In computed tomography (CT) systems, the optimal X-ray energy in imaging depends on the material composition and the subject size. Among the parameters related to the X-ray energy, we can arbitrarily change only the tube voltage. For years, the tube voltage has often been set at 120 kVp. However, since about 2000, there has been an increasing interest in reducing radiation dose, and it has led to the publication of various reports on low tube voltage. Furthermore, with the spread of dual-energy CT, virtual monochromatic X-ray images are widely used since the contrast can be adjusted by selecting the optional energy. Therefore, because of the renewed interest in X-ray energy in CT imaging, the issue of energy and imaging needs to be summarized. In this article, we describe the basics of physical characteristics of X-ray attenuation with materials and its influence on the process of CT imaging. Moreover, the relationship between X-ray energy and CT imaging is discussed for clinical applications.

Purpose: Although the signal-to-noise ratio (SNR) currently used in the field of medical X-ray CT is utilized for local image evaluation in a linear system, it is not used as a comprehensive evaluation index for an entire image. Additionally, since X-ray CT cannot produce a noiseless image for obtaining the signal power required to calculate the SNR, it is impossible to calculate SNR precisely even applying the conventional method. To resolve these problems, we propose SNR*, which is a new method for calculating the estimated value of SNR that can evaluate an entire image even when the original image cannot be obtained. Methods: First, we obtained SNR* using the signal power and noise power calculated respectively from covariance and the difference in the pair of observed images, which are noise-containing images scanned under the same imaging conditions. Next, we verified the error and the accuracy of SNR*. Third, we demonstrated the behavior and accuracy of the SNR* applied to the actually observed image. Results: In the verification experiment, the relative error of SNR* concerning the true value was 0.06% or less, and the coefficient of variation value of SNR* in the demonstration experiment was 0.015 or less, which denoted the accuracy of SNR*. Conclusion: The proposed method realizes SNR measurement even in cases in which only observed images can be obtained and original images cannot be obtained, such as X-ray CT images.

Purpose: The incident electron energy spectrum was determined by an estimation formula based on the Lévy distribution in order to calculate the PDD and OAR that is consistent with the measurement. Methods: EGSnrc was used to calculate PDD and OAR at nominal energies of 4, 6, 9, 12, and 15 MeV. The parameters for determining the incident electron energy spectrum were adjusted to be a reasonable value in the error between the measured and the calculated values. Results: Location and scaling parameters were determined to be 0.5 and 0.001, respectively. The calculated PDD based on the determination formula was in agreement with the measurement within 2 mm/2% at all depths. The OAR also was in agreement with the measurement within 2 mm/2%. Conclusion: In this study, the incident electron energy spectrum was estimated by determining the location and scaling parameters. This method is simpler and more accurate than previously reported, and can be applied to the calculation of dose distributions in Monte Carlo simulations.

Purpose: The purposes were to search which factor of cardiac function in echocardiography correlates with the CT value, to correct contrast injection conditions with cardiac function in addition to suppress error in the contrast effect between patients, and to achieve the target CT value (350 HU) in coronary computed tomography angiography (CCTA). Methods: In 112 patients (conventional group), the contrast material was administered at a fractional dose (FD) of 21 mgI/kg/s. We measured the aortic CT value in the coronary origin part. In 112 patients (correction group), the contrast material was administered at corrected injection conditions with the most correlated functional factor and CT value. Results: The CT value of the conventional group was an average of 400.8±51.5 HU. The most correlated factor with the CT value was stroke volume [SV (r=−0.555)]. The CT value of the conventional group was an average of 360±46 HU. The case of the aim CT level was improved from 46% to 74%. In the correction group, the average value of FD was 18.5 mgI/kg/s. This enabled the reduction of the contrast material in 95% of patients. Conclusion: The best correlation was obtained between the CT value of coronary arteries and SV. The contrast medium injection conditions were corrected for cardiac function in addition to body weight. As a result, we were able to control the CCTA target CT value of 300 to 400 HU at our hospital.

In the point dose verification of intensity-modulated radiation therapy (IMRT), we compared the commonly used method of measuring absolute dose (absolute method) with the measurement method by the American Association of Physicists in Medicine Task Group 119, which describes the point dose verification for IMRT using the ratio of reference irradiation and measured ionization. The target was 66 plans for head and neck cancer, 46 plans for lung cancer with 6 MV X-ray, and 31 plans for prostate cancer with 10 MV X-ray. They were treated with volumetric-modulated arc therapy (VMAT). Each plan was evaluated by the absolute method and the TG119 method using 3D-array. The average and 2SD of the verification results for head and neck cancer, lung cancer, and prostate cancer were 0.129±2.185%, 0.963±2.125%, and 0.259±2.019% by the absolute method, and 0.952±2.039%, 1.704±2.080%, and 0.524±1.274% by the TG119 method. The ratio between the average of the TG119 method and the absolute method corresponded to the error of reference irradiation dose. Considering that the measurement method is simple, the TG119 method enables more stable point dose verification of VMAT.

This study aimed to investigate the feasibility of estimating functional ischemia information from coronary artery computed tomography (CACT) data (i.e., morphological information). Fifty-five suspected ischemic heart disease patients were included in this study. To calculate the ischemic myocardium percentage (LV myocardial territories volume of distal portion the stenotic lesion/total LV myocardial volume) from CACT data with “coronary territories analysis, Ziostation2”, and compared with the ischemic LV myocardium percentage and the functional flow reserve (FFR). The results showed that ischemic LV myocardium percentage was correlated with the FFR (r=−0.57). The median ischemic LV myocardium percentage of the FFR-positive group (n=33) was 37.1% (interquartile range [IQR] 33, 41.4%) and that of the FFR-negative group (n=22) was 24.8% (IQR 19.6, 30.6%). The ischemic LV myocardium percentage was significantly higher in the FFR-positive group (p<0.01) than in the FFR-negative group. The receiver operating characteristic (ROC) curve showed that the cutoff value for the ischemic LV myocardium percentage was 30%, with the sensitivity of 90.9% and the specificity of 77.3%. In conclusion, myocardial ischemia to diagnosis of FFR may occur when ischemic LV myocardium percentage is over than 30% and is unlikely to occur when it is less than 30%. This study suggests that the analysis of CACT data may contribute to the diagnosis of functional ischemia.