The application of 3D printing technology in minimally invasive coronary artery bypass

The application of 3D printing technology in minimally invasive coronary artery bypass | 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 Research Article The application of 3D printing technology in minimally invasive coronary artery bypass Zhejun Zhang, Miao Liu, Shuo Liang, Wensi Wang, Yin Yang, Jinghui Li, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6339716/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Mar, 2026 Read the published version in Journal of Cardiothoracic Surgery → Version 1 posted 18 You are reading this latest preprint version Abstract Background: Minimally invasive cardiac surgery has gained importance for preserving sternum stability, reducing pulmonary complications, and enabling faster recovery. MICAB, a newer technique, involves bypassing coronary arteries with minimally invasive methods. Key challenges include determining the appropriate length of saphenous vein grafts (SVG), as errors in graft length can compromise the procedure. Objective: The aim of the study was to develop a 3D model of the patient's heart and coronary system using 3D printing technology to help with preoperative visualization, graft placement, and the determination of the optimal graft length for MICAB surgery. Methods: 20 patients with multivessel coronary artery disease were selected. Preoperatively, coronary CT scans were performed, followed by 3D reconstruction and modeling. Subsequently, patient-specific models were printed using stereolithography (SLA) technology. Under general anesthesia, a minimally invasive approach via left anterior mini-thoracotomy was used to perform MIDCAB. 30 days after surgery, coronary CT scans were performed to assess graft patency and morphology. Estimated length of vein graft was measured based on 3D heart model, while actual length of vein graft was obtained though postoperative CT scan. Results: The study demonstrated the feasibility and accuracy of using 3D-printed models for preoperative vein graft length estimation in MICAB. The mean difference between estimated and actual graft lengths was small, with excellent correlation between preoperative simulations and intraoperative findings. postoperative outcomes showed 100% graft patency with no in-hospital mortality. Conclusion: The study concludes that 3D printing technology is a reliable tool for preoperative planning in MICAB. It enhances surgical precision, reduces intraoperative adjustments, and improves patient outcomes, though further studies are needed to explore long-term effects and optimize workflow. 3D printing minimally invasive sugery CABG Background Over the past few decades, minimally invasive cardiac surgery has become a significant focus. Its benefits include preserving sternum stability, reducing pulmonary complications, and enabling faster recovery. 1,2 In recent years, minimally invasive coronary artery bypass (MICAB) has also emerged as a prominent trend. The most widely accepted MICAB technique resembles traditional off-pump coronary artery bypass grafting (OPCABG). This involves anastomosing the left internal mammary artery to the left anterior descending artery (LAD) and using saphenous vein grafts (SVG) for other occluded coronary arteries. 3 The length and the course of SVG is a crucial factor for the patency of the grafts in CABG. 4 An extremely long venous graft can lead to kinking and deformation, while an excessively short venous graft can cause excessive tension. Both conditions will compromise graft patency. In traditional OPCABG, surgeons can easily measure the length of SVG and position it appropriately. However, in MICAB, the smaller incision makes the graft measurement and placement more challenging. Dual source computer tomography (DSCT) can perform scanning with a single heartbeat based on the patients’ optimal characteristics. 5 CT three-dimensional (3D) reconstruction can provide highly detailed and realistic anatomical images, enhancing the ability to describe lesion characteristics and illustrating the anatomical structures relevant to surgical planning. 6 3D printing can create a full-scale physical model of the patient's heart and coronary system. 7 The 3D model serves as a valuable tool for surgical education and aids cardiac surgeons in visualizing and planning MICAB procedures. 8 The aim of this research is to develop a 3D model of the patients' heart and coronary system to simulate MICAB. This model would enable preoperative visualization and determination of graft placement and optimal graft length, helping to streamline the MICAB procedure. Methods and materials Study Design This study was a single center trial. It was conducted by cardiovascular surgery department at Tianjin Chest Hospital. The Institutional Review Board of Tianjin Chest Hospital approved this study. Participants A total of 20 eligible participants were selected from a cohort of patients who were referred to the cardiovascular surgery department of Tianjin Chest hospital between August and November 2023. The written informed consent was obtained from all the participants. Inclusion criteria were: 1. Multivessel coronary artery disease (≥2 vessels), including at least one vein graft. 2. Absence of significant aortic calcification. 3. Left ventricular ejection fraction ≥50%. Exclusion criteria included emergency surgery, severe comorbidities, or contraindications to contrast-enhanced CT. Interventions Preoperative coronary CT scans and 3D reconstruction Preoperatively, participants were required to perform the coronary CT scans, using a dual-source CT scanner (SOMATOM Force, Siemens Healthineers, Forchheim, Germany) with prospective ECG-gated high-pitch spiral acquisition (100 kV, 288 mAs). Data were uploaded to the Syngo VIA post-processing workstation for cardiac structure and coronary arteries post-processing. 