Purpose: In this study, we propose a system that combines a depth camera with a deep learning model for estimating the human skeleton and a depth camera to estimate the shooting part to be radiographed and to acquire the thickness of the subject, thereby providing optimized X-ray imaging conditions. Methods: We propose a system that provides optimized X-ray imaging conditions by estimating the shooting part and measuring the thickness of the subject using an RGB camera and a depth camera. The system uses OpenPose, a posture estimation library, to estimate the shooting part. Results: The recognition rate of the shooting part was 15.38% for the depth camera and 84.62% for the RGB camera at a distance of 100 cm, and 42.31% for the depth camera and 100% for the RGB camera at a distance of 120 cm. The measurement accuracy of the subject thickness was within ±10 mm except for a few cases, indicating that the X-ray imaging conditions were optimized for the subject thickness. Conclusion: The implementation of this system in an X-ray system is expected to enable automatic setting of X-ray imaging conditions. The system is also useful in preventing increased exposure dose due to excessive dose or decreased image quality due to insufficient dose caused by incorrect setting of X-ray imaging conditions.

Purpose: To compare the diagnostic capabilities of orbital synchronized helical scanning at lower extremity computed tomography angiography between the Add/Sub software and the deformable image registration. Methods: From March 2015 to December 2016, 100 dialysis patients underwent orbital synchronized lower limb CT subtraction angiography and lower limb endovascular treatment within 4 months. For the visual evaluation of blood vessels in the lower extremities, a stenosis rate of 50% or more was considered to be stenosis. It was classified into two areas: above-knee (AK) region (superficial femoral artery and popliteal artery) and below-knee (BK) region (anterior tibial artery, posterior tibial artery, and fibula artery). Considering angiography for the lower limb endovascular treatment as the golden standard, we calculated the sensitivity, specificity, positive-predictive value, negative-predictive value, and diagnostic capabilities. Receiver operating characteristic curve (ROC) analysis was performed to calculate the area under curve (AUC). Results: Calcification subtraction failure was observed to be 11% in the AK region and 2% in the BK region using the Add/Sub software. The specificity, positive-predictive value, diagnostic capabilities, and AUC of the deformable image registration were lower than those of the Add/Sub software. Conclusions: Add/Sub software and deformable image registration have high diagnostic capability to remove calcification. On the other hand, the specificity and AUC of the deformable image registration were lower than those of the Add/Sub software. Also, even if the same deformable image registration is used, caution is required because the diagnostic performance varies depending on the site.

Purpose: The purposes of this study were to evaluate the low-contrast detectability of CT images assuming hepatocellular carcinoma and to determine whether dose reduction in abdominal plain CT imaging is possible. Methods: A Catphan 600 was imaged at 350, 250, 150, and 50 mA using an Aquilion ONE PRISM Edition (Canon) and reconstructed using deep learning reconstruction (DLR) and model-based iterative reconstruction (MBIR). A low-contrast object-specific contrast-to-noise ratio (CNR_LO) was measured and compared in a 5-mm module with a CT value difference of 10 HU, assuming hepatocellular carcinoma; a visual examination was also performed. Moreover, an NPS within a uniform module was measured. Results: CNR_LO was higher for DLR at all doses (1.12 at 150 mA for DLR and 1.07 at 250 mA for MBIR). On visual evaluation, DLR could detect up to 150 mA and MBIR up to 250 mA. The NPS was lower for DLR at 0.1 cycles/mm at 150 mA. Conclusion: The low-contrast detection performance was better with DLR than with MBIR, indicating the possibility of dose reduction.

Purpose: To investigate fundamental dosimetric properties of surface dose, exit dose, and beam profile of the brass mesh bolus for 4, 6, and 10 MV high-energy photon beams in radiation therapy. Methods: Surface dose and exit dose in the water-equivalent phantom were measured, and percent depth doses (PDDs) were calculated with no bolus, one layer of brass mesh, two layers of brass mesh bolus, three layers of brass mesh bolus, and 0.5 cm tissue-equivalent (TE) bolus. Exit dose was measured at a phantom thickness of 10 cm. Beam profiles were measured at phantom depths of 0 cm and 10 cm. All dosimetry was performed for 4, 6, and 10 MV photon beams using a linear accelerator. Results: The surface dose at a phantom depth of 0 cm increased to 37.3%, 36.3%, and 31.0% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The surface dose decreased with one layer of brass mesh bolus compared to that with the 0.5 cm TE bolus. On the other hand, the exit dose increased to 22.0%, 23.1%, and 22.8% for 4, 6, and 10 MV, respectively, with the brass mesh bolus compared to the case of no bolus. The beam profile at the depth of 0 cm showed oscillations, and the difference between the maximum and minimum doses was up to 13.1% with one layer of brass mesh bolus. Conclusion: It was suggested that the brass mesh bolus not only increases the surface dose but also has different properties from the conventional TE bolus.

Purpose: The purpose of this study was to evaluate the effects of phantom factor on the verification of measured doses using cheese phantoms in tomotherapy. Methods: Two plans for dose verification (plan classes and plan class phantom sets with a virtual organ at the risk set) were evaluated. The calculated and measured doses were compared with and without the phantom factor using cheese phantoms. Additionally, the phantom factor was evaluated for two conditions (TomoHelical/TomoDirect) in clinical cases (breast and prostate). Results: When applying a phantom factor of 1.007, the deviation between the calculated and measured doses increased in Plan-Class and TomoDirect, decreased in TomoHelical, and increased in both clinical cases. Conclusion: When conducting dose verification, the effects of one phantom factor on measurement conditions may differ depending on when phantom factors were obtained (irradiation technique and irradiation field). It is therefore necessary to consider changes in measured doses due to changes in phantom scattering.

A magnetic resonance imaging (MRI) scan was performed to rule out a sternal fracture in a woman in 30s. Short tau inversion recovery (STIR) coronal showed no signal change in the sternum but increased signal from the mediastinum to the anterior thoracic region. We could not detect significant findings until midway through the examination. T₂-weighted fat-suppressed images revealed a suspected left first costal cartilage injury at the end of the examination. In addition, three-dimensional gradient-recalled echo (3D GRE) T₁-weighted fat-suppressed images clearly revealed a lesion area with a high signal intensity in the costal cartilage and a low signal intensity in the surrounding tissue, and we diagnosed costal cartilage injury definitely. In case of MRI for posttraumatic chest pain, T₁-weighted fat-suppressed images with 3D GRE may be useful for the detection of lesion area.