Incorporating cross-voxel exchange into the analysis of dynamic contrast-enhanced imaging data: theory, simulations and experimental results

Noha Sinno; Edward Taylor; Michael Milosevic; David A Jaffray; Catherine Coolens

doi:10.1088/1361-6560/ac2205

Incorporating cross-voxel exchange into the analysis of dynamic contrast-enhanced imaging data: theory, simulations and experimental results

Phys Med Biol. 2021 Oct 14;66(20). doi: 10.1088/1361-6560/ac2205.

Authors

Noha Sinno^{1

2}, Edward Taylor^{2

3

4}, Michael Milosevic^{2

3

5}, David A Jaffray^{2

3

6

4

7}, Catherine Coolens^{1

2

3

6

4}

Affiliations

¹ The Institute of Biomedical Engineering (BME), University of Toronto, Toronto, Canada.
² Princess Margaret Cancer Centre, University Health Network, Toronto, Canada.
³ Department of Radiation Oncology, University of Toronto, Toronto, Canada.
⁴ TECHNA Institute, University Health Network, Toronto, Canada.
⁵ Institute of Medical Science, University of Toronto, Toronto, Canada.
⁶ Department of Medical Biophysics, University of Toronto, Toronto, Canada.
⁷ University of Texas, MD Anderson Cancer Centre, Texas, United States of America.

PMID: 34650009
DOI: 10.1088/1361-6560/ac2205

Abstract

Predictions of tumour perfusion are key determinants of drug delivery and responsiveness to therapy. Pharmacokinetic models allow for the estimation of perfusion properties of tumour tissues but many assume no dispersion associated with tracer transport away from the capillaries and through the tissue. At the level of a voxel, this translates to assuming no cross-voxel tracer exchange, often leading to the misinterpretation of derived perfusion parameters. Tofts model (TM), a compartmental model widely used in oncology, also makes this assumption. A more realistic description is required to quantify kinetic properties of tracers, such as convection and diffusion. We propose a Cross-Voxel Exchange Model (CVXM) for analysing cross-voxel tracer kinetics.In silicodatasets quantifying the roles of convection and diffusion in tracer transport (which TM ignores) were employed to investigate the interpretation of Tofts' perfusion parameters compared to CVXM. TM returned inaccurate values ofKtransandvewhere diffusive and convective mechanisms are pronounced (up to 20% and 300% error respectively). A mathematical equation, developed in this work, predicts and gives the correct physiological interpretation of Tofts've.Finally, transport parameters were derived from dynamic contrast enhanced-magnetic resonance imaging of a TS-415 human cervical carcinoma xenograft by using TM and CVXM. The latter deduced lower values ofKtransandvecompared to TM (lower by up to 63% and 76% respectively). It also allowed the detection of a diffusive flux (mean diffusivity 155μm²s^-1) in the tumour tissue, as well as an increased convective flow at the periphery (mean velocity 2.3μm s^-1detected). The results serve as a proof of concept establishing the feasibility of using CVXM for accurately determining transport metrics that characterize the exchange of tracer between voxels. CVXM needs to be investigated further as its parameters can be linked to the tumour microenvironment properties (permeability, pressure…), potentially leading to enhanced personalized treatment planning.

Keywords: Tofts model; compartmental models; convection; cross-voxel transport; diffusion; transport model; tumour tissue.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Contrast Media* / pharmacokinetics
Diffusion Magnetic Resonance Imaging
Female
Humans
Kinetics
Magnetic Resonance Imaging / methods
Tumor Microenvironment
Uterine Cervical Neoplasms*

Substances

Contrast Media

Grants and funding

CIHR/Canada