AIMC Topic: Lymphatic Metastasis

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Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.

Scientific reports
To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of venous phase using deep learning (DL) and Radiomics approaches to predict lymphovascular invasion in gastric cancer prior to surgery. We retrospectiv...

An integrative analysis reveals mechanisms of Prunella vulgaris in thyroid cancer metastasis.

Phytomedicine : international journal of phytotherapy and phytopharmacology
BACKGROUND: Lymph node metastasis (LNM) in papillary thyroid carcinoma (PTC) is a major contributor to poor prognosis. Prunella vulgaris (P. vulgaris), a traditional medicinal herb, has shown potential in inhibiting PTC metastasis, but its molecular ...

Artificial intelligence-assisted endobronchial ultrasound for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis.

BMC pulmonary medicine
BACKGROUND: Endobronchial ultrasound (EBUS) is a widely used imaging modality for evaluating thoracic lymph nodes (LNs), particularly in the staging of lung cancer. Artificial intelligence (AI)-assisted EBUS has emerged as a promising tool to enhance...

Development and validation of a machine learning model for central compartmental lymph node metastasis in solitary papillary thyroid microcarcinoma via ultrasound imaging features and clinical parameters.

BMC medical imaging
BACKGROUND: Papillary thyroid microcarcinoma (PTMC) is the most common malignant subtype of thyroid cancer. Preoperative assessment of the risk of central compartment lymph node metastasis (CCLNM) can provide scientific support for personalized treat...

Development and validation of CT-based fusion model for preoperative prediction of invasion and lymph node metastasis in adenocarcinoma of esophagogastric junction.

BMC medical imaging
PURPOSE: In the context of precision medicine, radiomics has become a key technology in solving medical problems. For adenocarcinoma of esophagogastric junction (AEG), developing a preoperative CT-based prediction model for AEG invasion and lymph nod...

Prediction of axillary lymph node metastasis in triple negative breast cancer using MRI radiomics and clinical features.

Scientific reports
To develop and validate a machine learning-based prediction model to predict axillary lymph node (ALN) metastasis in triple negative breast cancer (TNBC) patients using magnetic resonance imaging (MRI) and clinical characteristics. This retrospective...

Multi-parameter MRI deep learning model for lymphovascular invasion assessment in invasive breast ductal carcinoma: A multicenter, retrospective study.

Clinical radiology
AIMS: To investigate the value of multi-parametric magnetic resonance imaging (MRI)-based deep learning (DL) in predicting the Lymphovascular Invasion (LVI) status of invasive breast ductal cancer (IBDC).

Preoperative Identification of Papillary Thyroid Carcinoma Subtypes and Lymph Node Metastasis via Deep Learning-Assisted Surface-Enhanced Raman Spectroscopy.

ACS nano
Accurate preoperative diagnosis of papillary thyroid carcinoma (PTC) histological subtypes and lymph node metastasis is essential for formulating personalized treatment strategies. However, their preoperative diagnosis is challenged by the limited re...

Prediction of Lymph Node Metastasis in Non-Small Cell Lung Carcinoma Using Primary Tumor Somatic Mutation Data.

JCO clinical cancer informatics
PURPOSE: Lymph node metastasis (LNM) significantly affects prognosis and treatment strategies in non-small cell lung cancer (NSCLC). Current diagnostic methods, including imaging and histopathology, have limited sensitivity and specificity. This stud...