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Rehani MM, Xu XG. Dose, dose, dose, but where is the patient dose? RADIATION PROTECTION DOSIMETRY 2024; 200:945-955. [PMID: 38847407 DOI: 10.1093/rpd/ncae137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/14/2024] [Accepted: 05/17/2024] [Indexed: 06/25/2024]
Abstract
The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed. Technological developments in recent years involving AI-based automatic organ segmentation and 'near real-time' Monte Carlo dose calculations suggest the feasibility and advantage of obtaining patient-specific organ doses. It appears that the time for ICRP and other international organizations to embrace 'patient-specific' dose quantity representing risk may have finally come. While the existing dose metrices meet specific demands, emphasis needs to be also placed on making radiation units understandable to the medical community.
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Affiliation(s)
- Madan M Rehani
- Massachusetts General Hospital, Radiology Department, Boston, MA, 02114, United States
| | - Xie George Xu
- University of Science and Technology of China (USTC), College of Nuclear Science & Technology, Hefei, Anhui Province, 230026, China
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2
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Ria F, Rehani MM, Samei E. Characterizing imaging radiation risk in a population of 8918 patients with recurrent imaging for a better effective dose. Sci Rep 2024; 14:6240. [PMID: 38485712 PMCID: PMC10940310 DOI: 10.1038/s41598-024-56516-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 03/07/2024] [Indexed: 03/18/2024] Open
Abstract
An updated extension of effective dose was recently introduced, namely relative effective dose ( E r ), incorporating age and sex factors. In this study we extended E r application to a population of about 9000 patients who underwent multiple CT imaging exams, and we compared it with other commonly used radiation protection metrics in terms of their correlation with radiation risk. Using Monte Carlo methods, E r , dose-length-product based effective dose ( E DLP ), organ-dose based effective dose ( E OD ), and organ-dose based risk index ( RI ) were calculated for each patient. Each metric's dependency to RI was assessed in terms of its sensitivity and specificity. E r showed the best sensitivity, specificity, and agreement with RI (R2 = 0.97); while E DLP yielded the lowest specificity and, along with E OD , the lowest sensitivity. Compared to other metrics, E r provided a closer representation of patient and group risk also incorporating age and sex factors within the established framework of effective dose.
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Affiliation(s)
- Francesco Ria
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Labs, Clinical Imaging Physics Group, Departments of Radiology, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA.
| | - Madan M Rehani
- Radiology Department, Massachusetts General Hospital, 175 Cambridge Str. Suite 0244, Boston, USA
| | - Ehsan Samei
- Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Labs, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
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3
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Alsaihati N, Ria F, Solomon J, Ding A, Frush D, Samei E. Making CT Dose Monitoring Meaningful: Augmenting Dose with Imaging Quality. Tomography 2023; 9:798-809. [PMID: 37104136 PMCID: PMC10145563 DOI: 10.3390/tomography9020065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 03/31/2023] [Accepted: 04/04/2023] [Indexed: 04/28/2023] Open
Abstract
Due to the concerns about radiation dose associated with medical imaging, radiation dose monitoring systems (RDMSs) are now utilized by many radiology providers to collect, process, analyze, and manage radiation dose-related information. Currently, most commercially available RDMSs focus only on radiation dose information and do not track any metrics related to image quality. However, to enable comprehensive patient-based imaging optimization, it is equally important to monitor image quality as well. This article describes how RDMS design can be extended beyond radiation dose to simultaneously monitor image quality. A newly designed interface was evaluated by different groups of radiology professionals (radiologists, technologists, and physicists) on a Likert scale. The results show that the new design is effective in assessing both image quality and safety in clinical practices, with an overall average score of 7.8 out of 10.0 and scores ranging from 5.5 to 10.0. Radiologists rated the interface highest at 8.4 out of 10.0, followed by technologists at 7.6 out of 10.0, and medical physicists at 7.5 out of 10.0. This work demonstrates how the assessment of the radiation dose can be performed in conjunction with the image quality using customizable user interfaces based on the clinical needs associated with different radiology professions.
