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Pace E, Caruana CJ, Bosmans H, Cortis K, D'Anastasi M, Valentino G. An inventory of patient-image based risk/dose, image quality and body habitus/size metrics for adult abdomino-pelvic CT protocol optimisation. Phys Med 2024; 125:103434. [PMID: 39096718 DOI: 10.1016/j.ejmp.2024.103434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 07/04/2024] [Accepted: 07/17/2024] [Indexed: 08/05/2024] Open
Abstract
PURPOSE Patient-specific protocol optimisation in abdomino-pelvic Computed Tomography (CT) requires measurement of body habitus/size (BH), sensitivity-specificity (surrogates image quality (IQ) metrics) and risk (surrogates often dose quantities) (RD). This work provides an updated inventory of metrics available for each of these three categories of optimisation variables derivable directly from patient measurements or images. We consider objective IQ metrics mostly in the spatial domain (i.e., those related directly to sharpness, contrast, noise quantity/texture and perceived detectability as these are used by radiologists to assess the acceptability or otherwise of patient images in practice). MATERIALS AND METHODS The search engine used was PubMed with the search period being 2010-2024. The key words used were: 'comput* tomography', 'CT', 'abdom*', 'dose', 'risk', 'SSDE', 'image quality', 'water equivalent diameter', 'size', 'body composition', 'habit*', 'BMI', 'obes*', 'overweight'. Since BH is critical for patient specific optimisation, articles correlating RD vs BH, and IQ vs BH were reviewed. RESULTS The inventory includes 11 BH, 12 IQ and 6 RD metrics. 25 RD vs BH correlation studies and 9 IQ vs BH correlation studies were identified. 7 articles in the latter group correlated metrics from all three categories concurrently. CONCLUSIONS Protocol optimisation should be fine-tuned to the level of the individual patient and particular clinical query. This would require a judicious choice of metrics from each of the three categories. It is suggested that, for increased utility in clinical practice, more future optimisation studies be clinical task based and involve the three categories of metrics concurrently.
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Affiliation(s)
- Eric Pace
- Medical Physics, Faculty of Health Science, University of Malta, Msida MSD2080, Malta.
| | - Carmel J Caruana
- Medical Physics, Faculty of Health Science, University of Malta, Msida MSD2080, Malta
| | - Hilde Bosmans
- Medical Physics & Quality Assessment, Department of Imaging & Pathology, KU Leuven, Leuven, Belgium
| | - Kelvin Cortis
- Medical Imaging Department, Mater Dei Hospital, Msida MSD2090, Malta
| | - Melvin D'Anastasi
- Medical Imaging Department, Mater Dei Hospital, Msida MSD2090, Malta
| | - Gianluca Valentino
- Communications & Computer Engineering Department, Faculty of Information and Communication Technology, University of Malta, Msida MSD2080, Malta
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Robatjazi M, Moayed M, Baghani HR, Molazadeh M, Shomoossi N. Evaluation of organ dose using size-specific dose estimation (SSDE) and related cancer risk due to chest CT scan during the COVID-19 pandemic. RADIATION AND ENVIRONMENTAL BIOPHYSICS 2024; 63:27-37. [PMID: 38185693 DOI: 10.1007/s00411-023-01056-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 12/08/2023] [Indexed: 01/09/2024]
Abstract
This study aimed to estimate lung and breast doses for individual patients using the size-specific dose estimate (SSDE) method, as well as calculating effective doses, in patients who underwent chest CT scans during the COVID-19 pandemic. Cancer risk incidence was estimated using excess relative risk (ERR), excess absolute risk (EAR), and lifetime attributable risk (LAR) models from the Biological Effects of Ionizing Radiation Report VII (BEIR-VII). Data from about 570 patients who underwent CT scans for COVID-19 screening were utilized for this study. Using the header of the CT images in a Python script, SSDE and effective dose were calculated for each patient. The SSDE obtained by water equivalent effective diameter (wSSDE) was considered as lung and breast dose, and applied in organ-specific cancer risk estimation. The mean wSSDE value for females (13.3 mGy) was slightly higher than that for males (13.1 mGy), but the difference was not statistically significant (P value = 0.41). No significant differences were observed between males and females in terms of calculated EAR and ERR for lung cancer at 5 and 30 years after exposure (P value = 0.47, 0.46, respectively). Similarly, there was no significant difference in lung cancer LAR values between females and males (P value = 0.48). The results also indicated a decrease in LAR values for both lung and breast cancers with increasing exposure age. In accordance with the ALARA (as low as reasonably achievable) principle, it is important for medical staff and the general public to consider the benefits of CT imaging in detecting such infections. Additionally, imaging medical physicists and CT scan experts should optimize imaging protocols and strike a balance between image quality for detecting abnormalities and radiation dose, all while adhering to the ALARA principle.
