Convective-Dispersion Modeling in 3D Contrast-Ultrasound Imaging for the Localization of Prostate Cancer.

Area of Science:

• Medical Imaging
• Biophysics
• Oncology

Background:

• Prostate cancer (PCa) is the most common solid tumor in Western men, yet lacks definitive imaging for lesion localization.
• Current diagnostic methods often require invasive systematic biopsies.
• Dynamic contrast-enhanced ultrasound imaging (DCE-US) offers quantitative vascular characterization in the prostate.

Purpose of the Study:

• To develop and validate a novel method for assessing contrast agent convective dispersion (D) and velocity (v) using 3D DCE-US.
• To evaluate the diagnostic value of these parameters for localizing PCa lesions.

Main Methods:

• A novel method was developed to solve the convective-dispersion equation from 3D DCE-US data, assuming locally constant D and v.
• This involved minimizing a regularized least-squares problem to generate 3D multiparametric maps of D and v.
• The generated maps were compared with 3D histopathology from radical prostatectomy specimens.

Main Results:

• The proposed method generated 3D multiparametric maps of convective dispersion (D) and velocity (v).
• Comparison with 3D histopathology showed diagnostic value for PCa localization.
• The pixel-wise area under the receiver operating characteristic curve was 0.72 for D and 0.80 for v.

Conclusions:

• The novel 3D DCE-US method provides quantitative maps of contrast bolus transport parameters (D and v).
• These parameters demonstrate significant diagnostic value in accurately localizing prostate cancer lesions.
• This technique holds potential for improving PCa diagnosis and reducing reliance on biopsies.