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Ntoufas N, Raissaki M, Damilakis J, Perisinakis K. Comparison of radiation exposure from dual- and single-energy CT imaging protocols resulting in equivalent contrast-to-noise ratio of lesions for adults and children: a phantom study. Eur Radiol 2025; 35:3528-3537. [PMID: 39694888 DOI: 10.1007/s00330-024-11273-7] [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] [Received: 08/09/2024] [Revised: 10/15/2024] [Accepted: 11/04/2024] [Indexed: 12/20/2024]
Abstract
OBJECTIVES To compare the radiation exposure from single-energy CT (SECT) against rapid kV-switching dual-energy CT (DECT) imaging in both adults and children when resulting image data offer equivalent lesion identification power. MATERIALS AND METHODS Lesions in an adult and a 10-year-old-child body phantom were imitated using iodine solutions of different concentrations. Phantoms were subjected to several SECT and DECT thoracic and abdominal scans using a rapid kV-switching DECT scanner. The contrast-to-noise ratio (CNR) of each lesion was measured on resulting SECT images and virtual monoenergetic images (VMI) available from DECT. The SECT scans that resulted in CNR values similar to the maximum CNR observed in VMIs derived from corresponding DECT scans were identified. SECT and DECT scans with equivalent lesion-discriminating power were compared regarding the associated radiation dose burden. Doses to the lung, breast, and esophagus from thoracic imaging and doses to the liver, kidneys, and stomach from abdominal imaging were determined through Monte Carlo simulations of SECT and DECT exposures. RESULTS Compared to SECT imaging of the adult body phantom, organ doses from DECT were found to be 5-11% lower in thoracic imaging and 44-45% lower in abdominal imaging. Compared to SECT imaging of the 10-year-old body phantom, organ doses from DECT were found to be 2.8-3.4 times higher in thoracic imaging and 1.5-1.6 times higher in abdominal imaging. CONCLUSION The use of rapid kV-switching DECT instead of SECT imaging may be associated with a similar or lower dose burden in adults but a noticeably higher dose burden in children. KEY POINTS Question How does the radiation exposure from single-energy and dual-energy CT imaging compare when both techniques provide equivalent lesion identification power? Findings Rapid kV-switching dual-energy CT compared to single-energy CT may result in a similar or lower radiation dose in adults, but higher radiation dose in children. Clinical relevance Rapid kV-switching dual-energy CT imaging in children should be preferred over single-energy CT imaging only in cases where the additional information provided is crucial for an effective diagnosis.
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Affiliation(s)
- Nikos Ntoufas
- University of Crete, Medical School, Department of Medical Physics, 71003, Heraklion, Crete, Greece
| | - Maria Raissaki
- University of Crete, Medical School, Department of Radiology, 71003, Heraklion, Crete, Greece
| | - John Damilakis
- University of Crete, Medical School, Department of Medical Physics, 71003, Heraklion, Crete, Greece
| | - Kostas Perisinakis
- University of Crete, Medical School, Department of Medical Physics, 71003, Heraklion, Crete, Greece.
- Computational BioMedicine Laboratory (CBML), Foundation for Research and Technology-Hellas (FORTH), Heraklion, Greece.
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Tzanis E, Damilakis J. A machine learning-based pipeline for multi-organ/tissue patient-specific radiation dosimetry in CT. Eur Radiol 2025; 35:919-928. [PMID: 39136706 DOI: 10.1007/s00330-024-11002-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 06/29/2024] [Accepted: 07/18/2024] [Indexed: 02/01/2025]
Abstract
OBJECTIVES To develop a machine learning-based pipeline for multi-organ/tissue personalized radiation dosimetry in CT. MATERIALS AND METHODS For the study, 95 chest CT scans and 85 abdominal CT scans were collected retrospectively. For each CT scan, a personalized Monte Carlo (MC) simulation was carried out. The produced 3D dose distributions and the respective CT examinations were utilized for the development of organ/tissue-specific dose prediction deep neural networks (DNNs). A pipeline that integrates a robust open-source organ segmentation tool with the dose prediction DNNs was developed for the automatic estimation of radiation doses for 30 organs/tissues including sub-volumes of the heart and lungs. The accuracy and time efficiency of the presented methodology was assessed. Statistical analysis (t-tests) was conducted to determine if the differences between the ground truth organ/tissue radiation dose estimates and the respective dose predictions were significant. RESULTS The lowest median percentage differences between MC-derived organ/tissue doses and DNN dose predictions were observed for the lung vessels (4.3%), small bowel (4.7%), pulmonary artery (4.7%), and colon (5.2%), while the highest differences were observed for the right lung's upper lobe (13.3%), spleen (13.1%), pancreas (12.1%), and stomach (11.6%). Statistical analysis showed that the differences were not significant (p-value > 0.18). Furthermore, the mean inference time, regarding the validation cohort, of the developed methodology was 77.0 ± 11.0 s. CONCLUSION The proposed workflow enables fast and accurate organ/tissue radiation dose estimations. The developed algorithms and dose prediction DNNs are publicly available ( https://github.com/eltzanis/multi-structure-CT-dosimetry ). CLINICAL RELEVANCE STATEMENT The accuracy and time efficiency of the developed pipeline compose a useful tool for personalized dosimetry in CT. By adopting the proposed workflow, institutions can utilize an automated pipeline for patient-specific dosimetry in CT. KEY POINTS Personalized dosimetry is ideal, but is time-consuming. The proposed pipeline composes a tool for facilitating patient-specific CT dosimetry in routine clinical practice. The developed workflow integrates a robust open-source segmentation tool with organ/tissue-specific dose prediction neural networks.
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Affiliation(s)
- Eleftherios Tzanis
- Department of Medical Physics, School of Medicine, University of Crete, Heraklion, Greece
| | - John Damilakis
- Department of Medical Physics, School of Medicine, University of Crete, Heraklion, Greece.
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Damilakis J, Stratakis J. Descriptive overview of AI applications in x-ray imaging and radiotherapy. JOURNAL OF RADIOLOGICAL PROTECTION : OFFICIAL JOURNAL OF THE SOCIETY FOR RADIOLOGICAL PROTECTION 2024; 44:041001. [PMID: 39681008 DOI: 10.1088/1361-6498/ad9f71] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Accepted: 12/16/2024] [Indexed: 12/18/2024]
Abstract
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimising radiation doses for x-ray imaging, improving radiotherapy outcomes, and briefly addresses the benefits, challenges, and limitations of AI integration into clinical workflows. In diagnostic radiology, AI plays a pivotal role in optimising radiation exposure, reducing noise, enhancing image contrast, and lowering radiation doses, especially in high-dose procedures like computed tomography (CT). Deep learning (DL)-powered CT reconstruction methods have already been incorporated into clinical routine. Moreover, AI-powered methodologies have been developed to provide real-time, patient-specific radiation dose estimates. These AI-driven tools have the potential to streamline workflows and potentially become integral parts of imaging practices. In radiotherapy, AI's ability to automate and enhance the precision of treatment planning is emphasised. Traditional methods, such as manual contouring, are time-consuming and prone to variability. AI-driven techniques, particularly DL models, are automating the segmentation of organs and tumours, improving the accuracy of radiation delivery, and minimising damage to healthy tissues. Moreover, AI supports adaptive radiotherapy, allowing continuous optimisation of treatment plans based on changes in a patient's anatomy over time, ensuring the highest accuracy in radiation delivery and better therapeutic outcomes. Some of these methods have been validated and integrated into radiation treatment systems, while others are not yet ready for routine clinical use mainly due to challenges in validation, particularly ensuring reliability across diverse patient populations and clinical settings. Despite the potential of AI, there are challenges in fully integrating these technologies into clinical practice. Issues such as data protection, privacy, data quality, model validation, and the need for large and diverse datasets are crucial to ensuring the reliability of AI systems.
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Affiliation(s)
- John Damilakis
- School of Medicine, University of Crete, Heraklion, Greece
- University Hospital of Heraklion, Crete, Greece
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Verfaillie G, Rutten J, Dewulf L, D'Asseler Y, Bacher K. Influence of X-ray spectrum and bowtie filter characterisation on the accuracy of Monte Carlo simulated organ doses: Validation in a whole-body CT scanning mode. Phys Med 2024; 127:104837. [PMID: 39461069 DOI: 10.1016/j.ejmp.2024.104837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 09/05/2024] [Accepted: 10/18/2024] [Indexed: 10/29/2024] Open
Abstract
PURPOSE For patient-specific CT dosimetry, Monte Carlo dose simulations require an accurate description of the CT scanner. However, quantitative spectral information and information on the bowtie filter material and shape from the manufacturer is often not available. In this study, the influence of different X-ray spectra and bowtie filter characterisation methods on simulated CT organ doses is studied. METHODS Using ImpactMC, organ doses of whole-body CTs were simulated in twenty adult whole-body voxel models, generated from PET/CT examinations previously conducted in these patients. Simulated CT organ doses based on the manufacturer X-ray spectra and bowtie filter data were compared with those obtained using alternative characterisation models, including spectrum generators and experimentally measured dose data. A total of four different X-ray spectra and one bowtie filter model were defined based on these data. RESULTS For all X-ray spectra and bowtie filter combinations, estimated CT organ doses are within 6% from those resulting from simulations with the CT characterisation models provided by the manufacturer. While varying the bowtie filter model results in CT organ dose differences smaller than 1%, dose differences up to 6% are observed when X-ray spectra are not based on the quantitative data from the manufacturer. CONCLUSIONS Estimated organ doses slightly depend on the applied CT characterisation model. When manufacturer's data are not available, half-value layer and dose measurements provide sufficient input to obtain equivalent X-ray spectra and bowtie filter profiles, respectively.