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Affiliation(s)
- Njood Alsaihati
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Francesco Ria
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Virtual Imaging Trials, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Justin Solomon
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Virtual Imaging Trials, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Aiping Ding
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Donald Frush
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Virtual Imaging Trials, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Ehsan Samei
- Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Clinical Imaging Physics Group, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
- Center for Virtual Imaging Trials, Department of Radiology, Duke University Medical Center, Durham, NC 27710, USA
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Fukunaga M, Matsubara K, Yamaguchi Y. [Organ and Effective Doses Using Automation Organ Dose Estimation Software for Lung Cancer Screening Using Low-dose Computed Tomography]. Nihon Hoshasen Gijutsu Gakkai Zasshi 2022; 78:1176-1186. [PMID: 36058849 DOI: 10.6009/jjrt.2022-1205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
PURPOSE The purpose of this study was to evaluate the differences in the organ doses and the effective doses using three types of automated organ dose estimation software for low-dose computed tomography (CT) screening for lung cancer and to evaluate the correlations between each dose and size-specific dose estimates (SSDEs). METHODS Seventy-two adults who underwent low-dose CT screening for lung cancer were included, and the organ doses and the effective doses were calculated using each of automated organ dose estimation software. We evaluated differences between software for the organ doses and the effective doses and the correlations between each dose and SSDEs. RESULTS Differences in organ doses and effective doses were observed among the software. The organ doses showed a strong correlation (r=0.833-0.995) with SSDEs for organs within the scan range. The effective doses showed a strong correlation (r=0.830-0.970) with SSDEs, although there were significant differences among the software. CONCLUSION Although the organ doses and the effective doses differed between software, it may be possible to estimate them from SSDEs by using linear regression equations.
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Affiliation(s)
- Masaaki Fukunaga
- Department of Radiological Technology, Kurashiki Central Hospital
| | - Kosuke Matsubara
- Department of Quantum Medical Technology, Faculty of Health Sciences, Institute of Medical, Pharmaceutical and Health Sciences, Kanazawa University
| | - Yuki Yamaguchi
- Department of Radiological Technology, Kurashiki Central Hospital
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Sharma S, Kapadia A, Ria F, Segars WP, Samei E. Dose coefficients for organ dosimetry in tomosynthesis imaging of adults and pediatrics across diverse protocols. Med Phys 2022; 49:5439-5450. [PMID: 35690885 PMCID: PMC9536505 DOI: 10.1002/mp.15798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/16/2022] [Accepted: 05/31/2022] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The gold-standard method for estimation of patient-specific organ doses in digital tomosynthesis (DT) requires protocol-specific Monte Carlo (MC) simulations of radiation transport in anatomically accurate computational phantoms. Although accurate, MC simulations are computationally expensive, leading to a turnaround time in the order of core hours for simulating a single exam. This limits their clinical utility. The purpose of this study is to overcome this limitation by utilizing patient- and protocol-specific MC simulations to develop a comprehensive database of air-kerma-normalized organ dose coefficients for a virtual population of adult and pediatric patient models over an expanded set of exam protocols in DT for retrospective and prospective estimation of radiation dose in clinical tomosynthesis. MATERIALS AND METHODS A clinically representative virtual population of 14 patient models was used, with pediatric models (M and F) at ages 1, 5, 10, and 15 and adult patient models (M and F) with body mass index (BMIs) at 10th, 50th, and 90th percentiles of the US population. A graphics processing unit (GPU)-based MC simulation framework was used to simulate organ doses in the patient models, incorporating the scanner-specific configuration of a clinical DT system (VolumeRad, GE Healthcare, Waukesha, WI, USA) and an expanded set of exam protocols, including 21 distinct acquisition techniques for imaging a variety of anatomical regions (head and neck, thorax, spine, abdomen, and knee). Organ dose coefficients (hn ) were estimated by normalizing organ dose estimates to air kerma at 70 cm (X70cm ) from the source in the scout view. The corresponding coefficients for projection radiography were approximated using organ doses estimated for the scout view. The organ dose coefficients were further used to compute air-kerma-normalized patient-specific effective dose coefficients (Kn ) for all combinations of patients and protocols, and a comparative analysis examining the variation of radiation burden across sex, age, and exam protocols in DT, and with projection radiography was performed. RESULTS The database of organ dose coefficients (hn ) containing 294 distinct combinations of patients and exam protocols was developed and made publicly available. The values of Kn were observed to produce estimates of effective dose in agreement with prior studies and consistent with magnitudes expected for pediatric and adult patients across the different exam protocols, with head and neck regions exhibiting relatively lower and thorax and C-spine (apsc, apcs) regions relatively higher magnitudes. The ratios (r = Kn /Kn ,rad ) quantifying the differences air-kerma-normalized patient-specific effective doses between DT and projection radiography were centered around 1.0 for all exam protocols, with the exception of protocols covering the knee region (pawk, patk). CONCLUSIONS This study developed a database of organ dose coefficients for a virtual population of 14 adult and pediatric XCAT patient models over a set of 21 exam protocols in DT. Using empirical measurements of air kerma in the clinic, these organ dose coefficients enable practical retrospective and prospective patient-specific radiation dosimetry. The computation of air-kerma-normalized patient-specific effective doses further enables the comparison of radiation burden to the patient populations between protocols and between imaging modalities (e.g., DT and projection radiography), as presented in this study.
