Caroll Co, Statistician, Social & Scientific Systems
Sandra McBride, Principal Statistician, Social & Scientific Systems Inc., A DLH Holdings Corp. Company
Shawn Harris, Statistician, Social & Scientific Systems Inc., A DLH Holdings Corp. Company
Debra A Tokarz, Senior Pathologist, Experimental Pathology Laboratories, Inc.
Thomas J Steinbach, Vice President/Senior Pathologist, Experimental Pathology Laboratories, Inc.
Mark F Cesta, Pathologist, National Institute of Environmental Health Sciences
Advances in digital image analysis have created opportunities for quantitative histopathology assessments in rodent toxicology studies. Microscopic evaluation of rodent spleen is performed to assess for test article-induced immunotoxic effects but can be subject to inter- and intra-pathologist variability in characterization of differences between treatment groups and across studies.
To address this problem, an image detection algorithm was trained to quantify tissue compartments in histologic sections of rodent spleen. Our aim was to design a study to evaluate how the image detection algorithm compared to digital annotations performed by human raters for specific features of the spleen, while keeping within operational constraints (e.g., rater time and effort).
In this talk, we show how we used JMP Custom Designer, using data generated by the image algorithm as inputs, to select and allocate a test set across human raters. We used a response surface model, which is designed to select samples that fall on the boundaries and center of the input space. The resulting study design allowed us to strategically select a test set and create a balanced sampling plan for use across several pathologists from different institutions.
