Imaging Mass Cytometry Dataset of Human Carotid Atherosclerotic Plaques_Cohort_2

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Description This repository contains de-identified raw and processed imaging mass cytometry (IMC) data generated from 62 human carotid atherosclerotic plaque specimens obtained from 47 patients in Cohort 2. The dataset comprises 227 regions of interest (ROIs) and 543,113 segmented cells. Pixel-level raw IMC signals were generated as TXT files concurrently with the corresponding proprietary MCD files during data acquisition. Each TXT file represents an individual ROI and contains spatial coordinates and raw ion-count intensities for all acquired metal channels. To protect participant confidentiality, only de-identified TXT files are deposited; the corresponding MCD containers were excluded because their embedded metadata contained potentially identifiable patient information. IMC preprocessing was performed using a Docker-containerized steinbock workflow. Cell segmentation was performed using a combined DeepCell–Cellpose2 workflow, followed by extraction of single-cell marker intensities, morphological features, spatial coordinates, and cell–cell neighbor relationships. The deposited files include pixel-level raw IMC data, preprocessed multichannel images, segmentation masks, single-cell intensity measurements, morphological and spatial features, neighbor information, compensation files, CellProfiler outputs, and a processed SpatialExperiment object. These data support spatial single-cell analyses of immune, stromal, vascular, and myeloid niches and their associations with plaque pathological features and imaging/pathology-defined instability. File descriptions raw_txt.zipContains de-identified, pixel-level raw IMC acquisition data generated concurrently with the corresponding MCD files. Each TXT file contains spatial coordinates and raw ion-count intensities for all acquired metal channels within an individual ROI. panel.csvContains antibody and channel information for the Cohort 2 IMC panel in steinbock-compatible format, including marker names and corresponding metal-isotope channels. sample_metadata.csv(Excel file S2-Cohort2.csv)Contains de-identified sample-level metadata, including study-specific patient and plaque identifiers, cohort information, imaging-based plaque classification, and histopathological annotations used for downstream analyses. images.csv (Table S4-ROI_metadata)Contains image-level metadata and links each anonymized IMC acquisition to its corresponding sample and ROI. img.zipContains preprocessed multichannel IMC images generated using the steinbock workflow. These images can be used for visualization, reprocessing, and downstream spatial analysis. masks.zipContains cell-segmentation masks. Each mask identifies individual segmented cells and can be combined with the corresponding multichannel image to reproduce single-cell feature extraction. intensities.zipContains mean marker-intensity measurements for every segmented cell and channel in each acquisition. regionprops.zipContains cell-level morphological and spatial measurements, including cell area, shape-related features, and centroid coordinates derived from the segmentation masks. neighbors.zipContains cell–cell spatial-neighbor relationships used for spatial-interaction and cellular-neighborhood analyses. compensation.zipContains the compensation-related files used for correction of channel spillover during IMC preprocessing. cellprofiler_output.zipContains CellProfiler output files generated during post-segmentation feature extraction and quality control. cell_measurement.cppipeContains the CellProfiler pipeline used to extract cell-level marker-intensity and morphological features from the multichannel images and segmentation masks. spe_cohort2.qsContains the processed SpatialExperiment object used for the principal downstream analyses. The object integrates single-cell marker expression, cell annotations, de-identified sample metadata, spatial coordinates, and cellular-neighborhood information. Data use note The SpatialExperiment object can be loaded in R using the qs package. Image-derived analyses can be reproduced using the raw TXT files, preprocessed images, segmentation masks, and associated single-cell feature tables. All deposited sample and ROI identifiers are study-specific pseudonyms and do not contain direct patient identifiers. These data support the study entitled “Spatial Single-Cell Proteomics Identifies Macrophage Niches Driving Human Carotid Plaque Instability.”

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