Quantification of viable tumor microvascular characteristics by multispectral analysis

Area of Science:

• Biomedical Imaging
• Oncology
• Radiology

Background:

• Tumor heterogeneity complicates microvascular quantification using dynamic contrast-enhanced MRI (DCE-MRI).
• Accurate assessment of tumor microvasculature is crucial for evaluating treatment efficacy.

Purpose of the Study:

• To develop and validate a novel approach combining DCE-MRI with diffusion-based multispectral (MS) analysis for quantifying microvascular characteristics in specific tumor tissue populations.
• To evaluate the ability of this MS DCE-MRI technique to detect microvascular changes following anti-VEGF treatment.

Main Methods:

• Diffusion-based MS segmentation using apparent diffusion coefficient, T(2), and proton density to identify distinct tumor tissue populations.
• Quantification of DCE-MRI parameters (e.g., K(trans)) within each identified tissue class.
• Evaluation in a tumor xenograft mouse model treated with an antibody to vascular endothelial growth factor-A (VEGF).

Main Results:

• Anti-VEGF treatment significantly reduced K(trans) in the MS viable tumor tissue class by 62% compared to pretreatment values (P < 0.01).
• A significant reduction in K(trans) was observed 24 hours posttreatment in the anti-VEGF group compared to controls (P < 0.01).
• Necrotic tissue classes did not provide meaningful data and introduced noise into DCE-MRI estimates.

Conclusions:

• The developed MS DCE-MRI approach effectively quantifies microvascular parameters within viable tumor tissue.
• This technique addresses tumor heterogeneity, improving the accuracy of DCE-MRI analysis for assessing treatment response.
• MS DCE-MRI shows promise for monitoring therapeutic effects targeting tumor vasculature.