Objectives: This study aims to evaluate the accuracy of physical density prediction in single-energy CT (SECT) and dual-energy CT (DECT) by adapting a fully simulation-based method using a material-based forward projection algorithm (MBFPA).
Methods: We used biological tissues referenced in ICRU Report 44 and tissue substitutes to prepare three different types of phantoms for calibrating the Hounsfield unit (HU)-to-density curves. Sinograms were first virtually generated by the MBFPA with four representative energy spectra ( 80 kVp, 100 kVp, 120 kVp, and 6 MVp) and then reconstructed to form realistic CT images by adding statistical noise. The HU-to-density curves in each spectrum and their pairwise combinations were derived from the CT images. The accuracy of these curves was validated using the ICRP110 human phantoms.
Results: The relative mean square errors (RMSEs) of the physical density by the HU-to-density curves calibrated with kV SECT nearly presented no phantom size dependence. The kV-kV DECT calibrated curves were also comparable with those from the kV SECT. The phantom size effect became notable when the MV X-ray beams were employed for both SECT and DECT due to beam-hardening effects. The RMSEs were decreased using the biological tissue phantom.
Conclusion: Simulation-based density prediction can be useful in the theoretical analysis of SECT and DECT calibrations. The results of this study indicated that the accuracy of SECT calibration is comparable with that of DECT using biological tissues. The size and shape of the calibration phantom could affect the accuracy, especially for MV CT calibrations.
Advances In Knowledge: The present study is based on a full simulation environment, which accommodates various situations such as SECT, kV-kV DECT, and even kV-MV DECT. In this paper, we presented the advances pertaining to the accuracy of the physical density prediction when applied to SECT and DECT in the MV X-ray energy range. To the best of our knowledge, this study is the first to validate the physical density estimation both in SECT and DECT using human-type phantoms.
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http://dx.doi.org/10.1259/bjr.20201236 | DOI Listing |
Alzheimers Dement
December 2024
Yonsei university, Wonju-si, Gangwon-do, Korea, Republic of (South).
Background: Sleep directly affects daily life, and lack of sleep affects cognitive function and mental health. So, this study analyzed the performance structures of daily activities affecting sleep using social network analysis.
Methods: The subjects were 313 people over 50 years old.
Alzheimers Dement
December 2024
Newcastle University, Newcastle, Tyne and Wear, United Kingdom.
Background: Approximately 944,000 people are living with dementia in the UK (∼0.8% of the population). The World Health Organisation consider dementia a public health priority.
View Article and Find Full Text PDFJ Exerc Rehabil
December 2024
Department of Physical Education, Kunsan National University, Gunsan, Korea.
To examine the changes in obesity-related hormones and metabolic syndrome markers in male high school students with obesity following a weekend-focused moderate- or high-intensity exercise program at the recommended weekly physical activity level, or a program of regular exercise 3 times a week at moderate intensity, over a 10-week period. Forty-eight male high school students who were obese with a body fat percentage of ≥25% were randomly assigned to one of three groups: a regular moderate-intensity exercise group (n=17) that freely selected and performed moderate-intensity aerobic and resistance training exercises, every Monday, Wednesday, and Friday, for a total of 150-300 min/wk; a weekend-focused moderate-intensity exercise group (n=15) that freely selected and performed aerobic and resistance training exercises every Saturday for 150-300 min; and a week-end-focused high-intensity exercise group (n=16) that freely selected and performed aerobic and resistance training exercises every Sunday for 75-150 min. Insulin and leptin levels significantly decreased in all the groups, with the greatest reduction in the regular exercise group.
View Article and Find Full Text PDFCureus
December 2024
Department of Obstetrics and Gynecology, Royal Medical Services, Amman, JOR.
Ovarian agenesis (OA) is a rare congenital condition characterized by the absence of one or both ovaries, often associated with chromosomal abnormalities, hormonal imbalances, and structural deformities. The condition is frequently diagnosed in females presenting with primary amenorrhea and delayed sexual development. This case report highlights a unique presentation of bilateral ovarian agenesis in a patient with chromosome X translocation, bone modeling disease, and primary amenorrhea.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Biomedical Engineering, College of Health Science, Yonsei University, Wonju, Republic of Korea.
Unlabelled: This study aims to create a fatigue recognition system that utilizes electroencephalogram (EEG) signals to assess a driver's physiological and mental state, with the goal of minimizing the risk of road accidents by detecting driver fatigue regardless of physical cues or vehicle attributes. A fatigue state recognition system was developed using transfer learning applied to partial ensemble averaged EEG power spectral density (PSD). The study utilized layer-wise relevance propagation (LRP) analysis to identify critical cortical regions and frequency bands for effective fatigue discrimination.
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