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Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies
Rossana Lazcano1, Frank Rojas1, Caddie Laberiano1
1Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Frontiers in Molecular Biosciences
|August 16, 2021
Summary
Pathology quality control (PQC) is crucial for multiplex immunofluorescence (mIF) analysis of tumor tissues. Ensuring sufficient malignant cells and appropriate tissue size are key to obtaining accurate immune profiling data from biopsies.
Area of Science:
- Pathology
- Immunology
- Biomedical Imaging
Background:
- Multiplex immunofluorescence (mIF) enables multi-biomarker analysis on single slides.
- Digital image analysis of core needle biopsies is vital for immune profiling.
- Established criteria for sample inclusion in mIF assays are currently lacking.
Purpose of the Study:
- To retrospectively analyze pathology quality control (PQC) data for mIF assays.
- To identify common exclusion criteria and their impact on tumor tissue immune profiling.
- To highlight the importance of PQC for accurate and reproducible mIF image analysis.
Main Methods:
- Retrospective review of PQC data from hematoxylin and eosin (H&E) and mIF samples.
- Analysis of 931 core needle biopsy reports.
- Identification of exclusion reasons and sample characteristics.
Main Results:
- 13.21% of 931 core needle biopsy samples were excluded during mIF PQC.
- Absence or low numbers (<100) of malignant cells were the primary exclusion reason (34.15%).
- Other exclusion factors included small tissue size (13.01%) and poor tissue quality (fibrosis, necrosis).
Conclusions:
- PQC is an essential step for reliable mIF image analysis.
- The absence of malignant cells is the most significant limiting factor for mIF analysis.
- Pathologists must consider sample characteristics to ensure reproducible image analysis data.
