Nihon Hoshasen Gijutsu Gakkai zasshi最新文献

Purpose: Image-guided radiation therapy using cone-beam computed tomography (CBCT) for prostate cancer is problematic due to the increasing exposure dose at each treatment session. This study aimed to evaluate the effect of exposure dose reduction using bismuth sheets for pelvic CBCT.

Methods: Using a radiophotoluminescence dosimeter (GD-352M) and CBCT imaging conditions with three X-ray tube rotation angles (292°-88°, 92°-248°, and 92°-88°), absorbed doses were measured in the rectum, anterior and posterior bladder walls, right and left pelvic subcutaneous at 5 cm superior the prostate center of the pelvic phantom and in a testis. Next, the same measurements were performed when these measurement points were covered with a bismuth sheet.

Results: The absorbed doses at 92°-248° with the bismuth sheets were reduced by 31.3% from 16.3±0.2 mGy to 11.2±0.2 mGy for the rectum and by 57.1% from 45.0±2.7 mGy to 19.3±1.0 mGy for the testis, which were the lowest among the imaging conditions. Although the anterior and posterior bladder walls were the highest dose at 48.7±11.5 and 20.2±0.4 mGy, the high reduction rates of 42.0% and 36.9%, respectively.

Conclusion: From the viewpoint of the exposure risk to the bladder, rectum, and testis, using bismuth sheets and the X-ray tube rotation angle of 92°-248° effectively reduced the exposure dose.

Purpose: Motion artifacts likely occur in patients with acute intracerebral hemorrhage (ICH). This study aimed to validate the image quality characteristics of non-contrast brain computed tomography (CT) with high-speed imaging technology, named Flash spiral (FS) (Siemens Healthineers, Erlangen, Germany). We verified the differences in CT values using a phantom that simulated hematoma.

Methods: A dual-source CT scanner (SOMATOM Drive; Siemens Healthineers) was used to obtain reference and FS images of a Catphan700 phantom (The Phantom Laboratory, Greenwich, NY, USA). The CT values were measured in the hematoma-simulated acrylic module and urethane within the phantom. The noise power spectrum (NPS), task transfer function (TTF), and system performance function (SPF) between reference and FS images were obtained to compare image quality in each scan.

Results: Compared with the phantom's reference and FS images, no significant differences were observed in the CT values between the samples simulating hematoma and their surrounding areas. The NPS showed lower values in the FS images than the reference images at spatial frequencies above approximately 0.4 cycles/mm, while the peak frequencies were nearly equivalent. The 10% TTF values were almost the same between both images. The SPF values were also equivalent between the two images at spatial frequencies above approximately 0.5 cycles/mm.

Conclusion: In the phantom experiment, the 10% TTF values of the FS images were comparable to those of the reference images, indicating similar resolution in the high spatial frequency domain. FS is expected to expand the applicability for detecting cerebral hemorrhage in patients with significant body movement, where detection is challenging under standard conditions.

Purpose: The purpose of this study was to compare the surface conformity of Clearfit Bolus II (Clearfit2) (Fujidenolo, Aichi) and Clearfit Bolus (Clearfit1) (Fujidenolo) using an anthropomorphic phantom.

Methods: Clearfit1 and Clearfit2 boluses (5 mm thick) were placed in three anatomical regions of the anthropomorphic phantom: nose, breast, and abdomen, and CT scans were performed. Digital Imaging and Communications in Medicine (DICOM) structural data were used to measure the air gap between the bolus and the surface of the phantom. The surface conformity area ratio at the threshold (1-5 mm) was calculated. Statistical analysis was performed using the Mann-Whitney U test.

Results: Clearfit2 had significantly reduced air gaps compared to Clearfit1: 2.9±2.0 mm in the nose, 1.8±2.1 mm in the breasts, and 0.1±0.1 mm in the abdomen, which were lower than Clearfit1's 5.8±2.9 mm, 11.4±8.4 mm, and 2.2±2.1 mm, respectively (p<0.001). In the abdominal region, Clearfit2 achieved near-perfect surface conformity with over 99% of the surface showing gaps ≤1 mm.

