Pilot Clinical Trial Of Neoadjuvant Toll-Like Receptor 7 Agonist (Imiquimod) Immunotherapy (2025)
- Quantitative image analysis was performed using QuPath and Python to assess tumor cell density and immune infiltration in pre- and post-treatment samples.
- Automated cell segmentation and classification were implemented using machine learning algorithms for accurate quantification of multiplex immunofluorescence markers.
- Spatial analysis metrics were developed to evaluate the proximity of immune cells to tumor cells, providing insights into the immunological effects of neoadjuvant TLR-7 agonist therapy.
Exploring Heterogeneity In Cancer And Renal Biology With Visium And Multiplexed IHC (2024)
- Computational methods were developed to assess hypoxia and proliferation gradients within histological tissue sections, enabling a spatially resolved analysis of tumor microenvironments.
- Machine learning-driven segmentation and classification techniques were applied to multiplexed immunohistochemistry (IMC) datasets, facilitating the characterization of spatial heterogeneity in glioblastoma and renal disease.
- Spatial analysis workflows were implemented to map immune cell localization in glioblastoma, acute kidney injury, and renal transplant rejection, incorporating spatial transcriptomics (Visium) to reveal transcriptional patterns linked to disease progression.
Exploring The Single Cell Immune Landscape Of Renal Allograft Inflammation Using IMC (2023)
- Quantitative image analysis was performed using QuPath and Python to assess immune cell composition and spatial organization in kidney allograft inflammation.
- Automated cell segmentation and classification were implemented using machine learning algorithms to accurately quantify imaging mass cytometry markers across tissue compartments.
- Spatial analysis techniques were applied to identify immune cell clustering patterns and their associations with different allograft rejection phenotypes, contributing to the development of a tissue-based classifier.
Cytokines and Immune Cell Phenotype In AKI Associated With Immune Checkpoint Inhibitors (2022)
- Imaging mass cytometry was used to analyze immune cell composition and spatial distribution in kidney biopsies from patients with immune checkpoint inhibitor (ICI)-associated acute kidney injury (AKI).
- Computational image analysis workflows were applied to identify and quantify immune cell subsets, including CD4 memory T cells, T helper cells, and dendritic cells, across renal compartments.
- Spatial mapping techniques were implemented to compare immune cell localization between AKI-ICI and other AKI causes, providing insights into potential biomarkers and immune-mediated mechanisms of kidney injury.
Mass Spectrometry Imaging Reveals A Gradient Of Cancer-Like Metabolic States (2021)
- Mass spectrometry imaging was used to analyze the spatial distribution of lipid metabolites in brain tissue adjacent to medulloblastoma tumors.
- Computational image analysis methods were applied to identify a gradient of cancer-like metabolic states extending beyond the histologic tumor margin.
- Spatial mapping techniques were implemented to compare lipid composition across tumor and healthy tissue, revealing metabolic alterations in regions previously considered normal.
Quantitative Visualization of Hypoxia and Proliferation Gradients Tissue Sections (2019)
- Image analysis methods were developed to visualize and quantify hypoxia and proliferation gradients within histological tissue sections.
- Vessel distance analysis was applied to assess the spatial relationship between hypoxia, proliferation, and perfused blood vessels, providing insights into oxygen diffusion and tumor microenvironmental heterogeneity.
- Computational segmentation techniques were implemented to classify tissue regions and quantify marker expression, enabling a more precise characterization of hypoxic and proliferative gradients in solid tumors.