Corp., Armonk, NY, USA). Continuous variables were tested for normality using the Shapiro\u0026ndash;Wilk test and are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median (interquartile range), as appropriate. Categorical variables are presented as number (percentage). Between-group comparisons were performed using the independent-samples t test or Mann\u0026ndash;Whitney U test for continuous variables and the chi-square test or Fisher\u0026rsquo;s exact test for categorical variables, as appropriate. All tests were two-sided, and p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Participant flow\u003c/h2\u003e \u003cp\u003eSixty medical students were enrolled and randomized, with 30 allocated to the AR group and 30 to the conventional teaching group. All participants completed the assigned teaching session and the immediate post-training assessment. Follow-up assessment at 4 weeks was completed by all participants.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Primary educational outcomes\u003c/h2\u003e \u003cp\u003eAR-assisted teaching was associated with better immediate learning outcomes than conventional instruction. Post-training test scores were significantly higher in the AR group than in the control group (4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4 vs. 3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the practical identification task, students in the AR group showed greater accuracy in recognizing portal venous branching patterns than those in the control group (92% vs. 58%, p\u0026thinsp;=\u0026thinsp;0.002), indicating improved three-dimensional anatomical understanding.\u003c/p\u003e \u003cp\u003eTraining efficiency also differed between groups. The mean time required to complete the learning session was shorter in the AR group than in the conventional teaching group (3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 h vs. 5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 h, p\u0026thinsp;=\u0026thinsp;0.01). At 4-week follow-up, knowledge retention remained higher in the AR group (85% vs. 62%, p\u0026thinsp;=\u0026thinsp;0.03), suggesting a sustained educational benefit (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimary educational outcomes after AR-assisted and conventional teaching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAR Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost- training test scores\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpatial recognition accuracy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraining time, h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 h\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKnowledge retention at 4 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or percentage, as appropriate.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Learner engagement and usability\u003c/h2\u003e \u003cp\u003eLearner engagement was greater in the AR group. Self-reported interest scores were significantly higher after AR-assisted teaching than after conventional instruction (4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3 vs. 2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In addition, AR sessions were associated with a higher level of active participation, reflected by a greater number of student-initiated questions during training.\u003c/p\u003e \u003cp\u003eUsability of the AR platform was assessed in the AR group using the System Usability Scale. The mean SUS score was 82\u0026thinsp;\u0026plusmn;\u0026thinsp;6, indicating high perceived usability. Furthermore, 94% of participants in the AR group reported that they preferred AR-assisted learning to textbook-based study when learning complex hepatic anatomy (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLearner engagement and usability outcomes.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAR Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInterest score (5-point Likert scale)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystem Usability Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreference for AR over textbooks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eFootnote\u003c/b\u003e: Usability and preference were assessed only in the AR group.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Summary of findings\u003c/h2\u003e \u003cp\u003eTaken together, these findings indicate that AR-assisted hepatic anatomy teaching improved anatomical test performance, spatial recognition, learning efficiency, and short-term knowledge retention, while also achieving high learner engagement and favorable usability ratings.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis randomized controlled study showed that AR-assisted teaching improved several key aspects of hepatic anatomy learning. Compared with conventional instruction, AR-based teaching was associated with better immediate test performance, improved spatial recognition of anatomically relevant structures, shorter training time, and better knowledge retention at 4 weeks. Taken together, these findings support the educational value of immersive three-dimensional visualization for anatomically complex hepatobiliary relationships that are difficult to fully appreciate using two-dimensional teaching materials alone[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom the perspective of anatomy education, the principal strength of AR in the present study appears to lie in its support for spatial understanding. Hepatic anatomy requires learners to integrate Couinaud segmentation with the three-dimensional arrangement of the portal venous system, hepatic veins, and biliary structures, which is a well-recognized source of difficulty in anatomical training[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Conventional atlases and sectional images require substantial mental transformation from two-dimensional representations into three-dimensional structures, increasing cognitive load for novice learners [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. By allowing users to rotate, magnify, and selectively visualize anatomical layers, AR-based platforms may reduce this cognitive burden and facilitate the construction of accurate mental models of anatomical relationships[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe present findings are also relevant to the teaching of clinically applied anatomy. In hepatobiliary surgery, anatomical understanding requires not only identification of structures but also interpretation of their spatial relationships in a manner relevant to surgical planning and intraoperative orientation[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Imaging-derived three-dimensional reconstructions have increasingly been used to bridge this gap between anatomical education and clinical application, particularly in liver surgery, where anatomical variability is common and clinically significant [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In this context, AR-based visualization may enhance the integration of anatomical knowledge with clinically meaningful interpretation.