A digital method to interpret the C-MYC stain in diffuse large B cell lymphoma

Area of Science:

• Hematopathology
• Digital Pathology
• Oncology

Background:

• Diffuse large B-cell lymphoma (DLBCL), not otherwise specified (NOS), is an aggressive and heterogeneous lymphoid malignancy.
• C-MYC expression, assessed via immunohistochemical stain (IHC), is a critical independent prognostic factor in DLBCL.
• Current manual quantification of MYC IHC in DLBCL is subjective, leading to significant intra- and interobserver variability.

Purpose of the Study:

• To develop and validate a simple digital algorithm for the precise quantitative evaluation of C-MYC expression in DLBCL, NOS.
• To assess the concordance of the digital method with manual pathological interpretation.
• To address the need for standardized and reproducible methods in quantifying MYC IHC.

Main Methods:

• High-resolution whole slide imaging of C-MYC immunostained DLBCL tissue sections.
• Utilizing Visiopharm Image Analysis software with a modified AI-based nuclei detection algorithm for quantification.
• Manual selection of neoplastic cell areas followed by automated scoring of positive and negative C-MYC nuclei.

Main Results:

• The digital algorithm demonstrated high concordance with pathologist interpretations, showing statistical significance (rs: 0.85968; p=0).
• The method provides precise and reproducible quantification of C-MYC staining percentage.
• Minor limitations included challenges with very weak staining and differentiating neoplastic from non-neoplastic cells in mixed areas.

Conclusions:

• A digital algorithm offers a precise and reproducible method for quantifying C-MYC expression in DLBCL, NOS.
• This digital approach has the potential to significantly reduce interobserver variability in clinical settings.
• Combined with manual review, this digital tool can improve the standardization and reliability of MYC IHC evaluation.