AIMC Topic: Neovascularization, Pathologic

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Micro-morphological feature visualization, auto-classification, and evolution quantitative analysis of tumors by using SR-PCT.

Cancer medicine
Tissue micro-morphological abnormalities and interrelated quantitative data can provide immediate evidences for tumorigenesis and metastasis in microenvironment. However, the multiscale three-dimensional nondestructive pathological visualization, mea...

Myricitrin inhibits vascular endothelial growth factor-induced angiogenesis of human umbilical vein endothelial cells and mice.

Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
In the present study, the protective effects of myricitrin against vascular endothelial growth factor (VEGF)-induced angiogenesis of vascular endothelial cells were characterized. Cells were induced with 50 ng/mL VEGF in the presence or absence of va...

Preoperative identification of microvascular invasion in hepatocellular carcinoma by XGBoost and deep learning.

Journal of cancer research and clinical oncology
PURPOSE: Microvascular invasion (MVI) is a valuable predictor of survival in hepatocellular carcinoma (HCC) patients. This study developed predictive models using eXtreme Gradient Boosting (XGBoost) and deep learning based on CT images to predict MVI...

Artificial neural network models to predict nodal status in clinically node-negative breast cancer.

BMC cancer
BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard staging procedure for nodal status in breast cancer, but lacks therapeutic benefit for patients with benign sentinel nodes. For patients with positive sentinel nodes, individualized surgical s...

Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment...

Artificial intelligence for the real-time classification of intrapapillary capillary loop patterns in the endoscopic diagnosis of early oesophageal squamous cell carcinoma: A proof-of-concept study.

United European gastroenterology journal
BACKGROUND: Intrapapillary capillary loops (IPCLs) represent an endoscopically visible feature of early squamous cell neoplasia (ESCN) which correlate with invasion depth - an important factor in the success of curative endoscopic therapy. IPCLs visu...

Deep Learning for Drug Discovery and Cancer Research: Automated Analysis of Vascularization Images.

IEEE/ACM transactions on computational biology and bioinformatics
Likely drug candidates which are identified in traditional pre-clinical drug screens often fail in patient trials, increasing the societal burden of drug discovery. A major contributing factor to this phenomenon is the failure of traditional in vitro...

Monitoring vascular normalization induced by antiangiogenic treatment with (18)F-fluoromisonidazole-PET.

Molecular oncology
BACKGROUND: Rationalization of antiangiogenics requires biomarkers. Vascular re-normalization is one widely accepted mechanism of action for this drug class. The interstitium of tumors with abnormal vasculature is hypoxic. We sought to track vascular...

A machine learning-derived angiogenesis signature for clinical prognosis and immunotherapy guidance in colon adenocarcinoma.

Scientific reports
Colon adenocarcinoma (COAD) is one of the most prevalent malignancies worldwide and its prognosis is extremely poor. Angiogenesis has been linked to clinical outcomes, tumor progression, and treatment sensitivity. However, the role of angiogenesis in...