Skip to main content
Springer Nature Link
Log in

Seeing is believing: increasing intraoperative awareness to scattered radiation in interventional procedures by combining augmented reality, Monte Carlo simulations and wireless dosimeters

  • Original Article
  • Published:
International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Surgical staff performing image-guided minimally invasive surgical procedures are chronically exposed to harmful ionizing radiation. Currently, no means exist to intraoperatively depict the 3D shape and intensity of scattered radiation fields or to assess the body-part exposure of clinicians. We propose a system for simulating and visualizing intraoperative scattered radiation using augmented reality.

Methods

We use a multi-camera RGBD system to obtain a 3D point cloud reconstruction of the current room layout. The positions of the clinicians, patient, table and C-arm are used to build a radiation propagation simulation model and compute the deposited dose distribution in the room. We use wireless dosimeters to calibrate the simulation and to evaluate its accuracy at each time step. The computed 3D risk map is shown in an augmented reality manner by overlaying the simulation results onto the 3D model.

Results

Several 3D visualizations showing scattered radiation propagation, clinicians’ body-part exposure and radiation risk maps under different irradiation conditions are proposed. The system is evaluated in an operating room equipped with a robotized X-ray imaging device by comparing the radiation simulation results to experimental measurements under several X-ray acquisition setups and room configurations.

Conclusions

The proposed system is capable to display intraoperative scattered radiation intuitively in 3D by using augmented reality. This can have a strong impact on improving clinicians’ awareness of their exposure to ionizing radiation and on reducing overexposure risks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Agostinelli S, Allison J, Amako K, Apostolakis J, Araujo H, Arce P, Asai M, Axen D, Banerjee S, Barrand G et al (2003) Geant4 a simulation toolkit. Nucl Instrum Methods Phys Res Sect A 506(3):250–303

    Article  CAS  Google Scholar 

  2. Badal A, Zafar F, Dong H, Badano A (2013) A real-time radiation dose monitoring system for patients and staff during interventional fluoroscopy using a gpu-accelerated monte carlo simulator and an automatic 3D localization system based on a depth camera. Proc SPIE 8668(28–28):11

    Google Scholar 

  3. Barrera F, Padoy N (2014) Piecewise planar decomposition of 3D point clouds obtained from multiple static RGB-D cameras. In: International Conference on 3D Vision (3DV)

  4. Bott OJ, Wagner M, Duwenkamp C, Hellrung N, Dresing K (2009) Improving education on c-arm operation and radiation protection with a computer-based training and simulation system. Int J Comput Assist Radiol Surg 4(4):399–407

    Article  PubMed  Google Scholar 

  5. Carinou E, Brodecki M, Domienik J, Donadille L, Koukorava C, Krim S, Nikodemova D, Ruiz-Lopez N, Sans-Merce M, Struelens L, Vanhavere F (2011a) Recommendations to reduce extremity and eye lens doses in interventional radiology and cardiology. Radiat Meas 46(11):1324–1329

    Article  CAS  Google Scholar 

  6. Carinou E, Ferrari P, Koukorava C, Krim S, Struelens L (2011b) Monte carlo calculations on extremity and eye lens dosimetry for medical staff at interventional radiology procedures. Radiat Prot Dosimetry 144(1–4):492–496

    Article  CAS  PubMed  Google Scholar 

  7. Durham J (2006) Concepts, quantities, and dose limits in radiation protection dosimetry. Radiat Meas 41(Supplement 1):S28–S35 The 2nd summer school on solid state dosimetry: concepts and trends in Medical Dosimetry

    Article  Google Scholar 

  8. ICRU (1980) Report No. n 33 in 1956–1964: National Bureau of Standards handbook. International Commission on Radiation Units and Measurements

  9. Kadkhodamohammadi A, Gangi A, de Mathelin M, Padoy N (2014) Temporally consistent 3D pose estimation in the interventional room using discrete MRF optimization over RGBD sequences. In: Stoyanov D, Collins D, Sakuma I, Abolmaesumi P, Jannin P (eds) Information processing in computer-assisted interventions, lecture notes in computer science, vol 8498. Springer International Publishing, Berlin, pp 168–177

    Chapter  Google Scholar 

  10. Koukorava C, Carinou E, Ferrari P, Krim S, Struelens L (2011) Study of the parameters affecting operator doses in interventional radiology using monte carlo simulations. Radiat Meas 46(11):1216–1222

    Article  CAS  Google Scholar 

  11. Krim S, Brodecki M, Carinou E, Donadille L, Jankowski J, Koukorava C, Dominiek J, Nikodemova D, Ruiz-Lopez N, Sans-Merce M, Struelens L, Vanhavere F (2011) Extremity doses of medical staff involved in interventional radiology and cardiology: correlations and annual doses (hands and legs). Radiat Meas 46(11):1223– 1227

