Comparison of Smartphone Augmented Reality, Smartglasses Augmented Reality, and 3D CBCT-guided Fluoroscopy Navigation for Percutaneous Needle Insertion: A Phantom Study.


Journal

Cardiovascular and interventional radiology
ISSN: 1432-086X
Titre abrégé: Cardiovasc Intervent Radiol
Pays: United States
ID NLM: 8003538

Informations de publication

Date de publication:
May 2021
Historique:
received: 14 07 2020
accepted: 23 12 2020
pubmed: 8 1 2021
medline: 29 6 2021
entrez: 7 1 2021
Statut: ppublish

Résumé

To compare needle placement performance using an augmented reality (AR) navigation platform implemented on smartphone or smartglasses devices to that of CBCT-guided fluoroscopy in a phantom. An AR application was developed to display a planned percutaneous needle trajectory on the smartphone (iPhone7) and smartglasses (HoloLens1) devices in real time. Two AR-guided needle placement systems and CBCT-guided fluoroscopy with navigation software (XperGuide, Philips) were compared using an anthropomorphic phantom (CIRS, Norfolk, VA). Six interventional radiologists each performed 18 independent needle placements using smartphone (n = 6), smartglasses (n = 6), and XperGuide (n = 6) guidance. Placement error was defined as the distance from the needle tip to the target center. Placement time was recorded. For XperGuide, dose-area product (DAP, mGy*cm The placement error using the smartphone, smartglasses, or XperGuide was similar (3.98 ± 1.68 mm, 5.18 ± 3.84 mm, 4.13 ± 2.38 mm, respectively, p = 0.11). Compared to CBCT-guided fluoroscopy, the smartphone and smartglasses reduced placement time by 38% (p = 0.02) and 55% (p = 0.001), respectively. The DAP for insertion using XperGuide was 3086 ± 2920 mGy*cm Smartphone- and smartglasses-based augmented reality reduced needle placement time and radiation exposure while maintaining placement accuracy compared to a clinically validated needle navigation platform.

Identifiants

pubmed: 33409547
doi: 10.1007/s00270-020-02760-7
pii: 10.1007/s00270-020-02760-7
doi:

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

774-781

Subventions

Organisme : intramural research program of the national institutes of health
ID : NIH Z01 1ZID BC011242 and CL040015

