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Asako Doi,1,2 Kentaro Iwata,3 Hiroshi Takegawa,4 Kanji Miki,5 Yumi Sono,1,2 Hiroaki Nishioka,2 Jumpei Takeshita,6 Keisuke Tomii,7 Tsunekazu Haruta11Department of Infectious Diseases, 2Department of General Internal Medicine, Kobe City Medical Center General Hospital, 3Division of Infectious Diseases, Kobe University Hospital, Japan; 4Department of Laboratory Medicine, Kobe City Medical Center General Hospital, Japan; 5Hyogo Health Service Association, Hyogo, 6Foundation of Biochemical Research and Innovation, Osaka, 7Department of Pulmonary Medicine, Kobe City Medical Center General Hospital, Hyogo, JapanAbstract: A 73-year-old man with no significant past medical history or any history of health care visits was hospitalized for pneumonia. Sputum culture revealed multidrug-resistant Streptococcus pneumoniae, even to carbapenems. The patient was later treated successfully with levofloxacin. Throat cultures from his two grandchildren revealed S. pneumoniae with the same susceptibility pattern. Analysis for resistant genes revealed gPRSP (pbp1a + pbp2x + pbp2b gene variants) in both the patient and his grandchildren, none of whom had received pneumococcal vaccines of any kind. This case illustrates the importance of the emergence of carbapenem-resistant S. pneumoniae. Non-rational use of carbapenems for community-acquired infections may be counterproductive. This case also highlights the importance of pneumococcal vaccinations in children and the elderly.Keywords: carbapenem resistance, Streptococcus pneumoniae, pneumonia

Cone-beam computed tomography (CBCT) is widely utilized in image-guided radiation therapy; however, its image quality is poor compared to planning CT (pCT), thus restricting its utility for adaptive radiotherapy (ART). Our objective was to enhance CBCT image quality utilizing a transformer-based deep learning model, SwinUNETR, which we compared with a conventional convolutional neural network (CNN) model, U-net. This retrospective study involved 260 patients undergoing prostate radiotherapy, with 245 patients used for training and 15 patients reserved as an independent hold-out test dataset. Employing a CycleGAN framework, we generated synthetic CT (sCT) images from CBCT images, employing SwinUNETR and U-net as generators. We evaluated sCT image quality and assessed its dosimetric impact for photon therapy through gamma analysis and dose-volume histogram (DVH) comparisons. The mean absolute error values for the CT numbers, calculated using all voxels within the patient's body contour and taking the pCT images as a reference, were 84.07, 73.49, and 64.69 Hounsfield units for CBCT, U-net, and SwinUNETR images, respectively. Gamma analysis revealed superior agreement between the dose on the pCT images and on the SwinUNETR-based sCT plans compared to those based on U-net. DVH parameters calculated on the SwinUNETR-based sCT deviated by < 1% from those in pCT plans. Our study showed that, compared to the U-net model, SwinUNETR could proficiently generate more precise sCT images from CBCT images, facilitating more accurate dose calculations. This study demonstrates the superiority of transformer-based models over conventional CNN-based approaches for CBCT-to-CT translation, contributing to the advancement of image synthesis techniques in ART., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

While dual-energy computed tomography (DECT) technology introduces energy-specific information in clinical practice, single-energy CT (SECT) is predominantly used, limiting the number of people who can benefit from DECT. This study proposed a novel method to generate synthetic low-energy virtual monochromatic images at 50 keV (sVMI 50keV ) from SECT images using a transformer-based deep learning model, SwinUNETR. Data were obtained from 85 patients who underwent head and neck radiotherapy. Among these, the model was built using data from 70 patients for whom only DECT images were available. The remaining 15 patients, for whom both DECT and SECT images were available, were used to predict from the actual SECT images. We used the SwinUNETR model to generate sVMI 50keV . The image quality was evaluated, and the results were compared with those of the convolutional neural network-based model, Unet. The mean absolute errors from the true VMI 50keV were 36.5 ± 4.9 and 33.0 ± 4.4 Hounsfield units for Unet and SwinUNETR, respectively. SwinUNETR yielded smaller errors in tissue attenuation values compared with those of Unet. The contrast changes in sVMI 50keV generated by SwinUNETR from SECT were closer to those of DECT-derived VMI 50keV than the contrast changes in Unet-generated sVMI 50keV . This study demonstrated the potential of transformer-based models for generating synthetic low-energy VMIs from SECT images, thereby improving the image quality of head and neck cancer imaging. It provides a practical and feasible solution to obtain low-energy VMIs from SECT data that can benefit a large number of facilities and patients without access to DECT technology., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Purpose: The purpose of this study was to evaluate the effect of a lead block for alveolar bone protection in image-guided high-dose-rate interstitial brachytherapy for tongue cancer., Material and Methods: We treated 6 patients and delivered 5,400 cGy in 9 fractions using a lead block. Effects of lead block (median thickness, 4 mm) on dose attenuation by distance were visually examined using TG-43 formalism-based dose distribution curves to determine whether or not the area with the highest dose is located in the alveolar bone, where there is a high-risk of infection. Dose re-calculations were performed using TG-186 formalism with advanced collapsed cone engine (ACE) for inhomogeneity correction set to cortical bone density for the whole mandible and alveolar bone, water density for clinical target volume (CTV), air density for outside body and lead density, and silastic density for lead block and its' silicon replica, respectively., Results: The highest dose was detected outside the alveolar bone in five of the six cases. For dose-volume histogram analysis, median minimum doses delivered per fraction to the 0.1 cm 3 of alveolar bone (D0.1cm 3 TG-43, ACE-silicon, and ACE-lead ) were 344.3 (range, 262.9-427.4) cGy, 336.6 (253.3-425.0) cGy, and 169.7 (114.9-233.3) cGy, respectively. D0.1cm 3 ACE-lead was significantly lower than other parameters. No significant difference was observed between CTV-related parameters., Conclusions: The results suggested that using a lead block for alveolar bone protection with a thickness of about 4 mm, can shift the highest dose area to non-alveolar regions. In addition, it reduced D0.1cm 3 of alveolar bone to about half, without affecting tumor dose., Competing Interests: Ken Yoshida has received an honorarium from Chiyoda Technol Corporation. The other authors report no conflict of interest., (Copyright © 2022 Termedia.)

