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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

Objective. Diffusion equation (DE) imaging processing is promising to enhance images showing lesions of bone metastasis (LBM). The Perona-Malik diffusion (PMD) model, which has been widely used and studied, is an anisotropic diffusion processing method to denoise or extract objects from an image effectively. However, the smoothing characteristics of PMD or its related method hinder extraction and enhancement of soft tissue regions of medical image such as computed tomography (CT), typically leaving an indistinct region with ambient tissues. Moreover, PMD expands the border region of the objects. A novel diffusion methodology must be used to enhance the LBM region effectively. Approach. For this study, we originally developed a DE quantification (DEQ) method that uses a filter function to selectively provide modulated diffusion according to the original locations of objects in an image. The structural similarity index measure (SSIM) and Lie derivative image analysis L -value map were used to evaluate image quality and processing. Main results. We determined superellipse function with its ordern=4as a better performing filter for the LBM region. DEQ was found to be more effective at contrasting LBM for various LBM CT images than PMD or its improved models when the filter was a positive exponential similar function. DEQ yields enhancement agreeing with the indications of positron emission tomography despite complex LBM comprising osteoblastic, osteoclastic, mixed tissues, and metal artifacts, which is innovative. Moreover, DEQ retained high quality of image (SSIM> 0.95), and achieved a low mean value of the L -value (<0.001), indicative of our intended selective diffusion compared to other PMD models. Significance. Our method improved the visibility of mixed tissue lesions, which can assist computer visional framework and can help radiologists to produce accurate diagnose of LBM regions which are frequently overlooked in radiology findings because of the various degrees of visibility in CT images., (Creative Commons Attribution license.)

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.)

Only a few studies have explored whether high-dose-rate interstitial brachytherapy (HDR-ISBT) can be indicated as a palliative/symptomatic treatment. We present the good results of palliative treatment using HDR-ISBT combined with external beam radiotherapy (ERT) in a patient of base of tongue cancer (cT4aN1M0). The patient was an 81-year-old male who complained of local pain. He had a previous irradiation history for head and neck cancer receiving ERT with systemic chemotherapy and radical surgery 15 years ago. Since it might be difficult for him to receive radical radiation doses using ERT alone, palliative ERT of relatively lower doses of 37.5 Gy in 15 fractions was selected. One month after ERT, HDR-ISBT was implemented as a booster. Considering the burden on physical condition, single-fraction HDR-ISBT was selected. We employed a new technique in which we did not penetrate the ventral surface of the tongue to reduce the risk of infection and bleeding. The planning-aim dose was 9.5 Gy. The dose that covered 90% of the clinical target volume was 9.6 Gy. The treatment ended without any problems. Acute complications were not observed. The tumor size decreased, and local pain disappeared at post-treatment day 84. No late complications were observed. Two years and 8 months after the treatment, the patient is alive without any obvious recurrence. Additional single-fraction HDR-ISBT boost may be a useful modality as a palliative/symptomatic intent. The implantation technique and dose-fraction schedule may be important for the safe treatment of older patients or those with poor performance status., (© 2024. The Author(s) under exclusive licence to Japanese Society for Oral and Maxillofacial Radiology.)

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.)

Background: Delivering cancer treatment to elderly patients with dementia is often challenging. We describe performing palliative surface mold brachytherapy (SMBT) in an elderly patient with advanced dementia for pain control using music therapy to assist with agitation. Case Description: The patient was a 97-year-old Japanese woman with advanced dementia. Exudate was observed from her tumor, and she complained of Grade 2 severity pain using Support team assessment schedule (STAS), especially when undergoing would dressings. Given her advanced dementia, she was not considered a candidate for radical surgery or external beam radiotherapy. We instead treated her with high-dose-rate (HDR) SMBT. Due to her advanced dementia associated with agitation, she could not maintain her position. She was able to remain calm while listening to traditional Japanese enka music, which enables our team to complete her radiation without using anesthetics or sedating analgesics. Her localized pain severity decreased ≤21 days and the exudate fluid disappeared ≤63 days after HDR-SMBT. Her tumor was locally controlled until her death from intercurrent disease 1 year after HDR-SMBT. Discussion: Single fraction palliative HDR-SMBT was useful for successful treatment of skin cancer in an elderly patient. Traditional Japanese music helped reduce her agitation to complete HDR-SMBT. For elderly patients with agitation associated with dementia, we should consider using music and music therapy to facilitate radiation therapy.

