Carotid plaques have been associated with ipsilateral neurological symptoms. High-resolution ultrasound can provide information not only on the degree of carotid artery stenosis but also on the characteristics of the arterial wall including the size and consistency of atherosclerotic plaques. The aim of this study was to determine cerebrovascular risk stratification based on ultrasonic plaque texture features and clinical features in patients with asymptomatic internal carotid artery (ICA) stenosis. It is shown that cerebrovascular risk stratification is possible using a combination of clinical and ultrasonic plaque features with very satisfactory results. However, these findings need to be validated in additional prospective studies in patients having current medical intervention.
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http://dx.doi.org/10.1109/IEMBS.2011.6091641 | DOI Listing |
J Anus Rectum Colon
January 2025
Department of Gastroenterological Surgery, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
Objectives: This study explored the clinical utility of CT radiomics-driven machine learning as a predictive marker for chemotherapy response in colorectal liver metastasis (CRLM) patients.
Methods: We included 150 CRLM patients who underwent first-line doublet chemotherapy, dividing them into a training cohort (n=112) and a test cohort (n=38). We manually delineated three-dimensional tumor volumes, selecting the largest liver metastasis for measurement, using pretreatment portal-phase CT images and extracted 107 radiomics features.
Breast Cancer (Auckl)
January 2025
Department of Diagnostic and Interventional Radiology, University of Leipzig, Leipzig, Germany.
Background: Texture analysis has the potential to deliver quantitative imaging markers. Patients receiving computed tomography (CT)-guided percutaneous bone biopsies could be characterized using texture analysis derived from CT. Especially for breast cancer (BC) patients, it could be crucial to better predict the outcome of the biopsy to better reflect the immunohistochemistry status of the tumor.
View Article and Find Full Text PDFCartilage
January 2025
High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
Objective: The objective of this study was to assess the maturation of matrix-associated autologous chondrocyte transplantation (MACT) grafts up to 2 years after the surgery using gray-level co-occurrence matrix (GLCM) texture analysis of quantitative T maps, compare the results with the microfracturing technique (MFX) control group, and relate these results to the morphological MOCART 2.0 score.
Design: A subcohort of 37 patients from prospective, multi-center study underwent examination on a 3T MR scanner, including a T mapping sequence at 3, 12, and 24 months after surgery.
Sci Rep
January 2025
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, 10300, Thailand.
Attention mechanisms such as the Convolutional Block Attention Module (CBAM) can help emphasize and refine the most relevant feature maps such as color, texture, spots, and wrinkle variations for the avocado ripeness classification. However, the CBAM lacks global context awareness, which may prevent it from capturing long-range dependencies or global patterns such as relationships between distant regions in the image. Further, more complex neural networks can improve model performance but at the cost of increasing the number of layers and train parameters, which may not be suitable for resource constrained devices.
View Article and Find Full Text PDFMagn Reson Imaging
January 2025
GE Healthcare, Guangzhou 510623, China.
Background: Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectiveness of integrating MRI radiomic features with clinical data using a deep learning approach to predict vascular invasion in breast cancer patients.
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