3D reconstruction in this study included two techniques, volumetric rendering (VRT) and cinematic rendering (CR). VRT can clearly visualize the morphology and position of the aorta, pulmonary artery, left atrium and ventricle, right atrium and ventricle, and coronary artery. Cinematic rendering (CR) technology provides three-dimensional visualization of complex anatomical structures, helping to understand surgical anatomy more accurately and quickly 3D modeling and printing DICOM datasets were imported into the 3D Slicer software for segmentation. A layer gap compensation strategy was applied to smooth the model while preserving crucial features like the coronary network. The heart model modeling work included photopolymer material formulas, shrinkage rate estimations, number of molding layers, layer fitting methods, molding speed, surface treatment of the finished product, and treatment of internal hollow structures. Threshold-based segmentation was used to isolate coronary arteries, followed by manual refinement to eliminate artifacts. Patient-specific heart models were made using stereolithography (SLA) with photopolymer resin, calibrated to account for shrinkage and ensure an error margin of ≤1.5%. Preoperative vein graft planning Once the 3D-printed heart models were prepared, we attached a string from aorta to the targeted coronary artery to simulate the morphology of the SVG bypass in MIDCAB. The string was fixed onto the 3D models to facilitate the measurement of its length. Surgical protocol Under general anesthesia, a 10 cm left anterior mini-thoracotomy was performed. The left internal mammary artery (LIMA) was harvested and anastomosed to the left anterior descending artery (LAD). Saphenous vein grafts (SVG) were proximally anastomosed to the ascending aorta using a side-biting clamp and distally to target vessels under Octopus™ stabilization. Postoperative evaluation Coronary CT scans were obtained again within 30 days following surgeries. It allows for an intuitive three-dimensional display of the spatial relationship between native vessels and graft vessels in post-processed images. The morphology and patency of the grafts were assessed. Primary outcomes The accuracy of preoperative vein graft length estimation was the main concern in this study. The estimated length of vein graft was obtained by measuring the string attached from the aorta to the targeted coronary artery in the 3D printed models. The morphology of the string and its position on the 3D heart model were simulated to represent the location of the vein graft in the MIDCAB procedure. The actual length of vein graft in MIDCAB was obtained by measuring the image of the vein graft after 3D reconstruction. We compared the estimated and actual lengths of the vein graft to assess the accuracy of preoperative vein graft length determination. secondary outcomes Secondary outcomes included duration of the operation, rates of converting to sternotomy, and in-hospital mortality. Statistical Analysis The analysis was processed using SPSS statistical software (version 28.0). The measurement data were expressed as mean ± standard deviation (X±S). Normality and homogeneity were assessed using Shapiro–Wilks test. A paired Student’s t -test was used to compare the estimated length of vein graft on 3D model (the length of string) and the actual length of vein graft in MIDCAB. Pearson’s correlation method was used to examine the associations between estimated length of vein graft and actual length of vein graft. P< 0.05 was considered as a statistically significant difference. Results The baseline and perioperative characteristics were shown in Table 1. The mean age of the patients was 64.4 ± 4.9 years. All procedures were performed via a left anterior mini-thoracotomy, without converting to sternotomy. The mean operation time was There was no in-hospital mortality in all patients. Post-operative coronary CT scans showed a good morphology of the vein grafts and a 100% graft patency 30 days after MIDCAB. Among the 20 patients, the average number of vein grafts was 1.5 ± 0.5, with grafts anastomosed to the diagonal artery (DIAG), obtuse marginal artery (OM), and posterior descending artery (PDA). The mean estimated SVG length for Ao-DIAG graft was 8.08 ± 1.70 cm, while the actual length measured by CT was 7.92 ± 1.73 cm, resulting in a mean difference of 0.16 ± 0.24 cm (P = 0.291). For Ao-OM graft, the estimated length was 13.32 ± 1.98 cm, compared to an actual CT-based measurement of 13.04 ± 2.03 cm. The mean difference was 0.28 ± 0.16 cm (P < 0.001). Similarly, the Ao-PDA graft showed an estimated length of 17.28 ± 2.26 cm, with an actual length of 16.85 ± 2.28 cm. The mean difference was 0.43 ± 0.19 cm (P < 0.001). (Table 2) 3D-printed models demonstrated excellent correlation with intraoperative findings (Table 3). Discussion 3D printing is an innovative technology that is widely utilized in the medical field, which has gained a lot of practical experience in areas such as orthopedics, cardiology, and vascular surgery. 7 It is employed for treatment planning, surgical procedures, educational purposes, and conducting interventions in non-sterile environments before surgery. 9,10 This study demonstrates the feasibility and accuracy of using 3D-printed patient-specific heart models for preoperative vein graft length estimation in MIDCAB. Our findings suggest that 3D modeling provides a reliable method for preoperative surgery planning, improving the precision of surgical grafting strategies. The primary outcome of this study was the accuracy of preoperative vein graft length estimation. From the result, we found that the estimated length of vein graft was longer than the actual length of vein graft. It could be that in the preoperative planning, we make the string a little bit longer on purpose. This adjustment was made to mitigate the risk of tension and anastomotic deformation that could result from an excessively short bypass vessel in the real world. The mean difference between estimated and actual length of vein graft in Ao-DIAG was 0.16 ± 0.24 cm (P = 0.291). While in Ao-OM graft and Ao-PDA graft, mean difference was 0.28 ± 0.16 cm (P < 0.001) and 0.43 ± 0.19 cm (P < 0.001), respectively. Although the mean difference between the estimated and actual length of the vein graft in OM and PDA was statistically significant, it does not necessarily indicate practical or clinical relevance. Small variations in graft length are expected due to intraoperative factors such as graft manipulation, vessel elasticity, and surgical technique. Moreover, the minimal differences observed in our study likely fall within an acceptable margin of error that does not compromise graft function. Further long-term studies are needed to assess whether these small discrepancies have any impact on long-term graft patency and patient outcomes. These results are aligned with previous studies that have demonstrated the utility of 3D printing in surgical planning, particularly in cardiovascular procedures. 