Commentaires et corrections

Type : CommentIn

Références

Racadio JM, Babic D, Homan R, Rampton JW, Patel MN, Racadio JM, et al. Live 3D guidance in the interventional radiology suite. AJR Am J Roentgenol. 2007;189(6):W357–64.
doi: 10.2214/AJR.07.2469
Busser WM, Braak SJ, Futterer JJ, van Strijen MJ, Hoogeveen YL, de Lange F, et al. Cone beam CT guidance provides superior accuracy for complex needle paths compared with CT guidance. Br J Radiol. 2013;86(1030):20130310.
doi: 10.1259/bjr.20130310
Floridi C, Reginelli A, Capasso R, Fumarola E, Pesapane F, Barile A, et al. Percutaneous needle biopsy of mediastinal masses under C-arm conebeam CT guidance: diagnostic performance and safety. Med Oncol. 2017;34(4):67.
doi: 10.1007/s12032-017-0911-8
Fior D, Vacirca F, Leni D, Pagni F, Ippolito D, Riva L, et al. Virtual guidance of percutaneous transthoracic needle biopsy with C-arm cone-beam CT: diagnostic accuracy, risk factors and effective radiation dose. Cardiovasc Intervent Radiol. 2019;42(5):712–9.
doi: 10.1007/s00270-019-02163-3
Braak SJ, van Strijen MJ, van Leersum M, van Es HW, van Heesewijk JP. Real-Time 3D fluoroscopy guidance during needle interventions: technique, accuracy, and feasibility. AJR Am J Roentgenol. 2010;194(5):W445–51.
doi: 10.2214/AJR.09.3647
Ahn SY, Park CM, Yoon SH, Kim H, Goo JM. Learning curve of C-arm cone-beam computed tomography virtual navigation-guided percutaneous transthoracic needle biopsy. Korean J Radiol. 2019;20(5):844–53.
doi: 10.3348/kjr.2018.0555
Wood BJ, Locklin JK, Viswanathan A, Kruecker J, Haemmerich D, Cebral J, et al. Technologies for guidance of radiofrequency ablation in the multimodality interventional suite of the future. J Vasc Interv Radiol. 2007;18(1 Pt 1):9–24.
doi: 10.1016/j.jvir.2006.10.013
Park BJ, Hunt SJ, Martin C, Nadolski GJ, Wood BJ, Gade TP. Augmented and mixed reality: technologies for enhancing the future of IR. J Vasc Interv Radiol. 2020;31:1074–82.
doi: 10.1016/j.jvir.2019.09.020
Uppot RN, Laguna B, McCarthy CJ, De Novi G, Phelps A, Siegel E, et al. Implementing virtual and augmented reality tools for radiology education and training, communication, and clinical care. Radiology. 2019;291(3):570–80.
doi: 10.1148/radiol.2019182210
Kenngott HG, Preukschas AA, Wagner M, Nickel F, Muller M, Bellemann N, et al. Mobile, real-time, and point-of-care augmented reality is robust, accurate, and feasible: a prospective pilot study. Surg Endosc. 2018;32(6):2958–67.
doi: 10.1007/s00464-018-6151-y
Heinrich F, Joeres F, Lawonn K, Hansen C. Comparison of projective augmented reality concepts to support medical needle insertion. IEEE Trans Vis Comput Graph. 2019;25(6):2157–67.
doi: 10.1109/TVCG.2019.2903942
Solbiati M, Passera KM, Rotilio A, Oliva F, Marre I, Goldberg SN, et al. Augmented reality for interventional oncology: proof-of-concept study of a novel high-end guidance system platform. Eur Radiol Exp. 2018;2:18.
doi: 10.1186/s41747-018-0054-5
Elsayed M, Kadom N, Ghobadi C, Strauss B, Al Dandan O, Aggarwal A, et al. Virtual and augmented reality: potential applications in radiology. Acta Radiol. 2020. https://doi.org/10.1177/0284185119897362 .
doi: 10.1177/0284185119897362 pubmed: 31928346
Pratt P, Ives M, Lawton G, Simmons J, Radev N, Spyropoulou L, et al. Through the HoloLens looking glass: augmented reality for extremity reconstruction surgery using 3D vascular models with perforating vessels. Eur Radiol Exp. 2018;2(1):2.
doi: 10.1186/s41747-017-0033-2
Barsom EZ, Graafland M, Schijven MP. Systematic review on the effectiveness of augmented reality applications in medical training. Surg Endosc. 2016;30(10):4174–83.
doi: 10.1007/s00464-016-4800-6
Li M, Seifabadi R, Long D, De Ruiter Q, Varble N, Hecht R, et al. Smartphone- versus smartglasses-based augmented reality (AR) for percutaneous needle interventions: system accuracy and feasibility study. Int J Computer Assist Radiol Surg. 2020;15:1921–30.
doi: 10.1007/s11548-020-02235-7
Hecht R, Li M, de Ruiter QMB, Pritchard WF, Li X, Krishnasamy V, et al. Smartphone augmented reality CT-based platform for needle insertion guidance: a phantom study. Cardiovasc Intervent Radiol. 2020;43:756–64.
doi: 10.1007/s00270-019-02403-6
Vovk A, Wild F, Guest W, Kuula T, editors. Simulator Sickness in Augmented Reality Training Using the Microsoft HoloLens. Conference on Human Factors in Computing Systems; 2018; Montreal, Canada. New York, NY United States: Association for Computing Machinery, New York, NY; 2018.
Rebenitsch L, Owen C. Review on cybersickness in applications and visual displays. Virtual Real. 2016;20(2):101–35.
doi: 10.1007/s10055-016-0285-9
Racadio JM, et al. Augmented reality on a C-arm system: a preclinical assessment for percutaneous needle localization. Radiology. 2016;281:249–55.
doi: 10.1148/radiol.2016151040
Nicolau SA, Pennec X, Soler L, Buy X, Gangi A, Ayache N, et al. An augmented reality system for liver thermal ablation: design and evaluation on clinical cases. Med Image Anal. 2009;13(3):494–506.
doi: 10.1016/j.media.2009.02.003
Fichtinger G, Deguet A, Masamune K, Balogh E, Fischer GS, Mathieu H, et al. Image overlay guidance for needle insertion in CT scanner. IEEE Trans Biomed Eng. 2005;52(8):1415–24.
doi: 10.1109/TBME.2005.851493
Si W, Liao X, Qian Y, Wang Q. Mixed reality guided radiofrequency needle placement: a pilot study. IEEE Access. 2018;6:31493–502.
doi: 10.1109/ACCESS.2018.2843378
Lin MA, Siu AF, Bae JH, Cutkosky MR, Daniel BL. HoloNeedle: augmented reality guidance system for needle placement investigating the advantages of three-dimensional needle shape reconstruction. IEEE Robot Autom Lett. 2018;3(4):4156–62.
doi: 10.1109/LRA.2018.2863381

Auteurs

Dilara J Long (DJ)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Ming Li (M)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA. ming.li@nih.gov.

Quirina M B De Ruiter (QMB)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Rachel Hecht (R)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Xiaobai Li (X)

Biostatistics and Clinical Epidemiology Service, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Nicole Varble (N)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.
Philips Research of North America, Cambridge, MA, 02141, USA.

Maxime Blain (M)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Michael T Kassin (MT)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Karun V Sharma (KV)

Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Health System, Washington, DC, USA.

Shawn Sarin (S)

Department of Interventional Radiology, George Washington University Hospital, Washington, DC, USA.

Venkatesh P Krishnasamy (VP)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

William F Pritchard (WF)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

John W Karanian (JW)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Bradford J Wood (BJ)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

Sheng Xu (S)

Center for Interventional Oncology, Radiology and Imaging Sciences, Clinical Center, National Institutes of Health, Bethesda, MD, 20892, USA.

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