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Mannudeep K. Kalra,Pragya Dang,Sarabjeet Singh,Sanjay Saini,Jo-Anne O. Shepard 대한영상의학회 2009 Korean Journal of Radiology Vol.10 No.2
Objective: To assess effects of off-centering, automatic exposure control, and padding on attenuation values, noise, and radiation dose when using in-plane bismuth-based shields for CT scanning. Materials and Methods: A 30 cm anthropomorphic chest phantom was scanned on a 64-multidetector CT, with the center of the phantom aligned to the gantry isocenter. Scanning was repeated after placing a bismuth breast shield on the anterior surface with no gap and with 1, 2, and 6 cm of padding between the shield and the phantom surface. The “shielded” phantom was also scanned with combined modulation and off-centering of the phantom at 2 cm, 4 cm and 6 cm below the gantry isocenter. CT numbers, noise, and surface radiation dose were measured. The data were analyzed using an analysis of variance. Results: The in-plane shield was not associated with any significant increment for the surface dose or CT dose index volume, which was achieved by comparing the radiation dose measured by combined modulation technique to the fixed mAs (p > 0.05). Irrespective of the gap or the surface CT numbers, surface noise increased to a larger extent compared to Hounsfield unit (HU) (0-6 cm, 26-55%) and noise (0-6 cm, 30-40%) in the center. With off-centering, in-plane shielding devices are associated with less dose savings, although dose reduction was still higher than in the absence of shielding (0 cm off-center, 90% dose reduction; 2 cm, 61%) (p < 0.0001). Streak artifacts were noted at 0 cm and 1 cm gaps but not at 2 cm and 6 cm gaps of shielding to the surface distances. Conclusion: In-plane shields are associated with greater image noise, artifactually increased attenuation values, and streak artifacts. However, shields reduce radiation dose regardless of the extent of off-centering. Automatic exposure control did not increase radiation dose when using a shield. Objective: To assess effects of off-centering, automatic exposure control, and padding on attenuation values, noise, and radiation dose when using in-plane bismuth-based shields for CT scanning. Materials and Methods: A 30 cm anthropomorphic chest phantom was scanned on a 64-multidetector CT, with the center of the phantom aligned to the gantry isocenter. Scanning was repeated after placing a bismuth breast shield on the anterior surface with no gap and with 1, 2, and 6 cm of padding between the shield and the phantom surface. The “shielded” phantom was also scanned with combined modulation and off-centering of the phantom at 2 cm, 4 cm and 6 cm below the gantry isocenter. CT numbers, noise, and surface radiation dose were measured. The data were analyzed using an analysis of variance. Results: The in-plane shield was not associated with any significant increment for the surface dose or CT dose index volume, which was achieved by comparing the radiation dose measured by combined modulation technique to the fixed mAs (p > 0.05). Irrespective of the gap or the surface CT numbers, surface noise increased to a larger extent compared to Hounsfield unit (HU) (0-6 cm, 26-55%) and noise (0-6 cm, 30-40%) in the center. With off-centering, in-plane shielding devices are associated with less dose savings, although dose reduction was still higher than in the absence of shielding (0 cm off-center, 90% dose reduction; 2 cm, 61%) (p < 0.0001). Streak artifacts were noted at 0 cm and 1 cm gaps but not at 2 cm and 6 cm gaps of shielding to the surface distances. Conclusion: In-plane shields are associated with greater image noise, artifactually increased attenuation values, and streak artifacts. However, shields reduce radiation dose regardless of the extent of off-centering. Automatic exposure control did not increase radiation dose when using a shield.