Objective . The gamma index ( γ ) has been extensively investigated in the medical physics and applied in clinical practice. However, γ has a significant limitation when used to evaluate the dose-gradient region, leading to inconveniences, particularly in stereotactic radiotherapy (SRT). This study proposes a novel evaluation method combined with γ to extract clinically problematic dose-gradient regions caused by irradiation including certain errors. Approach . A flow-vector field in the dose distribution is obtained when the dose is considered a scalar potential. Using the Lie derivative from differential geometry, we defined L , S , and U to evaluate the intensity, vorticity, and flow amount of deviation between two dose distributions, respectively. These metrics multiplied by γ ( γL , γS , γU ), along with the threshold value σ , were verified in the ideal SRT case and in a clinical case of irradiation near the brainstem region using radiochromic films. Moreover, Moran's gradient index (MGI), Bakai's χ factor, and the structural similarity index (SSIM) were investigated for comparisons. Main results . A high L- metric value mainly extracted high-dose-gradient induced deviations, which was supported by high S and U metrics observed as a robust deviation and an influence of the dose-gradient, respectively. The S- metric also denotes the measured similarity between the compared dose distributions. In the γ distribution, γL sensitively detected the dose-gradient region in the film measurement, despite the presence of noise. The threshold σ successfully extracted the gradient-error region where γ > 1 analysis underestimated, and σ = 0.1 (plan) and σ = 0.001 (film measurement) were obtained according to the compared resolutions. However, the MGI, χ, and SSIM failed to detect the clinically interested region. Significance . Although further studies are required to clarify the error details, this study demonstrated that the Lie derivative method provided a novel perspective for the identifying gradient-induced error regions and enabled enhanced and clinically significant evaluations of γ ., (Creative Commons Attribution license.)

Purpose: Spinal bone metastases directly affect quality of life, and patients with lytic-dominant lesions are at high risk for neurological symptoms and fractures. To detect and classify lytic spinal bone metastasis using routine computed tomography (CT) scans, we developed a deep learning (DL)-based computer-aided detection (CAD) system., Methods: We retrospectively analyzed 2125 diagnostic and radiotherapeutic CT images of 79 patients. Images annotated as tumor (positive) or not (negative) were randomized into training (1782 images) and test (343 images) datasets. YOLOv5m architecture was used to detect vertebra on whole CT scans. InceptionV3 architecture with the transfer-learning technique was used to classify the presence/absence of lytic lesions on CT images showing the presence of vertebra. The DL models were evaluated via fivefold cross-validation. For vertebra detection, bounding box accuracy was estimated using intersection over union (IoU). We evaluated the area under the curve (AUC) of a receiver operating characteristic curve to classify lesions. Moreover, we determined the accuracy, precision, recall, and F1 score. We used the gradient-weighted class activation mapping (Grad-CAM) technique for visual interpretation., Results: The computation time was 0.44 s per image. The average IoU value of the predicted vertebra was 0.923 ± 0.052 (0.684-1.000) for test datasets. In the binary classification task, the accuracy, precision, recall, F1-score, and AUC value for test datasets were 0.872, 0.948, 0.741, 0.832, and 0.941, respectively. Heat maps constructed using the Grad-CAM technique were consistent with the location of lytic lesions., Conclusion: Our artificial intelligence-aided CAD system using two DL models could rapidly identify vertebra bone from whole CT images and detect lytic spinal bone metastasis, although further evaluation of diagnostic accuracy is required with a larger sample size., (© 2023. CARS.)