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Affiliation(s)
- Gwenny Verfaillie
- Department of Human Structure and Repair, Ghent University, Proeftuinstraat 86 - Building N7, 9000 Ghent, Belgium.
| | - Jeff Rutten
- Department of Human Structure and Repair, Ghent University, Proeftuinstraat 86 - Building N7, 9000 Ghent, Belgium.
| | - Lore Dewulf
- Department of Human Structure and Repair, Ghent University, Proeftuinstraat 86 - Building N7, 9000 Ghent, Belgium.
| | - Yves D'Asseler
- Department of Nuclear Medicine, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium; Department of Diagnostic Sciences, Ghent University, Corneel Heymanslaan 10, 9000 Ghent, Belgium.
| | - Klaus Bacher
- Department of Human Structure and Repair, Ghent University, Proeftuinstraat 86 - Building N7, 9000 Ghent, Belgium.
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Verfaillie G, Rutten J, D'Asseler Y, Bacher K. Accuracy of patient-specific CT organ doses from Monte Carlo simulations: influence of CT-based voxel models. Phys Eng Sci Med 2024; 47:989-1000. [PMID: 38634980 PMCID: PMC11408396 DOI: 10.1007/s13246-024-01422-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 04/01/2024] [Indexed: 04/19/2024]
Abstract
Monte Carlo simulations using patient CT images as input are the gold standard to perform patient-specific dosimetry. However, in standard clinical practice patient's CT images are limited to the reconstructed CT scan range. In this study, organ dose calculations were performed with ImpactMC for chest and cardiac CT using whole-body and anatomy-specific voxel models to estimate the accuracy of CT organ doses based on the latter model. When the 3D patient model is limited to the CT scan range, CT organ doses from Monte Carlo simulations are the most accurate for organs entirely in the field of view. For these organs only the radiation dose related to scatter from the rest of the body is not incorporated. For organs lying partially outside the field of view organ doses are overestimated by not accounting for the non-irradiated tissue mass. This overestimation depends strongly on the amount of the organ volume located outside the field of view. To get a more accurate estimation of the radiation dose to these organs, the ICRP reference organ masses and densities could form a solution. Except for the breast, good agreement in dose was found for most organs. Voxel models generated from clinical CT examinations do not include the overscan in the z-direction. The availability of whole-body voxel models allowed to study this influence as well. As expected, overscan induces slightly higher organ doses.
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Affiliation(s)
- Gwenny Verfaillie
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium.
| | - Jeff Rutten
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
| | - Yves D'Asseler
- Department of Nuclear Medicine, Ghent University Hospital, Ghent, Belgium
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Klaus Bacher
- Department of Human Structure and Repair, Ghent University, Ghent, Belgium
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Berris T, Myronakis M, Stratakis J, Perisinakis K, Karantanas A, Damilakis J. Is deep learning-enabled real-time personalized CT dosimetry feasible using only patient images as input? Phys Med 2024; 122:103381. [PMID: 38810391 DOI: 10.1016/j.ejmp.2024.103381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/28/2024] [Accepted: 05/20/2024] [Indexed: 05/31/2024] Open
Abstract
PURPOSE To propose a novel deep-learning based dosimetry method that allows quick and accurate estimation of organ doses for individual patients, using only their computed tomography (CT) images as input. METHODS Despite recent advances in medical dosimetry, personalized CT dosimetry remains a labour-intensive process. Current state-of-the-art methods utilize time-consuming Monte Carlo (MC) based simulations for individual organ dose estimation in CT. The proposed method uses conditional generative adversarial networks (cGANs) to substitute MC simulations with fast dose image generation, based on image-to-image translation. The pix2pix architecture in conjunction with a regression model was utilized for the generation of the synthetic dose images. The lungs, heart, breast, bone and skin were manually segmented to estimate and compare organ doses calculated using both the original and synthetic dose images, respectively. RESULTS The average organ dose estimation error for the proposed method was 8.3% and did not exceed 20% for any of the organs considered. The performance of the method in the clinical environment was also assessed. Using segmentation tools developed in-house, an automatic organ dose calculation pipeline was set up. Calculation of organ doses for heart and lung for each CT slice took about 2 s. CONCLUSIONS This work shows that deep learning-enabled personalized CT dosimetry is feasible in real-time, using only patient CT images as input.
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Affiliation(s)
- Theocharis Berris
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete, Greece
| | - Marios Myronakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete, Greece
| | - John Stratakis
- Department of Medical Physics, University Hospital of Iraklion, 71110 Iraklion, Crete, Greece
| | - Kostas Perisinakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete, Greece
| | - Apostolos Karantanas
- Department of Radiology, School of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete, Greece
| | - John Damilakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003 Iraklion, Crete, Greece.
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Tsironi F, Myronakis M, Stratakis J, Sotiropoulou V, Damilakis J. Organ dose prediction for patients undergoing radiotherapy CBCT chest examinations using artificial intelligence. Phys Med 2024; 119:103305. [PMID: 38320358 DOI: 10.1016/j.ejmp.2024.103305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/13/2024] [Accepted: 01/29/2024] [Indexed: 02/08/2024] Open
Abstract
PURPOSE To propose an artificial intelligence (AI)-based method for personalized and real-time dosimetry for chest CBCT acquisitions. METHODS CT images from 113 patients who underwent radiotherapy treatment were collected for simulating thorax examinations using cone-beam computed tomography (CBCT) with the Monte Carlo technique. These simulations yielded organ dose data, used to train and validate specific AI algorithms. The efficacy of these AI algorithms was evaluated by comparing dose predictions with the actual doses derived from Monte Carlo simulations, which are the ground truth, utilizing Bland-Altman plots for this comparative analysis. RESULTS The absolute mean discrepancies between the predicted doses and the ground truth are (0.9 ± 1.3)% for bones, (1.2 ± 1.2)% for the esophagus, (0.5 ± 1.3)% for the breast, (2.5 ± 1.4)% for the heart, (2.4 ± 2.1)% for lungs, (0.8 ± 0.6)% for the skin, and (1.7 ± 0.7)% for integral. Meanwhile, the maximum discrepancies between the predicted doses and the ground truth are (14.4 ± 1.3)% for bones, (12.9 ± 1.2)% for the esophagus, (9.4 ± 1.3)% for the breast, (14.6 ± 1.4)% for the heart, (21.2 ± 2.1)% for lungs, (10.0 ± 0.6)% for the skin, and (10.5 ± 0.7)% for integral. CONCLUSIONS AI models that can make real-time predictions of the organ doses for patients undergoing CBCT thorax examinations as part of radiotherapy pre-treatment positioning were developed. The results of this study clearly show that the doses predicted by analyzed AI models are in close agreement with those calculated using Monte Carlo simulations.
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Affiliation(s)
- Fereniki Tsironi
- Department of Medical Physics, University Hospital of Crete, Iraklion, Greece
| | - Marios Myronakis
- Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece
| | - John Stratakis
- Department of Medical Physics, University Hospital of Crete, Iraklion, Greece; Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece
| | | | - John Damilakis
- Department of Medical Physics, University Hospital of Crete, Iraklion, Greece; Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece.
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Tzanis E, Stratakis J, Myronakis M, Damilakis J. A fully automated machine learning-based methodology for personalized radiation dose assessment in thoracic and abdomen CT. Phys Med 2024; 117:103195. [PMID: 38048731 DOI: 10.1016/j.ejmp.2023.103195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/26/2023] [Accepted: 11/28/2023] [Indexed: 12/06/2023] Open
Abstract
PURPOSE To develop a machine learning-based methodology for patient-specific radiation dosimetry in thoracic and abdomen CT. METHODS Three hundred and thirty-one thoracoabdominal radiotherapy-planning CT examinations with the respective organ/patient contours were collected retrospectively for the development and validation of segmentation 3D-UNets. Moreover, 97 diagnostic thoracic and 89 diagnostic abdomen CT examinations were collected retrospectively. For each of the diagnostic CT examinations, personalized MC dosimetry was performed. The data derived from MC simulations along with the respective CT data were used for the training and validation of a dose prediction deep neural network (DNN). An algorithm was developed to utilize the trained models and perform patient-specific organ dose estimates for thoracic and abdomen CT examinations. The doses estimated with the DNN were compared with the respective doses derived from MC simulations. A paired t-test was conducted between the DNN and MC results. Furthermore, the time efficiency of the proposed methodology was assessed. RESULTS The mean percentage differences (range) between DNN and MC dose estimates for the lungs, liver, spleen, stomach, and kidneys were 7.2 % (0.2-24.1 %), 5.5 % (0.4-23.0 %), 7.9 % (0.6-22.3 %), 6.9 % (0.0-23.0 %) and 6.7 % (0.3-22.6 %) respectively. The differences between DNN and MC dose estimates were not significant (p-value = 0.12). Moreover, the mean processing time of the proposed workflow was 99 % lower than the respective time needed for MC-based dosimetry. CONCLUSIONS The proposed methodology can be used for rapid and accurate patient-specific dosimetry in chest and abdomen CT.