11 Our results also suggest that 3D modeling can enhance preoperative assessment in surgeries with limited operating space, such as MIDCAB. Preoperative estimation of vein graft length and simulation of vein graft routing could potentially reduce the risk of graft-related complications such as kinking or excessive tension in MIDCAB. 12 The intraoperative results showed that all MIDCAB were successfully completed without converting to sternotomy, and the mean operative time was comparable to conventional CABG. Postoperative CTA confirmed a perfect graft patency rate (100%), with an excellent vein graft morphology and no evidence of kinking. This reinforces the clinical applicability of 3D modeling in optimizing graft positioning and reducing postoperative complications. Our findings also indicate that 3D-printed models demonstrated excellent correlation with intraoperative findings. These 3D heart models provided a patient-specific visualization of coronary anatomy, potentially aiding in more precise graft length estimation and anastomotic positioning. Previous studies have indicated that 3D printing facilitates the development of patient-specific surgical guides and implants, improving the accuracy and efficiency of preoperative planning as well as providing substantial benefits for surgical simulation and training. 13,14 The results in our study contribute to the growing body of evidence supporting the integration of 3D printing technology into cardiac surgery. In MIDCAB, where surgical access is limited, 3D printing could offer significant advantages in planning minimally invasive approaches. 15 By improving accuracy in graft sizing and placement, these models could help reduce intraoperative adjustments and optimize surgical efficiency. However, the cost and accessibility of 3D printing technology remain considerations for widespread adoption in routine clinical practice. Despite these promising findings, several limitations must be acknowledged. The small sample size (n=20) and single-center design may limit the generalizability of the results. A larger cohort would provide more robust statistical power to assess the clinical impact of length discrepancies. Additionally, the cost and time required for 3D modeling and printing remain potential barriers to widespread clinical adoption. Future research should focus on streamlining the integration of 3D modeling into routine surgical practice. Furthermore, the follow-up period was only 30 days, preventing assessment of long-term graft patency and clinical outcomes. Future studies with extended follow-up and larger patient cohorts are needed to determine whether these small length differences influence long-term graft performance. Conclusion In conclusion, this study highlights the accuracy and clinical utility of 3D-printed models in preoperative vein graft length estimation for minimally invasive CABG. The strong correlation between preoperative simulations and intraoperative findings suggests that 3D modeling can improve surgical planning and outcomes. Further research is warranted to refine this approach, optimize workflow efficiency, and evaluate its cost-effectiveness in broader clinical settings. Declarations Funding This study was supported by the Tianjin Science and Technology Project (No. 21JCQNJC00630). The funders had no role in the study design, data collection, analysis, or preparation of the manuscript. References Lapierre H, Chan V, Sohmer B, Mesana TG, Ruel M. Minimally invasive coronary artery bypass grafting via a small thoracotomy versus off-pump: a case-matched study. Eur J Cardiothorac Surg . 2011;40:804–10. Ruel M, Une D, Bonatti J, McGinn JT. Minimally invasive coronary artery bypass grafting: is it time for the robot? Curr Opin Cardiol . 2013;28:639–45. McGinn JT, Usman S, Lapierre H, Pothula VR, Mesana TG, Ruel M. Minimally invasive coronary artery bypass grafting: dual-center experience in 450 consecutive patients. Circulation . 2009;120:S78-84. Goor DA. The genius of C. Walton Lillehei and the true history of open heart surgery . Vantage Press, Inc, 2007. Cademartiri F, Casolo G, Clemente A, et al. Coronary CT angiography: a guide to examination, interpretation, and clinical indications. Expert Rev Cardiovasc Ther . 2021;19:413–425. Recht HS, Fishman EK. Cinematic Rendering of an Atrial Septal Occluder Device. Radiology . 2020;294:507. Vukicevic M, Mosadegh B, Min JK, Little SH. Cardiac 3D Printing and its Future Directions. JACC Cardiovasc Imaging . 2017;10:171–184. Sun Z, Ng CKC, Squelch A. Synchrotron radiation computed tomography assessment of calcified plaques and coronary stenosis with different slice thicknesses and beam energies on 3D printed coronary models. Quant Imaging Med Surg . 2019;9:6–22. Mahmood F, Owais K, Taylor C, et al. Three-dimensional printing of mitral valve using echocardiographic data. JACC Cardiovasc Imaging . 2015;8:227–9. Maragiannis D, Jackson MS, Igo SR, et al. Replicating Patient-Specific Severe Aortic Valve Stenosis With Functional 3D Modeling. Circ Cardiovasc Imaging . 2015;8:e003626. Wang C, Zhang L, Qin T, et al. 3D printing in adult cardiovascular surgery and interventions: a systematic review. J Thorac Dis . 2020;12:3227–3237. Gocer H, Durukan AB, Tunc O, Naseri E, Ercan E. A Novel Method to Adjust Saphenous Vein Graft Lengths Using 3D Printing Models. Heart Surg Forum . 2020;23:E135–E139. Frithioff A, Frendø M, Pedersen DB, Sørensen MS, Wuyts Andersen SA. 3D-Printed Models for Temporal Bone Surgical Training: A Systematic Review. Otolaryngol Head Neck Surg . 2021;165:617–625. Hoang D, Perrault D, Stevanovic M, Ghiassi A. Surgical applications of three-dimensional printing: a review of the current literature & how to get started. Ann Transl Med . 2016;4:456. Ravi P, Burch MB, Giannopoulos AA, et al. Desktop 3D printed anatomic models for minimally invasive direct coronary artery bypass. 3D Print Med . 