Diagnostic Potential of Apparent Diffusion Coefficient-Based Lymph Node Classification in Breast Cancer Patients...

Area of Science:

• Oncology
• Radiology
• Medical Imaging

Background:

• Accurate lymph node staging is crucial for breast cancer patient management.
• Distinguishing between benign and malignant lymph nodes can be challenging with conventional imaging.
• Integrating advanced MRI techniques may improve diagnostic accuracy.

Purpose of the Study:

• To assess the diagnostic utility of apparent diffusion coefficient (ADC) values for classifying lymph nodes in breast cancer patients.
• To correlate ADC values with [18F]FDG-PET/MRI findings for nodal malignancy.
• To evaluate ADC as a potential imaging biomarker for lymph node characterization.

Main Methods:

• Retrospective analysis of 199 thoracic lymph nodes in 113 newly diagnosed breast cancer patients.
• Patients underwent [18F]FDG-PET/MRI staging between July 2017 and June 2021.
• Mean ADC values and short-axis diameters were compared with pathological node status and nodal FDG uptake.

Main Results:

• FDG-positive lymph nodes exhibited significantly lower ADC values (0.72 ± 0.14 × 10^-3 mm²/s) compared to FDG-negative nodes (1.18 ± 0.18 × 10^-3 mm²/s).
• An ADC cut-off of 0.95 × 10^-3 mm²/s demonstrated high diagnostic performance (AUC: 0.98).
• ADC values achieved 98% sensitivity, 97% specificity, and 97% accuracy in differentiating lymph node types.

Conclusions:

• Apparent diffusion coefficient (ADC) values derived from MRI are significantly associated with [18F]FDG uptake in lymph nodes.
• ADC values show strong potential as a complementary imaging biomarker for lymph node characterization in breast cancer.
• This finding may enhance the accuracy of breast cancer staging and treatment planning.