Spatial frequency analysis of anisotropic drug transport in tumor samples

Stewart Russell,Kimberley S Samkoe,Thienan A Nguyen,P Jack Hoopes,Robert R Alfano,Brian W Pogue,Milo J Russell,Jason R Gunn

doi:10.1117/1.jbo.19.1.015005

Abstract

Directional Fourier spatial frequency analysis was used on standard histological sections to identify salient directional bias in the spatial frequencies of stromal and epithelial patterns within tumor tissue. This directional bias is shown to be correlated to the pathway of reduced fluorescent tracer transport. Optical images of tumor specimens contain a complex distribution of randomly oriented aperiodic features used for neoplastic grading that varies with tumor type, size, and morphology. The internal organization of these patterns in frequency space is shown to provide a precise fingerprint of the extracellular matrix complexity, which is well known to be related to the movement of drugs and nanoparticles into the parenchyma, thereby identifying the characteristic spatial frequencies of regions that inhibit drug transport. The innovative computational methodology and tissue validation techniques presented here provide a tool for future investigation of drug and particle transport in tumor tissues, and could potentially be used a priori to identify barriers to transport, and to analyze real-time monitoring of transport with respect to therapeutic intervention.

Highlights

The challenge of characterizing the seemingly random geometric relationships between the visible biological features of tissues can be simplified by examining the Fourier spatial frequency (FSF) spectrum of the image.[1]
While the phenomenological features of drug delivery limitations are known, understanding ways to mitigate the problem remains an ongoing research challenge. The characterization of this seemingly random microheterogeneity is an issue that would benefit significantly from automated methods to quantify delivery efficacy. With this as a goal, in this study, the features of tumor sections were analyzed for anisotropic structures and how this relates to flow kinetics, by examining the FSF spectrum of the image features
We show that the characteristic spatial frequency spectrum of intratumor protein associated with directional anisotropy of tracer distribution is a unique identifier of transport barriers and establishs a systematic method of quantifying the relationship between tumor structure and drug distribution

Summary

Introduction

The challenge of characterizing the seemingly random geometric relationships between the visible biological features of tissues can be simplified by examining the Fourier spatial frequency (FSF) spectrum of the image.[1] Drug delivery to tumors is well known to be chaotic and limited, partly from the perfusion limitations of dysfunctional neovasculature, and because of the microscopic regional variations in composition which occur.[2,3] while the phenomenological features of drug delivery limitations are known, understanding ways to mitigate the problem remains an ongoing research challenge. The characterization of this seemingly random microheterogeneity is an issue that would benefit significantly from automated methods to quantify delivery efficacy With this as a goal, in this study, the features of tumor sections were analyzed for anisotropic structures and how this relates to flow kinetics, by examining the FSF spectrum of the image features. This letter presents the conceptual development of how structure could be used to automatically classify transport in systems of wellcharacterized tracers and tumor types

Methods

Results

Conclusion