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Affiliation(s)
- Shobhit Sharma
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.,Department of Physics, Duke University, Durham, North Carolina, USA
| | - Anuj Kapadia
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.,Department of Physics, Duke University, Durham, North Carolina, USA
| | - Francesco Ria
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.,Clinical Imaging Physics Group, Department of Radiology, Duke University, Durham, North Carolina, USA
| | - W Paul Segars
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.,Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
| | - Ehsan Samei
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.,Department of Physics, Duke University, Durham, North Carolina, USA.,Clinical Imaging Physics Group, Department of Radiology, Duke University, Durham, North Carolina, USA.,Department of Biomedical Engineering, Duke University, Durham, North Carolina, USA
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Effective dose for kidney-ureter-bladder plain radiography, intravenous urography, and abdominal computed tomography scan: A phantom study. Appl Radiat Isot 2022; 187:110339. [DOI: 10.1016/j.apradiso.2022.110339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 05/07/2022] [Accepted: 06/17/2022] [Indexed: 11/21/2022]
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Lee S, Kim KW, Kwon HJ, Lee J, Koo K, Song GW, Lee SG. Relationship of body mass index and abdominal fat with radiation dose received during preoperative liver CT in potential living liver donors: a cross-sectional study. Quant Imaging Med Surg 2022; 12:2206-2212. [PMID: 35371965 PMCID: PMC8923845 DOI: 10.21037/qims-21-977] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 12/31/2021] [Indexed: 10/08/2023]
Abstract
BACKGROUND Although contrast-enhanced computed tomography (CT) is currently the most widely-used imaging modality for the preoperative evaluation of potential living liver donors, radiation exposure remains a major concern. The present study aimed to determine the relationship of body mass index (BMI) and abdominal fat with the effective radiation dose received during liver CT scans as part of a pre-donation work-up in potential living donors. METHODS This retrospective cross-sectional study included 695 potential living donors (mean age, 30.5±9.7 years; 445 men and 250 women) who had undergone preoperative liver CT scans between 2017 and 2018. The following measures were evaluated: BMI, abdominal fat as measured at the level of the third lumbar vertebra, and effective dose based on the dose length product (DLP). Correlations between the effective dose and other variables were evaluated using Pearson's correlation coefficient. RESULTS The mean BMI, total fat area (TFA), and effective dose were 23.6±3.3 kg/m2, 218.7±110.0 cm2, and 9.4±3.3 mSv, respectively. The effective dose during liver CT scans had a strong positive correlation with both BMI (r=0.715; P<0.001) and TFA (r=0.792; P<0.001). As BMI and TFA increased, so did the effective dose. CONCLUSIONS Higher BMI and TFA significantly increased the radiation dose received during liver CT scans in potential living donors.
