Organ-based estimation and minimization of clinician's X-ray dose.
Dosimetry
Gradient-free optimization
Monte Carlo simulation
Radiation protection
Journal
International journal of computer assisted radiology and surgery
ISSN: 1861-6429
Titre abrégé: Int J Comput Assist Radiol Surg
Pays: Germany
ID NLM: 101499225
Informations de publication
Date de publication:
Dec 2022
Dec 2022
Historique:
received:
24
02
2022
accepted:
24
06
2022
pubmed:
26
7
2022
medline:
16
11
2022
entrez:
25
7
2022
Statut:
ppublish
Résumé
Hybrid surgeries, allowing real-time visualization of patient inner anatomy, are possible through the use of intraoperative X-ray imaging. However, the intensive use of X-rays can have undesired consequences for the clinicians or the patient in the operating room (OR). In this paper, we provide a tool to visualize the X-rays and to optimally place protective shields in the hybrid operating room to reduce the clinician's dose according to their most sensitive body parts. We first acquire measurements in a hybrid operating room with dosimeters placed at different locations on a mannequin simulating a clinician. We demonstrate that a small displacement of a protective shield has significant consequences on the dose received by a clinician. Then, we reproduce the scene virtually and use Monte Carlo simulations to estimate the dose received by the clinician. Finally, we optimally place protective shields with a Nelder-Mead-based numerical optimization algorithm. The results show a high sensitivity of the clinician's dose to protective shield placement. Numerical optimization of the shields' placement can help to reduce the dose and show a decrease between 79 and 89% of the exposition when comparing no external shield protection and our optimal external shield position. Our work can help to raise awareness of the risks induced by X-rays during intraoperative surgery and reduce the dose received by the clinicians. In future work, our approach can be linked with human pose estimation algorithms to trace surgeons' moves, estimate dynamically the dose and summarize it in a surgical report, giving the dose for important organs.
Identifiants
pubmed: 35877018
doi: 10.1007/s11548-022-02710-3
pii: 10.1007/s11548-022-02710-3
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2357-2364Subventions
Organisme : Agence Nationale de la Recherche
ID : ANR-19-CE45-0011
Organisme : Agence Nationale de la Recherche
ID : ANR-10-IAHU-02
Informations de copyright
© 2022. CARS.
Références
Artis zee. https://www.siemens-healthineers.com/fr/angio/artis-interventional-angiography-systems/artis-zee . Accessed 27 April 2022
Alnewaini Z, Langer E, Schaber P, David M, Kretz D, Steil V, Hesser J (2017) Real-time, ray casting-based scatter dose estimation for C-arm X-ray system. J Appl Clin Med Phys 18(2):144–153
doi: 10.1002/acm2.12036
pubmed: 28300387
pmcid: 5689942
Bert J, Perez-Ponce H, El Bitar Z, Jan S, Boursier Y, Vintache D, Bonissent A, Morel C, Brasse D, Visvikis D (2013) Geant4-based Monte Carlo simulations on GPU for medical applications. Phys Med Biol 58(16):5593
doi: 10.1088/0031-9155/58/16/5593
pubmed: 23892709
Boone JM, Seibert JA (1997) An accurate method for computer-generating tungsten anode X-ray spectra from 30 to 140 kv. Med Phys 24(11):1661–1670
doi: 10.1118/1.597953
pubmed: 9394272
Charles MW (2008) ICRP publication 103: recommendations of the ICRP
Dauer LT, Ainsbury EA, Dynlacht J, Hoel D, Klein BE, Mayer D, Prescott CR, Thornton RH, Vano E, Woloschak GE, Flannery MC, Goldstein LE, Hamada N, Tran KP, Grissom MP, Blakely AE (2016) Status of NCRP scientific committee 1–23 commentary on guidance on radiation dose limits for the lens of the eye. Health Phys 110(2):182
