Publications by authors named "Sato J"

Background This study aimed to identify factors affecting the length of hospital stay (LOS) after total knee arthroplasty (TKA) in patients classified as American Society of Anesthesiologists (ASA) physical status I or II, with a focus on patient-dependent determination of discharge. The goal was to explore strategies to shorten LOS. Methods A retrospective cohort study was conducted on 398 patients (494 knees) who underwent primary TKA.

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Missed critical imaging findings, particularly those indicating cancer, are a common issue that can result in delays in patient follow-up and treatment. To address this, we developed a rule-based natural language processing (NLP) algorithm to detect cancer-suspicious findings from Japanese radiology reports. The dataset used consisted of chest and abdomen CT reports from six institutions.

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CBA-1205 is a novel humanized antibody targeting delta-like 1 homolog (DLK1) that enhances antibody-dependent cellular cytotoxicity activity. DLK1 overexpression has been reported in various cancer types, such as hepatocellular carcinoma and neuroblastoma. CBA-1205 demonstrates potent antitumor activity in multiple tumor models, making it a potential treatment option for DLK1-expressing cancers.

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Alcohol use disorder (AUD) is a multifactorial disease closely related to neurodevelopment and environmental factors that influence behavior. This study explored the relationships between brain volume and behavior from an Exploratory Structural Equation Modeling (ESEM) based on the Research Domain Criteria. High-resolution magnetic resonance imaging scans were acquired from recent patients with AUD (n = 50) and healthy controls (HC=50).

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Objective: This study aimed to introduce and evaluate a novel software-based system, BioTrace, designed for real-time monitoring of thermal ablation tissue damage during image-guided radiofrequency ablation for hepatocellular carcinoma (HCC).

Methods: BioTrace utilizes a proprietary algorithm to analyze the temporo-spatial behavior of thermal gas bubble activity during ablation, as seen in conventional B-mode ultrasound imaging. Its predictive accuracy was assessed by comparing the ablation zones it predicted with those annotated by radiologists using contrast-enhanced computed tomography (CECT) 24 hours post-treatment, considered the gold standard.

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Background: Lowering barometric pressure (LP) can exacerbate neuropathic pain. However, animal studies in this field are limited to a few conditions. Furthermore, although sympathetic involvement has been reported as a possible mechanism, whether the sympathetic nervous system is involved in the hypothalamic-pituitary-adrenal (HPA) axis remains unknown.

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Background: Opioids are known to induce delirium, and the incidence of delirium induced by individual opioids has been investigated. However, only a limited number of studies have examined the incidence of delirium induced by oral hydromorphone.

Objective: To investigate whether differences exist in the incidence of delirium associated with oral morphine and oral hydromorphone during the initiation phase of treatment.

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We describe a rare case of spontaneous remission of Pneumocystis jirovecii pneumonia (PCP) in a 42-year-old patient with human immunodeficiency virus (HIV) infection, followed by severe pulmonary nocardiosis. To our knowledge, this is the first report of spontaneous remission of PCP in a completely untreated patient with HIV infection. The patient, a bisexual Japanese man, presented with fever and anorexia and had a history of non-compliance with antiretroviral therapy (ART) for 13 years.

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Purpose: Systems equipped with natural language (NLP) processing can reduce missed radiological findings by physicians, but the annotation costs are burden in the development. This study aimed to compare the effects of active learning (AL) algorithms in NLP for estimating the significance of head computed tomography (CT) reports using bidirectional encoder representations from transformers (BERT).

Methods: A total of 3728 head CT reports annotated with five categories of importance were used and UTH-BERT was adopted as the pre-trained BERT model.

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Article Synopsis
  • Self-supervised learning (SSL) is increasingly being used in medical imaging, particularly through methods like the Jigsaw puzzle task, which helps models learn features and relationships within images without needing labeled data.
  • The study evaluated different pre-training methods on mammographic images from the Chinese Mammography Database, comparing the effectiveness of models that used Jigsaw puzzles, ImageNet tasks, or no pre-training at all in detecting breast cancer.
  • Results showed that models utilizing the Jigsaw puzzle task achieved the highest area under the curve (AUC) scores, indicating its potential to improve classification accuracy even with limited data.
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Introduction: We aimed to determine the impact of prior antimicrobial treatment on recurrent Clostridioides difficile infection (CDI) based on days of antibiotic spectrum coverage (DASC) and predict the risk of recurrence to guide the selection of appropriate initial therapeutic agents.

Methods: We assessed the antimicrobial treatment administered to 195 patients with a history of CDI for 28 days before testing positive for C. difficile using DASC and illness severity using ATLAS scores.

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Background: Doxorubicin-induced cardiotoxicity is still an important medical problem associated with a high mortality rate in cancer survivors. p53 plays a key role in doxorubicin-induced cardiotoxicity. Diacylglycerol kinase ζ (Dgkζ), a 130-kDa enzyme abundant in cardiomyocytes, regulates the p53 protein expression level in neurons.

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Background: The sensitivity of reverse-transcription polymerase chain reaction (RT-PCR) is limited for diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Chest computed tomography (CT) is reported to have high sensitivity; however, given the limited availability of chest CT during a pandemic, the assessment of more readily available imaging, such as chest radiographs, augmented by artificial intelligence may substitute for the detection of the features of coronavirus disease 2019 (COVID-19) pneumonia.

