Spatial Immunophenotyping from Whole-Slide Multiplexed Tissue Imaging Using Convolutional Neural Networks.

The multiplexed immunofluorescence (mIF) platform enables biomarker discovery through the simultaneous detection of multiple markers on a single tissue slide, offering detailed insights into intratumor heterogeneity and the tumor-immune microenvironment at spatially resolved single cell resolution. However, current mIF image analyses are labor-intensive, requiring specialized pathology expertise which limits their scalability and clinical application. To address this challenge, we developed CellGate, a deep-learning (DL) computational pipeline that provides streamlined, end-to-end whole-slide mIF image analysis including nuclei detection, cell segmentation, cell classification, and combined immuno-phenotyping across stacked images.

Clinical implications of nintedanib pharmacokinetics in patients with pulmonary fibrosis.

Background: Nintedanib is used to treat both idiopathic and progressive pulmonary fibrosis (IPF/PPF). Evidence of both an exposure-response relationship and an exposure-toxicity relationship has been found, suggesting the potential value of therapeutic drug monitoring (TDM). We aimed to define the therapeutic window of nintedanib in a real-world cohort.