A statistical framework for analyzing hypothesized interactions between cells imaged using multispectral microscopy and multiple immunohistochemical markers

Abstract

Background: Multispectral microscopy and multiple staining can be used to identify cells with distinct immunohistochemical (IHC) characteristics. We present here a method called hypothesized interaction distribution (HID) analysis for characterizing the statistical distribution of pair-wise spatial relationships between cells with particular IHC characteristics and apply it to clinical data. Materials and Methods: We retrospectively analyzed data from a study of 26 follicular lymphoma patients in which sections were stained for CD20 and YY1. HID analysis, using leave-one-out validation, was used to assign patients to one of two groups. We tested the null hypothesis of no difference in Kaplan-Meier survival curves between the groups. Results: Shannon entropy of HIDs assigned patients to groups that had significantly different survival curves (median survival was 7.70 versus 110 months, P = 0.00750). Hypothesized interactions between pairs of cells positive for both CD20 and YY1 were associated with poor survival. Conclusions: HID analysis provides quantitative inferences about possible interactions between spatially proximal cells with particular IHC characteristics. In follicular lymphoma, HID analysis was able to distinguish between patients with poor versus good survival, and it may have diagnostic and prognostic utility in this and other diseases.

Keywords

• Cellular interactions
• follicular lymphoma
• image analysis
• immunohistochemical staining
• multispectral microscopy