Purpose: Deep learning (DL) is a state-of-the-art technique for developing artificial intelligence in various domains and it improves the performance of natural language processing (NLP). Therefore, we aimed to develop a DL-based NLP model that classifies the status of bone metastasis (BM) in radiology reports to detect patients with BM., Materials and Methods: The DL-based NLP model was developed by training long short-term memory using 1,749 free-text radiology reports written in Japanese. We adopted five-fold cross-validation and used 200 reports for testing the five models. The accuracy, sensitivity, specificity, precision, and area under the receiver operating characteristics curve (AUROC) were used for the model evaluation., Results: The developed model demonstrated classification performance with mean ± standard deviation of 0.912 ± 0.012, 0.924 ± 0.029, 0.901 ± 0.014, 0.898 ± 0.012, and 0.968 ± 0.004 for accuracy, sensitivity, specificity, precision, and AUROC, respectively., Conclusion: The proposed DL-based NLP model may help in the early and efficient detection of patients with BM., (© 2023. The Author(s) under exclusive licence to Japan Radiological Society.)

Accurate clinical target volume (CTV) delineation is important for head and neck intensity-modulated radiation therapy. However, delineation is time-consuming and susceptible to interobserver variability (IOV). Based on a manual contouring process commonly used in clinical practice, we developed a deep learning (DL)-based method to delineate a low-risk CTV with computed tomography (CT) and gross tumor volume (GTV) input and compared it with a CT-only input. A total of 310 patients with oropharynx cancer were randomly divided into the training set (250) and test set (60). The low-risk CTV and primary GTV contours were used to generate label data for the input and ground truth. A 3D U-Net with a two-channel input of CT and GTV (U-Net GTV ) was proposed and its performance was compared with a U-Net with only CT input (U-Net CT ). The Dice similarity coefficient (DSC) and average Hausdorff distance (AHD) were evaluated. The time required to predict the CTV was 0.86 s per patient. U-Net GTV showed a significantly higher mean DSC value than U-Net CT (0.80 ± 0.03 and 0.76 ± 0.05) and a significantly lower mean AHD value (3.0 ± 0.5 mm vs 3.5 ± 0.7 mm). Compared to the existing DL method with only CT input, the proposed GTV-based segmentation using DL showed a more precise low-risk CTV segmentation for head and neck cancer. Our findings suggest that the proposed method could reduce the contouring time of a low-risk CTV, allowing the standardization of target delineations for head and neck cancer., (Copyright © 2022 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.)