2024;10:19. Tables Table 1. Perioperative clinical characteristics of patients Characteristics n=20 Gender Male 14 (70%) Female 6 (30%) Age, mean (SD), years 64.4 (4.9) History of smoking 13 (65%) Comorbidities Hypertension 9 (45%) DM 5 (25%) Cerebral vascular disease 3 (15%) History of PCI 5 (25%) History of MI 3 (15%) Number of vein grafts, mean (SD) 1.5 (0.5) Operation time, mean (SD), minutes MV time, mean (SD), minutes 759.9 (191) ICU stay, mean (SD), hours 40.3 (6.1) PLOS, mean (SD), days 6.4(0.6) DM: Diabetes Mellitus; PCI: Percutaneous Coronary Intervention; MI: Myocardial Infarction; MV: Mechanical Ventilation; ICU: Intensive Care Unit; PLOS: Postoperative Length of Hospital Stay Table 2. Comparison of estimated and actual SVG length SVG location Estimated SVG length Actual SVG length with CT scan length difference P value Ao-DIAG 8.08 (1.70) 7.92 (1.73) 0.16 (0.24) 0.291 Ao-OM 13.32 (1.98) 13.04 (2.03) 0.28 (0.16) <0.001 Ao-PDA 17.28 (2.26) 16.85(2.28) 0.43 (0.19) <0.001 SVG: Saphenous Vein Graft; Ao: Aorta; DIAG: Diagonal artery; OM: Obtuse Marginal artery; PDA: Posterior Descending artery Table 3. Pearson’s correlation of estimated and actual SVG length SVG location (estimated versus actual) Pearson's correlation P value Ao-DIAG 0.99 0.01 Ao-OM 0.997 <0.001 Ao-PDA 0.997 <0.001 SVG: Saphenous Vein Graft; Ao: Aorta; DIAG: Diagonal artery; OM: Obtuse Marginal artery; PDA: Posterior Descending artery Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Mar, 2026 Read the published version in Journal of Cardiothoracic Surgery → Version 1 posted Editorial decision: Revision requested 27 Jul, 2025 Reviews received at journal 14 Jun, 2025 Reviews received at journal 12 Jun, 2025 Reviews received at journal 11 Jun, 2025 Reviewers agreed at journal 09 Jun, 2025 Reviews received at journal 08 Jun, 2025 Reviews received at journal 07 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers agreed at journal 03 Jun, 2025 Reviewers invited by journal 03 Jun, 2025 Editor assigned by journal 31 Mar, 2025 Submission checks completed at journal 31 Mar, 2025 First submitted to journal 30 Mar, 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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Its benefits include preserving sternum stability, reducing pulmonary complications, and enabling faster recovery.\u003csup\u003e1,2\u003c/sup\u003e In recent years, minimally invasive coronary artery bypass (MICAB) has also emerged as a prominent trend. The most widely accepted MICAB technique resembles traditional off-pump coronary artery bypass grafting (OPCABG). This involves anastomosing the left internal mammary artery to the left anterior descending artery (LAD) and using saphenous vein grafts (SVG) for other occluded coronary arteries.\u003csup\u003e3\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; The length and the course of SVG is a crucial factor for the patency of the grafts in CABG.\u003csup\u003e4\u003c/sup\u003e An extremely long venous graft can lead to kinking and deformation, while an excessively short venous graft can cause excessive tension. Both conditions will compromise graft patency. In traditional OPCABG, surgeons can easily measure the length of SVG and position it appropriately. However, in MICAB, the smaller incision makes the graft measurement and placement more challenging.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Dual source computer tomography (DSCT) can perform scanning with a single heartbeat based on the patients\u0026rsquo; optimal characteristics.\u003csup\u003e5\u003c/sup\u003e CT three-dimensional (3D) reconstruction can provide highly detailed and realistic anatomical images, enhancing the ability to describe lesion characteristics and illustrating the anatomical structures relevant to surgical planning.\u003csup\u003e6\u003c/sup\u003e 3D printing can create a full-scale physical model of the patient\u0026apos;s heart and coronary system.\u003csup\u003e7\u003c/sup\u003e The 3D model serves as a valuable tool for surgical education and aids cardiac surgeons in visualizing and planning MICAB procedures.\u003csup\u003e8\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; The aim of this research is to develop a 3D model of the patients\u0026apos; heart and coronary system to simulate MICAB. This model would enable preoperative visualization and determination of graft placement and optimal graft length, helping to streamline the MICAB procedure.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy Design\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; This study was a single center trial. It was conducted by cardiovascular surgery department at Tianjin Chest Hospital. The Institutional Review Board of Tianjin Chest Hospital approved this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eParticipants\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; A total of 20 eligible participants were selected from a cohort of patients who were referred to the cardiovascular surgery department of Tianjin Chest hospital between August and November 2023. The written informed consent was obtained from all the participants. Inclusion criteria were: 1. Multivessel coronary artery disease (\u0026ge;2 vessels), including at least one vein graft. 2. Absence of significant aortic calcification. 3. Left ventricular ejection fraction \u0026ge;50%. Exclusion criteria included emergency surgery, severe comorbidities, or contraindications to contrast-enhanced CT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInterventions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003ePreoperative coronary CT scans and 3D reconstruction\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Preoperatively, participants were required to perform the coronary CT scans, using a dual-source CT scanner (SOMATOM Force, Siemens Healthineers, Forchheim, Germany) with prospective ECG-gated high-pitch spiral acquisition (100 kV, 288 mAs). Data were\u0026nbsp;uploaded to the Syngo VIA post-processing workstation for cardiac structure and coronary arteries post-processing. 3D reconstruction in this study included two techniques, volumetric rendering (VRT) and cinematic rendering (CR). VRT can clearly visualize the morphology and position of the aorta, pulmonary artery, left atrium and ventricle, right atrium and ventricle, and coronary artery. Cinematic rendering (CR) technology provides three-dimensional visualization of complex anatomical structures, helping to understand surgical anatomy more accurately and quickly\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e3D modeling and printing\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp; DICOM datasets were imported into the 3D Slicer software for segmentation. A layer gap compensation strategy was applied to smooth the model while preserving crucial features like the coronary network. The heart model modeling work included photopolymer material formulas, shrinkage rate estimations, number of molding layers, layer fitting methods, molding speed, surface treatment of the finished product, and treatment of internal hollow structures. Threshold-based segmentation was used to isolate coronary arteries, followed by manual refinement to eliminate artifacts. Patient-specific heart models were made using stereolithography (SLA) with photopolymer resin, calibrated to account for shrinkage and ensure an error margin of \u0026le;1.5%.