Conclusion: We demonstrated that Clearfit2 significantly improves the surface conformity by reducing air gaps between the bolus and the phantom surface compared to Clearfit1.

Purpose: The aim of this study was to attempt to make a decision on priorities in measures to prevent recurrence of previously reported low-level incidents using the priority monitoring score.

Methods: A survey of the low-level incidents reported over the past 5 years in the department of radiation therapy was conducted among 7 radiological technologists. From the results of the survey, the priority monitoring score was calculated by multiplying each score of the potential incident level, the occurrence frequency, and the detectability. Additionally, the relationship between the priority monitoring score and each factor was investigated.

Results: From the results of a survey of 67 low-level incidents, the mean+standard deviation (23.1) of the priority monitoring score was set as the threshold for a decision of priorities. The strongest correlation was observed between the priority monitoring score and the potential incident level (a correlation coefficient, r=0.74).

Conclusion: It is suggested that the possibility of prioritizing the decision of low-level incidents that require measures to prevent recurrence be considered by setting the threshold for the priority monitoring score. On the other hand, the reporting requirements and the level classification for incidents vary among facilities. Therefore, the threshold for the decision of priorities needs to be considered in each facility.

Purpose: The purpose of this study was to compare true non-contrast (TNC) images and virtual non-contrast (VNC) images obtained using photon-counting detector computed tomography (PCD-CT) and to evaluate the accuracy of VNC images in the assessment of hepatic lesions.

Methods: The study included 79 patients who underwent contrast-enhanced CT and were diagnosed with hepatic lesions. The hepatic lesions consisted of 19 cases of hepatocellular carcinoma, 22 cases of metastatic liver tumors, 20 cases of hemangiomas, and 18 cases of cysts. CT values and standard deviations of hepatic lesions and background liver parenchyma were measured on TNC images and on VNC images reconstructed from equilibrium-phase scans. Using the measured values, the contrast-to-noise ratio (CNR) of hepatic lesions was calculated, and CT values and CNRs of the lesions were compared between true TNC and VNC images.

Results: The CT values of hepatic lesions on TNC and VNC images were 37.5±15.1 and 38.7±16.1 HU, respectively, while those of background liver parenchyma were 61.2±5.91 and 64.3±6.02 HU, respectively; all demonstrated good agreement. The correlation coefficients of CT values between TNC and VNC images were 0.898 for hepatic lesions and 0.933 for background liver parenchyma. Furthermore, when analyzed by lesion type, no significant differences were observed in CT values and CNRs (p>0.05).

Conclusion: The accuracy of VNC images for liver lesions was very high, and for typical hepatic lesions in particular, the findings suggest that TNC images may be omitted.

Purpose: This study aims to compare the effects of two types of deep learning (DL) techniques on brain CT values, image noise content, and contrast-to-noise ratio (CNR) between white and gray matter in low-noise head CT images, along with adaptive iterative dose reduction 3D (AIDR 3D).

Methods: Twenty-one normal patients with no abnormal findings who underwent head CT for identification of acute illness were included in the study. DL techniques used were Advanced intelligent Clear-IQ Engine (AiCE, Canon Medical systems, Tochigi, Japan) and PixelShine (FUJIFILM Medical, Tokyo, Japan). We performed CT value measurements of 26 cerebrum regions, image noise measurements, and CNR calculations. We also conducted a visual assessment of image noise and white matter-gray matter contrast on a 5-point scale.

Results: Image noise significantly decreased with DL techniques. CT values changed significantly with AiCE. CNR for white matter-gray matter was the highest with PixelShine (P<0.01). The visual assessment of white matter-gray matter contrast was the highest for PixelShine and the lowest for AiCE (P<0.01).

Conclusion: While DL techniques reduce image noise, there are differences in CT values and visual impression, especially white matter-gray matter contrast, so care should be taken when using it.