Purpose: Deep learning (DL)-based dose distribution prediction can potentially reduce the cost of inverse planning process. We developed and introduced a structure-focused loss (L struct ) for 3D dose prediction to improve prediction accuracy. This study investigated the influence of L struct on DL-based dose prediction for patients with prostate cancer. The proposed L struct , which is similar in concept to dose-volume histogram (DVH)-based optimization in clinical practice, has the potential to provide more interpretable and accurate DL-based optimization., Methods: This study involved 104 patients who underwent prostate radiotherapy. We used 3D U-Net-based architecture to predict dose distributions from computed tomography and contours of the planning target volume and organs-at-risk. We trained two models using different loss functions: L2 loss and L struct . Predicted doses were compared in terms of dose-volume parameters and the Dice similarity coefficient of isodose volume., Results: DVH analysis showed that the L struct model had smaller errors from the ground truth than the L2 model. The L struct model achieved more consistent dose distributions than the L2 model, with errors close to zero. The isodose Dice score of the L struct model was greater than that of the L2 model by >20% of the prescribed dose., Conclusions: We developed L struct using labels of inputted contours for DL-based dose prediction for prostate radiotherapy. L struct can be generalized to any DL architecture, thereby enhancing the dose prediction accuracy., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Objective. A large optimization volume for intensity-modulated radiation therapy (IMRT), such as the remaining volume at risk (RVR), is traditionally unsuitable for dose-volume constraint control and requires planner-specific empirical considerations owing to the patient-specific shape. To enable less empirical optimization, the generalized equivalent uniform dose (gEUD) optimization is effective; however, the utilization of parameter a -values remains elusive. Our study clarifies the a -value characteristics for optimization and to enable effective a -value use. Approach. The gEUD can be obtained as a function of its a -value, which is the weighted generalized mean; its curve has a continuous, differentiable, and sigmoid shape, deforming in its optimization state with retained curve characteristics. Using differential geometry, the gEUD curve changes in optimization is considered a geodesic deviation intervened by the forces between deforming and retaining the curve. The curvature and gradient of the curve are radically related to optimization. The vertex point ( a = a k ) was set and the a -value roles were classified into the following three parts of the curve with respect to the a -value: (i) high gradient and middle curvature, (ii) middle gradient and high curvature, and (iii) low gradient and low curvature. Then, a strategy for multiple a -values was then identified using RVR optimization. Main results. Eleven head and neck patients who underwent static seven-field IMRT were used to verify the a -value characteristics and curvature effect for optimization. The lower a -value (i) ( a = 1-3) optimization was effective for the whole dose-volume range; in contrast, the effect of higher a -value (iii) ( a = 12-20) optimization addressed strongly the high-dose range of the dose volume. The middle a -value (ii) (around a = a k ) showed intermediate but effective high-to-low dose reduction. These a -value characteristics were observed as superimpositions in the optimization. Thus, multiple gEUD-based optimization was significantly superior to the exponential constraints normally applied to the RVR that surrounds the PTV, normal tissue objective (NTO), resulting in up to 25.9% and 8.1% improvement in dose-volume indices D2% and V10Gy, respectively. Significance. This study revealed an appropriate a -value for gEUD optimization, leading to favorable dose-volume optimization for the RVR region using fixed multiple a -value conditions, despite the very large and patient-specific shape of the region., (© 2023 Institute of Physics and Engineering 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.)

Purpose: To develop a deep learning-based metal artifact reduction (DL-MAR) method using unpaired data and to evaluate its dosimetric impact in head and neck intensity-modulated radiation therapy (IMRT) compared with the water density override method., Methods: The data set comprised the data of 107 patients who underwent radiotherapy. Fifteen patients with dental fillings were used as the test data set. The computed tomography (CT) images of the remaining 92 patients were divided into two domains: the metal artifact and artifact-free domains. CycleGAN was used for domain translation. The artifact index of the DL-MAR images was compared with that of the original uncorrected (UC) CT images. The dose distributions of the DL-MAR and UC plans were created by comparing the reference clinical plan with the water density override method (water plan) in each dataset. Dosimetric deviation in the oral cavity from the water plan was evaluated., Results: The artifact index of the DL-MAR images was significantly smaller than that of the UC images in all patients (13.2 ± 4.3 vs. 267.3 ± 113.7). Compared with the reference water plan, dose differences of the UC plans were greater than those of the DL-MAR plans. DL-MAR images provided dosimetric results that were more similar to those of the water plan than the UC plan., Conclusions: We developed a fast DL-MAR method using CycleGAN for head and neck IMRT. The proposed method could provide consistent dose calculation against metal artifact and improve the efficiency of the planning process by eliminating manual delineation., (Copyright © 2020 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.)

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.

Actinomycosis is a rare, chronic, slowly progressive granulomatous disease caused by filamentous gram-positive anaerobic bacteria from the Actinomycetaceae family (genus Actinomyces). It has become a rare condition because of the widespread use of antibiotics. When clinical symptoms are not typical, diagnosis of this condition becomes difficult. This report describes a case involving an 82-year-old woman who was diagnosed with actinomycotic osteomyelitis of the mandible using matrix assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS). The patient was referred to the authors' department with chief complaints of swelling, multiple fistulae in the left preauricular region, and trismus. The authors performed fine-needle aspiration microbiology (FNAM) and identified Actinomyces oris using MALDI-TOF MS. A diagnosis of actinomycotic osteomyelitis of the mandible was made and the patient was treated with minocycline and extraction of the culprit tooth. The findings from this case have 2 important implications. First, for patients with clinically suspected actinomycosis, bacteriologic examinations should include not only surface swab tests but also FNAM; moreover, communication with the laboratory medical technologist is important to improve detection of the causative organisms. Second, MALDI-TOF MS could be an effective tool for improving the diagnosis and treatment outcomes of actinomycosis., (Copyright © 2018 American Association of Oral and Maxillofacial Surgeons. All rights reserved.)

