Using Bland–Altman Analysis to Identify Appropriate Clonogenic Assay Colony Counting Techniques

Abstract

Objective Determine the interchangeability of various methods utilized for counting colonies in clonogenic assays. Methods Clonogenic assays of 2 head and neck cancer cell lines were counted through 4 different counting modalities: Manual counting pen, via microscope, 1 publicly available automated algorithm, and a semiautomated algorithm presented by the authors. Each method counted individual wells (N = 24). Pen and microscopic counts were performed by 2 observers. Parameters included both low-growth (<150 colonies/well) and high-growth (>150 colonies/well) cell lines. Correlational and Bland–Altman analyses were performed using SPSS software. Results Interobserver manual pen count correlation R2 value in both growth conditions was 0.902; controlling for only low-growth conditions decreased R2 to 0.660. Correlation of microscopic versus pen counts R2 values for observers 1 and 2 were 0.955 and 0.775, respectively. Comparing techniques, Bland–Altman revealed potential bias with respect to the magnitude of measurement ( P < .001) for both observers. Correlation of microscopic counts for both interobserver ( R2 = 0.902) and intraobserver ( R2 = 0.916) were analyzed. Bland–Altman revealed no bias ( P = .489). Automated versus microscopic counts revealed no bias between methodologies ( P = .787) and a lower correlation coefficient ( R2 = 0.384). Semiautomated versus microscopic counts revealed no bias with respect to magnitude of measurement for either observer ( P = .327, .229); Pearson correlation was 0.985 ( R2 = 0.970) and 0.965 ( R2 = 0.931) for observer 1 and 2. Semiautomated versus manual pen colony counts revealed a significant bias with respect to magnitude of measurement ( P < .001). Conclusion Counting with a manual pen demonstrated significant bias when compared to microscopic and semiautomated colony counts; 2 methods were deemed to be interchangeable. Thus, training algorithms based on manual counts may introduce this bias as well. Algorithms trained to select colonies based on size (pixels2) and shape (circularity) should be prioritized. Solely relying on Bland–Altman or correlational analyses when determining method interchangeability should be avoided; they rather should be used in conjunction.