ArticleFrontiers in molecular biosciences2021
Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies.
Article in Frontiers in molecular biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- SPP1-positive macrophages drive trastuzumab resistance in HER2-positive breast cancer.Cell communication and signaling : CCS · 2026Article
- Antibody-Based Multiplex Image Analysis: Standard Analytical Workflows and Artificial Intelligence Tools for Pathologists.Laboratory investigation; a journal of technical methods and pathology · 2025Review
- Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon.Molecular oncology · 2025Review
- Quantitative image analysis pipeline for detecting circulating hybrid cells in immunofluorescence images with human-level accuracy.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2024Article
- Companion diagnostic requirements for spatial biology using multiplex immunofluorescence and multispectral imaging.Frontiers in molecular biosciences · 2023Review
- Developing image analysis methods for digital pathology.The Journal of pathology · 2022Review
- Challenges and Opportunities for Immunoprofiling Using a Spatial High-Plex Technology: The NanoString GeoMxFrontiers in oncology · 2022Review
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analysis of core needle biopsies is an important step in any laboratory to avoid wasting time and materials. Although there are currently no established inclusion and exclusion criteria for samples used in this type of assay, a PQC is necessary to achieve accurate and reproducible data. We retrospectively reviewed PQC data from hematoxylin and eosin (H&E) slides and from mIF image analysis samples obtained during 2019. We reviewed a total of 931 reports from core needle biopsy samples; 123 (13.21%) were excluded during the mIF PQC. The most common causes of exclusion were the absence of malignant cells or fewer than 100 malignant cells in the entire section (n = 42, 34.15%), tissue size smaller than 4 × 1 mm (n = 16, 13.01%), fibrotic tissue without inflammatory cells (n = 12, 9.76%), and necrotic tissue (n = 11, 8.94%). Baseline excluded samples had more fibrosis (90 vs 10%) and less necrosis (5 vs 90%) compared with post-treatment excluded samples. The most common excluded organ site of the biopsy was the liver (n = 19, 15.45%), followed by soft tissue (n = 17, 13.82%) and the abdominal region (n = 15, 12.20%). We showed that the PQC is an important step for image analysis and that the absence of malignant cells is the most limiting sample characteristic for mIF image analysis. We also discuss other challenges that pathologists need to consider to report reliable and reproducible image analysis data.
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