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Affiliation(s)
- Eleftherios Tzanis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, Heraklion, Crete 71003, Greece
| | - John Stratakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, Heraklion, Crete 71003, Greece
| | - Marios Myronakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, Heraklion, Crete 71003, Greece
| | - John Damilakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, Heraklion, Crete 71003, Greece.
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Myronakis M, Stratakis J, Damilakis J. Rapid estimation of patient-specific organ doses using a deep learning network. Med Phys 2023; 50:7236-7244. [PMID: 36918360 DOI: 10.1002/mp.16356] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 01/23/2023] [Accepted: 02/26/2023] [Indexed: 03/16/2023] Open
Abstract
BACKGROUND Patient-specific organ-dose estimation in diagnostic CT examinations can provide useful insights on individualized secondary cancer risks, protocol optimization, and patient management. Current dose estimation techniques mainly rely on time-consuming Monte Carlo methods or/and generalized anthropomorphic phantoms. PURPOSE We proposed a proof-of-concept rapid workflow based on deep learning networks to estimate organ doses for individuals following thorax Computed Tomography (CT) examinations. METHODS CT scan data from 95 individuals undergoing thorax CT examinations were used. Monte Carlo simulations were performed and three-dimensional (3D) dose distributions for each patient were obtained. A fully connected sequential deep learning network model was constructed and trained for each organ considered in this study. Water-equivalent diameter (WED), scan length, and tube current were the independent variables. Organ doses for heart, lungs, esophagus, and bones were calculated from the Monte Carlo 3D distribution and used to train the deep learning networks. Organ dose predictions from each network were evaluated using an independent data set of 19 patients. RESULTS The trained networks provided organ dose predictions within a second. There was very good agreement between the deep learning network predictions and reference organ dose values calculated from Monte Carlo simulations. The average difference was -1.5% for heart, -1.6% for esophagus, -1.0% for lungs, and -0.4% for bones in the 95 patients dataset, and -5.1%, 4.3%, 0.9%, and 1.4% respectively in the 19 patients test dataset. CONCLUSIONS The proposed workflow demonstrated that patient-specific organ-doses can be estimated in nearly real-time using deep learning networks. The workflow can be readily implemented and requires a small set of representative data for training.
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Affiliation(s)
- Marios Myronakis
- Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece
| | - John Stratakis
- Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece
- Medical Physics Department, University Hospital of Crete, Iraklion, Greece
| | - John Damilakis
- Department of Medical Physics, School of Medicine, University of Crete, Iraklion, Greece
- Medical Physics Department, University Hospital of Crete, Iraklion, Greece
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Faj D, Bassinet C, Brkić H, De Monte F, Dreuil S, Dupont L, Ferrari P, Gallagher A, Gallo L, Huet C, Knežević Ž, Kralik I, Krstić D, Maccia C, Majer M, Malchair F, O'Connor U, Pankowski P, Sans Merce M, Sage J, Simantirakis G. Management of pregnant or potentially pregnant patients undergoing diagnostic and interventional radiology procedures: Investigation of clinical routine practice. Phys Med 2023; 115:103159. [PMID: 37852021 DOI: 10.1016/j.ejmp.2023.103159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Revised: 08/26/2023] [Accepted: 10/01/2023] [Indexed: 10/20/2023] Open
Abstract
It is well known that foetuses are highly sensitive to ionising radiation and special attention to justification and optimisation of radiological procedures involving a pregnant patient is required. A task to review, validate and compare different approaches to managing the pregnant patient and to estimating the associated foetal doses arising from a diagnostic or interventional radiology (DIR) procedure was designed in the framework of EURADOS working group 12. As a first step, a survey of radiation protection practice including dosimetry considerations among EURADOS members was performed using online questionnaire. Then, to evaluate the possible differences in the estimated foetal doses, a comparison of assessed dose values was made for three cases of pregnant patients that underwent different CT procedures. More than 120 professionals from 108 institutions and 17 countries that are involved in managing pregnant patients undergoing DIR procedures answered the questionnaire. Most of the respondents use national or hospital guidelines on the management of pregnant patients undergoing DIR procedures. However, the guidelines differ considerably among respondents. Comparison of foetal dose assessments performed by dosimetry experts showed the variety of methods used as well as large variability of estimated foetal doses in all three cases. Although European and International commission on radiation protection guidelines already exist, they are more than 20 years old and, in some aspects, they are obsolete. This paper shows that there is a need to revise and update these guidelines.
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Affiliation(s)
- Dario Faj
- Faculty of Medicine, J. J. Strossmayer University of Osijek, J. Huttlera 4, Osijek, Croatia; Faculty of Dental Medicine and Health, J. J. Strossmayer University of Osijek, Crkvena 21, Osijek, Croatia
| | - Céline Bassinet
- Institute for Radiation Protection and Nuclear Safety, 31 avenue de la division Leclerc, Fontenay-aux-Roses, France
| | - Hrvoje Brkić
- Faculty of Medicine, J. J. Strossmayer University of Osijek, J. Huttlera 4, Osijek, Croatia; Faculty of Dental Medicine and Health, J. J. Strossmayer University of Osijek, Crkvena 21, Osijek, Croatia.
| | | | - Serge Dreuil
- Institute for Radiation Protection and Nuclear Safety, 31 avenue de la division Leclerc, Fontenay-aux-Roses, France
| | - Laura Dupont
- University Hospital of Geneva, Geneva, Switzerland
| | | | | | - Lara Gallo
- Veneto Institute of Oncology IOV - IRCCS, Padua, Italy
| | - Christelle Huet
- Institute for Radiation Protection and Nuclear Safety, 31 avenue de la division Leclerc, Fontenay-aux-Roses, France
| | | | - Ivana Kralik
- Dubrava University Hospital, Avenija Gojka Suska 6, Zagreb, Croatia
| | - Dragana Krstić
- University of Kragujevac, Faculty of Science, R. Domanovica 12, 34000 Kragujevac, Serbia
| | | | - Marija Majer
- Ruđer Boškovć Institute, Bijenička 54, Zagreb, Croatia
| | | | - Una O'Connor
- Medical Physics & Bioengineering Dept, St. James's Hospital, Dublin, Ireland
| | - Piotr Pankowski
- Faculty of Physics and Applied Informatics, University of Lodz, Pomorska St. 149/153, 90-236 Lodz, Poland
| | | | - Julie Sage
- Institute for Radiation Protection and Nuclear Safety, 31 avenue de la division Leclerc, Fontenay-aux-Roses, France
| | - George Simantirakis
- Greek Atomic Energy Commission, P.O. Box 60092, 153 10, Agia Paraskevi, Athens, Greece
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Mazloumi M, Van Gompel G, Tanaka K, Argacha JF, de Mey J, Buls N. The impact of iodine contrast agent on radiation dose of heart and blood: a comparison between coronary CT angiography and cardiac calcium scoring CT. Acta Radiol 2023; 64:2387-2392. [PMID: 37138465 DOI: 10.1177/02841851231170850] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
BACKGROUND Iodine contrast agent (CA) is widely used in cardiac computed tomography (CT). The CA can increase the organ radiation doses due to the photoelectric effect. PURPOSE To investigate the impact of CA on radiation dose in cardiac CT by comparing the radiation dose between contrast coronary CT angiography (CCTA) and non-contrast calcium scoring CT (CSCT). MATERIAL AND METHODS Radiation doses were computationally calculated for 30 individual patients who received CSCT and CCTA in the same exam session. The geometry and acquisition parameters were modeled in the simulations based on individual patient CT images and acquisitions. Doses in the presence and absence of CA were obtained in the aorta, left ventricle (LV), right ventricle (RV), and myocardial tissue (MT). The dose values were normalized by size-specific dose estimate (SSDE). The dose enhancement factors (DEFSSDE) were calculated as the ratio of doses in CCTA over doses in CSCT. RESULTS Compared to the CSCT scans, doses increase in the CCTA scans in the aorta (DEFSSDE = 2.14 ± 0.20), LV (DEFSSDE = 1.78 ± 0.26), and RV (DEFSSDE = 1.31 ± 0.22). A linear relation is observed between the local CA concentrations and the dose increase in the heart; DEFSSDE = 0.07*I(mg/mL) + 0.80 (R2 = 0.8; p < 0.01). The DEFSSDE in the MT (DEFSSDE = 0.96 ± 0.08) showed no noticeable impact of CA on the dose in this tissue. In addition, patient variability in the dose distributions was observed. CONCLUSION A linear causal relation exists between local CA concentration and increase in radiation dose in cardiac CT. For the same CT exposure, dose to the heart is on average 55% higher in contrast cardiac CT.