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Affiliation(s)
- Sunyoung Lee
- Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Kyoung Won Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Heon-Ju Kwon
- Department of Radiology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jeongjin Lee
- School of Computer Science and Engineering, Soongsil University, Seoul, Republic of Korea
| | - Kyoyeong Koo
- School of Computer Science and Engineering, Soongsil University, Seoul, Republic of Korea
| | - Gi-Won Song
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Sung-Gyu Lee
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
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Ria F, D’Ercole L, Origgi D, Paruccini N, Pierotti L, Rampado O, Rossetti V, Strocchi S, Torresin A, Torresin A, Pierotti L, Belli G, Bregant P, Isoardi P, Mari A, Nitrosi A, Nocetti L, Paruccini N, Quattrocchi MG, Radice A, Rampado O, Scrittori N, Sottocornola C, Strocchi S, Sutto M, Zatelli G, Acchiappati D, Aoja RA, Brambilla M, Branchini M, Cannatà V, Costi T, Cutaia C, D.’Ercole L, Del Vecchio A, Delle Canne S, Di Pasquale M, Elisabetta S, Fabbri C, Faico MD, Fantinato D, Ghetti C, Giannelli M, Giordano C, Grisotto S, Guidi G, Lisciandro F, Manco L, Giorgio Marini P, Moresco P, Oberhofer N, Origgi D, Palleri F, Pasquali C, Pasquino M, Peruzzo A, Petrillo G, Pini S, Rembado D, Ria F, Riccardi L, Rosasco R, Serelli G, Soavi R, Stasi M, Taddeucci A, Tonini E, Trianni A, Turano P, Venturi G, Zefiro D, Zito F. Statement of the Italian Association of Medical Physics (AIFM) task group on radiation dose monitoring systems. Insights Imaging 2022; 13:23. [PMID: 35124735 PMCID: PMC8818083 DOI: 10.1186/s13244-022-01155-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 12/18/2021] [Indexed: 11/25/2022] Open
Abstract
The evaluation of radiation burden in vivo is crucial in modern radiology as stated also in the European Directive 2013/59/Euratom—Basic Safety Standard. Although radiation dose monitoring can impact the justification and optimization of radiological procedure, as well as effective patient communication, standardization of radiation monitoring software is far to be achieved. Toward this goal, the Italian Association of Medical Physics (AIFM) published a report describing the state of the art and standard guidelines in radiation dose monitoring system quality assurance. This article reports the AIFM statement about radiation dose monitoring systems (RDMSs) summarizing the different critical points of the systems related to Medical Physicist Expert (MPE) activities before, during, and after their clinical implementation. In particular, the article describes the general aspects of radiation dose data management, radiation dose monitoring systems, data integrity, and data responsibilities. Furthermore, the acceptance tests that need to be implemented and the most relevant dosimetric data for each radiological modalities are reported under the MPE responsibility.
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Sharma S, Kapadia A, Brown J, Segars WP, Bolch W, Samei E. A GPU-accelerated framework for individualized estimation of organ doses in digital tomosynthesis. Med Phys 2022; 49:891-900. [PMID: 34902159 PMCID: PMC8828666 DOI: 10.1002/mp.15400] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 11/16/2021] [Accepted: 11/24/2021] [Indexed: 02/03/2023] Open
Abstract
PURPOSE Estimation of organ doses in digital tomosynthesis (DT) is challenging due to the lack of existing tools that accurately and flexibly model protocol- and view-specific collimations and motion trajectories of the source and detector for a variety of exam protocols, and the computational inefficiencies of conducting MC simulations. The purpose of this study was to overcome these limitations by developing and benchmarking a GPU-accelerated MC simulation framework compatible with patient-specific computational phantoms for individualized estimation of organ doses in DT. MATERIALS AND METHODS The framework for individualized estimation of dose in DT was developed as a two-step workflow: (1) a custom MATLAB code that accepts a patient-specific computational phantom and exam description (organ markers for defining the extremities of the anatomical region of interest, tube voltage, source-to-image distance, angular sweep range, number of projection views, and the pivot point to image distance - PPID) to compute the field of views (FOVs) for a clinical DT system, and (2) a MC tool (developed using MC-GPU) modeling the configuration of a clinical DT system to estimate organ doses based on the computed FOVs. Using this framework, we estimated organ doses for 28 radiosensitive organs in an adult reference patient model (M; 30 years) imaged using a commercial DT system (VolumeRad, GE Healthcare, Waukesha, WI). The estimates were benchmarked against values from a comparable organ dose estimation framework (reference dataset developed by the Advanced Laboratory for Radiation Dosimetry Studies at University of Florida) for a posterior-anterior chest exam. The resulting differences were quantified as percent relative errors and analyzed to identify any potential sources of bias and uncertainties. The timing performance (run duration in seconds) of the framework was also quantified for the same simulation to gauge the feasibility of the workflow for time-constrained clinical applications. RESULTS The organ dose estimates from the developed framework showed a close agreement with the reference dataset, with percent relative errors ranging from -6.9% to 5.0% and a mean absolute percent difference of 1.7% over all radiosensitive organs, with the exception of testes and eye lens, for which the percent relative errors were higher at -18.9% and -27.6%, respectively, due to their relative positioning outside the primary irradiation field, leading to fewer photons depositing energy and consequently higher errors in estimated organ doses. The run duration for the same simulation was 916.3 s, representing a substantial improvement in performance over existing nonparallelized MC tools. CONCLUSIONS This study successfully developed and benchmarked a GPU-accelerated framework compatible with patient-specific anthropomorphic computational phantoms for accurate individualized estimation of organ doses in DT. By enabling patient-specific estimation of organ doses, this framework can aid clinicians and researchers by providing them with tools essential for tracking the radiation burden to patients for dose monitoring purposes and identifying the trends and relationships in organ doses for a patient population to optimize existing and develop new exam protocols.
