Nihon Hoshasen Gijutsu Gakkai zasshi最新文献

Purpose: The purpose of this study is to evaluate the detection accuracy of a high-definition optical surface imaging (OSI) system for non-coplanar radiotherapy (by rotating a phantom instead of a couch rotation).

Methods: The constancy, reproducibility, and accuracy of the positioning of the OSI system, Catalyst HD (CHD), for non-coplanar treatment were examined by rotating the head phantom around the isocenter. For all the tests, the phantom was rotated by ±30°, ±45°, ±60°, ±90° after correction of the phantom position within 0.0 mm±0.2 mm, and 0.0°±0.1° using Cone Beam CT (CBCT); the CBCT images were acquired again after rotation. We compared the phantom position derived from CHD, translational displacements of the isocenter (Dev.), and rotational displacements (Rot.) to the position derived from CBCT. The constancy of monitoring was evaluated by observing the variation in the isocenter position for 30 min. For evaluating reproducibility, the positions derived from CHD were compared with those from the planning data. The accuracy of positioning was evaluated by comparing CHD and CBCT findings after the couch rotation of ±0.5°.

Results: The constancy test revealed a maximum Rot. of 0.02±0.01° and Dev. of 0.20±0.08 mm, and the reproducibility test showed a maximum Rot. of 0.26±0.15° and Dev. of 0.93±0.26 mm. In the accuracy tests, when the phantom was further rotated by +0.5°, the maximum values were Rot. of 0.73±0.05° and Dev. of 0.35±0.15 mm; at -0.5°, the values were Rot. of -0.37±0.34° and Dev. of 0.43±0.24 mm.

Conclusion: A high-resolution OSI system is useful for position detection during treatment, even in non-coplanar irradiation.

Purpose: This study was to investigate the cases of ferromagnetic objects brought into the MRI room by using incident reports.

Methods: We included incident reports on ferromagnetic objects brought into the MRI room over the past 10 years from January 2012 to December 2021. We investigated the incidence rate of the ferromagnetic objects into the MRI room, the cause for bringing ferromagnetic objects, the number of years of MRI experience, the time of occurrence, and the names of ferromagnetic objects.

Results: There were 248 incident reports, including 26 cases related to the ferromagnetic objects. The frequency of occurrence shows that the highest number of cases occurred within the first year of experience, accounting for approximately half of the case related to MRI staff. For newcomers, there are more incidents in the second quarter than in other quarters.

Conclusion: The number of cases of bringing in ferromagnetic objects was higher in the second quarter as there was less experience with MRI.

Purpose: Cone beam computed tomography (CBCT) is the most commonly used technique for target localization in radiation therapy. Four-dimensional CBCT (4D CBCT) is valuable for localizing tumors in the lung and liver regions, where the localization accuracy is affected by respiratory motions. However, in image-guided radiation therapy for organs subject to respiratory motion, position verification is often performed using 3D cone beam CT or 2D X-ray images. While it is possible to collimate tumors at specific respiratory phases during breath-holding and to determine the tumor's motion range by taking inspiratory and expiratory breath-hold images, it remains difficult to track the tumor's trajectory at each respiratory phase. The aim of this study is to investigate the positional phases of targets that move with respiration using phantom experiments with 4D CT and 4D CBCT.

Methods: To simulate respiratory motion, we captured images of a moving phantom with a simulated tumor synchronized to simulated breathing using 4D CT and 4D CBCT. The simulated tumor was set to have respiratory cycles of 3, 4, 5, and 7.5 s, with displacements 20, 16, 10, 8, and 4 mm per breath. Under these conditions, 4D CT and 4D CBCT images were captured. Using the treatment planning system, regions of interest for the simulated tumors were set from the obtained images of each respiratory phase, identifying the tumor and setting the region as the target. Volume, positional error, and Dice coefficient of the target centroid in the corresponding phase images of 4D CT and 4D CBCT were measured with the treatment planning system.

Results: The positional error of the target centroid between 4D CT and 4D CBCT was generally within ±1 mm. The Dice coefficient for each respiratory phase under each condition of 4D CT and 4D CBCT was generally above 0.8.

Conclusion: It has been suggested that 4D CBCT has the same detection ability as 4D CT for targets with respiratory movement.

Purpose: In single-photon emission computed tomography (SPECT), the standardized uptake value requires a becquerel calibration factor (BCF). The changes over time in BCF due to different radionuclides and collimators was examined.

Methods: The BCF (cps/MBq) was monthly calculated from the radioactivity of syringe formulations and dispensed sources measured with a dose calibrator, and planar acquisition counts. In addition, relative errors with respect to the maximum BCF over 44 months were calculated.

Results: The average BCF was 46.0 for ¹²³I with a low-penetration high-resolution collimator (¹²³I-LPHR) and 124.1 for ¹³¹I with a medium-energy low-penetration collimator (¹³¹I-MELP). The standard deviation of the BCF for any radionuclides and collimators was less than 3.4 and the differences between detectors were small. Relative errors of the BCF were less than 10% for ^99mTc with a low-energy high-resolution collimator (^99mTc-LEHR), ¹²³I-MELP, ⁶⁷Ga-MELP, and ¹³¹I-MELP, and less than 5% for ¹²³I-MELP. Relative errors for ¹²³I-LEHR and ¹²³I-LPHR were initially slightly higher but decreased to less than 10% after 7 months.

Conclusion: The BCF measured by planar acquisition were stable and reproducible over time with a wide variety of nuclides and collimators.

Purpose: This study aimed to propose a mathematical model to describe motion blur in hepatobiliary-phase magnetic resonance images.

Methods: Simulated images were constructed based on the mathematical model of motion blur, and this model was then validated by comparing the simulated images with the magnetic resonance images obtained using a dynamic phantom. The mathematical model employed a convolution integral that combined the stationary-state signal distribution and the probability density distribution of the positional shifts during acquisition. The stationary signal distribution was obtained from the magnetic resonance images of a bottle phantom, and the probability density distribution was derived from sinusoidal motion mimicking respiratory movement. Both visual and quantitative evaluations were performed between the simulated images based on the mathematical model and the magnetic resonance images acquired using the dynamic phantom.

Results: The simulated and acquired magnetic resonance images exhibited similar shapes. The difference in the lengths of the respective high-intensity regions was 0.7 mm.

Conclusion: The proposed mathematical model effectively represents motion blur in magnetic resonance images.