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Affiliation(s)
- Mahta Mazloumi
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Gert Van Gompel
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Kaoru Tanaka
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Jean-François Argacha
- Department of Cardiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Johan de Mey
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
| | - Nico Buls
- Department of Radiology, Vrije Universiteit Brussel, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium
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Tzanis E, Damilakis J. A novel methodology to train and deploy a machine learning model for personalized dose assessment in head CT. Eur Radiol 2022; 32:6418-6426. [PMID: 35384458 DOI: 10.1007/s00330-022-08756-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/28/2022] [Accepted: 03/19/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To propose a machine learning-based methodology for the creation of radiation dose maps and the prediction of patient-specific organ/tissue doses associated with head CT examinations. METHODS CT data were collected retrospectively for 343 patients who underwent standard head CT examinations. Patient-specific Monte Carlo (MC) simulations were performed to determine the radiation dose distribution to patients' organs/tissues. The collected CT images and the MC-produced dose maps were processed and used for the training of the deep neural network (DNN) model. For the training and validation processes, data from 231 and 112 head CT examinations, respectively, were used. Furthermore, a software tool was developed to produce dose maps from head CT images using the trained DNN model and to automatically calculate the dose to the brain and cranial bones. RESULTS The mean (range) percentage differences between the doses predicted from the DNN model and those provided by MC simulations for the brain, eye lenses, and cranial bones were 4.5% (0-17.7%), 5.7% (0.2-19.0%), and 5.2% (0.1-18.9%), respectively. The graphical user interface of the software offers a user-friendly way for radiation dose/risk assessment. The implementation of the DNN allowed for a 97% reduction in the computational time needed for the dose estimations. CONCLUSIONS A novel methodology that allows users to develop a DNN model for patient-specific CT dose prediction was developed and implemented. The approach demonstrated herein allows accurate and fast radiation dose estimation for the brain, eye lenses, and cranial bones of patients who undergo head CT examinations and can be used in everyday clinical practice. KEY POINTS • The methodology presented herein allows fast and accurate radiation dose estimation for the brain, eye lenses, and cranial bones of patients who undergo head CT examinations and can be implemented in everyday clinical practice. • The scripts developed in the current study will allow users to train models for the acquisition protocols of their CT scanners, generate dose maps, estimate the doses to the brain and cranial bones, and estimate the lifetime attributable risk of radiation-induced brain cancer.
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Affiliation(s)
- Eleftherios Tzanis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003, Heraklion, Crete, Greece
| | - John Damilakis
- Department of Medical Physics, School of Medicine, University of Crete, P.O. Box 2208, 71003, Heraklion, Crete, Greece.
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Papadakis AE, Damilakis J. Organ doses and normalized organ doses for various age groups in ultralow dose pediatric C-arm cone-beam CT. Eur Radiol 2022; 32:5790-5798. [PMID: 35364713 DOI: 10.1007/s00330-022-08767-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 02/18/2022] [Accepted: 03/22/2022] [Indexed: 12/21/2022]
Abstract
OBJECTIVES To estimate organ dose to major radiosensitive organs during pediatric body C-arm CBCT and determine normalized organ doses using a state-of-the-art equipment. METHODS This is a study performed utilizing physical anthropomorphic phantoms. Four anthropomorphic phantoms that simulate the average individual as a neonate, 1-year-old, 5-year-old, and 10-year-old child were used. Personalized Monte Carlo (MC)-based dosimetry was performed to estimate organ doses in children referred to thorax and abdomen C-arm CBCT acquisitions on a recently released latest generation C-arm CBCT system. Age-specific normalized organ doses were generated and organ dose was estimated for skin, bone, breast, lungs, esophagus, thymus, and heart, in the thorax, and liver, adrenals, kidneys, pancreas, stomach, gall bladder, and spleen in the abdomen. Estimated doses were compared to corresponding values obtained with physical measurements performed using thermoluminescent dosimeters (TLD). RESULTS The results consist of organ doses for thorax and abdomen acquisition protocols. The majority of organs received a dose below 1 mSv. For all ages, the normalized organ doses decreased from neonate to 10-year-old. The difference between the organ doses obtained with MC and TLDs was less than 8%. CONCLUSIONS Normalized organ doses in pediatric C-arm CBCT varied with age. Pediatric C-arm CBCT with latest-generation systems may be performed with sub mGy dose for most organs. KEY POINTS • The dose to the majority of organs from pediatric C-arm CBCT is in the sub mSv level. • The normalized organ doses decreased from neonate to 10-year-old. • Reported normalized organ doses may be used to estimate organ dose in pediatric C-arm cone-beam CT on modern equipment.
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Affiliation(s)
- Antonios E Papadakis
- Medical Physics Department, University General Hospital of Heraklion, Stavrakia, 71110, Crete, Greece.
| | - John Damilakis
- Medical Physics Department, University of Crete, Stavrakia, 71110, Crete, Greece
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Dose assessment for daily cone-beam CT in lung radiotherapy patients and its combination with treatment planning. Phys Eng Sci Med 2022; 45:231-237. [PMID: 35076869 DOI: 10.1007/s13246-022-01105-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 01/19/2022] [Indexed: 10/19/2022]
Abstract
With the increased use of X-ray imaging for patient alignment in external beam radiation therapy, particularly with cone-beam computed tomography (CBCT), the additional dose received by patients has become of greater consideration. In this study, we analysed the radiation dose from CBCT for clinical lung radiotherapy and assessed its relative contribution when combined with radiation treatment planning for a variety of lung radiotherapy techniques. The Monte Carlo simulation program ImpactMC was used to calculate the 3D dose delivered by a Varian TrueBeam linear accelerator to patients undergoing thorax CBCT imaging. The concomitant dose was calculated by simulating the daily CBCT irradiation of ten lung cancer patients. Each case was planned with a total dose of 50-60 Gy to the target lesion in 25-30 fractions using the 3DCRT or IMRT plan and retrospectively planned using VMAT. For each clinical case, the calculated CBCT dose was summed with the planned dose, and the dose to lungs, heart, and spinal cord were analysed according to conventional dose conformity metrics. Our results indicate greater variations in dose to the heart, lungs, and spinal cord based on planning technique, (3DCRT, IMRT, VMAT) than from the inclusion of daily cone-beam imaging doses over 25-30 fractions. The average doses from CBCT imaging per fraction to the lungs, heart and spinal cord were 0.52 ± 0.10, 0.49 ± 0.15 and 0.39 ± 0.08 cGy, respectively. Lung dose variations were related to the patient's size and body composition. Over a treatment course, this may result in an additional mean absorbed dose of 0.15-0.2 Gy. For lung V5, the imaging dose resulted in an average increase of ~ 0.6% of the total volume receiving 5 Gy. The increase in V20 was more dependent on the planning technique, with 3DCRT increasing by 0.11 ± 0.09% with imaging and IMRT and VMAT increasing by 0.17 ± 0.05% and 0.2 ± 0.06%, respectively. In this study, we assessed the concomitant dose for daily CBCT lung cancer patients undergoing radiotherapy. The additional radiation dose to the normal lungs from daily CBCT was found to range from 0.15 to 0.2 Gy when the patient was treated with 25-30 fractions. Consideration of potential variation in relative biological effectiveness between kilovoltage imaging and megavoltage treatment dose was outside the scope of this study. Regardless of this, our results show that the assessment of imaging dose can be incorporated into the treatment planning process and the relative effect on overall dose distribution was small compared to the difference among planning techniques.
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Kim J, Kim HK. A NOVEL METHOD FOR ESTIMATING PATIENT-SPECIFIC PRIMARY DOSE IN CONE-BEAM COMPUTED TOMOGRAPHY. RADIATION PROTECTION DOSIMETRY 2021; 196:71-84. [PMID: 34487179 DOI: 10.1093/rpd/ncab128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 07/12/2021] [Accepted: 08/04/2021] [Indexed: 06/13/2023]
Abstract
For the purpose of real-time scan-protocol optimisation and patient-specific dose management in cone-beam computed tomography, we introduce a numerical algorithm that estimates the primary dose distributions in reconstructed images. The proposed algorithm is based on the ray-tracing technique and utilises reconstructed voxel data and scanning protocol. The algorithm is validated with the Monte Carlo (MC) and conventional model-based dose reconstruction methods for the simple cylindrical water and anthropomorphic head phantoms. The algorithm shows good agreement with both methods in terms of the zeroth-order x-ray interactions, which exclude the higher-order x-ray interactions at sites distant from the first interactions, and it consumes a significantly lower computational cost compared with the MC method. The differences between the proposed algorithm and the model-based dose reconstruction method as well as the improvement strategies of the algorithm are discussed in detail.