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Affiliation(s)
- Shobhit Sharma
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd, Suite 302, Durham, NC 27705, USA,Department of Physics, Duke University, Science Drive, Durham, NC 27708, USA,Corresponding author:, Address: 2424 Erwin Rd. (Hock Plaza), Suite 302, NC, USA 27705
| | - Anuj Kapadia
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd, Suite 302, Durham, NC 27705, USA,Department of Physics, Duke University, Science Drive, Durham, NC 27708, USA
| | - J. Brown
- Division of Medical Physics, Department of Radiology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - W. Paul Segars
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd, Suite 302, Durham, NC 27705, USA,Department of Biomedical Engineering, Duke University Pratt School of Engineering, Science Drive, Durham, NC 27708, USA
| | - W. Bolch
- Division of Medical Physics, Department of Radiology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
| | - Ehsan Samei
- Center for Virtual Imaging Trials and Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd, Suite 302, Durham, NC 27705, USA,Department of Physics, Duke University, Science Drive, Durham, NC 27708, USA,Department of Biomedical Engineering, Duke University Pratt School of Engineering, Science Drive, Durham, NC 27708, USA,Department of Electrical and Computer Engineering, Duke University Pratt School of Engineering, Durham, NC 27708, USA
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Zewde N, Ria F, Rehani MM. Organ doses and cancer risk assessment in patients exposed to high doses from recurrent CT exams. Eur J Radiol 2022; 149:110224. [DOI: 10.1016/j.ejrad.2022.110224] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 01/24/2022] [Accepted: 02/16/2022] [Indexed: 11/03/2022]
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Ria F, Fu W, Hoye J, Segars WP, Kapadia AJ, Samei E. Comparison of 12 surrogates to characterize CT radiation risk across a clinical population. Eur Radiol 2021; 31:7022-7030. [PMID: 33624163 PMCID: PMC11229091 DOI: 10.1007/s00330-021-07753-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/07/2021] [Accepted: 02/04/2021] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Quantifying radiation burden is essential for justification, optimization, and personalization of CT procedures and can be characterized by a variety of risk surrogates inducing different radiological risk reflections. This study compared how twelve such metrics can characterize risk across patient populations. METHODS This study included 1394 CT examinations (abdominopelvic and chest). Organ doses were calculated using Monte Carlo methods. The following risk surrogates were considered: volume computed tomography dose index (CTDIvol), dose-length product (DLP), size-specific dose estimate (SSDE), DLP-based effective dose (EDk ), dose to a defining organ (ODD), effective dose and risk index based on organ doses (EDOD, RI), and risk index for a 20-year-old patient (RIrp). The last three metrics were also calculated for a reference ICRP-110 model (ODD,0, ED0, and RI0). Lastly, motivated by the ICRP, an adjusted-effective dose was calculated as [Formula: see text]. A linear regression was applied to assess each metric's dependency on RI. The results were characterized in terms of risk sensitivity index (RSI) and risk differentiability index (RDI). RESULTS The analysis reported significant differences between the metrics with EDr showing the best concordance with RI in terms of RSI and RDI. Across all metrics and protocols, RSI ranged between 0.37 (SSDE) and 1.29 (RI0); RDI ranged between 0.39 (EDk) and 0.01 (EDr) cancers × 103patients × 100 mGy. CONCLUSION Different risk surrogates lead to different population risk characterizations. EDr exhibited a close characterization of population risk, also showing the best differentiability. Care should be exercised in drawing risk predictions from unrepresentative risk metrics applied to a population. KEY POINTS • Radiation risk characterization in CT populations is strongly affected by the surrogate used to describe it. • Different risk surrogates can lead to different characterization of population risk. • Healthcare professionals should exercise care in ascribing an implicit risk to factors that do not closely reflect risk.
