Japanese Journal of Radiological Technology
Online ISSN : 1881-4883
Print ISSN : 0369-4305
ISSN-L : 0369-4305
Volume 77, Issue 1
Displaying 1-16 of 16 articles from this issue
Opening Article
New Year's Round Table Discussion
  • Mami Nishikawa, Kaori Tominaga, Tokitaka Ueno, Shiori Yasukawa, Kana H ...
    2021 Volume 77 Issue 1 Pages 14-22
    Published: 2021
    Released on J-STAGE: January 20, 2021

    Purpose: Digital breast tomosynthesis (DBT) imaging uses two types of image reconstruction. methods, i.e., filtered back projection (FBP) method and an iterative reconstruction (IR) method. Although the effect of the difference in the image reconstruction method on the image quality has been reported, these studies were performed using different apparatus or conditions. In this study, we examined the effect of image reconstruction on the image quality using the same equipment under the same conditions. Method: We measured reflection artifact, sharpness, signal detection ability, and granularity using DBT-photographed images by both the FBP and the IR methods. Result: Although the difference between the two methods was subtle for granularity, IR was found to be superior to FBP in all items tested. Conclusion: This study suggested the clinical usefulness of IR over FBP.

    Download PDF (1340K)
Clinical Technologies
  • Takaaki Ito, Mikoto Tamura, Hajime Monzen, Kenji Matsumoto, Kiyoshi Na ...
    2021 Volume 77 Issue 1 Pages 23-31
    Published: 2021
    Released on J-STAGE: January 20, 2021

    Purpose: Knowledge-based planning (KBP) has disadvantages of high monitor unit (MU) and complex multi-leaf collimator (MLC) motion. We investigated the optimal aperture shape controller (ASC) level for the KBP to reduce these factors in volumetric modulated arc therapy (VMAT) for prostate cancer. Methods: The KBP model was created based on 51 clinical plans (CPs) of patients who underwent the VMAT for prostate cancer. Another 10 CPs were selected randomly, and the KBPs with/without ASC, changed stepwise from very low (KBP-VL) to very high (KBP-VH), were performed with a single auto-optimization. The parameters of dose-volume histograms (DVHs) and MLC performance metrics were evaluated. We obtained the modulation complexity score for VMAT (MCSv), closed leaf score (CLS), small aperture score (SAS), leaf travel (LT), and total MU. Results: The ASC did not affect the DVH parameters negatively. The following comparisons of MLC performance were obtained (KBP vs. KBP-VL vs. KBP-VH, respectively): 0.25 vs. 0.27 vs. 0.30 (MCSv), 0.19 vs. 0.18 vs. 0.16 (CLS), 0.50 vs. 0.45 vs. 0.40 (SAS10 mm), 0.73 vs. 0.68 vs. 0.63 (SAS20 mm), 768.35 mm vs. 671.50 mm vs. 551.32 mm (LT), and 672.87 vs. 642.36 vs. 607.59 (MU). There were significant differences between KBP and KBP-VH for MCSv and LT (p<0.05). Conclusions: The KBP using an ASC set to the very high level could reduce the complexity of MLC motion significantly more without deterioration of the DVH parameters compared with the KBP in VMAT for prostate cancer.

    Download PDF (753K)
  • Kei Wagatsuma, Kenta Miwa, Muneyuki Sakata, Kenji Ishibashi, Kenji Ish ...
    2021 Volume 77 Issue 1 Pages 32-40
    Published: 2021
    Released on J-STAGE: January 20, 2021

    Background: 18F-florbetapir is an amyloid β (Aβ) -targeted 18F-labeled positron emission tomography (PET) tracer for the clinical diagnosis of Alzheimer's disease. The standardized uptake value ratio (SUVR) serves as a tool with which to differentially diagnose. The present study aimed to cross-validate and compare SUVR derived from Amygo neuro and MIMneuro software. Methods: We injected 40 individuals with 18F-florbetapir and then acquired PET images from 50 to 60 minutes later. All images were separately normalized to the standard 18F-florbetapir PET template using Amygo neuro and MIMneuro. Volumes of interest (VOIs) were automatically placed on six target regions each in Amygo neuro and MIMneuro. The composite SUVR (cSUVR) and regional SUVR (rSUVR) were calculated from mean values measured in VOI. A cSUVR of>1.10 was defined as representing Aβ positivity. Correlation coefficients were calculated in the two types of software. Results: A cSUVR>1.10 was determined by Amygo neuro and MIMneuro in 15 of the 40 individuals. The rSUVR in the posterior cingulate, parietal lobe, precuneus, and temporal lobe significantly differed between Amygo neuro and MIMneuro, whereas the cSUVR did not. The SUVR calculated by the two types of software closely correlated to each other (R=0.89-0.96, P<0.05). Conclusions: The cSUVR was not different between Amygo neuro and MIMneuro. We suggest that Amygo neuro is comparable to MIMneuro in quantitative analysis using SUVR for 18F-florbetapir imaging, thus facilitating the use of standardized quantitative approaches to amyloid PET imaging.

    Download PDF (1186K)
  • Koichi Okuda, Hiroki Nosaka, Toshimune Ito, Norikazu Matsutomo, Hajime ...
    2021 Volume 77 Issue 1 Pages 41-47
    Published: 2021
    Released on J-STAGE: January 20, 2021

    Validation study of simulation codes was performed based on the measurement of a sphere phantom and the National Electrical Manufacturers Association (NEMA) body phantoms. SIMIND and Prominence Processor were used for the simulation. Both source and density maps were generated using the characteristics of 99mTc energy. A full width at half maximum (FWHM) of the sphere phantom was measured and simulated. Simulated recovery coefficient and the background count coefficient of variation were also compared with the measured values in the body phantom study. When the two simulation codes were compared with actual measurements, maximum relative errors of FWHM values were 3.6% for Prominence Processor and -10.0% for SIMIND. The maximum relative errors of relative recovery coefficients exhibited 11.8% for Prominence Processor and -2.0% for SIMIND in the body phantom study. The coefficients of variation of the SPECT count in the background were significantly different among the measurement and two simulation codes. The simulated FWHM values and recovery coefficients paralleled measured results. However, the noise characteristic differed among actual measurements and two simulation codes in the background count statistics.

    Download PDF (938K)
Educational Lecture-Future Radiographic Imaging Technique-
Educational Lecture-Patient Safety-
Educational Lecture-Radiation Therapy Technology for Beginners-
Educational Lecture-Basics and Advances in CT Technology-
Educational Lecture-Phantom Study for the Radiological Technology-
Contribution: Special Feature on COVID-19
The 14th JART-JSRT Joint Public Lecture
JIRA Topics