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Affiliation(s)
- Jinwoo Kim
- Center for Advanced Medical Engineering Research, Pusan National University, Busan 46241, Republic of Korea
| | - Ho Kyung Kim
- Center for Advanced Medical Engineering Research, Pusan National University, Busan 46241, Republic of Korea
- School of Mechanical Engineering, Pusan National University, Busan 46241, Republic of Korea
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Mansour HH, Alajerami YS, Foster T. Estimation of Radiation Doses and Lifetime Attributable Risk of Radiation-induced Cancer from A Single Coronary Artery Bypass Graft Computed Tomography Angiography. ELECTRONIC JOURNAL OF GENERAL MEDICINE 2021. [DOI: 10.29333/ejgm/11208] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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The presence of contrast agent increases organ radiation dose in contrast-enhanced CT. Eur Radiol 2021; 31:7540-7549. [PMID: 33783569 PMCID: PMC8452580 DOI: 10.1007/s00330-021-07763-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 01/08/2021] [Accepted: 02/05/2021] [Indexed: 01/09/2023]
Abstract
Objectives Routine dosimetry calculations do not account for the presence of iodine in organs and tissues during CT acquisition. This study aims to investigate the impact of contrast agent (CA) on radiation dose. Methods First, relation between absorbed radiation dose and iodine concentrations was investigated using a cylindrical water phantom with iodine-saline dilution insertions. Subsequently, a retrospective study on abdominal dual-energy CT (DECT) patient data was performed to assess the increase of the local absorbed radiation dose compared to a non-contrast scan. Absorbed doses were estimated with Monte Carlo simulations using the individual CT voxel data of phantom and patients. Further, organ segmentations were performed to obtain the dose in liver, liver parenchyma, left kidney, right kidney, aorta, and spleen. Results In the phantom study, a linear relation was observed between the radiation dose normalized by computed tomography dose index (CTDI) and CA concentrations Iconc (mg/ml) for three tube voltages; \documentclass[12pt]{minimal}
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\begin{document}$$ \frac{D_{80 kVp}}{CTDI_{vol}} $$\end{document}D80kVpCTDIvol = 0.14 × Iconc + 1.02, \documentclass[12pt]{minimal}
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\begin{document}$$ \frac{D_{120 kVp}}{CTDI_{vol}} $$\end{document}D120kVpCTDIvol = 0.16 × Iconc + 1.21, \documentclass[12pt]{minimal}
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\begin{document}$$ \frac{D_{140 kVp}}{CTDI_{vol}} $$\end{document}D140kVpCTDIvol = 0.16 × Iconc + 1.24, and for DECT acquisition; \documentclass[12pt]{minimal}
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\begin{document}$$ \frac{D_{DECT}}{CTDI_{vol}} $$\end{document}DDECTCTDIvol = 0.15 × Iconc + 1.09. Similarly, a linear relation was observed between the dose increase and the organ iodine contents (R2 = 0.86 and pvalue < 0.01) in the patient study. The relative doses increased in the liver (21 ± 5%), liver parenchyma (20 ± 5%), right kidney (37 ± 7%), left kidney (39 ± 7%), aorta (34 ± 6%) and spleen (26 ± 4%). In addition, the local dose distributions changed based on patient’s anatomy and physiology. Conclusions Compared to a non-contrast scan, the organ doses increase by 30% in contrast-enhanced abdominal CT. This study suggests considering CA in dosimetry calculations, epidemiological studies, and organ dose estimations while developing new CT protocols. Key Points • The presence of contrast media increases radiation absorption in CT, and this increase is related to the iodine content in the organs. • The increased radiation absorption due to contrast media can lead to an average 30% increase in absorbed organ dose. • Iodine should be considered in CT radiation safety studies.
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Perisinakis K, Ntoufas N, Velivassaki M, Tzedakis A, Myronakis M, Hatzidakis A, Damilakis J. Effect of scan projection radiography coverage on tube current modulation in pediatric and adult chest CT. Z Med Phys 2020; 30:259-270. [PMID: 32513526 DOI: 10.1016/j.zemedi.2020.05.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 04/22/2020] [Accepted: 05/03/2020] [Indexed: 11/30/2022]
Abstract
PURPOSE To investigate the effect of scan projection radiography (SPR) coverage on tube current modulation in pediatric and adult thoracic CT examinations. METHODS Sixty pediatric and 60 adult chest CT examinations were retrospectively studied to determine the incidence rate of examinations involving SPRs that did not include the entire image volume (IV) or the entire primarily exposed body volume (PEBV). The routine chest CT acquisition procedure on a modern 64-slice CT system was imitated on five anthropomorphic phantoms of different size. SPRs of varying length were successively acquired. The same IV was prescribed each time and the computed tube current modulation plan was recorded. The SPR boundaries were altered symmetrically by several steps of ±10mm with respect to the IV boundaries. RESULTS The upper IV boundary was found to be excluded from SPR in 52% of pediatric and 40% adult chest CT examinations. The corresponding values for the lower boundary were 15% and 20%, respectively. The computed tube current modulation was found to be considerably affected when the SPR did not encompass the entire IV. SPR deficit of 3cm was found to induce up to 46% increase in the computed tube current value to be applied during the first tube rotations over lung apex. CONCLUSIONS The tube current modulation mechanism functions properly only if the IV set by the operator is entirely included in the localizing SPR image. Operators should cautiously set the SPR boundaries to avoid partial exclusion of prescribed IV from SPRs and thus achieve optimum tube current modulation.
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Affiliation(s)
- Kostas Perisinakis
- University of Crete, Medical School, Department of Medical Physics, 71003 Heraklion, Crete, Greece; University Hospital of Heraklion, Department of Medical Physics, P.O. Box 1352, 71110 Heraklion, Crete, Greece.
| | - Nikos Ntoufas
- University of Crete, Medical School, Department of Medical Physics, 71003 Heraklion, Crete, Greece
| | - Mary Velivassaki
- University Hospital of Heraklion, Department of Medical Physics, P.O. Box 1352, 71110 Heraklion, Crete, Greece
| | - Antonis Tzedakis
- University Hospital of Heraklion, Department of Medical Physics, P.O. Box 1352, 71110 Heraklion, Crete, Greece
| | - Marios Myronakis
- University of Crete, Medical School, Department of Medical Physics, 71003 Heraklion, Crete, Greece; Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School
| | - Adam Hatzidakis
- University of Crete, Medical School, Department of Radiology, Heraklion, Crete, Greece
| | - John Damilakis
- University of Crete, Medical School, Department of Medical Physics, 71003 Heraklion, Crete, Greece; University Hospital of Heraklion, Department of Medical Physics, P.O. Box 1352, 71110 Heraklion, Crete, Greece
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Prinsen P, Trattner S, Wiegert J, Gerland EL, Shefer E, Morton T, Thompson CM, Cheng B, Halliburton SS, Einstein AJ. High correlation between radiation dose estimates for 256-slice CT obtained by highly parallelized hybrid Monte Carlo computation and solid-state metal-oxide semiconductor field-effect transistor measurements in physical anthropomorphic phantoms. Med Phys 2019; 46:5216-5226. [PMID: 31442300 DOI: 10.1002/mp.13780] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 07/11/2019] [Accepted: 08/06/2019] [Indexed: 11/06/2022] Open
Abstract
PURPOSE Accurate, patient-specific radiation dosimetry for CT scanning is critical to optimize radiation doses and balance dose against image quality. While Monte Carlo (MC) simulation is often used to estimate doses from CT, comparison of estimates to experimentally measured values is lacking for advanced CT scanners incorporating novel design features. We aimed to compare radiation dose estimates from MC simulation to doses measured in physical anthropomorphic phantoms using metal-oxide semiconductor field-effect transistors (MOSFETs) in a 256-slice CT scanner. METHODS Fifty MOSFETs were placed in organs within tissue-equivalent anthropomorphic adult and pediatric radiographic phantoms, which were scanned using a variety of chest, cardiac, abdomen, brain, and whole-body protocols on a 256-slice system. MC computations were performed on voxelized CT reconstructions of the phantoms using a highly parallel MC tool developed specifically for diagnostic X-ray energies and rapid computation. Doses were compared between MC estimates and physical measurements. RESULTS The average ratio of MOSFET to MC dose in the in-field region was close to 1 (range, 0.96-1.12; mean ± SD, 1.01 ± 0.04), indicating outstanding agreement between measured and simulated doses. The difference between measured and simulated doses tended to increase with distance from the in-field region. The error in the MC simulations due to the limited number of simulated photons was less than 1%. The errors in the MOSFET dose determinations in the in-field region for a single scan were mainly due to the calibration method and were typically about 6% (8% if the error in the reading of the ionization chamber that was used for the MOSFET calibration was included). CONCLUSIONS Radiation dose estimation using a highly parallelized MC method is strongly correlated with experimental measurements in physical adult and infant anthropomorphic phantoms for a wide range of scans performed on a 256-slice CT scanner. Incorporation into CT scanners of radiation-dose distribution estimation, employing the scanner's reconstructed images of the patient, may offer the potential for accurate patient-specific CT dosimetry.