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Affiliation(s)
- Francesco Ria
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA.
- Clinical Imaging Physics Group, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA.
| | - Wanyi Fu
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
| | - Jocelyn Hoye
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
| | - W Paul Segars
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
| | - Anuj J Kapadia
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
| | - Ehsan Samei
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
- Clinical Imaging Physics Group, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
- Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University, 2424 Erwin Road, Suite 302, Durham, NC, 27710, USA
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Ria F, Fu W, Chalian H, Abadi E, Segars PW, Fricks R, Khoshpouri P, Samei E. A comparison of COVID-19 and imaging radiation risk in clinical patient populations. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2020; 40:10.1088/1361-6498/abbf3b. [PMID: 33027775 PMCID: PMC9757494 DOI: 10.1088/1361-6498/abbf3b] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 10/07/2020] [Indexed: 06/11/2023]
Abstract
The outbreak of coronavirus SARS-COV2 affected more than 180 countries necessitating fast and accurate diagnostic tools. Reverse transcriptase polymerase chain reaction (RT-PCR) has been identified as a gold standard test with Chest CT and Chest Radiography showing promising results as well. However, radiological solutions have not been used extensively for the diagnosis of COVID-19 disease, partly due to radiation risk. This study aimed to provide quantitative comparison of imaging radiation risk versus COVID risk. The analysis was performed in terms of mortality rate per age group. COVID-19 mortality was extracted from epidemiological data across 299, 004 patients published by ISS-Integrated surveillance of COVID-19 in Italy. For radiological risk, the study considered 659 Chest CT performed in adult patients. Organ doses were estimated using a Monte Carlo method and then used to calculate Risk Index that was converted into an upper bound for related mortality rate following NCI-SEER data. COVID-19 mortality showed a rapid rise for ages >30 years old (min: 0.30%; max: 30.20%), whereas only four deaths were reported in the analysed patient cohort for ages <20 years old. The rates decreased for radiation risk across age groups. The median mortality rate across all ages for Chest-CT and Chest-Radiography were 0.007% (min: 0.005%; max: 0.011%) and 0.0003% (min: 0.0002%; max: 0.0004%), respectively. COVID-19, Chest Radiography, and Chest CT mortality rates showed different magnitudes and trends across age groups. In higher ages, the risk of COVID-19 far outweighs that of radiological exams. Based on risk comparison alone, Chest Radiography and CT for COVID-19 care is justified for patients older than 20 and 30 years old, respectively. Notwithstanding other aspects of diagnosis, the present results capture a component of risk consideration associated with the use of imaging for COVID. Once integrated with other diagnostic factors, they may help inform better management of the pandemic.
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Affiliation(s)
- Francesco Ria
- Carl E. Ravin Advanced Imaging Labs and Clinical Imaging Physics Group, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
| | - Wanyi Fu
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
| | - Hamid Chalian
- Radiology Department, Duke University Health System, 2301 Erwin Road, Durham, NC 27710, United States of America
| | - Ehsan Abadi
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
| | - Paul W Segars
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
| | - Rafael Fricks
- Carl E. Ravin Advanced Imaging Labs, Duke University Health System, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
- Department of Veterans Affairs, 508 Fulton St, Durham, NC 27705, United States of America
| | - Pegah Khoshpouri
- Radiology Department, Duke University Health System, 2301 Erwin Road, Durham, NC 27710, United States of America
| | - Ehsan Samei
- Carl E. Ravin Advanced Imaging Labs, Clinical Imaging Physics Group, Medical Physics Graduate Program, Departments of Radiology, Physics, Biomedical Engineering, and Electrical and Computer Engineering, Duke University, 2424 Erwin Road, Suite 302, Durham, NC 27710, United States of America
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