Multiplex-brightfield immunohistochemistry (IHC) staining and quantitative measurement of multiple biomarkers can
support therapeutic targeting of carcinoma-associated fibroblasts (CAF). This paper presents an automated digitalpathology
solution to simultaneously analyze multiple biomarker expressions within a single tissue section stained with
an IHC duplex assay. Our method was verified against ground truth provided by expert pathologists. In the first stage,
the automated method quantified epithelial-carcinoma cells expressing cytokeratin (CK) using robust nucleus detection
and supervised cell-by-cell classification algorithms with a combination of nucleus and contextual features. Using
fibroblast activation protein (FAP) as biomarker for CAFs, the algorithm was trained, based on ground truth obtained
from pathologists, to automatically identify tumor-associated stroma using a supervised-generation rule. The algorithm
reported distance to nearest neighbor in the populations of tumor cells and activated-stromal fibroblasts as a wholeslide
measure of spatial relationships. A total of 45 slides from six indications (breast, pancreatic, colorectal, lung, ovarian,
and head-and-neck cancers) were included for training and verification. CK-positive cells detected by the algorithm were
verified by a pathologist with good agreement (R2=0.98) to ground-truth count. For the area occupied by FAP-positive
cells, the inter-observer agreement between two sets of ground-truth measurements was R2=0.93 whereas the algorithm
reproduced the pathologists’ areas with R2=0.96. The proposed methodology enables automated image analysis to
measure spatial relationships of cells stained in an IHC-multiplex assay. Our proof-of-concept results show an automated
algorithm can be trained to reproduce the expert assessment and provide quantitative readouts that potentially support a
cutoff determination in hypothesis testing related to CAF-targeting-therapy decisions.
Auranuch Lorsakul, Emilia Andersson, Suzana Vega Harring, Hadassah Sade, Oliver Grimm, and Joerg Bredno, "Automated wholeslide analysis of multiplex-brightfield IHC images for cancer cells and carcinoma-associated fibroblasts," Proc. SPIE 10140, Medical Imaging 2017: Digital Pathology, 1014007 (Presented at SPIE Medical Imaging: February 12, 2017; Published: 1 March 2017); https://doi.org/10.1117/12.2254459.
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