Related Experiment Video
Updated: Jul 18, 2026
High-Dimensionality Flow Cytometry for Immune Function Analysis of Dissected Implant Tissues
Published on: September 15, 2021
"Virtual flow cytometry" of immunostained lymphocytes on microscopic tissue slides: iHCFlow tissue cytometry
Hernani D Cualing1, Eric Zhong, Lynn Moscinski
1H. Lee Moffitt Cancer Center and Research Institute, University of South Florida, Tampa, Florida, USA. cualinhd@moffitt.usf.edu
Insights
A new digital microscopy technique, iHCFlow Tissue Cytometry (TC), automates lymphocyte analysis from tissue samples. This virtual flow cytometry approach offers a clinically valid alternative to traditional methods for cancer diagnosis and prognosis.
Area of Science:
- Digital pathology
- Immunohistochemistry
- Flow cytometry
- Cytomics
Background:
- A novel method, iHCFlow Tissue Cytometry (TC), has been developed for automated measurement of immunostained lymphocytes in tissue sections.
- This technique utilizes digital color microscopy and advanced cell analysis, converting immunohistochemistry (IHC) data into a flow cytometry-like dot-plot display, termed virtual flow cytometry.
- Seven technical challenges for virtual flow cytometry were identified and addressed.
Purpose of the Study:
- To present validation data for population statistics of immunostained lymphocytes using tissue cytometry (TC).
- To introduce a new paradigm in tissue cytometry that converts IHC staining of lymphocytes into automated, flow cytometry-like results.
- To establish iHCFlow TC as a potential clinical surrogate for diagnostic and prognostic analyses.
Main Methods:
- Image segmentation of 512 x 474 RGB images and statistical result tabulation were performed using proprietary algorithms in 12-15 seconds.
- A panel of seven antibodies (CD3, CD4, CD8, Bcl-1, Ki-67, CD20, CD5) was used for validation on 14 mantle cell lymphoma cases.
- Results from TC were compared against manual counts by expert observers and flow cytometric immunophenotyping of the same specimens.
Main Results:
- High concordance was observed between manual counts, flow cytometry, and TC results, with correlation coefficients of r = 0.9365 (Manual vs. TC) and r = 0.9537 (FC vs. TC).
- The system successfully evaluated 2,027 image frames, encompassing 810,800 cell objects.
- Technical issues were resolved, and the solutions were evaluated and presented.
Conclusions:
- The iHCFlow TC technology demonstrates potential as a clinically valid surrogate for manual and flow cytometry analyses when only tissue IHC is available.
- This automated system facilitates objective, rapid counting of immunostained cells in tissues, providing percentage results for cancer diagnosis, monitoring, and prognosis.
- The intuitive dot plot histogram display offers pathologists an automated tool for rapid characterization of cell populations, satisfying criteria for Cytomics.
Background:
A method and approach is developed for fully automated measurements of immunostained lymphocytes in tissue sections by means of digital color microscopy and patent pending advanced cell analysis. The validation data for population statistic measurements of immunostained lymphocytes in tissue sections using tissue cytometry (TC) is presented. The report is the first to describe the conversion of immunohistochemistry (IHC) data to a flow cytometry-like two parameter dot-plot display, hence the technique is also a virtual flow cytometry. We believe this approach is a paradigm shift, as well as novel, and called the system iHCFlow TC. Seven issues related to technical obstacles to virtual flow cytometry (FC) are identified.
Design:
Segmentation of a 512 x 474 RGB image and tabular display of statistical results table took 12-15 s using proprietary developed algorithms. We used a panel of seven antibodies for validation on 14 cases of mantle cell lymphoma giving percentage positive, total lymphocytes, and staining density. A total of 2,027 image frames with 810,800 cell objects (COBs) were evaluated. Antibodies to CD3, CD4, CD8, Bcl-1, Ki-67, CD20, CD5 were subjected to virtual FC on tissue. The results of TC were compared with manual counts of expert observers and with the results of flow cytometric immunophenotyping of the same specimen.
Results:
The correlation coefficient and 95% confidence interval by linear regression analysis yielded a high concordance between manual human results (M), FC results, and TC results per antibody, (r = 0.9365 M vs. TC, r= 0.9537 FC vs. TC). The technical issues were resolved and the solutions and results were evaluated and presented.
Conclusion:
These results suggest the new technology of TC by iHCFlow could be a clinically valid surrogate for both M and FC analysis when only tissue IHC is available for diagnosis and prognosis. The application for cancer diagnosis, monitoring, and prognosis is for objective, rapid, automated counting of immunostained cells in tissues with percentage results. We report a new paradigm in TC that converts IHC staining of lymphocytes to automated results and a flow cytometry-like report. The dot plot histogram display is familiar, intuitive, informative, and provides the pathologists with an automated tool to rapidly characterize the staining and size distribution of the immunoreactive as well as the negative cell population in the tissue. This systems tool is a major improvement over existing ones and satisfies fully the criteria to perform Cytomics (Ecker and Tarnok, Cytometry A 2005;65:1; Ecker and Steiner, Cytometry A 2004;59:182-190; Ecker et al., Cytometry A 2004;59:172-181).
