Results 61 to 70 of about 851,421 (273)
In-depth Assessment of an Interactive Graph-based Approach for the Segmentation for Pancreatic Metastasis in Ultrasound Acquisitions of the Liver with two Specialists in Internal Medicine [PDF]
The manual outlining of hepatic metastasis in (US) ultrasound acquisitions from patients suffering from pancreatic cancer is common practice. However, such pure manual measurements are often very time consuming, and the results repeatedly differ between the raters.
arxiv +1 more source
We quantified and cultured circulating tumor cells (CTCs) of 62 patients with various cancer types and generated CTC‐derived tumoroid models from two salivary gland cancer patients. Cellular liquid biopsy‐derived information enabled molecular genetic assessment of systemic disease heterogeneity and functional testing for therapy selection in both ...
Nataša Stojanović Gužvić+31 more
wiley +1 more source
Summary: Organotypic brain cultures are short-term assays that phenotypically and functionally recapitulate brain metastatic cells in vivo. Here, we present a protocol to generate murine organotypic brain cultures for drug screening.
Lucía Zhu+4 more
doaj
A Robust and Effective Approach Towards Accurate Metastasis Detection and pN-stage Classification in Breast Cancer [PDF]
Predicting TNM stage is the major determinant of breast cancer prognosis and treatment. The essential part of TNM stage classification is whether the cancer has metastasized to the regional lymph nodes (N-stage). Pathologic N-stage (pN-stage) is commonly performed by pathologists detecting metastasis in histological slides.
arxiv
The authors analyzed the spatial distributions of gene and metabolite profiles in cervical cancer through spatial transcriptomic and spatially resolved metabolomic techniques. Pivotal genes and metabolites within these cases were then identified and validated.
Lixiu Xu+3 more
wiley +1 more source
Lymph Node Graph Neural Networks for Cancer Metastasis Prediction [PDF]
Predicting outcomes, such as survival or metastasis for individual cancer patients is a crucial component of precision oncology. Machine learning (ML) offers a promising way to exploit rich multi-modal data, including clinical information and imaging to learn predictors of disease trajectory and help inform clinical decision making.
arxiv
The authors applied joint/mixed models that predict mortality of trifluridine/tipiracil‐treated metastatic colorectal cancer patients based on circulating tumor DNA (ctDNA) trajectories. Patients at high risk of death could be spared aggressive therapy with the prospect of a higher quality of life in their remaining lifetime, whereas patients with a ...
Matthias Unseld+7 more
wiley +1 more source
Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam+2 more
wiley +1 more source
Many sensitizers have not only photodynamic effects, but also sonodynamic effects. Therefore, the combination of sonodynamic therapy (SDT) and photodynamic therapy (PDT) using sensitizers for sono-photodynamic therapy (SPDT) provides alternative ...
Yilin Zheng+4 more
doaj
A Theoretical Model of Chaotic Attractor in Tumor Growth and Metastasis [PDF]
This paper proposes a novel chaotic reaction-diffusion model of cellular tumor growth and metastasis. The model is based on the multiscale diffusion cancer-invasion model (MDCM) and formulated by introducing strong nonlinear coupling into the MDCM. The new model exhibits temporal chaotic behavior (which resembles the classical Lorenz strange attractor)
arxiv