Estimation of Immune Cell Densities in Immune Cell Conglomerates: An Approach for High-Throughput Quantification

Determining the correct number of positive immune cells in immunohistological sections of colorectal cancer and other tumor entities is emerging as an important clinical predictor and therapy selector for an individual patient. This task is usually obstructed by cell conglomerates of various sizes. We here show that at least in colorectal cancer the inclusion of immune cell conglomerates is indispensable for estimating reliable patient cell counts. Integrating virtual microscopy and image processing principally allows the high-throughput evaluation of complete tissue slides.For such large-scale systems we demonstrate a robust quantitative image processing algorithm for the reproducible quantification of cell conglomerates on CD3 positive T cells in colorectal cancer. While isolated cells (28 to 80 microm(2)) are counted directly, the number of cells contained in a conglomerate is estimated by dividing the area of the conglomerate in thin tissues sections (< or =6 microm) by the median area covered by an isolated T cell which we determined as 58 microm(2). We applied our algorithm to large numbers of CD3 positive T cell conglomerates and compared the results to cell counts obtained manually by two independent observers. While especially for high cell counts, the manual counting showed a deviation of up to 400 cells/mm(2) (41% variation), algorithm-determined T cell numbers generally lay in between the manually observed cell numbers but with perfect reproducibility.In summary, we recommend our approach as an objective and robust strategy for quantifying immune cell densities in immunohistological sections which can be directly implemented into automated full slide image processing systems

Conglomerates and single cells.

<p>Liver metastasis of colorectal cancer with strong T cell infiltrate (CD3 staining: dark red with hematoxylin counterstaining, A: overview, digital magnification 10×, B: conglomerate (magnification 40×), C: single cells, (magnification 40×).</p

Repeated quantification (six times) of a large conglomerate by one observer.

<p>Triangles show single values for each repetition and thin vertical lines indicate range, thick horizontal line indicates average value.</p

Cell counts of T cells (CD3+) in thirty different fields of 1 mm² size.

<p>Fields with maximum differences between manual cell counts are highlighted.</p><p>Abs. Diff. Man. = Absolute Difference between Manual1 and Manual2, % Diff. Man. = Percentage Difference between Manual1 and Manual2.</p

Impact of cell counts from conglomerates on total cell counts in 10 individual 1 mm² fields from sections of 10 different patients.

<p>Omitting conglomerates in the quantification would substantially distort the total cell counts.</p

Cell area sizes of T cells (CD3+) measured in histological sections of different tissues with 2 µm thickness.

<p>Cell area sizes of T cells (CD3+) measured in histological sections of different tissues with 2 µm thickness.</p

Exemplary workflow for the described algorithm.

<p>Stained immune cells are either counted individually (where possible) or the number of cells is estimated by the conglomerate surface. Both results are added.</p

Cell counts for 30 different fields with one ore more conglomerates, each evaluated by two observers (“Manual1” and “Manual2”) and the here presented algorithm (“Automated”).

<p>Note the up to 41% variation between the observers at high cell counts (1000-1.500). For quantitative data comparison see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0007847#pone-0007847-t001" target="_blank">table 1</a>.</p

Rationale behind the presented approach.

<p>The figure shows the relation of the size of T cells to the height of the used tissue sections (2 µm). The sections are so thin, that there is only minimal overlap between the individual cells of a conglomerate. This allows for calculating the number of cells in a conglomerate by its total area.</p