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Novel Visualization Tool for Percutaneous Renal Puncture Training Using Augmented Reality Technology

基于增强现实技术的新型经皮肾穿刺训练可视化工具

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Abstract

We aim to develop a novel visualization tool for percutaneous renal puncture training based on augmented reality (AR) and compare the needle placement performance of this AR system with ultrasound-guided freehand navigation in phantoms. A head-mounted display-based AR navigation system was developed using the Unity3D software and Visual Studio to enable the overlay of the preoperative needle path and the complex anatomical structures onto a phantom in real time. The spatial location of the stationary phantom and the percutaneous instrument motion were traced by a Qualisys motion capture system. To evaluate the tracking accuracy, 15 participants (7 males and 8 females) performed a single needle insertion using AR navigation (the number of punctures n = 75) and ultrasound-guided freehand navigation (n = 75). The needle placement error was measured as the Euclidean distance between the actual needle tip and the virtual target by MicronTracker. All participants demonstrated a superior needle insertion efficiency when using the AR-assisted puncture method compared with the ultrasound-guided freehand method. The needle insertion error of the ultrasound-guided method showed an increased error compared with the AR method (5.54mm ± 2.59mm, 4.34mm ± 2.10mm, respectively, p < 0.05). The ultrasound-guided needle placements showed an increased time compared with the AR method (19.08 s ± 3.59 s, 15.14 s ± 2.72 s, respectively, p < 0.0001). Our AR training system facilitates the needle placement performance and solves hand-eye coordination problems. The system has the potential to increase efficiency and effectiveness of percutaneous renal puncture training.

摘要

本研究的目的是开发一种基于增强现实(AR)的新型经皮肾穿刺训练可视化工具, 并比较模型中该AR系统与超声引导徒手导航的针头放置性能. 本研究使用Unity3D和Visual Studio软件开发了一种基于头戴式显示器的AR导航系统, 可以使术前入针路径和复杂的解剖结构影像实时覆盖到穿刺模型上. 我们通过Qualisys 运动捕捉系统来跟踪静止模型和经皮器械运动的空间位置. 为了评估跟踪的准确性, 15名参与者(7名男性和8名女性)使用AR导航(穿刺次数n = 75)和超声引导下的徒手导航(n = 75)方式进行了单次置针操作. 针尖与虚拟目标之间的欧氏距离为置针误差, 该距离使用MicronTracker测量. 与超声引导徒手穿刺相比, AR辅助穿刺方法具有更好的置针效率. 超声引导的置针误差高于AR导航的误差(5.54 mm ± 2.59 mm, 4.34 mm ± 2.10 mm, p < 0.05). 同时, 超声引导的置针时间也高于AR导航的时间 (19.08 s ±3.59 s, 15.14 s ± 2.72 s, respectively, p < 0.000 1). 结果表明, 本研究开发的AR训练系统提升了置针效率并解决了操作者的手眼协同问题. 在提高经皮肾穿刺训练的效率和有效性方面, 该系统展现出一定的潜力.

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References

  1. NG C F. Training in percutaneous nephrolithotomy: The learning curve and options [J]. Arab Journal of Urology, 2014, 12(1): 54–57.

    Article  Google Scholar 

  2. STERN J, ZELTSER I S, PEARLE M S. Percutaneous renal access simulators [J]. Journal of Endourology, 2007, 21(3): 270–273.

    Article  Google Scholar 

  3. MISHRA S, SABNIS R B, DESAI M. Staghorn morphometry: A new tool for clinical classification and prediction model for percutaneous nephrolithotomy monotherapy [J]. Journal of Endourology, 2012, 26(1): 6–14.

    Article  Google Scholar 

  4. ALLEN D, O’BRIEN T, TIPTAFT R, et al. Defining the learning curve for percutaneous nephrolithotomy [J]. Journal of Endourology, 2005, 19(3): 279–282.

    Article  Google Scholar 

  5. DE LA ROSETTE J, ASSIMOS D, DESAI M, et al. The Clinical Research Office of the Endourological Society Percutaneous Nephrolithotomy Global Study: Indications, complications, and outcomes in 5803 patients [J]. Journal of Endourology, 2011, 25(1): 11–17.

    Article  Google Scholar 

  6. YOON J W, CHEN R E, KIM E J, et al. Augmented reality for the surgeon: Systematic review [J]. The International Journal of Medical Robotics and Computer Assisted Surgery, 2018, 14(4): e1914.

    Article  Google Scholar 

  7. JUTZI S, IMKAMP F, KUCZYK M A, et al. New ex vivo organ model for percutaneous renal surgery using a laparoendoscopic training box: The sandwich model [J]. World Journal of Urology, 2014, 32(3): 783–789.

    Article  Google Scholar 

  8. KALLIDONIS P, KYRIAZIS I, VASILAS M, et al. Modular training for percutaneous nephrolithotripsy: The safe way to go [J]. Arab Journal of Urology, 2015, 13(4): 270–276.

    Article  Google Scholar 

  9. VIJAYAKUMAR M, BALAJI S, SINGH A, et al. A novel biological model for training in percutaneous renal access [J]. Arab Journal of Urology, 2019, 17(4): 292–297.

    Article  Google Scholar 

  10. VENEZIANO D, SMITH A, REIHSEN T, et al. The SimPORTAL fluoro-less C-arm trainer: An innovative device for percutaneous kidney access [J]. Journal of Endourology, 2015, 29(2): 240–245.

    Article  Google Scholar 

  11. TURNEY B W. A new model with an anatomically accurate human renal collecting system for training in fluoroscopy-guided percutaneous nephrolithotomy access [J]. Journal of Endourology, 2014, 28(3): 360–363.

