AIMC Topic: Lymph Nodes

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Radiomics-based MRI models for predicting breast cancer axillary lymph node involvement in comparison with Node-RADS: a proof-of-concept study.

European radiology experimental
BACKGROUND: Detection of axillary lymph node (LN) involvement is essential for staging breast cancer and optimizing treatment. This proof-of-concept two-center study explored the feasibility of magnetic resonance imaging (MRI) radiomics-based machine...

Non-Hodgkin's lymphoma classification using 3D radiomics machine learning models for precision imaging in oncology.

BMC medical imaging
PURPOSE: To apply quantitative imaging analysis for noninvasive classification of the most frequent subtypes of Non-Hodgkin Lymphoma (NHL) as a basis for a clinical imaging genomic model to support therapeutic monitoring and clinical decision making.

Ultrasound-based radiomics model for predicting axillary lymph node metastasis of breast cancer.

BMC medical imaging
OBJECTIVE: This study aims to explore the impact of different ROI delineation strategies on the axillary lymph nodes metastasis (ALNM) prediction model by analyzing two-dimensional ultrasound images of lymph nodes. In addition, we integrated clinical...

Detection, localization, and staging of breast cancer lymph node metastasis in digital pathology whole slide images using selective neighborhood attention-based deep learning.

Scientific reports
Accurate detection, localization, and staging of breast cancer lymph node metastases are critical for guiding treatment decisions and predicting patient outcomes. This study presents a selective neighborhood attention-based deep learning framework th...

Deep learning-powered multi-parametric ultrasound for classifying metastatic versus reactive axillary lymph nodes.

Breast cancer research : BCR
PURPOSE: To propose a multi-parametric ultrasound imaging-based deep learning method for accurately classifying metastatic and non-metastatic axillary lymph nodes in breast cancer patients.

Machine learning-based prediction of N2 lymph node metastasis in non-small cell lung cancer.

BMC pulmonary medicine
BACKGROUND: Lung cancer is a leading cause of cancer-related mortality worldwide. Accurate staging of mediastinal lymph nodes is a crucial step in determining appropriate treatment approaches. Current noninvasive diagnostic methods do not provide suf...

Automated contouring of gross tumor volume lymph nodes in lung cancer by deep learning.

BMC cancer
PURPOSE: The precise contouring of gross tumor volume lymph nodes (GTVnd) is an essential step in clinical target volume delineation. This study aims to propose and evaluate a deep learning model for segmenting GTVnd specifically in lung cancer, repr...

A specific gene expression program underlies antigen archiving by lymphatic endothelial cells in mammalian lymph nodes.

Nature communications
Lymph node (LN) lymphatic endothelial cells (LEC) actively acquire and archive foreign antigens. Here, we address questions of how LECs achieve durable antigen archiving and whether LECs with high levels of antigen express unique transcriptional prog...

Historical evolution and current research status of lymph node staging in gastric cancer: a review.

World journal of surgical oncology
Lymph node metastasis (LNM) is an independent prognostic factor for patients with gastric cancer (GC), and an accurate lymph node (LN) staging system is crucial for guiding adjuvant therapy and assessing patient prognosis. The most commonly used stag...

CT-based machine learning model integrating intra- and peri-tumoral radiomics features for predicting occult lymph node metastasis in peripheral lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate preoperative assessment of occult lymph node metastasis (OLNM) plays a crucial role in informing therapeutic decision-making for lung cancer patients. Computed tomography (CT) is the most widely used imaging modality for preopera...