Whole Slide Image Analysis
The use of whole slide image analysis software to quantify stains based on color and morphology can help advance the standardization of IHC and other techniques used within pathology today.
Studies have shown that immunohistochemistry (IHC) scoring by human visual inspection is subject to a variety of issues including inter- and intra-observer variability.
The reproducibility that computer assisted analysis provides allows pathologists and researchers to obtain more consistent and accurate interpretations of IHC studies. Whole slide image analysis algorithms also automate many tedious analysis tasks such as cell counting. Repetitive and tedious tasks like determination of percent positivity, mitotic counts, and rare event detection can be simplified and expedited by algorithms, thereby saving time and energy for the pathologist.
Whole slide image analysis can also decrease subjectivity in the interpretation of various types of studies. Image analysis provides more accurate and quantitative results on larger numbers of cells, thereby decreasing intra- and inter-observer variability in the scoring of difficult studies such as Her2-neu IHC. Obtaining the correct result, regardless of the pathologist interpreting the study, is critical, as expensive and potentially harmful therapies are determined by the results of some of these pathology studies.
IHC and fluorescence in situ hybridization (FISH) studies are being used by pathologists to determine positivity of various markers. The results of these studies are then used to guide clinicians in therapeutic decisions for their patients. Digital slides serve as the springboard for a complete digital pathology environment in which the pathologist can view, retrieve, annotate, archive images while applying sophisticated quantitative image analysis protocols as aids in diagnosis.