\u003c/p\u003e \u003cp\u003eAnother notable finding was the higher learner engagement observed in the AR group. Although engagement is not a direct measure of learning outcome, active interaction with educational content has been associated with improved attention and knowledge retention in medical education[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Interactive visualization tools may promote repeated exploration of complex anatomical structures and encourage self-directed learning, which may partially explain the improved short-term retention observed in the present study[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese findings should also be interpreted in the context of the limitations of traditional anatomy teaching resources. Cadaveric dissection remains the gold standard for anatomical education; however, access to cadaveric material is limited in many institutions, and available specimens may not adequately represent the spectrum of anatomical variation encountered in clinical practice[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Digital and imaging-based models provide an opportunity for repeated, standardized exposure to anatomical structures and may serve as an effective adjunct to conventional teaching methods, particularly in spatially complex regions such as the liver[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, this was a single-center study with a relatively small sample size, which may limit generalizability. Second, the participants were medical students rather than surgical residents or practicing trainees, and the findings therefore primarily reflect early-stage anatomy learning rather than technical or intraoperative performance. Third, learner engagement was assessed using a project-specific questionnaire that has face validity but lacks the broader external validation of established educational instruments. Fourth, the duration of follow-up was limited, and it remains uncertain whether the observed educational benefit is maintained over longer periods or transferred to more clinically authentic tasks. Future studies should evaluate AR-assisted anatomy teaching across different learner populations, include longer follow-up, and compare immersive visualization not only with conventional instruction but also with other three-dimensional teaching modalities[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOverall, the present study suggests that AR-assisted teaching may be a useful adjunct in hepatic anatomy education, particularly for learning anatomically complex spatial relationships. Its contribution appears to be most relevant in supporting three-dimensional understanding and in linking anatomical knowledge with clinically applied interpretation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAR-assisted teaching improved anatomical comprehension, spatial recognition, learning efficiency, and short-term retention in hepatic anatomy education. As an adjunct to conventional teaching, it may be particularly useful for anatomically complex and clinically applied subject areas in which spatial understanding is essential. AR-based visualization may therefore broaden access to structured hepatic anatomy learning, especially in settings where cadaveric resources are limited.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eThis study does not contain identifying images or personal details that would compromise participant anonymity; therefore, consent for publication was not required.\u003c/p\u003e\n\u003ch2\u003eData availability\u003c/h2\u003e\n\u003cp\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026rsquo; contributions\u003c/h2\u003e\n\u003cp\u003eDB and CZ designed the study. SC, ZY, KL, PW, and YL performed data collection. YH supervised the study and revised the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank all participants for their involvement in this study.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by Shangda Translational Medicine Fund of the Shanghai University Wenzhou Research Institute（Grant No. SDTMF2023EP05） and Wenzhou Municipal Science and Technology Bureau Project（Grant No.2022Y1645）.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration\u003c/strong\u003e: not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray, F. et al. \u003cem\u003eGlobal cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.\u003c/em\u003e CA Cancer J Clin, 74(3): pp. 229\u0026ndash;263.dol: (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3322/caac.21834\u003c/span\u003e\u003cspan address=\"10.3322/caac.21834\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan, B. et al. \u003cem\u003eCancer incidence and mortality in China, 2022.\u003c/em\u003e J Natl Cancer Cent, 4(1): pp. 47\u0026ndash;53.dol: (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jncc.2024.01.006\u003c/span\u003e\u003cspan address=\"10.1016/j.jncc.2024.01.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCatalano, O. 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Augmented reality (AR) offers a potential solution by enabling interactive visualization of anatomical structures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eIn this randomized controlled study, participants were assigned to either conventional teaching or AR-assisted hepatic anatomy training. The AR system provided interactive three-dimensional visualization of liver segments and vascular structures. Outcomes included anatomical knowledge assessment, spatial cognition performance, and usability evaluation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eParticipants receiving AR-assisted training demonstrated significantly improved understanding of hepatic segmental anatomy and vascular relationships compared with the control group. Spatial reasoning ability was also enhanced. Usability assessment indicated high acceptance and perceived effectiveness of the AR system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eAR-assisted training improves anatomical comprehension and spatial cognition in hepatic surgical anatomy. This approach provides an effective supplement to conventional anatomy education and may facilitate clinically relevant anatomical learning.\u003c/p\u003e","manuscriptTitle":"Augmented reality enhances spatial cognition in hepatic surgical anatomy: evidence from a randomized controlled study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 14:25:35","doi":"10.21203/rs.3.rs-9358745/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"312507782336938353335189806237308298683","date":"2026-05-13T02:23:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-04T06:13:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T06:12:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-21T02:34:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-13T15:38:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-04-13T12:32:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"67580833-25ab-4f0e-955e-9a0c5bb7ec1f","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"312507782336938353335189806237308298683","date":"2026-05-13T02:23:26+00:00","index":66,"fulltext":""},{"type":"reviewersInvited","content":"17","date":"2026-05-04T06:13:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-04T06:12:55+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67621406,"name":"Health sciences/Anatomy"},{"id":67621407,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-05-12T14:25:41+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 14:25:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9358745","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9358745","identity":"rs-9358745","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}