\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003ePreoperative vein graft planning\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;Once the 3D-printed heart models were prepared, we attached a string from aorta to the targeted coronary artery to simulate the morphology of the SVG bypass in MIDCAB. The string was fixed onto the 3D models to facilitate the measurement of its length.\u003c/p\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003eSurgical protocol\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp; Under general anesthesia, a 10 cm left anterior mini-thoracotomy was performed. The left internal mammary artery (LIMA) was harvested and anastomosed to the left anterior descending artery (LAD). Saphenous vein grafts (SVG) were proximally anastomosed to the ascending aorta using a side-biting clamp and distally to target vessels under Octopus\u0026trade; stabilization.\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003ePostoperative evaluation\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003e\u0026nbsp; Coronary CT scans were obtained again within 30 days following surgeries. It allows for an intuitive three-dimensional display of the spatial relationship between native vessels and graft vessels in post-processed images. The morphology and patency of the grafts were assessed. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePrimary outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe accuracy of preoperative vein graft length estimation was the main concern in this study. The estimated length of vein graft was obtained by measuring the string attached from the aorta to the targeted coronary artery in the 3D printed models. The morphology of the string and its position on the 3D heart model were simulated to represent the location of the vein graft in the MIDCAB procedure. The actual length of vein graft in MIDCAB was obtained by measuring the image of the vein graft after 3D reconstruction. We compared the estimated and actual lengths of the vein graft to assess the accuracy of preoperative vein graft length determination.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e\u003cem\u003esecondary outcomes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSecondary outcomes included duration of the operation, rates of converting to sternotomy, and in-hospital mortality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003e\u003cem\u003eStatistical Analysis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; The analysis was processed using SPSS statistical software (version 28.0). The measurement data were expressed as mean \u0026plusmn; standard deviation (X\u0026plusmn;S). Normality and homogeneity were assessed using Shapiro\u0026ndash;Wilks test. A paired Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test was used to compare the estimated length of vein graft on 3D model (the length of string) and the actual length of vein graft in MIDCAB. Pearson\u0026rsquo;s correlation method was used to examine the associations between estimated length of vein graft and actual length of vein graft. P\u0026lt; 0.05 was considered as a statistically significant difference.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u0026nbsp; The baseline and perioperative characteristics were shown in Table 1. The mean age of the patients was 64.4 \u0026plusmn; 4.9 years. All procedures were performed via a left anterior mini-thoracotomy, without converting to sternotomy. The mean operation time was There was no in-hospital mortality in all patients. Post-operative coronary CT scans showed a good morphology of the vein grafts and a 100% graft patency 30 days after MIDCAB.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; Among the 20 patients, the average number of vein grafts was 1.5 \u0026plusmn; 0.5, with grafts anastomosed to the diagonal artery (DIAG), obtuse marginal artery (OM), and posterior descending artery (PDA). The mean estimated SVG length for Ao-DIAG graft was 8.08 \u0026plusmn; 1.70 cm, while the actual length measured by CT was 7.92 \u0026plusmn; 1.73 cm, resulting in a mean difference of 0.16 \u0026plusmn; 0.24 cm (P = 0.291). For Ao-OM graft, the estimated length was 13.32 \u0026plusmn; 1.98 cm, compared to an actual CT-based measurement of 13.04 \u0026plusmn; 2.03 cm. The mean difference was 0.28 \u0026plusmn; 0.16 cm (P \u0026lt; 0.001). Similarly, the Ao-PDA graft showed an estimated length of 17.28 \u0026plusmn; 2.26 cm, with an actual length of 16.85 \u0026plusmn; 2.28 cm. The mean difference was 0.43 \u0026plusmn; 0.19 cm (P \u0026lt; 0.001). (Table 2) 3D-printed models demonstrated excellent correlation with intraoperative findings (Table 3).\u003c/p\u003e\n"},{"header":"Discussion","content":"\u003cp\u003e\u0026nbsp; 3D printing is an innovative technology that is widely utilized in the medical field, which has gained a lot of practical experience in areas such as orthopedics, cardiology, and vascular surgery.\u003csup\u003e7\u003c/sup\u003e It is employed for treatment planning, surgical procedures, educational purposes, and conducting interventions in non-sterile environments before surgery.