Monte Carlo-based patient internal dosimetry in fluoroscopy-guided interventional procedures: A review |
| |
| Institution: | 1. Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia;2. Division of Radiological Sciences, Singapore General Hospital, Outram Rd, Singapore 169608, Singapore;1. Palindromo Consulting, W. de Croylaan 51 3000 Leuven, Belgium;2. CHU UCL Namur site Sainte Elisabeth, Department of Cardiology, 5000 Namur, Belgium;3. GE Healthcare, 283 Rue de la Minière, 78530 Buc, France;1. Higher Institute of Medical Technologies of Tunis, Tunis El Manar University, Tunisia;2. Nuclear Physics and High Energy Unit, Faculty of Sciences of Tunis, Tunis El Manar University, Tunisia;3. University Hospital Center of Bordeaux. Bordeaux, France;4. Université de Bordeaux, CNRS/IN2P3, UMR5797, Centre d’Études Nucléaires de Bordeaux Gradignan, 33175 Gradignan, France;1. Instituto de Física, Universidade Federal de Uberlândia (INFIS/UFU), Uberlândia, MG, Brazil;2. Instituto Federal da Bahia (IFBA), Vitória da Conquista, BA, Brazil;3. Instituto de Pesquisas Energéticas e Nucleares, Comissão Nacional de Energia Nuclear (IPEN-CNEN/SP), São Paulo, SP, Brazil;4. Hospital Universitário Júlio Müller, Universidade Federal de Mato Grosso, Cuiabá, MT, Brazil;5. Programa de Pós-Graduação em Engenharia Biomédica, Faculdade de Engenharia Elétrica, Universidade Federal de Uberlândia, MG, Brazil;1. Department of Physics, Engineering Physics and Optics and Cancer Research Center, Université Laval, Quebec City, QC G1V 0A6, Canada;2. CRCT, UMR 1037, Inserm, Université Toulouse III Paul Sabatier, Toulouse, France;3. Department of Radiation Oncology and Research Center of CHU de Québec - Université Laval, Quebec City, QC G1R 2J6, Canada;1. Institut de Tècniques Energètiques, Universitat Politècnica de Catalunya, Avda. Diagonal, 647, 08028 Barcelona, Spain;2. IRSN – Institut de Radioprotection et de Sûreté Nucléaire, BP-17, 92262 Fontenay-aux-Roses, France;3. ENEA – IRP – Radiation Protection Institute, Via Martiri di Monte Sole, 4, 40129 Bologna, Italy;4. Greek Atomic Energy Commission (GAEC), Agia Paraskevi, Attiki, PO BOX 60092, Greece;1. Section of Radiological Sciences, Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Italy;2. Istituto Nazionale di Fisica Nucleare, Sezione di Catania, Italy;3. MIFT Department, University of Messina, Italy;4. Medical Applications Unit, Centro de Investigaciones Energéticas, MedioAmbientales y Tecnológicas (CIEMAT), Madrid, Spain;5. Nuclear Medicine Unit, University Hospital “G. Martino”, Messina, Italy |
| |
| Abstract: | PurposeThis systematic review aims to understand the dose estimation approaches and their major challenges. Specifically, we focused on state-of-the-art Monte Carlo (MC) methods in fluoroscopy-guided interventional procedures.MethodsAll relevant studies were identified through keyword searches in electronic databases from inception until September 2020. The searched publications were reviewed, categorised and analysed based on their respective methodology.ResultsHundred and one publications were identified which utilised existing MC-based applications/programs or customised MC simulations. Two outstanding challenges were identified that contribute to uncertainties in the virtual simulation reconstruction. The first challenge involves the use of anatomical models to represent individuals. Currently, phantom libraries best balance the needs of clinical practicality with those of specificity. However, mismatches of anatomical variations including body size and organ shape can create significant discrepancies in dose estimations. The second challenge is that the exact positioning of the patient relative to the beam is generally unknown. Most dose prediction models assume the patient is located centrally on the examination couch, which can lead to significant errors.ConclusionThe continuing rise of computing power suggests a near future where MC methods become practical for routine clinical dosimetry. Dynamic, deformable phantoms help to improve patient specificity, but at present are only limited to adjustment of gross body volume. Dynamic internal organ displacement or reshaping is likely the next logical frontier. Image-based alignment is probably the most promising solution to enable this, but it must be automated to be clinically practical. |
| |
| Keywords: | Interventional radiological procedures Patient organ dosimetry Fluoroscopy-guided Monte Carlo methods |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