    Article  CAS  Google Scholar 

  12. Ladikos A, Cagniart C, Ghotbi R, Reiser M, Navab N (2010) Estimating radiation exposure in interventional environments. In: Jiang T, Navab N, Pluim JP, Viergever MA (eds) Medical image computing and computer-assisted intervention MICCAI 2010. Lecture Notes in Computer Science, vol 6363. Springer, Berlin Heidelberg, pp 237–244

    Google Scholar 

  13. Loy Rodas N, Padoy N (2014) 3D global estimation and augmented reality visualization of intra-operative X-ray dose. In: Golland P, Hata N, Barillot C, Hornegger J, Howe R (eds) Medical image computing and computer-assisted intervention MICCAI 2014, lecture notes in computer science. Springer International Publishing, Berlin, pp 415–422

    Google Scholar 

  14. Miller DL, Society for Interventional Radiology (2009) Interventional fluoroscopy: reducing radiation risks for patients and staff. J Vasc Int Radiol JVIR 20(7 Suppl):S274

    Article  Google Scholar 

  15. OpenNI (2013) Primesense NiTE library. http://www.openni.org/files/nite

  16. RaySafe (2014) Raysafe i2 active dosimetry system. http://www.raysafe.com/en/Products/Staff/RaySafe

  17. Roguin A, Goldstein J, Bar O, Goldstein JA (2013) Brain and neck tumors among physicians performing interventional procedures. Am J Cardiol 111(9):1368–1372

    Article  PubMed  Google Scholar 

  18. Siemens HealthCare (2014) Artis zeego robotised X-ray imaging system. http://www.healthcare.siemens.com/medical-imaging/angio/artis-zee

  19. Siemens OEM Products (2014) X-ray toolbox. https://w9.siemens.com/cms/oemproducts/Home/X-rayToolbox

  20. Struelens L, Carinou E, Clairand I, Donadille L, Ginjaume M, Koukorava C, Krim S, Mol H, Sans-Merce M, Vanhavere F (2011) Use of active personal dosemeters in interventional radiology and cardiology: tests in hospitals oramed project. Radiat Meas 46(11):1258–1261 International workshop on optimization of radiation protection of medical staff, ORAMED 2011

    Article  CAS  Google Scholar 

  21. Vanhavere F, Carinou E, Gualdrini G, Clairand I, Merce M, Ginjaume M (2009) The oramed project: Optimisation of radiation protection for medical staff. In: Dssel O, Schlegel WC (eds) World Congress on Medical Physics and Biomedical Engineering, September 7–12, 2009, Munich, Germany, IFMBE Proceedings, vol 25/3. Springer, Berlin Heidelberg, pp 470–473

  22. Wagner M, Duwenkamp C, Dresing K, Bott OJ (2009) An approach to calculate and visualize intraoperative scattered radiation exposure. Stud Health Technol Inform 150:831–835

  23. Wagner M, Dresing K, Wolfram L, Ahrens CA, Bott OJ (2012) Siscar-gpu: fast simulation and visualization of intraoperative scattered radiation to support radiation protection training. MIE 180:968–972

Download references

Acknowledgments

This work was supported by French state funds managed by the ANR within the Investissements d’Avenir program under references ANR-11-LABX-0004 (Labex CAMI), ANR-10-IDEX-0002-02 (IdEx Unistra) and ANR-10-IAHU-02 (IHU Strasbourg). The authors would like to thank Siemens and RaySafe for their help with the devices as well as Nicolas Clauss and Ziad El Bitar for interesting discussions.

Conflict of interest

Nicolas Loy Rodas and Nicolas Padoy declare that they have no conflict of interest.

Ethical standard This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent Statement of informed consent was not applicable since the manuscript does not contain any patient data.

Author information

Authors and Affiliations

  1. ICube, University of Strasbourg, CNRS, IHU Strasbourg, 1 Place de l’Hopital, 67000, Strasbourg, France

    Nicolas Loy Rodas & Nicolas Padoy

Authors
  1. Nicolas Loy Rodas
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Nicolas Padoy
    View author publications

    You can also search for this author inPubMed Google Scholar

Corresponding author

Correspondence to Nicolas Loy Rodas.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Loy Rodas, N., Padoy, N. Seeing is believing: increasing intraoperative awareness to scattered radiation in interventional procedures by combining augmented reality, Monte Carlo simulations and wireless dosimeters. Int J CARS 10, 1181–1191 (2015). https://doi.org/10.1007/s11548-015-1161-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11548-015-1161-x

Keywords