\u003csup\u003e9,10\u003c/sup\u003e This study demonstrates the feasibility and accuracy of using 3D-printed patient-specific heart models for preoperative vein graft length estimation in MIDCAB. Our findings suggest that 3D modeling provides a reliable method for preoperative surgery planning, improving the precision of surgical grafting strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe primary outcome of this study was the accuracy of preoperative vein graft length estimation. From the result, we found that the estimated length of vein graft was longer than the actual length of vein graft. It could be that in the preoperative planning, we make the string a little bit longer on purpose. This adjustment was made to mitigate the risk of tension and anastomotic deformation that could result from an excessively short bypass vessel in the real world. The mean difference between estimated and actual length of vein graft in Ao-DIAG was 0.16 \u0026plusmn; 0.24 cm (P = 0.291). While in Ao-OM graft and Ao-PDA graft, mean difference was 0.28 \u0026plusmn; 0.16 cm (P \u0026lt; 0.001) and 0.43 \u0026plusmn; 0.19 cm (P \u0026lt; 0.001), respectively. Although the mean difference between the estimated and actual length of the vein graft in OM and PDA was statistically significant, it does not necessarily indicate practical or clinical relevance. Small variations in graft length are expected due to intraoperative factors such as graft manipulation, vessel elasticity, and surgical technique. Moreover, the minimal differences observed in our study likely fall within an acceptable margin of error that does not compromise graft function. Further long-term studies are needed to assess whether these small discrepancies have any impact on long-term graft patency and patient outcomes. These results are aligned with previous studies that have demonstrated the utility of 3D printing in surgical planning, particularly in cardiovascular procedures.\u003csup\u003e11\u003c/sup\u003e Our results also suggest that 3D modeling can enhance preoperative assessment in\u0026nbsp;surgeries with limited operating space, such as MIDCAB. Preoperative estimation of vein graft length and simulation of vein graft routing could potentially reduce the risk of graft-related complications such as kinking or excessive tension in MIDCAB.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe intraoperative results showed that all MIDCAB were successfully completed without converting to sternotomy, and the mean operative time was comparable to conventional CABG. \u0026nbsp; Postoperative CTA confirmed a perfect graft patency rate (100%), with an excellent vein graft morphology and no evidence of kinking. This reinforces the clinical applicability of 3D modeling in optimizing graft positioning and reducing postoperative complications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Our findings also indicate that 3D-printed models demonstrated excellent correlation with intraoperative findings. These 3D heart models provided a patient-specific visualization of coronary anatomy, potentially aiding in more precise graft length estimation and anastomotic positioning. Previous studies have indicated that 3D printing facilitates the development of patient-specific surgical guides and implants, improving the accuracy and efficiency of preoperative planning as well as providing substantial benefits for surgical simulation and training.\u003csup\u003e13,14\u003c/sup\u003e The results in our study contribute to the growing body of evidence supporting the integration of 3D printing technology into cardiac surgery. In MIDCAB, where surgical access is limited, 3D printing could offer significant advantages in planning minimally invasive approaches.\u003csup\u003e15\u003c/sup\u003e By improving accuracy in graft sizing and placement, these models could help reduce intraoperative adjustments and optimize surgical efficiency. However, the cost and accessibility of 3D printing technology remain considerations for widespread adoption in routine clinical practice.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Despite these promising findings, several limitations must be acknowledged. The small sample size (n=20) and single-center design may limit the generalizability of the results. A larger cohort would provide more robust statistical power to assess the clinical impact of length discrepancies. Additionally, the cost and time required for 3D modeling and printing remain potential barriers to widespread clinical adoption. Future research should focus on streamlining the integration of 3D modeling into routine surgical practice. Furthermore, the follow-up period was only 30 days, preventing assessment of long-term graft patency and clinical outcomes. Future studies with extended follow-up and larger patient cohorts are needed to determine whether these small length differences influence long-term graft performance.\u003c/p\u003e\n"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study highlights the accuracy and clinical utility of 3D-printed models in preoperative vein graft length estimation for minimally invasive CABG. The strong correlation between preoperative simulations and intraoperative findings suggests that 3D modeling can improve surgical planning and outcomes. Further research is warranted to refine this approach, optimize workflow efficiency, and evaluate its cost-effectiveness in broader clinical settings.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Tianjin Science and Technology Project (No.\u0026nbsp;21JCQNJC00630). The funders had no role in the study design, data collection, analysis, or preparation of the manuscript.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLapierre H, Chan V, Sohmer B, Mesana TG, Ruel M. Minimally invasive coronary artery bypass grafting via a small thoracotomy versus off-pump: a case-matched study. \u003cem\u003eEur J Cardiothorac Surg\u003c/em\u003e. 2011;40:804\u0026ndash;10.\u003c/li\u003e\n\u003cli\u003eRuel M, Une D, Bonatti J, McGinn JT. Minimally invasive coronary artery bypass grafting: is it time for the robot? \u003cem\u003eCurr Opin Cardiol\u003c/em\u003e. 2013;28:639\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eMcGinn JT, Usman S, Lapierre H, Pothula VR, Mesana TG, Ruel M. Minimally invasive coronary artery bypass grafting: dual-center experience in 450 consecutive patients. \u003cem\u003eCirculation\u003c/em\u003e. 2009;120:S78-84.\u003c/li\u003e\n\u003cli\u003eGoor DA. \u003cem\u003eThe genius of C. Walton Lillehei and the true history of open heart surgery\u003c/em\u003e. Vantage Press, Inc, 2007.\u003c/li\u003e\n\u003cli\u003eCademartiri F, Casolo G, Clemente A, et al. Coronary CT angiography: a guide to examination, interpretation, and clinical indications. \u003cem\u003eExpert Rev Cardiovasc Ther\u003c/em\u003e. 2021;19:413\u0026ndash;425.\u003c/li\u003e\n\u003cli\u003eRecht HS, Fishman EK. Cinematic Rendering of an Atrial Septal Occluder Device. \u003cem\u003eRadiology\u003c/em\u003e. 2020;294:507.\u003c/li\u003e\n\u003cli\u003eVukicevic M, Mosadegh B, Min JK, Little SH. Cardiac 3D Printing and its Future Directions. \u003cem\u003eJACC Cardiovasc Imaging\u003c/em\u003e. 2017;10:171\u0026ndash;184.