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Zhang J, Zhang X. Size specific dose estimation in pediatric CT: preliminary study and conversion factors. Radiat Prot Dosimetry 2024; 200:677-686. [PMID: 38678314 DOI: 10.1093/rpd/ncae104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 03/02/2024] [Accepted: 04/11/2024] [Indexed: 04/29/2024]
Abstract
The objective of this paper is to compare the differences between volumetric CT dose index (CTDIVOL) and size-specific dose estimate (SSDEWED) based on water equivalent diameter (WED) in radiation dose measurement, and explore a new method for fast calculation of SSDEWED. The imaging data of 1238 cases of head, 1152 cases of chest and 976 cases of abdominopelvic were analyzed retrospectively, and they were divided into five age groups: ≤ 0.5, 0.5 ~ ≤ 1, 1 ~ ≤ 5, 5 ~ ≤ 10 and 10 ~ ≤ 15 years according to age. The area of interest (AR), CT value (CTR), lateral diameter (LAT) and anteroposterior diameter (AP) of the median cross-sectional image of the standard scanning range and the SSDEWED were manually calculated, and a t-test was used to compare the differences between CTDIVOL and SSDEWED in different age groups. Pearson analyzed the correlations between DE and age, DE and WED, f and age, and counted the means of conversion factors in each age group, and analyze the error ratios between SSDE calculated based on the mean age group conversion factors and actual measured SSDE. The CTDIVOL in head was (9.41 ± 1.42) mGy and the SSDEWED was (8.25 ± 0.70) mGy: the difference was statistically significant (t = 55.04, P < 0.001); the CTDIVOL of chest was (2.68 ± 0.91) mGy and the SSDEWED was (5.16 ± 1.16) mGy, with a statistically significant difference (t = -218.78, P < 0.001); the CTDIVOL of abdominopelvic was (3.09 ± 1.58) mGy and the SSDEWED was (5.89 ± 2.19) mGy: the difference was also statistically significant (t = -112.28, P < 0.001). The CTDIVOL was larger than the SSDEWED in the head except for the ≤ 0.5 year subgroup, and CTDIVOL was smaller than SSDEWED within each subgroup in chest and abdominopelvic. There were strong negative correlations between f and age (head: r = -0.81; chest: r = -0.89; abdominopelvic: r = -0.86; P < 0.001). The mean values of f at each examination region were 0.81 ~ 1.01 for head, 1.65 ~ 2.34 for chest and 1.71 ~ 2.35 for abdominopelvic region. The SSDEWED could be accurately estimated using the mean f of each age subgroup. SSDEWED can more accurately measure the radiation dose of children. For children of different ages and examination regions, the SSDEWED conversion factors based on age subgroup can be quickly adjusted and improve the accuracy of radiation dose estimation.
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Affiliation(s)
- Jian Zhang
- Department of Radiology, Children's Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Xiaojun Zhang
- Department of Radiology, Children's Hospital of Nanjing Medical University, Nanjing 210000, China
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Tan Z, Zhang L, Sun X, Yang M, Makamure J, Wu H, Wang J. Dual-Layer Detector Head CT to Maintain Image Quality While Reducing the Radiation Dose in Pediatric Patients. AJNR Am J Neuroradiol 2023; 44:1212-1218. [PMID: 37735089 PMCID: PMC10549953 DOI: 10.3174/ajnr.a7999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 08/02/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND AND PURPOSE Radiation exposure in the CT diagnostic imaging process is a conspicuous concern in pediatric patients. This study aimed to evaluate whether 60-keV virtual monoenergetic images of the pediatric cranium in dual-layer CT can reduce the radiation dose while maintaining image quality compared with conventional images. MATERIALS AND METHODS One hundred six unenhanced pediatric head scans acquired by dual-layer CT were retrospectively assessed. The patients were assigned to 2 groups of 53 and scanned with 250 and 180 mAs, respectively. Dose-length product values were retrieved, and noise, SNR, and contrast-to-noise ratio were calculated for each case. Two radiologists blinded to the reconstruction technique used evaluated image quality on a 5-point Likert scale. Statistical assessment was performed with ANOVA and the Wilcoxon test, adjusted for multiple comparisons. RESULTS Mean dose-length product values were 717.47 (SD, 41.52) mGy×cm and 520.74 (SD, 42) mGy×cm for the 250- and 180-mAs groups, respectively. Irrespective of the radiation dose, noise was significantly lower, SNR and contrast-to-noise ratio were significantly higher, and subjective analysis revealed significant superiority of 60-keV virtual monoenergetic images compared with conventional images (all P < .001). SNR, contrast-to-noise ratio, and subjective evaluation in 60-keV virtual monoenergetic images were not significantly different between the 2 scan groups (P > .05). Radiation dose parameters were significantly lower in the 180-mAs group compared with the 250-mAs group (P < .001). CONCLUSIONS Dual-layer CT 60-keV virtual monoenergetic images allowed a radiation dose reduction of 28% without image-quality loss in pediatric cranial CT.
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Affiliation(s)
- Zhengwu Tan
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Lan Zhang
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Xiaojie Sun
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Ming Yang
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Joyman Makamure
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Hongying Wu
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
| | - Jing Wang
- From the Department of Radiology (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
- Hubei Province Key Laboratory of Molecular Imaging (Z.T., L.Z., X.S., M.Y., J.M., H.W., J.W.), Wuhan, Hubei, China
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