Two-dimensional matrix algorithm using detrended fluctuation analysis to distinguish Burkitt and diffuse large B-cell...

Area of Science:

• Medical image analysis
• Hematopathology
• Biophysics

Background:

• Burkitt lymphoma (BL) and diffuse large B-cell lymphoma (DLBCL) exhibit distinct 5-year survival rates post-chemotherapy.
• Accurate differentiation between BL and DLBCL is crucial for effective treatment strategies.

Purpose of the Study:

• To apply a 2-dimensional detrended fluctuation analysis (2D DFA) method for recharacterizing lymph section images.
• To evaluate the efficacy of 2D DFA in distinguishing between BL and DLBCL based on image characteristics.

Main Methods:

• Utilized 2-dimensional detrended fluctuation analysis (2D DFA) on digital images of lymph sections.
• Classified 18 BL images into Group A (1-5 cytogenetic changes) and Group B (>5 cytogenetic changes).
• Classified 10 DLBCL images into Group C.

Main Results:

• The short-term correlation exponent (α1) values for Groups A, B, and C were 0.370 ± 0.033, 0.382 ± 0.022, and 0.435 ± 0.053, respectively.
• A significantly lower α1 value was observed in BL images (Groups A and B) compared to DLBCL images (Group C) (P < 0.05).
• No significant difference in α1 values was found between the two BL groups (A and B).

Conclusions:

• The α1 value derived from 2D DFA statistical analysis can effectively differentiate between BL and DLBCL lymph section images.
• 2D DFA provides a quantitative method for distinguishing aggressive lymphomas with different prognoses.