\u003c/li\u003e\n\u003cli\u003eSun Z, Ng CKC, Squelch A. Synchrotron radiation computed tomography assessment of calcified plaques and coronary stenosis with different slice thicknesses and beam energies on 3D printed coronary models. \u003cem\u003eQuant Imaging Med Surg\u003c/em\u003e. 2019;9:6\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eMahmood F, Owais K, Taylor C, et al. Three-dimensional printing of mitral valve using echocardiographic data. \u003cem\u003eJACC Cardiovasc Imaging\u003c/em\u003e. 2015;8:227\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eMaragiannis D, Jackson MS, Igo SR, et al. Replicating Patient-Specific Severe Aortic Valve Stenosis With Functional 3D Modeling. \u003cem\u003eCirc Cardiovasc Imaging\u003c/em\u003e. 2015;8:e003626.\u003c/li\u003e\n\u003cli\u003eWang C, Zhang L, Qin T, et al. 3D printing in adult cardiovascular surgery and interventions: a systematic review. \u003cem\u003eJ Thorac Dis\u003c/em\u003e. 2020;12:3227\u0026ndash;3237.\u003c/li\u003e\n\u003cli\u003eGocer H, Durukan AB, Tunc O, Naseri E, Ercan E. A Novel Method to Adjust Saphenous Vein Graft Lengths Using 3D Printing Models. \u003cem\u003eHeart Surg Forum\u003c/em\u003e. 2020;23:E135\u0026ndash;E139.\u003c/li\u003e\n\u003cli\u003eFrithioff A, Frend\u0026oslash; M, Pedersen DB, S\u0026oslash;rensen MS, Wuyts Andersen SA. 3D-Printed Models for Temporal Bone Surgical Training: A Systematic Review. \u003cem\u003eOtolaryngol Head Neck Surg\u003c/em\u003e. 2021;165:617\u0026ndash;625.\u003c/li\u003e\n\u003cli\u003eHoang D, Perrault D, Stevanovic M, Ghiassi A. Surgical applications of three-dimensional printing: a review of the current literature \u0026amp; how to get started. \u003cem\u003eAnn Transl Med\u003c/em\u003e. 2016;4:456.\u003c/li\u003e\n\u003cli\u003eRavi P, Burch MB, Giannopoulos AA, et al. Desktop 3D printed anatomic models for minimally invasive direct coronary artery bypass. \u003cem\u003e3D Print Med\u003c/em\u003e. 2024;10:19. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Perioperative clinical characteristics of patients\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"565\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003en=20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e14 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e6 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eAge, mean (SD), years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e64.4 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eHistory of smoking\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e13 (65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e9 (45%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e\u0026nbsp; DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e5 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Cerebral vascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e3 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eHistory of PCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e5 (25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eHistory of MI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e3 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eNumber of vein grafts, mean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e1.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eOperation time, mean (SD), minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eMV time, mean (SD), minutes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e759.9 (191)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003eICU stay, mean (SD), hours\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e40.3 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003ePLOS, mean (SD), days\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50%;\"\u003e\n \u003cp\u003e6.4(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eDM: Diabetes Mellitus; PCI: Percutaneous Coronary Intervention; MI: Myocardial Infarction;\u003c/p\u003e\n\u003cp\u003eMV: Mechanical Ventilation; ICU: Intensive Care Unit; PLOS: Postoperative Length of Hospital Stay\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of estimated and actual SVG length\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.6102%;\"\u003e\n \u003cp\u003eSVG location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.5593%;\"\u003e\n \u003cp\u003eEstimated SVG length\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 28.6441%;\"\u003e\n \u003cp\u003eActual SVG length with CT scan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20.1695%;\"\u003e\n \u003cp\u003elength difference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11.0169%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.6102%;\"\u003e\n \u003cp\u003eAo-DIAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.5593%;\"\u003e\n \u003cp\u003e8.08 (1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 28.6441%;\"\u003e\n \u003cp\u003e7.92 (1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20.1695%;\"\u003e\n \u003cp\u003e0.16 (0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11.0169%;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.6102%;\"\u003e\n \u003cp\u003eAo-OM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.5593%;\"\u003e\n \u003cp\u003e13.32 (1.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 28.6441%;\"\u003e\n \u003cp\u003e13.04 (2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20.1695%;\"\u003e\n \u003cp\u003e0.28 (0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11.0169%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.6102%;\"\u003e\n \u003cp\u003eAo-PDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 23.5593%;\"\u003e\n \u003cp\u003e17.28 (2.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 28.6441%;\"\u003e\n \u003cp\u003e16.85(2.