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Affiliation(s)
- Peter Prinsen
- Philips Research, Eindhoven, 5656AE, The Netherlands
| | - Sigal Trattner
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY, 10032, USA
| | - Jens Wiegert
- Philips Research, Eindhoven, 5656AE, The Netherlands
| | - Elazar-Lars Gerland
- P-Cure Ltd,, Moshav Shilat, 7318800, Israel.,Philips Healthcare, Haifa, 31004, Israel
| | | | | | - Carla M Thompson
- Division of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.,Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, OH, 44195, USA.,Vanderbilt Center for Science Outreach, Vanderbilt University, Nashville, TN, 37235, USA
| | - Bin Cheng
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY, 10032, USA
| | - Sandra S Halliburton
- Philips Healthcare, Cleveland, OH, 44122, USA.,Division of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.,Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44195, USA.,Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, OH, 44195, USA
| | - Andrew J Einstein
- Department of Medicine, Division of Cardiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY, 10032, USA.,Department of Radiology, Columbia University Irving Medical Center and New York-Presbyterian Hospital, New York, NY, 10032, USA
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Rosendahl S, Büermann L, Borowski M, Kortesniemi M, Sundell VM, Kosunen A, Siiskonen T. CT beam dosimetric characterization procedure for personalized dosimetry. Phys Med Biol 2019; 64:075009. [PMID: 30856614 DOI: 10.1088/1361-6560/ab0e97] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Personalized dosimetry in computed tomography (CT) can be realized by a full Monte Carlo (MC) simulation of the scan procedure. Essential input data needed for the simulation are appropriate CT x-ray source models and a model of the patient's body which is based on the CT image. The purpose of this work is to develop comprehensive procedures for the determination of CT x-ray source models and their verification by comparison of calculated and measured dose distributions in physical phantoms. Mobile equipment together with customized software was developed and used for non-invasive determination of equivalent source models of CT scanners under clinical conditions. Standard and physical anthropomorphic CT dose phantoms equipped with real-time CT dose probes at five representative positions were scanned. The accumulated dose was measured during the scan at the five positions. ImpactMC, an MC-based CT dose software program, was used to simulate the scan. The necessary inputs were obtained from the scan parameters, from the equivalent source models and from the material-segmented CT images of the phantoms. 3D dose distributions in the phantoms were simulated and the dose values calculated at the five positions inside the phantom were compared to measured dose values. Initial results were obtained by means of a General Electric Optima CT 660 and a Toshiba (Canon) Aquilion ONE. In general, the measured and calculated dose values were within relative uncertainties that had been estimated to be less than 10%. The procedures developed were found to be viable and rapid. The procedures are applicable to any scanner type under clinical conditions without making use of the service mode with stationary x-ray tube position. Results show that the procedures are well suited for determining and verifying the equivalent source models needed for personalized CT dosimetry based on post-scan MC calculations.
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Affiliation(s)
- S Rosendahl
- Physikalisch-Technische Bundesanstalt, Bundesallee 100, 38116 Braunschweig, Germany
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Kaasalainen T, Mäkelä T, Kelaranta A, Kortesniemi M. The Use of Model-based Iterative Reconstruction to Optimize Chest CT Examinations for Diagnosing Lung Metastases in Patients with Sarcoma: A Phantom Study. Acad Radiol 2019; 26:50-61. [PMID: 29724675 DOI: 10.1016/j.acra.2018.03.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 03/23/2018] [Accepted: 03/29/2018] [Indexed: 12/20/2022]
Abstract
RATIONALE AND OBJECTIVES This phantom study aimed to evaluate low-dose (LD) chest computed tomography (CT) protocols using model-based iterative reconstruction (MBIR) for diagnosing lung metastases in patients with sarcoma. MATERIALS AND METHODS An adult female anthropomorphic phantom was scanned with a 64-slice CT using four LD protocols and a standard-dose protocol. Absorbed organ doses were measured with 10 metal-oxide-semiconductor field-effect transistor dosimeters. Furthermore, Monte Carlo simulations were performed to estimate organ and effective doses. Image quality in terms of image noise, contrast, and resolution was measured from the CT images reconstructed with conventional filtered back projection, adaptive statistical iterative reconstruction, and MBIR algorithms. All the results were compared to the performance of the standard-dose protocol. RESULTS Mean absorbed organ and effective doses were reduced by approximately 95% with the LD protocol (100-kVp tube voltage and a fixed 10-mA tube current) compared to the standard-dose protocol (120-kVp tube voltage and tube current modulation) while yielding an acceptable image quality for diagnosing round-shaped lung metastases. The effective doses ranged from 0.16 to 2.83 mSv in the studied protocols. The image noise, contrast, and resolution were maintained or improved when comparing the image quality of LD protocols using MBIR to the performance of the standard-dose chest CT protocol using filtered back projection. The small round-shaped lung metastases were delineated at levels comparable to the used protocols. CONCLUSIONS Radiation exposure in patients can be reduced significantly by using LD chest CT protocols and MBIR algorithm while maintaining image quality for detecting round-shaped lung metastases.
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Fetal radiation dose in three common CT examinations during pregnancy - Monte Carlo study. Phys Med 2017; 43:199-206. [PMID: 28941740 DOI: 10.1016/j.ejmp.2017.09.120] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2017] [Revised: 07/31/2017] [Accepted: 09/07/2017] [Indexed: 12/14/2022] Open
Abstract
PURPOSE To determine fetal doses in different stages of pregnancy in three common computed tomography (CT) examinations: pulmonary CT angiography, abdomino-pelvic and trauma scan with Monte Carlo (MC) simulations. METHODS An adult female anthropomorphic phantom was scanned with a 64-slice CT using pulmonary angiography, abdomino-pelvic and trauma CT scan protocols. Three different sized gelatin boluses placed on the phantom's abdomen simulated different stages of pregnancy. Intrauterine dose was used as a surrogate to a dose absorbed to the fetus. MC simulations were performed to estimate uterine doses. The simulation dose levels were calibrated with volumetric CT dose index (CTDIvol) measurements and MC simulations in a cylindrical CTDI body phantom and compared with ten point doses measured with metal-oxide-semiconductor field-effect-transistor dosimeters. Intrauterine volumes and uterine walls were segmented and the respective dose volume histograms were calculated. RESULTS The mean intrauterine doses in different stages of pregnancy varied from 0.04 to 1.04mGy, from 4.8 to 5.8mGy, and from 9.8 to 12.6mGy in the CT scans for pulmonary angiography, abdomino-pelvic and trauma CT scans, respectively. MC simulations showed good correlation with the MOSFET measurement at the measured locations. CONCLUSIONS The three studied examinations provided highly varying fetal doses increasing from sub-mGy level in pulmonary CT angiography to notably higher levels in abdomino-pelvic and trauma scans where the fetus is in the primary exposure range. Volumetric dose distribution offered by MC simulations in an appropriate anthropomorphic phantom provides a comprehensive dose assessment when applied in adjunct to point-dose measurements.
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Xie T, Poletti PA, Platon A, Becker CD, Zaidi H. Assessment of CT dose to the fetus and pregnant female patient using patient-specific computational models. Eur Radiol 2017; 28:1054-1065. [DOI: 10.1007/s00330-017-5000-z] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 07/04/2017] [Accepted: 07/21/2017] [Indexed: 11/29/2022]
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Perisinakis K, Tzedakis A, Spanakis K, Papadakis AE, Hatzidakis A, Damilakis J. The effect of iodine uptake on radiation dose absorbed by patient tissues in contrast enhanced CT imaging: Implications for CT dosimetry. Eur Radiol 2017; 28:151-158. [DOI: 10.1007/s00330-017-4970-1] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 06/01/2017] [Accepted: 06/28/2017] [Indexed: 11/25/2022]
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Hadad K, Saeedi-Moghadam M, Zeinali-Rafsanjani B. Voxel dosimetry: Comparison of MCNPX and DOSXYZnrc Monte Carlo codes in patient specific phantom calculations. Technol Health Care 2016; 25:29-35. [PMID: 27447407 DOI: 10.3233/thc-161240] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
INTRODUCTION Dose evaluation with two Monte Carlo codes using patient specific voxel phantom is presented in this paper. We employ both MCNPX and DOSXYZnrc to perform dosimetry for mathematical voxel phantoms generated by our in-house developed voxel phantom generator and EGSnrc/CTCreate respectively. MATERIAL AND METHOD Our case study was a 2.5 × 2.4 × 2.4 cm3 tumor in the middle lobe of right lung of a male patient exposed to 6MV parallel beam. In order to compare these Monte Carlo codes with together gross tumor volume (GTV) and organ at risks (OAR) doses and dose volume histograms (DVH) were calculated. RESULTS Comparing the mean absorbed dose results (in Gy) from both codes indicates that gross tumor volume, heart and spinal cord have 2% to 10% difference. The 10% difference between the codes were from the spinal cord region where was not in the therapy beam and it just received the scatter radiation. The dose volume DVH obtained from DOSXYZnrc results demonstrate a milder slope compared with MCNPX DVHs. CONCLUSION It was revealed that MCNPX has some advantages in comparison to DOSXYZnrc, but it is important to consider that for equal precision in voxel dosimetry calculation, DOSXYZnrc runs faster than MCNPX and it is a great advantage.
