Abstract
Diffuse large B-cell lymphoma, not otherwise specified (DLBCL, NOS) is a heterogenous group of aggressive lymphomas. C-MYC expression by immunohistochemical stain (IHC) is shown to be an independent prognostic factor in DLBCL. In the clinical setting, MYC stain is currently evaluated by manual quantification with a minimum positivity cut-off 40%. Manual quantification methods can be subjective and may show intra- and interobserver variability and variability between centers. Thus, stains which require definitive quantification such as MYC needs better standardized and precise methods. Here we present a simple digital algorithm for quantitative evaluation of MYC stain in DLBCL, NOS. For this, slides immunostained for C-MYC were scanned at 40X with a high-resolution, Philips Ultra Fast scanner (Koninklijke Philips N.V. Cambridge, MA). The images were manually assessed and appropriate areas with neoplastic cells were selected. For quantification, positive and negative C-MYC staining nuclei were scored using a modified Visiopharm APP Nuclei Detection, AI (Brightfield) using Visiopharm Image Analysis software (Visiopharm, Hørsholm, Denmark version 2018.09). The percentage positivity resulted by the digital method was concordant with the pathologist's interpretation with statistical significance (rs: 0.85968; p (2-tailed) = 0). Minor disadvantages were observed including failure to detect very weak staining and inability to separate neoplastic and non-neoplastic nuclei when admixed in the same area. If combined with a quick manual evaluation, a digital method like this with precision and reproducibility will be of great use in quantitative evaluation of MYC and other similar stains in clinical setting and will reduce intra- and interobserver variability.