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Affiliation(s)
- Mostafa Robatjazi
- Department of Medical Physics and Radiological Sciences, Sabzevar University of Medical Sciences, Sabzevar, Iran
- Non-Communicable Disease Research Center, Sabzevar University of Medical Sciences, Sabzevar, Iran
| | - Mahdis Moayed
- Department of Medical Physics and Radiological Sciences, Sabzevar University of Medical Sciences, Sabzevar, Iran
| | | | - Mikaeil Molazadeh
- Department of Medical Physics, Tabriz University of Medical Sciences, Tabriz, Iran
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Shao W, Lin X, Yi Y, Huang Y, Qu L, Zhuo W, Liu H. Fast prediction of patient-specific organ doses in brain CT scans using support vector regression algorithm. Phys Med Biol 2024; 69:025010. [PMID: 38086079 DOI: 10.1088/1361-6560/ad14c7] [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: 08/31/2023] [Accepted: 12/12/2023] [Indexed: 01/11/2024]
Abstract
Objectives. This study aims to develop a method for predicting patient-specific head organ doses by training a support vector regression (SVR) model based on radiomics features and graphics processing unit (GPU)-calculated reference doses.Methods. In this study, 237 patients who underwent brain CT scans were selected, and their CT data were transferred to an autosegmentation software to segment head regions of interest (ROIs). Subsequently, radiomics features were extracted from the CT data and ROIs, and the benchmark organ doses were computed using fast GPU-accelerated Monte Carlo (MC) simulations. The SVR organ dose prediction model was then trained using the radiomics features and benchmark doses. For the predicted organ doses, the relative root mean squared error (RRMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) were evaluated. The robustness of organ dose prediction was verified by changing the patient samples on the training and test sets randomly.Results. For all head organs, the maximal difference between the reference and predicted dose was less than 1 mGy. For the brain, the organ dose was predicted with an absolute error of 1.3%, and theR2reached up to 0.88. For the eyes and lens, the organ doses predicted by SVR achieved an RRMSE of less than 13%, the MAPE ranged from 4.5% to 5.5%, and theR2values were more than 0.7.Conclusions. Patient-specific head organ doses from CT examinations can be predicted within one second with high accuracy, speed, and robustness by training an SVR using radiomics features.
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Affiliation(s)
- Wencheng Shao
- Institute of Radiation Medicine, Fudan University, Shanghai, People's Republic of China
| | - Xin Lin
- Institute of Radiation Medicine, Fudan University, Shanghai, People's Republic of China
| | - Yanling Yi
- Institute of Radiation Medicine, Fudan University, Shanghai, People's Republic of China
| | - Ying Huang
- Department of Nuclear Science and Technology, Institute of Modern Physics, Fudan University, Shanghai, People's Republic of China
- Key Lab of Nucl. Phys. & Ion-Beam Appl. (MOE), Fudan University, Shanghai, People's Republic of China
- Department of Radiation Oncology, Shanghai Jiao Tong University Chest Hospital Shanghai, People's Republic of China
| | - Liangyong Qu
- Department of Radiology, Shanghai Zhongye Hospital, Shanghai, People's Republic of China
| | - Weihai Zhuo
- Institute of Radiation Medicine, Fudan University, Shanghai, People's Republic of China
| | - Haikuan Liu
- Institute of Radiation Medicine, Fudan University, Shanghai, People's Republic of China
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Costa PR, Tomal A, de Oliveira Castro JC, Nunes IPF, Nersissian DY, Sawamura MVY, Leão Filho H, Lee C. Diagnostic reference level quantities for adult chest and abdomen-pelvis CT examinations: correlation with organ doses. Insights Imaging 2023; 14:60. [PMID: 37024637 PMCID: PMC10079797 DOI: 10.1186/s13244-023-01403-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 03/11/2023] [Indexed: 04/08/2023] Open
Abstract
OBJECTIVES To evaluate correlations between DRL quantities (DRLq) stratified into patient size groups for non-contrast chest and abdomen-pelvis CT examinations in adult patients and the corresponding organ doses. METHODS This study presents correlations between DRLq (CTDIvol, DLP and SSDE) stratified into patient size ranges and corresponding organ doses shared in four groups: inside, peripheral, distributed and outside. The demographic, technical and dosimetric parameters were used to identify the influence of these quantities in organ doses. A robust statistical method was implemented in order to establish these correlations and its statistical significance. RESULTS Median values of the grouped organ doses are presented according to the effective diameter ranges. Organ doses in the regions inside the imaged area are higher than the organ doses in peripheral, distributed and outside regions, excepted to the peripheral doses associated with chest examinations. Different levels of statistical significance between organ doses and the DRLq were presented. CONCLUSIONS Correlations between DRLq and target-organ doses associated with clinical practice can support guidance's to the establishment of optimization criteria. SSDE demonstrated to be significant in the evaluation of organ doses is also highlighted. The proposed model allows the design of optimization actions with specific risk-reduction results.
