Physiological modeling of tumor-affected renal circulation

Area of Science:

• Medical Imaging
• Physiological Modeling
• Computational Biology

Background:

• Tumor growth causes anatomical and functional changes in organs, particularly affecting vascularization.
• Understanding these vascular modifications is crucial for diagnosing and monitoring diseases like renal cell carcinoma.

Purpose of the Study:

• To develop a computational model of renal circulation that accounts for kidney heterogeneity in the presence of tumors.
• To simulate vascular alterations and computed tomography (CT) scans of a kidney with renal cell carcinoma.

Main Methods:

• A computational model representing local kidney heterogeneity (cortex, medulla) was developed.
• Simulations included vascular modifications (structure, geometry, density, blood flow) specific to renal cell carcinoma.
• The model was used to simulate CT scans at two post-contrast injection times.

Main Results:

• The model successfully represented tumor-induced vascular changes in the kidney.
• Simulated CT scans reflected expected contrast agent dynamics in diseased renal tissue.
• The framework linked imaging features to underlying physiological perturbations.

Conclusions:

• The proposed physiological and image acquisition model provides a framework for understanding tumor-affected renal circulation.
• This approach can assist radiologists by correlating imaging findings with pathological markers.
• It offers a novel tool for enhancing diagnostic capabilities in renal cell carcinoma detection.