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更新于：2026-04-26
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更新于：2026-04-26
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NCT07467980
Anastomotic Site Mucosal Oxygen Tension and Its Association With Anastomotic Complications
NCT07471750
Acquisition and Clinical Image Evaluation of Fujifilm High Resolution (HR) Digital Breast Tomosynthesis (DBT) Images
NCT06867731
Endosonographic Shear Wave Elastography to Assess Liver Fibrosis
100 项与 FUJIFILM Holdings Corp. 相关的临床结果
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2026-05-01EJSO
Artificial intelligence for accurate tumor size assessment and non-invasive adenocarcinoma prediction in small-sized lung cancer
Article
作者: Nakamura, Taiyo ; Ikeda, Norihiko ; Kudo, Yujin ; Ichinose, Akimichi ; Matsubayashi, Jun ; Kakihana, Masatoshi ; Masumoto, Jun ; Hagiwara, Masaru ; Ohira, Tatsuo ; Nagao, Toshitaka ; Park, Jinho ; Shimada, Yoshihisa
INTRODUCTION:
Accurate preoperative imaging is essential for improving the treatment of small lung cancers. Precise identification of non-invasive adenocarcinomas is critical for determining the suitability of sublobar resection. Conventional methodologies frequently demonstrate variability, particularly for small tumors or ground-glass nodules (GGNs). Artificial intelligence (AI) offers a consistent and objective alternative, enhancing non-invasive cancer diagnosis and facilitating more effective treatment decisions.
MATERIALS AND METHODS:
A retrospective analysis was conducted on 324 patients who underwent surgical resection for small-sized lung adenocarcinomas at Tokyo Medical University. The Synapse Vincent system (Fujifilm Corporation, Japan) was employed to measure tumor size and classify the nodules as GGN (AI-GGN) or non-GGN (non-AI-GGN) based on confidence scores. The ability of AI to predict pathological non-invasive adenocarcinomas was evaluated.
RESULTS:
AI-measured tumor sizes were significantly more accurate than those measured by thoracic surgeons (p < 0.001) AI-GGN demonstrated a high specificity of 98.3% for predicting pathological non-invasive adenocarcinoma, closely aligned with the 98.3% specificity of the traditional consolidation tumor ratio (CTR) method. The positive predictive values of AI-GGN and CTR were similarly high, (98.5% and 98.2%, respectively), confirming the effectiveness of both methods in identifying non-invasive adenocarcinomas.
CONCLUSION:
AI technology significantly enhances the precision of tumor size measurement and identification of non-invasive adenocarcinomas in small-sized lung tumors. By providing objective and automated evaluations, AI can refine surgical planning and decision-making. Further prospective multicenter studies are warranted to validate these findings and to fully integrate AI into clinical practice, ultimately improving patient outcomes.
2026-03-02TOXICOLOGICAL SCIENCES
Short-term electrical stimulation promotes partial functional and morphological maturation of human-induced pluripotent stem cell-derived cardiomyocytes enabling cardiotoxicity risk mitigation at early-stage drug discovery for cardiac contractility modulation
Article
作者: Hori, Ritsuko ; Miyoshi, Hayato ; Kamei, Ayako ; Watanabe, Eriko ; Yamazaki, Rika ; Mochizuki, Nobuyuki ; Kazusa, Katsuyuki ; Morimura, Kaoru ; Hara, Reiko
Abstract:
In drug discovery, assessing cardiac contractile force is crucial because of its association with the development of cardiovascular events and heart failure. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a promising in vitro model for drug discovery, particularly for assessing proarrhythmic risk. However, the availability of robust in vitro models to evaluate cardiac contractility has been limited. Here, we demonstrate that subjecting hiPSC-CMs to electrical stimulation for 48 h using a multielectrode array system induces partial functional and morphological maturation, as evidenced by a positive force–frequency relationship, increased conduction velocity of depolarization signals and improved sarcomere orientation with distinct Z-bands compared to unstimulated controls. We confirmed that electrical stimulation enables the evaluation of the positive inotropic effects of drug compounds with diverse pharmacological actions. The functional maturation induced by the electrical stimulation was observed across different facilities. The method also effectively detected prolonged QT intervals. These findings demonstrate the utility of the electrical stimulation for 48 h for hiPSC-CMs using the multielectrode array assay system to assess drug-induced contractile function and detect prolonged QT intervals in a single experiment, thereby enhancing the early-stage assessment of cardiotoxicity in drug discovery.
2026-03-01ULTRASONICS
Optimized Apodizations with Training Simulations (OATS): Learned depth-dependent apodizations via differentiable beamforming for reduced operator tuning
Article
作者: Nahas, Hassan ; Yu, Alfred C H ; Xiao, Di ; Kishimoto, Aya ; Hiroshima, Misaki
Ultrasound is a point-of-care imaging modality that allows for real-time operation. While real-time capabilities are advantageous, one potential concern is the operator dependency of the modality as settings selected by the operator can alter the image appearance. Improvement of the B-mode image to necessitate fewer adjustments can reduce the operator dependency. Here, we propose a supervised learning framework (Optimal Apodizations with Training Simulations - OATS) to devise new apodization weights for image quality improvement. Our framework relies on the use of a differentiable beamformer to iteratively optimize apodization weights by comparing differences between simulated ground truth images and the corresponding post-beamformed images (simulated training set of over 200 images). We experimentally verified that these apodization weights resulted in higher quality B-mode images on both simulated and real-world data for focused and unfocused imaging scenarios. In the focused imaging scenario, the OATS-apodized images demonstrated reduced sidelobe artifact, improved lateral resolution (11 %), and improved signal equalization across depth when compared to a conventional Hanning apodization. In the unfocused imaging scenario, we observed reduced sidelobe artifacts and improved tissue-to-lesion contrast by up to 13 dB when compared against fixed F-number beamforming. Additionally, the OATS apodization weights were physically interpretable and learned to emulate image formation parameters such as time-gain compensation, F-number limited aperture, and transmit focus through the supervised learning procedure. Overall, the proposed framework successfully learned generalizable receive apodizations to improve image quality.
2026-04-24
·百度百家
细胞疗法信使RNA疫苗基因疗法免疫疗法
2026-04-24
100 项与 FUJIFILM Holdings Corp. 相关的药物交易
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100 项与 FUJIFILM Holdings Corp. 相关的转化医学
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