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Affiliation(s)
- Paulo Roberto Costa
- Institute of Physics, University of São Paulo, R. Do Matão, 1371, Butantã, São Paulo, SP, 05508-090, Brazil.
| | - Alessandra Tomal
- Institute of Physics Gleb Watagin, University of Campinas, Campinas, Brazil
| | | | | | - Denise Yanikian Nersissian
- Institute of Physics, University of São Paulo, R. Do Matão, 1371, Butantã, São Paulo, SP, 05508-090, Brazil
| | | | - Hilton Leão Filho
- Division of Radiology, Medical School, University of São Paulo, São Paulo, Brazil
| | - Choonsik Lee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health (NIH), Bethesda, MD, USA
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Abstract
Nuclear medicine provides methods and techniques in that has benefited pediatric patients and their referring physicians for over 40 years. Nuclear medicine provides qualitative and quantitative information about overall and regional function of organs, systems, and lesions in the body. This involves applications in many organ systems including the skeleton, the brain, the kidneys and the heart as well as in the diagnosis and treatment of cancer. The practice of nuclear medicine requires the administration of radiopharmaceuticals which expose the patient to very low levels of ionizing radiation. Advanced approaches in the estimation of radiation dose from the internal distribution of radiopharmaceuticals in patients of various sizes and shapes have been developed in the past 20 years. Although there is considerable uncertainty in the estimation of the risk of adverse health effects from radiation at the very low exposure levels typically associated with nuclear medicine, some considers it prudent to be more cautious when applied to children as they are generally considered to be at higher risk than adults. Standard guidelines for administered activities for nuclear medicine procedures in children have been established including the North American consensus guidelines and the Paediatric Dosage Card developed by the European Association of Nuclear Medicine. As we move into the future, these guidelines would likely be reviewed in response to changes in clinical practice, a better understanding of radiation dosimetry as applied to children as well as new clinical applications, new advancements in the field with respect to both instrumentation and image reconstruction and processing.
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Affiliation(s)
- S Ted Treves
- Harvard Medical School; Brigham and Women's Hospital.
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Li X, Marschall TA, Yang K, Liu B. Advancing size-specific dose estimates in CT examinations: Dose estimates at longitudinal positions of scans. Med Phys 2021; 49:1303-1311. [PMID: 34894408 DOI: 10.1002/mp.15402] [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: 07/26/2021] [Revised: 10/29/2021] [Accepted: 11/22/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE American Association of Physicists in Medicine (AAPM) (Report 204) introduced the size-specific dose estimate (SSDE) for the average dose to the center of a fixed-mA scan. International standards establish a method that CT manufacturers and radiation dose index monitoring software may use to calculate SSDE(z) at longitudinal positions of scans with fixed mA or tube current modulation, and its scan range average SSDE ( z ) ¯ . We sought to test how accurate SSDE(z) is in tracking the average dose to the transverse slab of an axial image slice (Dslice ), evaluated with Monte Carlo calculation, in the chest and abdominopelvic examinations. METHODS We retrospectively identified 65 consecutive adult patients undergoing whole-body CT for transcatheter aortic valve implantation planning. Examination parameters (kV, mA, CTDIvol ) were extracted from the DICOM headers. Patient water equivalent diameter DW (z) was calculated at each image slice, excluding the patient table. A previously validated Monte Carlo simulation (Geant4) program was used to evaluate Dslice from the chest and abdominopelvic examinations. Alternatively, SSDE(z) was calculated at each slice. The results of the two methods were compared with descriptive statistical outcomes (R, version 4.0.2). RESULTS In chest and abdominopelvic CT examinations, Dslice largely changed with anatomic location and uniformly fell off toward scan range edges. Scan range averages SSDE ( z ) ¯ and D slice ¯ were consistent within 2.5%-3.1% (median) and 6.3%-10.4% (maximum) in two examinations. On individual image slices, SSDE(z) could be lower or higher than Dslice , with deviation ranging from -18.3% to 85% in two edges (2 × 5 cm) of scan range and from -35.2% to 18.7% in the remaining central region of the scan. CONCLUSION This study provides critical inputs for quality assurance programs. SSDE ( z ) ¯ is useful to track the average dose of all image slices, but further development may be useful for tracking patient dose at the level of individual image slices, especially near a scan range edge.
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Affiliation(s)
- Xinhua Li
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Theodore A Marschall
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Kai Yang
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Bob Liu
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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