Inter-Vendor Variability of Perfusion Parameters Derived from Dynamic Contrast-Enhanced MRI in Patients with Prostate...

Area of Science:

• Radiology and Imaging Science
• Oncology and Cancer Research
• Medical Physics and Biomedical Engineering

Background:

• Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) is crucial for assessing prostate cancer (PCa) characteristics.
• Perfusion parameters derived from DCE-MRI, such as K^trans, k_ep, v_e, and v_p, provide insights into tumor vascularity and permeability.
• The variability in perfusion parameter quantification across different commercial software solutions necessitates investigation into their agreement.

Purpose of the Study:

• To evaluate the agreement of perfusion parameters calculated using two distinct commercial DCE-MRI software solutions.
• To assess the reproducibility and comparability of key perfusion metrics (K^trans, k_ep, v_e, v_p) in prostate cancer patients.

Main Methods:

• Retrospective analysis of DCE-MRI data from 50 prostate cancer patients who underwent radical prostatectomy.
• Tumor segmentation performed by consensus of two radiologists following radiologic-pathologic correlation.
• Calculation of four perfusion parameters using two different commercial solutions, both employing an extended Tofts model and population-based arterial input function.

Main Results:

• Significant differences (p < 0.0001) were observed for all calculated perfusion parameters (K^trans, k_ep, v_e, v_p) between the two solutions.
• Mean differences ranged from -0.029 (v_p) to -0.763 (k_ep), indicating systematic discrepancies.
• Intraclass correlation coefficients (ICCs) for average measures showed poor to moderate agreement, with values ranging from -0.133 (v_e) to 0.688 (k_ep).

Conclusions:

• The two commercial DCE-MRI solutions yield significantly different perfusion parameter values for prostate cancer.
• The observed discrepancies and poor agreement suggest that direct comparison of perfusion parameters across these solutions is not advisable.
• Clinical interpretation and treatment decisions based on DCE-MRI perfusion parameters require careful consideration of the software solution used.