Infections occur more frequently in patients receiving biologics. However, cryptococcal infection is uncommon in patients receiving tocilizumab, an interleukin-6 inhibitor, in contrast to patients receiving tumor necrosis factor-α inhibitors. In this report, we describe a case of disseminated cryptococcosis in a 55-year-old man who was receiving tocilizumab every 2 weeks along with daily prednisolone and cyclosporine for Castleman's disease. He initially developed cellulitis on both upper limbs, and his condition worsened despite antibacterial therapy. Chest X-ray scanning and computed tomography demonstrated bilateral pulmonary infiltration. Cryptococcus neoformans was detected in blood, skin, and sputum cultures. He was diagnosed with disseminated cryptococcosis, and successfully treated with liposomal amphotericin B for a week followed by oral fluconazole for 11 months. The findings of this study indicate that cryptococcosis should be considered during the differential diagnosis of infection in patients receiving tocilizumab, especially in the presence of other risk factors for infections or a short tocilizumab dosing interval., (Copyright © 2017 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Salmonella enterica subsp. arizonae is a bacteria commonly found in the gut of reptiles. In humans, infections caused by this organism are rare. Most cases originate from southwestern United States, where rattlesnake products are often used in traditional medicine. In Asia, only a few cases have been described. This case report documents a case involving a 64-year-old woman with pyelonephritis caused by S. arizonae in Japan. She had no history of contact with reptiles or foreign travel. The likely route of transmission is unclear. She was treated with cephalosporins for 14 days and the pyelonephritis appeared to be resolved; however recurrence occurred twice -after two weeks and then after one month. Prolonged antibiotic therapy with amoxicillin resolved the infection. This case demonstrates that pyelonephritis associated with S. arizonae can be found outside of the typical geographic region and may not be associated with typical animal hosts., (Copyright © 2017 Japanese Society of Chemotherapy and The Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Purpose: To investigate the impact of setup and range uncertainties, breathing motion, and interplay effects using scanning pencil beams in robustly optimized intensity modulated proton therapy (IMPT) for stage III non-small cell lung cancer (NSCLC)., Methods and Materials: Three-field IMPT plans were created using a minimax robust optimization technique for 10 NSCLC patients. The plans accounted for 5- or 7-mm setup errors with ±3% range uncertainties. The robustness of the IMPT nominal plans was evaluated considering (1) isotropic 5-mm setup errors with ±3% range uncertainties; (2) breathing motion; (3) interplay effects; and (4) a combination of items 1 and 2. The plans were calculated using 4-dimensional and average intensity projection computed tomography images. The target coverage (TC, volume receiving 95% of prescribed dose) and homogeneity index (D2 - D98, where D2 and D98 are the least doses received by 2% and 98% of the volume) for the internal clinical target volume, and dose indexes for lung, esophagus, heart and spinal cord were compared with that of clinical volumetric modulated arc therapy plans., Results: The TC and homogeneity index for all plans were within clinical limits when considering the breathing motion and interplay effects independently. The setup and range uncertainties had a larger effect when considering their combined effect. The TC decreased to <98% (clinical threshold) in 3 of 10 patients for robust 5-mm evaluations. However, the TC remained >98% for robust 7-mm evaluations for all patients. The organ at risk dose parameters did not significantly vary between the respective robust 5-mm and robust 7-mm evaluations for the 4 error types. Compared with the volumetric modulated arc therapy plans, the IMPT plans showed better target homogeneity and mean lung and heart dose parameters reduced by about 40% and 60%, respectively., Conclusions: In robustly optimized IMPT for stage III NSCLC, the setup and range uncertainties, breathing motion, and interplay effects have limited impact on target coverage, dose homogeneity, and organ-at-risk dose parameters., (Copyright © 2016 Elsevier Inc. All rights reserved.)

