Abstract
Vascular hydraulic conductivity (Lp) plays important roles in cancer metastasis, progression, and treatments. To date, there are a few noninvasive methods to image Lp in cancers, and these methods rely on several assumptions. Common assumptions include that vascular conductivity is dominant over interstitial conductivity inside the tumor and that interstitial effects in the background are dominant over interstitial effects inside the tumor, limiting their applicability to cancers with a narrow range of Lp. In this article, we propose a new method to image a wide range of Lp in cancers using ultrasound spatiotemporal elastography data, without the limitations of existing methods. The method is based on the knowledge of Young's modulus, Poisson's ratio, and volumetric strain. This method shows superior performance with respect to the previous methods in terms of percent-relative-error in simulation studies. In vivo experimental results in an orthotopic mouse model of breast cancer show that Lp estimated by ultrasound imaging using the proposed method is highly correlated with histological CD31 data. The proposed imaging methods can thus provide clinically significant information noninvasively and cost-effectively.
| Original language | English |
|---|---|
| Article number | pgaf354 |
| Journal | PNAS Nexus |
| Volume | 4 |
| Issue number | 11 |
| DOIs | |
| State | Published - Nov 1 2025 |
Funding
We thank Anthony Wood and Robin Vander Pol from Houston Methodist Research Institute, TX to assist in performing in vivo experiments. This work was supported in part by the U.S. Department of Defense under grant W81XWH-18-1-0544 (BC171600) and Cancer Prevention and Research Institute of Texas (CPRIT) under grant #RP200452. This work was supported in part by the U.S. Department of Defense under grant W81XWH-18-1-0544 (BC171600) and Cancer Prevention and Research Institute of Texas (CPRIT) under grant #RP200452.
Keywords
- cancer imaging
- poroelastic
- poroelastography
- vascular hydraulic permeability
- vessel density