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Affiliation(s)
- Kamal Hadad
- Department of Nuclear Engineering, School of Mechanical Engineering, Shiraz University, Shiraz, Iran
| | - Mahdi Saeedi-Moghadam
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Banafsheh Zeinali-Rafsanjani
- Medical Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.,Nuclear Medicine and Molecular Imaging Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Papadakis AE, Perisinakis K, Damilakis J. Development of a method to estimate organ doses for pediatric CT examinations. Med Phys 2016; 43:2108. [DOI: 10.1118/1.4944867] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
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Norris ET, Liu X, Hsieh J. Deterministic absorbed dose estimation in computed tomography using a discrete ordinates method. Med Phys 2015; 42:4080-7. [PMID: 26133608 DOI: 10.1118/1.4922000] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE Organ dose estimation for a patient undergoing computed tomography (CT) scanning is very important. Although Monte Carlo methods are considered gold-standard in patient dose estimation, the computation time required is formidable for routine clinical calculations. Here, the authors instigate a deterministic method for estimating an absorbed dose more efficiently. METHODS Compared with current Monte Carlo methods, a more efficient approach to estimating the absorbed dose is to solve the linear Boltzmann equation numerically. In this study, an axial CT scan was modeled with a software package, Denovo, which solved the linear Boltzmann equation using the discrete ordinates method. The CT scanning configuration included 16 x-ray source positions, beam collimators, flat filters, and bowtie filters. The phantom was the standard 32 cm CT dose index (CTDI) phantom. Four different Denovo simulations were performed with different simulation parameters, including the number of quadrature sets and the order of Legendre polynomial expansions. A Monte Carlo simulation was also performed for benchmarking the Denovo simulations. A quantitative comparison was made of the simulation results obtained by the Denovo and the Monte Carlo methods. RESULTS The difference in the simulation results of the discrete ordinates method and those of the Monte Carlo methods was found to be small, with a root-mean-square difference of around 2.4%. It was found that the discrete ordinates method, with a higher order of Legendre polynomial expansions, underestimated the absorbed dose near the center of the phantom (i.e., low dose region). Simulations of the quadrature set 8 and the first order of the Legendre polynomial expansions proved to be the most efficient computation method in the authors' study. The single-thread computation time of the deterministic simulation of the quadrature set 8 and the first order of the Legendre polynomial expansions was 21 min on a personal computer. CONCLUSIONS The simulation results showed that the deterministic method can be effectively used to estimate the absorbed dose in a CTDI phantom. The accuracy of the discrete ordinates method was close to that of a Monte Carlo simulation, and the primary benefit of the discrete ordinates method lies in its rapid computation speed. It is expected that further optimization of this method in routine clinical CT dose estimation will improve its accuracy and speed.
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Affiliation(s)
- Edward T Norris
- Nuclear Engineering, Missouri University of Science and Technology, Rolla, Missouri 65409
| | - Xin Liu
- Nuclear Engineering, Missouri University of Science and Technology, Rolla, Missouri 65409
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Oh JS, Koea JB. Radiation risks associated with serial imaging in colorectal cancer patients: Should we worry? World J Gastroenterol 2014; 20:100-109. [PMID: 24415862 PMCID: PMC3885998 DOI: 10.3748/wjg.v20.i1.100] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2013] [Revised: 07/31/2013] [Accepted: 08/09/2013] [Indexed: 02/06/2023] Open
Abstract
To provide an overview of the radiation related cancer risk associated with multiple computed tomographic scans required for follow up in colorectal cancer patients. A literature search of the PubMed and Cochrane Library databases was carried out and limited to the last 10 years from December 2012. Inclusion criteria were studies where computed tomographic scans or radiation from other medical imaging modalities were used and the risks associated with ionizing radiation reported. Thirty-six studies were included for appraisal with no randomized controlled trials. Thirty-four of the thirty-six studies showed a positive association between medical imaging radiation and increased risk of cancer. The radiation dose absorbed and cancer risk was greater in children and young adults than in older patients. Most studies included in the review used a linear, no-threshold model to calculate cancer risks and this may not be applicable at low radiation doses. Many studies are retrospective and ensuring complete follow up on thousands of patients is difficult. There was a minor increased risk of cancer from ionizing radiation in medical imaging studies. The radiation risks of low dose exposure (< 50 milli-Sieverts) are uncertain. A clinically justified scan in the context of colorectal cancer is likely to provide more benefits than harm but current guidelines for patient follow up will need to be revised to accommodate a more aggressive approach to treating metastatic disease.
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Montes C, Tamayo P, Hernandez J, Gomez-Caminero F, García S, Martín C, Rosero A. Estimation of the total effective dose from low-dose CT scans and radiopharmaceutical administrations delivered to patients undergoing SPECT/CT explorations. Ann Nucl Med 2013; 27:610-7. [PMID: 23568252 DOI: 10.1007/s12149-013-0724-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2012] [Accepted: 03/28/2013] [Indexed: 01/30/2023]
Abstract
UNLABELLED Hybrid imaging, such as SPECT/CT, is used in routine clinical practice, allowing coregistered images of the functional and structural information provided by the two imaging modalities. However, this multimodality imaging may mean that patients are exposed to a higher radiation dose than those receiving SPECT alone. OBJECTIVES The study aimed to determine the radiation exposure of patients who had undergone SPECT/CT examinations and to relate this to the Background Equivalent Radiation Time (BERT). METHODS 145 SPECT/CT studies were used to estimate the total effective dose to patients due to both radiopharmaceutical administrations and low-dose CT scans. The CT contribution was estimated by the Dose-Length Product method. Specific conversion coefficients were calculated for SPECT explorations. RESULTS The radiation dose from low-dose CTs ranged between 0.6 mSv for head and neck CT and 2.6 mSv for whole body CT scan, representing a maximum of 1 year of background radiation exposure. These values represent a decrease of 80-85% with respect to the radiation dose from diagnostic CT. The radiation exposure from radiopharmaceutical administration varied from 2.1 mSv for stress myocardial perfusion SPECT to 26 mSv for gallium SPECT in patients with lymphoma. The BERT ranged from 1 to 11 years. CONCLUSIONS The contribution of low-dose CT scans to the total radiation dose to patients undergoing SPECT/CT examinations is relatively low compared with the effective dose from radiopharmaceutical administration. When a CT scan is only acquired for anatomical localization and attenuation correction, low-dose CT scan is justified on the basis of its lower dose.
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Affiliation(s)
- Carlos Montes
- Medical Physics Department, University Hospital of Salamanca, Paseo de San Vicente, 58-182, 37007, Salamanca, Spain.
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Pulmonary CT Angiography as First-Line Imaging for PE: Image Quality and Radiation Dose Considerations. AJR Am J Roentgenol 2013; 200:522-8. [PMID: 23436840 DOI: 10.2214/ajr.12.9928] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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Perisinakis K, Seimenis I, Tzedakis A, Papadakis AE, Damilakis J. The effect of head size∕shape, miscentering, and bowtie filter on peak patient tissue doses from modern brain perfusion 256-slice CT: how can we minimize the risk for deterministic effects? Med Phys 2013; 40:011911. [PMID: 23298102 DOI: 10.1118/1.4773042] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
PURPOSE To determine patient-specific absorbed peak doses to skin, eye lens, brain parenchyma, and cranial red bone marrow (RBM) of adult individuals subjected to low-dose brain perfusion CT studies on a 256-slice CT scanner, and investigate the effect of patient head size∕shape, head position during the examination and bowtie filter used on peak tissue doses. METHODS The peak doses to eye lens, skin, brain, and RBM were measured in 106 individual-specific adult head phantoms subjected to the standard low-dose brain perfusion CT on a 256-slice CT scanner using a novel Monte Carlo simulation software dedicated for patient CT dosimetry. Peak tissue doses were compared to corresponding thresholds for induction of cataract, erythema, cerebrovascular disease, and depression of hematopoiesis, respectively. The effects of patient head size∕shape, head position during acquisition and bowtie filter used on resulting peak patient tissue doses were investigated. The effect of eye-lens position in the scanned head region was also investigated. The effect of miscentering and use of narrow bowtie filter on image quality was assessed. RESULTS The mean peak doses to eye lens, skin, brain, and RBM were found to be 124, 120, 95, and 163 mGy, respectively. The effect of patient head size and shape on peak tissue doses was found to be minimal since maximum differences were less than 7%. Patient head miscentering and bowtie filter selection were found to have a considerable effect on peak tissue doses. The peak eye-lens dose saving achieved by elevating head by 4 cm with respect to isocenter and using a narrow wedge filter was found to approach 50%. When the eye lies outside of the primarily irradiated head region, the dose to eye lens was found to drop to less than 20% of the corresponding dose measured when the eye lens was located in the middle of the x-ray beam. Positioning head phantom off-isocenter by 4 cm and employing a narrow wedge filter results in a moderate reduction of signal-to-noise ratio mainly to the peripheral region of the phantom. CONCLUSIONS Despite typical peak doses to skin, eye lens, brain, and RBM from the standard low-dose brain perfusion 256-slice CT protocol are well below the corresponding thresholds for the induction of erythema, cataract, cerebrovascular disease, and depression of hematopoiesis, respectively, every effort should be made toward optimization of the procedure and minimization of dose received by these tissues. The current study provides evidence that the use of the narrower bowtie filter available may considerably reduce peak absorbed dose to all above radiosensitive tissues with minimal deterioration in image quality. Considerable reduction in peak eye-lens dose may also be achieved by positioning patient head center a few centimeters above isocenter during the exposure.
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Affiliation(s)
- Kostas Perisinakis
- Department of Medical Physics, University of Crete, Heraklion, Crete, Greece.
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Screening computed tomography colonography with 256-slice scanning: should patient radiation burden and associated cancer risk constitute a major concern? Invest Radiol 2012; 47:451-6. [PMID: 22766908 DOI: 10.1097/rli.0b013e318250a58c] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
OBJECTIVES The aim of this study was to determine the radiation burden and the lifetime attributable risk (LAR) of radiation-induced cancer in patients undergoing screening 256-slice computed tomography colonography (CTC) and compare CTC-related radiogenic risks to corresponding nominal lifetime intrinsic risk of cancer. MATERIALS AND METHODS A Monte Carlo simulation software dedicated for computed tomography (CT) dosimetry was used to determine absorbed doses to primarily exposed radiosensitive organs of 31 women and 29 men subjected to screening CTC on a 256-slice CT scanner. Effective dose was estimated from (a) organ dose data and (b) dose-length product. Organ-specific and total LARs of cancer were estimated using published risk factors. Cumulative LARs from repeated CTC studies on individuals participating in a colorectal cancer screening program were compared with corresponding lifetime intrinsic risks. RESULTS The mean organ dose-derived effective dose was estimated to be 2.92 and 2.61 mSv for female and male individuals, respectively. The dose-length product method was found to overestimate effective dose from CTC by 26% and 13% in female and male individuals, respectively. Compared with previously published results for 64-slice CT scanners, 256-slice CTC was found to be associated with up to 45% less radiation burden. The cumulative LAR of radiation-induced cancer from repeated quinquennial screening CTC studies between the ages of 50 and 80 years was estimated to increase the lifetime intrinsic risk of cancer by less than 0.2%. CONCLUSION The level of patient radiation burden and theoretical radiogenic cancer risks associated with screening CTC performed using modern low-dose protocols and techniques may not justify disapproval of CTC as a mass screening tool.