Priyanka Prakash,Mannudeep K. Kalra,Matthew D. Gilman,Jo-Anne O. Shepard,Subba R. Digumarthy 대한영상의학회 2010 Korean Journal of Radiology Vol.11 No.1
Objective: To assess the effects of radiation dose reduction in the chest CT using a weight-based adjustment of the automatic exposure control (AEC) technique. Materials and Methods: With Institutional Review Board Approval, 60 patients (mean age, 59.1 years; M:F = 35:25) and 57 weight-matched patients (mean age, 52.3 years, M:F = 25:32) were scanned using a weight-adjusted AEC and nonweight-adjusted AEC, respectively on a 64-slice multidetector CT with a 0.984:1 pitch, 0.5 second rotation time, 40 mm table feed/rotation, and 2.5 mm section thickness. Patients were categorized into 3 weight categories; < 60 kg (n = 17), 60-90 kg (n = 52), and > 90 kg (n = 48). Patient weights, scanning parameters, CT dose index volumes (CTDIvol) and dose length product (DLP) were recorded, while effective dose (ED) was estimated. Image noise was measured in the descending thoracic aorta. Data were analyzed using a standard statistical package (SAS/STAT) (Version 9.1, SAS institute Inc, Cary, NC). Results: Compared to the non-weight-adjusted AEC, the weight-adjusted AEC technique resulted in an average decrease of 29% in CTDIvol and a 27% effective dose reduction (p < 0.0001). With weight-adjusted AEC, the CTDIvol decreased to 15.8, 15.9, and 27.3 mGy for the < 60, 60-90 and > 91 kg weight groups, respectively, compared to 20.3, 27.9 and 32.8 mGy, with non-weightadjusted AEC. No significant difference was observed for objective image noise between the chest CT acquired with the non-weight-adjusted (15.0 ± 3.1) and weight-adjusted (16.1 ± 5.6) AEC techniques (p > 0.05). Conclusion: The results of this study suggest that AEC should be tailored according to patient weight. Without weight-based adjustment of AEC, patients are exposed to a 17 - 43% higher radiation-dose from a chest CT. Objective: To assess the effects of radiation dose reduction in the chest CT using a weight-based adjustment of the automatic exposure control (AEC) technique. Materials and Methods: With Institutional Review Board Approval, 60 patients (mean age, 59.1 years; M:F = 35:25) and 57 weight-matched patients (mean age, 52.3 years, M:F = 25:32) were scanned using a weight-adjusted AEC and nonweight-adjusted AEC, respectively on a 64-slice multidetector CT with a 0.984:1 pitch, 0.5 second rotation time, 40 mm table feed/rotation, and 2.5 mm section thickness. Patients were categorized into 3 weight categories; < 60 kg (n = 17), 60-90 kg (n = 52), and > 90 kg (n = 48). Patient weights, scanning parameters, CT dose index volumes (CTDIvol) and dose length product (DLP) were recorded, while effective dose (ED) was estimated. Image noise was measured in the descending thoracic aorta. Data were analyzed using a standard statistical package (SAS/STAT) (Version 9.1, SAS institute Inc, Cary, NC). Results: Compared to the non-weight-adjusted AEC, the weight-adjusted AEC technique resulted in an average decrease of 29% in CTDIvol and a 27% effective dose reduction (p < 0.0001). With weight-adjusted AEC, the CTDIvol decreased to 15.8, 15.9, and 27.3 mGy for the < 60, 60-90 and > 91 kg weight groups, respectively, compared to 20.3, 27.9 and 32.8 mGy, with non-weightadjusted AEC. No significant difference was observed for objective image noise between the chest CT acquired with the non-weight-adjusted (15.0 ± 3.1) and weight-adjusted (16.1 ± 5.6) AEC techniques (p > 0.05). Conclusion: The results of this study suggest that AEC should be tailored according to patient weight. Without weight-based adjustment of AEC, patients are exposed to a 17 - 43% higher radiation-dose from a chest CT.
Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review
Khanna Narendra N,Singh Manasvi,Maindarkar Mahesh,Kumar Ashish,Johri Amer M.,Mentella Laura,Laird John R,Paraskevas Kosmas I.,Ruzsa Zoltan,Singh Narpinder,Kalra Mannudeep K.,Fernandes Jose Fernandes E 대한의학회 2023 Journal of Korean medical science Vol.38 No.46
Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.