Methods: We trained a deep convolutional neural network to detect SARS-CoV-2 pneumonia using publicly available chest radiography imaging data including 8,851 normal, 6,045 pneumonia, and 200 COVID-19 pneumonia radiographs.

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Background: Continuous subcutaneous administration of injectable opioids is simple and effective; however, skin disorders may occur when high opioid dosages are used. Therefore, we investigated opioid injection drugs with a low risk of skin disorders.

Methods: A retrospective study was conducted using the electronic medical records of patients prescribed 1% hydromorphone hydrochloride or 4% morphine hydrochloride with instructions for continuous subcutaneous administration at Shizuoka Cancer Center from January 2017 to December 2021.

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Background: Acute pancreatitis (AP) severity is correlated with systemic infection incidence in the acute phase, and it is important to assess inflammation during the disease course and to recognize infection at an early stage. As in sepsis, inflammation in AP impairs tissue oxygen metabolism and disrupts microcirculation. We performed a vascular occlusion test (VOT) via near-infrared spectroscopy (NIRS), which noninvasively monitors local oxygen in peripheral tissues, to evaluate tissue oxygen metabolism and blood circulation during the acute AP phase.

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Background: Endoscopic resection (ER) of non-ampullary duodenal epithelial tumors (NADETs) is associated with a high incidence of delayed bleeding (DB). While previous reports have identified composite risk factors for delayed adverse events, including both DB and delayed perforation, the specific factors associated with DB remain unclear. This study aimed to identify factors associated with DB after ER of NADETs.

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Background: In a global phase I/II study (GO29781; NCT02500407), single-agent mosunetuzumab had a manageable safety profile and induced durable complete responses in patients with relapsed/refractory (R/R) B-cell non-Hodgkin lymphoma, including in patients with R/R follicular lymphoma (FL). In this analysis, the efficacy and safety of mosunetuzumab monotherapy were evaluated in an expansion cohort, FLMOON-1, in Japanese patients with R/R FL who had received  ≥ 2 prior lines of therapy in a phase I study (JO40295, jRCT2080223801).

Methods: Mosunetuzumab was administered intravenously at the recommended phase II dose (with cycle 1 step-up dosing) for eight cycles or up to 17 cycles, or until disease progression or unacceptable toxicity.

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Background/objectives: The detection of pancreatic cancer (PC) often depends on indirect indicators such as parenchyma atrophy (PPA), main pancreatic duct stenosis, and low echoic areas, particularly when no mass is evident on imaging. While pathological evaluation is the gold standard for differentiating malignant from benign conditions, endoscopic ultrasound-guided fine-needle aspiration/biopsy is not always feasible in such cases. Serial pancreatic juice aspiration cytologic examination (SPACE) via endoscopic nasopancreatic drainage (NPD) has emerged as an alternative diagnostic method, though its accuracy remains underevaluated.

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Background: This study was designed to compare the 1-year outcome among the groups with different low-dosage triamcinolone acetonide (TA) injections for trigger finger.

Methods: In the study period, trigger digits were initially injected with 2, 4, or 8 mg TA. We checked whether they had a second injection or surgery during the following year by either patients' revisit or telephone interview.

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Article Synopsis
  • AI systems can assist radiologists by detecting abnormalities in abdominal CT scans, but they often lack sufficient expert-annotated datasets for training.
  • This study developed a deep-learning pipeline that utilizes free-text radiology reports to identify abnormalities in various abdominal organs, using data from multiple institutions for training and testing.
  • The model achieved an AUC of 0.886 for detecting organ abnormalities during external validation, showing that it performed better with large datasets utilizing automatically extracted labels compared to those with manual annotations.
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Purpose: To compare the variability of quantitative values from lung adenocarcinoma CT images independently assessed by 2 radiologists and AI-based software under different display conditions, and to identify predictors of pathological lymph node metastasis (LNM), disease-free survival (DFS), and overall survival (OS).

Methods: Preoperative CT images of 307 patients were displayed under 4 conditions: lung-1, lung-2, mediastinum-1, and mediastinum-2. Two radiologists (R1, R2) measured total diameter (tD) and the longest solid diameter (sD) under each condition.

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Purpose: In radiology, large language models (LLMs), including ChatGPT, have recently gained attention, and their utility is being rapidly evaluated. However, concerns have emerged regarding their reliability in clinical applications due to limitations such as hallucinations and insufficient referencing. To address these issues, we focus on the latest technology, retrieval-augmented generation (RAG), which enables LLMs to reference reliable external knowledge (REK).

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Article Synopsis
  • Poultry red mites (PRMs), tropical fowl mites (TFMs), and northern fowl mites (NFMs) are blood-feeding pests that seriously affect poultry welfare and production worldwide.
  • The study focuses on histamine release factor (HRF), a promising vaccine antigen, and its effectiveness across different types of avian mites.
  • Researchers found that antibodies against HRFs from TFMs, NFMs, and PRMs showed cross-reactivity, leading to higher mortality in PRM nymphs when exposed to immune plasma, indicating potential for a universal vaccine against these mites.
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The global prevalence of oral squamous cell carcinoma (OSCC) has been increasing. OSCC at the advanced stage tends to resist conventional treatment and causes local recurrence and distant metastasis, resulting in poor prognosis. Therefore, detecting this cancer at an early stage and performing early intervention are important.

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