    Article  Google Scholar 

  12. KLEIN J T, RASSWEILER J, RASSWEILER-SEYFRIED M C. Validation of a novel cost effective easy to produce and durable in vitro model for kidney-puncture and percutaneous nephrolitholapaxy-simulation [J]. Journal of Endourology, 2018, 32(9): 871–876.

    Article  Google Scholar 

  13. MISHRA S, KURIEN A, PATEL R, et al. Validation of virtual reality simulation for percutaneous renal access training [J]. Journal of Endourology, 2010, 24(4): 635–640.

    Article  Google Scholar 

  14. RANGARAJAN K, DAVIS H, PUCHER P H. Systematic review of virtual haptics in surgical simulation: A valid educational tool? [J]. Journal of Surgical Education, 2020, 77(2): 337–347.

    Article  Google Scholar 

  15. MISRA S, RAMESH K T, OKAMURA A M. Modeling of tool-tissue interactions for computer-based surgical simulation: A literature review [J]. Presence, 2008, 17(5): 463.

    Article  Google Scholar 

  16. BOTDEN S M B I, TORAB F, BUZINK S N, et al. The importance of haptic feedback in laparoscopic suturing training and the additive value of virtual reality simulation [J]. Surgical Endoscopy, 2008, 22(5): 1214–1222.

    Article  Google Scholar 

  17. DETMER F J, HETTIG J, SCHINDELE D, et al. Virtual and augmented reality systems for renal interventions: A systematic review [J]. IEEE Reviews in Biomedical Engineering, 2017, 10: 78–94.

    Article  Google Scholar 

  18. JAVIA L, SARDESAI M G. Physical models and virtual reality simulators in otolaryngology [J]. Otolaryngologic Clinics of North America, 2017, 50(5): 875–891.

    Article  Google Scholar 

  19. SCHIAVINA R, BIANCHI L, CHESSA F, et al. Augmented reality to guide selective clamping and tumor dissection during robot-assisted partial nephrectomy: A preliminary experience [J]. Clinical Genitourinary Cancer, 2021, 19(3): e149–e155.

    Article  Google Scholar 

  20. CHAUVET P, COLLINS T, DEBIZE C, et al. Augmented reality in a tumor resection model [J]. Surgical Endoscopy, 2018, 32(3): 1192–1201.

    Article  Google Scholar 

  21. LU S, SANCHEZ PERDOMO Y P, JIANG X T, et al. Integrating eye-tracking to augmented reality system for surgical training [J]. Journal of Medical Systems, 2020, 44(11): 1–7.

    Article  Google Scholar 

  22. BOTDEN S M, BUZINK S N, SCHIJVEN M P, et al. Augmented versus virtual reality laparoscopic simulation: what is the difference? [J]. World Journal of Surgery, 2007, 31(4): 764–772.

    Article  Google Scholar 

  23. MÜLLER M, RASSWEILER M C, KLEIN J, et al. Mobile augmented reality for computer-assisted percutaneous nephrolithotomy [J]. International Journal of Computer Assisted Radiology and Surgery, 2013, 8(4): 663–675.

    Article  Google Scholar 

  24. APPELBAUM L, SOSNA J, NISSENBAUM Y, et al. Electromagnetic navigation system for CT-guided biopsy of small lesions [J]. AJR American Journal of Roentgenology, 2011, 196(5): 1194–1200.

    Article  Google Scholar 

  25. WU J H, ZHOU P Y, LUO X, et al. Novel laser positioning navigation to aid puncture during percutaneous nephrolithotomy: A preliminary report [J]. World Journal of Urology, 2019, 37(6): 1189–1196.

    Article  Google Scholar 

  26. FICHTINGER G, DEGUET A, MASAMUNE K, et al. Image overlay guidance for needle insertion in CT scanner [J]. IEEE Transactions on Bio-Medical Engineering, 2005, 52(8): 1415–1424.

    Article  Google Scholar 

  27. RACADIO J M, NACHABE R, HOMAN R, et al. Augmented reality on a C-arm system: A preclinical assessment for percutaneous needle localization [J]. Radiology, 2016, 281(1): 249–255.

    Article  Google Scholar 

  28. SOLBIATI M, PASSERA K M, ROTILIO A, et al. Augmented reality for interventional oncology: Proof-of-concept study of a novel high-end guidance system platform [J]. European Radiology Experimental, 2018, 2: 18.

    Article  Google Scholar 

Download references

Acknowledgments

The authors thank the timely help given by American Journal Experts in improving the linguistics, punctuation, and grammar of the article.

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Authors and Affiliations

  1. School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Jiaqi Yu  (于佳琪), Shuyi Wang  (王殊轶), Yuqi Wang  (王浴屺), Zhanglei Wu  (吴张檑), Xiaoni Fu  (付小妮) & Bangfeng Ma  (马邦峰)

  2. Department of Urology, Shanghai Children’s Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200062, China

    Hua Xie  (谢 华)

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  1. Jiaqi Yu  (于佳琪)
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Correspondence to Shuyi Wang  (王殊轶).

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Foundation item: the National Natural Science Foundation of China (No. 11502146)

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Yu, J., Wang, S., Wang, Y. et al. Novel Visualization Tool for Percutaneous Renal Puncture Training Using Augmented Reality Technology. J. Shanghai Jiaotong Univ. (Sci.) 28, 517–525 (2023). https://doi.org/10.1007/s12204-022-2554-y

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  • DOI: https://doi.org/10.1007/s12204-022-2554-y

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