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Quality assurance of imaging techniques used in the clinical management of osteoporosis. LA RADIOLOGIA MEDICA 2012; 117:1347-54. [PMID: 23090242 DOI: 10.1007/s11547-012-0881-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2012] [Accepted: 07/24/2012] [Indexed: 10/27/2022]
Abstract
Recent advances in the densitometric and imaging techniques involved in the management of osteoporosis are associated with increasing accuracy and precision as well as with higher exposure to ionising radiation. Therefore, special attention to quality assurance (QA) procedures is needed in this field. The development of effective and efficient QA programmes is mandatory to guarantee optimal image quality while reducing radiation exposure levels to the ALARA principle (as low as reasonably achievable). In this review article, the basic QA procedures are discussed for the techniques applied to everyday clinical practice.
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Triple-rule-out computed tomography angiography with 256-slice computed tomography scanners: patient-specific assessment of radiation burden and associated cancer risk. Invest Radiol 2012; 47:109-15. [PMID: 21857528 DOI: 10.1097/rli.0b013e31822d0cf3] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
OBJECTIVES Risk-benefit analysis of triple-rule-out 256-slice computed tomography angiography (TRO-CTA) requires data on associated cancer risks, currently not available. The aim of the current study was to provide estimates of patient radiation burden and lifetime attributable risk (LAR) of radiation-induced cancer in patients undergoing typical 256-slice TRO-CTA. MATERIALS AND METHODS Standard step-and-shoot 256-slice TRO-CTA exposures were simulated on 31 male and 31 female individual-specific voxelized phantoms using a Monte Carlo CT dosimetry software. Dose images were generated depicting the dose deposition on the exposed body region of the patient. Organ doses were obtained for all primarily irradiated radiosensitive organs. Organ doses were correlated to patient body size. TRO-CTA effective dose was estimated from (a) organ doses and (b) dose-length product data. Recently published sex-, age-, and organ-specific cancer risk factors were used to estimate the total LAR of radiation-induced cancer. The theoretical risks of radiation-induced cancer to the lung and breast following a 256-slice TRO-CTA were compared with the corresponding nominal risks for each of the studied patients. RESULTS The highest organ doses were observed for the breast, heart, esophagus, and lung. Mean effective dose estimated using organ dose data was found to be 6.5 ± 1.0 mSv for female and 3.8 ± 0.7 mSv for male individuals subjected to 256-slice TRO-CTA. The associated mean LARs of cancer was found to be 41 per 10 female and 17 per 10 male patients. The total radiation-induced cancer risk was found to markedly decrease with patient age. TRO-CTA exposure was found to increase the intrinsic risks of developing lung or breast cancer during the remaining lifetime by less than 0.5% and 0.1%, respectively. CONCLUSIONS The mean theoretical risk of radiation-induced cancer for a patient cohort subjected to step-and-shoot 256-slice TRO-CTA may be considered to be low compared with the intrinsic risk of developing cancer.
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von Boetticher H, Lüllau T, Lammers M, Kamau EN, Poppe B. The deviation of liver dose in real patients for thoracic computed tomography scans: a new approach to individual dosimetry with methods of radiotherapy treatment planning. HEALTH PHYSICS 2011; 101:79-83. [PMID: 21617394 DOI: 10.1097/hp.0b013e31820be7a5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The increasing use of computed tomography (CT) in diagnostic imaging is associated with a relevant increase in patient dose and requires CT dose optimization. Anthropomorphic phantoms and mathematical patient models have been developed to improve the dosimetry in diagnostic imaging. Nevertheless, the doses calculated in these models and the ones individual patients can receive may differ considerably. In particular, the assessment of organ doses is problematic when organs and tissues receive only a partial exposure. A typical example for this situation is the exposure of the liver within a thoracic CT. To evaluate the impact of the field boundary and the liver volume on the individual organ dose, 50 CT scans from 25 male and 25 female patients between the ages of 27 to 87 were analyzed in this study with the volumetric tools of a treatment planning system for radiotherapy. The relative volume of the liver within a thoracic CT was assessed and compared to results from dosimetry methods using standardized patient models. The differences between an individual dose and the results from standardized patients are considerable. The fraction of the liver volume within a thoracic CT with a standard lower boundary extends from 48-92%, resulting in a possible dose difference of up to a factor of 1.7. Results from mathematical phantoms can underestimate the liver dose by more than a factor of 2.6. From the determined data, correction factors for the dosimetry of the liver using standard programs can be derived.
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Affiliation(s)
- Heiner von Boetticher
- Institute for Radiology and Academy of Radiation Protection, Klinikum Links der Weser, Bremen, Germany.
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Perisinakis K, Seimenis I, Tzedakis A, Papadakis AE, Damilakis J. Individualized assessment of radiation dose in patients undergoing coronary computed tomographic angiography with 256-slice scanning. Circulation 2010; 122:2394-402. [PMID: 21098451 DOI: 10.1161/circulationaha.109.935346] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Available data on the radiation burden from coronary computed tomography (CT) angiography (CCTA) are mostly limited to effective dose estimates. This study provides individualized estimates of doses and associated life attributable risks of radiation-induced cancer in a clinical patient population undergoing 256-slice CCTA. METHODS AND RESULTS Typical retrospectively and prospectively ECG-gated CCTA exposures in a 256-slice CT scanner were simulated on 52 patient-specific voxelized phantoms. Dose images depicting the dose deposition on the exposed region were generated, and normalized organ doses for all primarily irradiated radiosensitive organs were derived and correlated to patient body habitus. Lung, breast, and esophagus absorbed doses were then determined in 136 consecutive patients subjected to CCTA. Projected life attributable risks of radiation-induced cancer were estimated through the use of appropriate sex-, age- and organ-specific cancer risk factors and compared with corresponding nominal cancer risks. The total projected life attributable risk of radiogenic cancer after CCTA decreases steeply with age at exposure, and lung cancer constitutes the most probable detriment for both sexes. The relative risks of lung cancer associated with prospectively ECG-gated CCTA were 1.0032 and 1.0008 for women and men, respectively. The mean total projected life attributable risks were estimated to be 24.9±7.4 and 71.5±30.0 per 100,000 women undergoing prospectively and retrospectively ECG-gated CCTA, respectively. The corresponding values for men were 7.3±1.3 and 31.4±5.0 per 100 000 patients. CONCLUSIONS The mean projected life attributable risks of radiation-induced cancer in a typical clinical patient cohort undergoing standard prospectively ECG-gated CCTA with a 256-slice scanner were found to inconsequentially increase the natural cancer incidence rates.
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Affiliation(s)
- Kostas Perisinakis
- Department of Medical Physics, Faculty of Medicine, University of Crete, Crete, Greece.
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Damilakis J, Perisinakis K, Tzedakis A, Papadakis AE, Karantanas A. Radiation Dose to the Conceptus from Multidetector CT during Early Gestation: A Method That Allows for Variations in Maternal Body Size and Conceptus Position. Radiology 2010; 257:483-9. [DOI: 10.1148/radiol.10092397] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Damilakis J, Guglielmi G. Quality Assurance and Dosimetry in Bone Densitometry. Radiol Clin North Am 2010; 48:629-40. [DOI: 10.1016/j.rcl.2010.02.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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Yu L, Liu X, Leng S, Kofler JM, Ramirez-Giraldo JC, Qu M, Christner J, Fletcher JG, McCollough CH. Radiation dose reduction in computed tomography: techniques and future perspective. IMAGING IN MEDICINE 2009; 1:65-84. [PMID: 22308169 PMCID: PMC3271708 DOI: 10.2217/iim.09.5] [Citation(s) in RCA: 236] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Despite universal consensus that computed tomography (CT) overwhelmingly benefits patients when used for appropriate indications, concerns have been raised regarding the potential risk of cancer induction from CT due to the exponentially increased use of CT in medicine. Keeping radiation dose as low as reasonably achievable, consistent with the diagnostic task, remains the most important strategy for decreasing this potential risk. This article summarizes the general technical strategies that are commonly used for radiation dose management in CT. Dose-management strategies for pediatric CT, cardiac CT, dual-energy CT, CT perfusion and interventional CT are specifically discussed, and future perspectives on CT dose reduction are presented.
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Affiliation(s)
- Lifeng Yu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Xin Liu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Shuai Leng
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - James M Kofler
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | | | - Mingliang Qu
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Jodie Christner
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Joel G Fletcher
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Cynthia H McCollough
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
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