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 20.1695%;\"\u003e\n \u003cp\u003e0.43 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11.0169%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSVG: Saphenous Vein Graft; Ao: Aorta; DIAG: Diagonal artery; OM: Obtuse Marginal artery;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePDA: Posterior Descending artery\u003c/p\u003e\n\u003cp\u003eTable 3. Pearson\u0026rsquo;s correlation of estimated and actual SVG length\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"536\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.4403%;\"\u003e\n \u003cp\u003eSVG location (estimated versus actual)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29.1045%;\"\u003e\n \u003cp\u003ePearson\u0026apos;s correlation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4552%;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.4403%;\"\u003e\n \u003cp\u003eAo-DIAG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29.1045%;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4552%;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.4403%;\"\u003e\n \u003cp\u003eAo-OM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29.1045%;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4552%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 49.4403%;\"\u003e\n \u003cp\u003eAo-PDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29.1045%;\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 21.4552%;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSVG: Saphenous Vein Graft; Ao: Aorta; DIAG: Diagonal artery; OM: Obtuse Marginal artery;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePDA: Posterior Descending artery\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-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"3D printing, minimally invasive sugery, CABG","lastPublishedDoi":"10.21203/rs.3.rs-6339716/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6339716/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMinimally invasive cardiac surgery has gained importance for preserving sternum stability, reducing pulmonary complications, and enabling faster recovery. MICAB, a newer technique, involves bypassing coronary arteries with minimally invasive methods. Key challenges include determining the appropriate length of saphenous vein grafts (SVG), as errors in graft length can compromise the procedure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe aim of the study was to develop a 3D model of the patient's heart and coronary system using 3D printing technology to help with preoperative visualization, graft placement, and the determination of the optimal graft length for MICAB surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e20 patients with multivessel coronary artery disease were selected. Preoperatively, coronary CT scans were performed, followed by 3D reconstruction and modeling. Subsequently, patient-specific models were printed using stereolithography (SLA) technology. Under general anesthesia, a minimally invasive approach via left anterior mini-thoracotomy was used to perform MIDCAB. 30 days after surgery, coronary CT scans were performed to assess graft patency and morphology. Estimated length of vein graft was measured based on 3D heart model, while actual length of vein graft was obtained though postoperative CT scan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study demonstrated the feasibility and accuracy of using 3D-printed models for preoperative vein graft length estimation in MICAB. The mean difference between estimated and actual graft lengths was small, with excellent correlation between preoperative simulations and intraoperative findings. postoperative outcomes showed 100% graft patency with no in-hospital mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study concludes that 3D printing technology is a reliable tool for preoperative planning in MICAB. It enhances surgical precision, reduces intraoperative adjustments, and improves patient outcomes, though further studies are needed to explore long-term effects and optimize workflow.\u003c/p\u003e","manuscriptTitle":"The application of 3D printing technology in minimally invasive coronary artery bypass","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-06 08:03:38","doi":"10.21203/rs.3.rs-6339716/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-27T06:37:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-14T17:58:21+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-12T17:42:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-11T05:54:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116662386209879886142637820596953039095","date":"2025-06-09T13:42:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-08T10:38:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-07T10:31:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"177376630645864226094172961518351715640","date":"2025-06-04T23:26:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"112180357886640805216265308159844772576","date":"2025-06-04T17:34:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"84136441936010199155981632844339289863","date":"2025-06-04T09:46:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71773431339491601186448834417934096818","date":"2025-06-03T22:58:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9342743860352972532922476974540046532","date":"2025-06-03T14:34:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130331701273897840457337262025190036642","date":"2025-06-03T14:08:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187882182970015480029454656402116698825","date":"2025-06-03T13:40:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-06-03T13:26:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-31T14:59:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-31T14:58:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Cardiothoracic Surgery","date":"2025-03-30T17:26:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-cardiothoracic-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jcts","sideBox":"Learn more about [Journal of Cardiothoracic Surgery](http://cardiothoracicsurgery.biomedcentral.com)","snPcode":"13019","submissionUrl":"https://submission.nature.com/new-submission/13019/3","title":"Journal of Cardiothoracic Surgery","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbc02d1f-4ae6-4b60-ac2b-6d7a94bc46a0","owner":[],"postedDate":"June 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-09T16:00:57+00:00","versionOfRecord":{"articleIdentity":"rs-6339716","link":"https://doi.org/10.1186/s13019-026-03873-9","journal":{"identity":"journal-of-cardiothoracic-surgery","isVorOnly":false,"title":"Journal of Cardiothoracic Surgery"},"publishedOn":"2026-03-03 15:57:44","publishedOnDateReadable":"March 3rd, 2026"},"versionCreatedAt":"2025-06-06 08:03:38","video":"","vorDoi":"10.1186/s13019-026-03873-9","vorDoiUrl":"https://doi.org/10.1186/s13019-026-03873-9","workflowStages":[]},"version":"v1","identity":"rs-6339716","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6339716","identity":"rs-6339716","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}