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Title: The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions

Abstract

Purpose: To investigate the benefits and limitations of patient-phantom matching for determining organ dose during fluoroscopy guided interventions. Methods: In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient-specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patient-dependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections (PA/left lateral) and two abdominal projections (RAO/LPO). Organ dose conversion coefficients were then calculated for each patient-specific and patient-dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patient-specificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient-specific dose conversion coefficients as the reference. Results: Patient-phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient-phantom matching wasmore » clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections. Conclusions: The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient-phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient-dependent series.« less

Authors:
; ; ; ; ;  [1]
  1. Nuclear and Radiological Engineering, University of Florida, Gainesville, Florida 32611 (United States)
Publication Date:
OSTI Identifier:
22096889
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 38; Journal Issue: 2; Other Information: (c) 2011 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
61 RADIATION PROTECTION AND DOSIMETRY; 60 APPLIED LIFE SCIENCES; ACCURACY; COMPUTERIZED TOMOGRAPHY; DOSIMETRY; FLUOROSCOPY; METABOLIC DISEASES; MONTE CARLO METHOD; PATIENTS; PHANTOMS; RADIATION DOSES; SPECIFICITY

Citation Formats

Johnson, Perry B., Geyer, Amy, Borrego, David, Ficarrotta, Kayla, Johnson, Kevin, Bolch, Wesley E., Radiology, University of Florida, Jacksonville, Florida 32209, and Department of Nuclear and Radiological/Biomedical Engineering, University of Florida, Gainesville, Florida 32611-8300. The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions. United States: N. p., 2011. Web. doi:10.1118/1.3544353.
Johnson, Perry B., Geyer, Amy, Borrego, David, Ficarrotta, Kayla, Johnson, Kevin, Bolch, Wesley E., Radiology, University of Florida, Jacksonville, Florida 32209, & Department of Nuclear and Radiological/Biomedical Engineering, University of Florida, Gainesville, Florida 32611-8300. The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions. United States. https://doi.org/10.1118/1.3544353
Johnson, Perry B., Geyer, Amy, Borrego, David, Ficarrotta, Kayla, Johnson, Kevin, Bolch, Wesley E., Radiology, University of Florida, Jacksonville, Florida 32209, and Department of Nuclear and Radiological/Biomedical Engineering, University of Florida, Gainesville, Florida 32611-8300. 2011. "The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions". United States. https://doi.org/10.1118/1.3544353.
@article{osti_22096889,
title = {The impact of anthropometric patient-phantom matching on organ dose: A hybrid phantom study for fluoroscopy guided interventions},
author = {Johnson, Perry B. and Geyer, Amy and Borrego, David and Ficarrotta, Kayla and Johnson, Kevin and Bolch, Wesley E. and Radiology, University of Florida, Jacksonville, Florida 32209 and Department of Nuclear and Radiological/Biomedical Engineering, University of Florida, Gainesville, Florida 32611-8300},
abstractNote = {Purpose: To investigate the benefits and limitations of patient-phantom matching for determining organ dose during fluoroscopy guided interventions. Methods: In this study, 27 CT datasets representing patients of different sizes and genders were contoured and converted into patient-specific computational models. Each model was matched, based on height and weight, to computational phantoms selected from the UF hybrid patient-dependent series. In order to investigate the influence of phantom type on patient organ dose, Monte Carlo methods were used to simulate two cardiac projections (PA/left lateral) and two abdominal projections (RAO/LPO). Organ dose conversion coefficients were then calculated for each patient-specific and patient-dependent phantom and also for a reference stylized and reference hybrid phantom. The coefficients were subsequently analyzed for any correlation between patient-specificity and the accuracy of the dose estimate. Accuracy was quantified by calculating an absolute percent difference using the patient-specific dose conversion coefficients as the reference. Results: Patient-phantom matching was shown most beneficial for estimating the dose to heavy patients. In these cases, the improvement over using a reference stylized phantom ranged from approximately 50% to 120% for abdominal projections and for a reference hybrid phantom from 20% to 60% for all projections. For lighter individuals, patient-phantom matching was clearly superior to using a reference stylized phantom, but not significantly better than using a reference hybrid phantom for certain fields and projections. Conclusions: The results indicate two sources of error when patients are matched with phantoms: Anatomical error, which is inherent due to differences in organ size and location, and error attributed to differences in the total soft tissue attenuation. For small patients, differences in soft tissue attenuation are minimal and are exceeded by inherent anatomical differences. For large patients, difference in soft tissue attenuation can be large. In these cases, patient-phantom matching proves most effective as differences in soft tissue attenuation are mitigated. With increasing obesity rates, overweight patients will continue to make up a growing fraction of all patients undergoing medical imaging. Thus, having phantoms that better represent this population represents a considerable improvement over previous methods. In response to this study, additional phantoms representing heavier weight percentiles will be added to the UFHADM and UFHADF patient-dependent series.},
doi = {10.1118/1.3544353},
url = {https://www.osti.gov/biblio/22096889}, journal = {Medical Physics},
issn = {0094-2405},
number = 2,
volume = 38,
place = {United States},
year = {Tue Feb 15 00:00:00 EST 2011},
month = {Tue Feb 15 00:00:00 EST 2011}
}