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.)

Disseminated Scedosporium prolificans infection occurs mainly in immunocompromised patients. The mortality rate is high, as the fungus is resistant to most antifungal agents. Here, we present the case of a 66-year-old female with acute myeloid leukemia who developed infective endocarditis caused by S. prolificans infection during induction chemotherapy. Her 1,3-β-D-glucan levels were elevated and computed tomography revealed bilateral sinusitis and disseminated small nodular masses within the lungs and spleen; it nonetheless took 6 days to identify S. prolificans by blood culture. The patient died of multi-organ failure despite the combined use of voriconazole and terbinafine. Autopsy revealed numerous mycotic emboli within multiple organs (caused by mitral valve vegetation) and endocarditis (caused by S. prolificans). The geographic distribution of this infection is limited to Australia, the United States, and southern Europe, particularly Spain. The first Japanese case was reported in 2011, and four cases have been reported to date, including this one. Recently, the incidence of S. prolificans-disseminated infection in immunocompromised patients has increased in Japan. Therefore, clinicians should consider S. prolificans infection as a differential diagnosis when immunocompromised patients suffer disseminated infections with elevated 1,3-β-D-glucan levels.

Scedosporium prolificans (S. prolificans) is a type of mold, which rarely affects immunocompromised people. We treated a 71-year-old woman with acute myeloid leukemia (AML-M5a) with low-dose cytarabine, acralubicin, and filgrastim as the induction therapy. On day 7 after the initiation of chemotherapy, she became febrile and agranulocytic, and developed anal pain ; therefore, we discontinued the chemotherapy on day 8. Broad-spectrum antibiotics, micafungin, and then liposomal amphotericin B were ineffective. The serum concentration of β-D-glucan was 525 pg/mL. She died of multiple organ failure on day 17. S. prolificans was detected from the blood culture on day 13. Physicians should consider Scedosporium spp. infection when principal antifungal agents are ineffective and fungal infection is strongly suspected.

The kenkiporter II (KP II) transport system is commonly used in many hospitals in Japan for transporting bacterial specimens to microbiology laboratories. Recently, the BBL Port-A-Cul (PAC) fluid vial became available. However, no reports thus far have compared the effectiveness of these two transport systems. We chose 4 aerobic and facultative anaerobic bacteria as well as 8 anaerobic organisms, and prepared three strains of each bacterium in culture media for placement into PAC and KP II containers. We compared the effectiveness of each transport system for preserving each organism at 6, 24, and 48 h after inoculation at room temperature. Thirty-six strains out of 12 bacteria were used in this study. The PAC system yielded better recovery in quantity of organisms than the KP II system at 6, 24 and 48 h. More strains were significantly recovered with the PAC system than with the KP II at 24 h (36/36 vs. 23/36, P < 0.001) and 48 h (30/36 vs. 12/36, P < 0.001). The PAC system was better in the recovery of viable organisms counted at 24 and 48 h after inoculation compared with the KP II system. The PAC system may be recommended for the transfer of bacterial specimens in clinical settings., (Copyright © 2013 Japanese Society of Chemotherapy and the Japanese Association for Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Four-dimensional radiation therapy (4DRT) and adaptive radiation therapy (ART) are treatments to account for respiratory motion and anatomical changes during a course of treatment, respectively. Recent development of both imaging and delivery techniques made these radiation therapy possible. In these planning, dose distributions are calculated with multiple image sets for example each respiratory phase constituting 4-dimensional computed tomography and cone-beam computed tomography acquired on each treatment day. To evaluate overall dose distributions, we need to accumulate dose distributions calculated with multiple image sets. However, pixel-wise dose accumulation is impossible because it does not accumulate dose based on anatomy if image sets are different. Deformable image registration (DIR) is used to find corresponding anatomical points between image sets. Thus, dose accumulation based on DIR is a promising technology to enable us to evaluate overall dose distributions of 4DRT and ART. In this article, I will briefly introduce dose accumulation based on DIR and its application to 4DRT and ART.