doi: 10.1097/HP.0000000000000412
pubmed: 26717175
pmcid: 4697269
Della Vecchia E, Modenese A, Loney T, Muscatello M, Paulo MS, Rossi G, Gobba F (2020) Risk of cataract in health care workers exposed to ionizing radiation: a systematic review. La Medicina del Lavoro 111(4):269
pubmed: 32869764
pmcid: 7809955
Geant4-a simulation toolkit. https://geant4.web.cern.ch/ . Accessed 21 February 2022
Götz TI, Schmidkonz C, Chen S, Al-Baddai S, Kuwert T, Lang E (2020) A deep learning approach to radiation dose estimation. Phys Med Biol 65(3):035007
doi: 10.1088/1361-6560/ab65dc
pubmed: 31881547
Harrison JD, Balonov M, Bochud F, Martin CJ, Menzel HG, Smith-Bindman R, Ortiz-López P, Simmonds J, Wakeford R (2021) The use of dose quantities in radiological protection: ICRP publication 147 ANN ICRP 50 (1) 2021. J Radiol Prot 41(2):410
doi: 10.1088/1361-6498/abe548
Heymsfield S, Gonzalez M, Thomas D, Murray K, Jia G, Cattrysse E, Clarys JP, Scafoglieri A (2016) Adult human ocular volume: scaling to body size and composition. Anat Physiol 6(5):1000239
doi: 10.4172/2161-0940.1000239
ITIS foundation kernel description. https://itis.swiss/virtual-population/tissue-properties/database/density/ . Accessed 17 September 2021
Katz A, Shtub A, Solomonica A, Poliakov A, Roguin A (2017) Simulator training to minimize ionizing radiation exposure in the catheterization laboratory. Int J Cardiovasc Imaging 33(3):303–310
doi: 10.1007/s10554-016-1009-7
pubmed: 27817133
Kržanović N, Blideanu V, Ciraj-Bjelac O, Plagnard J, Schoonjans W, Živanović M, Dabin J (2021) Performance testing of dosimeters used in interventional radiology: results from the veridic project. Radiat Meas 141:106515
doi: 10.1016/j.radmeas.2021.106515
Ray safe. https://www.raysafe.com/products/real-time-staff-dosimetry/raysafe-i2-real-time-radiation-dosimeter . Accessed 22 October 2021
Reeves RR, Ang L, Bahadorani J, Naghi J, Dominguez A, Palakodeti V, Tsimikas S, Patel MP, Mahmud E (2015) Invasive cardiologists are exposed to greater left sided cranial radiation: the brain study (brain radiation exposure and attenuation during invasive cardiology procedures). JACC Cardiovasc Interv 8(9):1197–1206
doi: 10.1016/j.jcin.2015.03.027
pubmed: 26292583
Rodas NL, Bert J, Visvikis D, De Mathelin M, Padoy N (2017) Pose optimization of a C-arm imaging device to reduce intraoperative radiation exposure of staff and patient during interventional procedures. In: 2017 IEEE international conference on robotics and automation (ICRA). IEEE, pp 4200–4207
Singer S, Nelder J (2009) Nelder–Mead algorithm. Scholarpedia 4(7):2928
doi: 10.4249/scholarpedia.2928
Srivastav V, Gangi A, Padoy N (2019) Human pose estimation on privacy-preserving low-resolution depth images. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 583–591
Srivastav V, Gangi A, Padoy N (2020) Self-supervision on unlabelled or data for multi-person 2D/3D human pose estimation. In: International conference on medical image computing and computer-assisted intervention. Springer, pp 761–771
Streffer C (2007) The ICRP 2007 recommendations. Radiat Prot Dosim 127(1–4):2–7
doi: 10.1093/rpd/ncm246
Takata T, Kondo H, Yamamoto M, Shiraishi K, Kobayashi T, Furui S, Okamoto T, Oba H, Kotoku J (2020) Immersive radiation experience for interventional radiology with virtual reality radiation dose visualization using fast Monte Carlo dose estimation. Interv Radiol 5(2):58–66
doi: 10.22575/interventionalradiology.2019-0007
Thurston J (2010) NCRP report no. 160: ionizing radiation exposure of the population of the United States