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http://dx.doi.org/10.1016/j.gassur.2025.101964 | DOI Listing |
J Control Release
September 2025
Department of Ultrasound, China-Japan Friendship Hospital, Beijing 100029, China; National Center for Respiratory Medicine; State Key Laboratory of Respiratory Health and Multimorbidity; National Clinical Research Center for Respiratory Diseases; Institute of Respiratory Medicine, Chinese Academy of
Anaplastic thyroid cancer (ATC) is the most aggressive form of thyroid malignancy and currently lacks effective treatment options. While anti-PD1 therapy has shown remarkable clinical results in some cases, only a subset of ATC patients responds to it. Eganelisib (IPI549), a highly selective PI3Kγ inhibitor, can alleviate the tumor immunosuppressive state by reducing the proportion of M2-like tumor associated macrophages, partially overcoming patient resistance to anti-PD1 therapy and synergizing with its efficacy.
View Article and Find Full Text PDFJ Clin Pathol
September 2025
Department of Pathology, Tata Memorial Center, Homi Bhabha National Institute (HBNI), Mumbai, Maharashtra, India
Aims: gene is amplified in 15%-20% of invasive breast cancers (IBCs), serving as critical prognostic and predictive marker. -targeted therapies have improved outcomes for -positive patients, highlighting the importance of accurate assessment. Immunohistochemistry is commonly used for screening overexpression, with equivocal cases reflex tested using in situ hybridisation (ISH) methods like fluorescence (FISH) or dual-colour dual ISH (D-DISH).
View Article and Find Full Text PDFNeural Netw
September 2025
School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, China; Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, 200240, China.
3D shape defect detection plays an important role in autonomous industrial inspection. However, accurate detection of anomalies remains challenging due to the complexity of multimodal sensor data, especially when both color and structural information are required. In this work, we propose a lightweight inter-modality feature prediction framework that effectively utilizes multimodal fused features from the inputs of RGB, depth and point clouds for efficient 3D shape defect detection.
View Article and Find Full Text PDFIEEE Trans Autom Sci Eng
January 2025
H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.
Cone beam computed tomography (CBCT) is a widely-used imaging modality in dental healthcare. It is an important task to segment each 3D CBCT image, which involves labeling lesions, bone, teeth, and restorative material on a voxel-by-voxel basis, as it aids in lesion detection, diagnosis, and treatment planning. The current clinical practice relies on manual segmentation, which is labor-intensive and demands considerable expertise.
View Article and Find Full Text PDFMach Learn Health
December 2025
Medical Artificial Intelligence and Automation Laboratory, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States of America.
Online adaptive radiation therapy (ART) personalizes treatment plans by accounting for daily anatomical changes, requiring workflows distinct from conventional radiotherapy. Deep learning-based dose prediction models can enhance treatment planning efficiency by rapidly generating accuracy dose distributions, reducing manual trial-and-error and accelerating the overall workflow; however, most existing approaches overlook critical pre-treatment plan information-specifically, physician-defined clinical objectives tailored to individual patients. To address this limitation, we introduce the multi-headed U-Net (MHU-Net), a novel architecture that explicitly incorporates physician intent from pre-treatment plans to improve dose prediction accuracy in adaptive head and neck cancer treatments.
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