Whole dose distribution results from well-conceived treatment plans including patient-specific (location, size and shape of tumor, etc.) and facility-specific (clinical policy and goal, equipment, etc.) information. To evaluate the whole dose distribution efficiently and effectively, we propose a method to apply spherical projection and real spherical harmonics (SH) expansion, thus leading to the expanded coefficients as a rank-2 tensor, SH coefficient tensor, for every patient-specific dose distribution. To verify the feature of this tensor, we introduce Isomap from the manifold learning method and multi-dimensional scaling (MDS). Subsequently, we obtained the MDS distance representing similarity, η, and the SH score, ζ, which is a Frobenius norm of the SH coefficient tensor. These were then validated in the intensity-modulated radiation therapy (IMRT) data sets of: (i) 375 mixing treated regions, (ii) 135 head and neck (HN), and (iii) 132 prostate cases, respectively. The MDS map indicated that the SH coefficient tensor enabled a quantitative feature extraction of whole dose distributions. In particular, the SH score systematically detected irregular cases as the deviation higher than +1.5 standard deviations (SD) from the average case, which matched up with clinically irregular case that required very complicated dose distributions. In summary, the proposed SH coefficient tensor is a useful representation of the whole dose distribution. The SH score from the SH coefficient tensor is a convenient and simple criterion used to characterize the entire dose distributions, which is not dependent on the data set., (© The Author(s) 2021. Published by Oxford University Press on behalf of The Japanese Radiation Research Society and Japanese Society for Radiation Oncology.)

Background/aim: The Purpose of this study was to develop a Monte Carlo (MC) model for the Agility multileaf collimator (MLC) mounted and to validate its accuracy., Materials and Methods: To describe the Agility MLC in the BEAMnrc MC code, an existing component module code was modified to include its characteristics. The leaf characterization of the MC model was validated by comparing the calculated interleaf transmission and tongue-and-groove effect with EBT2 film and diode measurements and IMRT and VMAT calculations with film measurements., Results: Agreement between mean calculated and measured leaf transmissions was within 0.1%. The discrepancy between MC calculation and measurement in a static irregular field was less than 2%/2 mm. Gamma analysis of the comparison of MC and EBT2 film measurements in IMRT and VMAT fields yielded pass rates of 99.1% and 99.5% with 3%/3 mm criteria, respectively., Conclusion: Our findings demonstrate the accuracy of the MC model using an adapted BEAMnrc component module for the Agility MLC., (Copyright© 2020, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Background: Non-tuberculous mycobacteria cause chronic pulmonary infection, but pleuritis and pleural effusion are rarely associated with infection with non-tuberculous mycobacteria, especially rapid-growing mycobacteria., Case Presentation: A 68-year-old woman with rheumatoid arthritis who was using prednisone, azathioprine, and certolizumab pegol presented complaining of fever, dry cough, and night sweats for the past 2 weeks. Chest examination revealed bilateral opacity that was more pronounced on her right side. Bronchoalveolar lavage fluid and pleural effusion fluid were obtained, and revealed coinfection with Mycobacterium fortuitum and Mycobacterium mageritense. Imipenem/cilastatin, levofloxacin, and minocycline were prescribed for 6 months, and the patient was well and asymptomatic for the subsequent 6 months., Conclusions: This is the first case report describing pleural effusion associated with coinfection with two different mycobacterial species. If the species cannot be identified, the possibility of mycobacterial coinfection should be considered.

Helicobacter cinaedi causes bacteremia, cellulitis, and gastroenteritis. We report the first case of vertebral osteomyelitis caused by H. cinaedi in an elderly man with low back pain and fever. The pathogen was detected in blood and lumbar disc, and the infection was successfully treated with oral doxycycline for 11 weeks., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Changes in the genetic structure of the Katsunuma natural population of Drosophila melanogaster have been examined during the past 35 years. The frequency of recessive lethal genes on the second chromosome once increased from 15% to 30% in the early 1970s, then decreased to about 24% in the late 1970s, and thereafter showed no significant changes. Sterility genes, the frequency of which is always less than the lethals, showed a similar tendency. The SD (segregation distorter) mutant gene disappeared but some others such as rbl (reduced bristle) and bw (brown) persisted in the population. The frequency of inversion-carrying chromosomes gradually decreased in the period, such that the standard chromosome frequency in the second and third chromosomes increased from about 40% to more than 80%. Coincident with these frequency changes is the invasion of a transposable element P into the Katsunuma population. The P element should have invaded into Katsunuma in the late 1960s. It spread over the population apparently inducing deleterious mutations, causing the decrease in the allelism rate, and hence increasing the effective population size. Soon, however, most flies became resistant to the P element-mediated transposition as they began to harbor defective P elements. During the course of spreading, the P element must also have induced deleterious mutations on the polymorphic inversions, breaking up the heterotic gene complexes along the chromosomes, which probably caused the reduction in the frequency of inversion chromosomes. Temporal invasion of D. simulans, a sibling species of D. melanogaster, into Katsunuma occurred several times after 1978, and the species seems to have been settled since 1990. This, however, did not have any effect on the genetic structure of D. melanogaster population.