Feasibility of spatial frequency domain imaging (SFDI) for optically characterizing a preclinical oncology model

Abstract

Determination of chemotherapy efficacy early during treatment would provide more opportunities for physicians to alter and adapt treatment plans. Diffuse optical technologies may be ideally suited to track early biological events following chemotherapy administration due to low cost and high information content. We evaluated the use of spatial frequency domain imaging (SFDI) to characterize a small animal tumor model in order to move towards the goal of endogenous optical monitoring of cancer therapy in a controlled preclinical setting. The effects of key measurement parameters including the choice of imaging spatial frequency and the repeatability of measurements were evaluated. The precision of SFDI optical property extractions over repeat mouse measurements was determined to be within 3.52% for move and replace experiments. Baseline optical properties and chromophore values as well as intratumor heterogeneity were evaluated over 25 tumors. Additionally, tumor growth and chemotherapy response were monitored over a 45 day longitudinal study in a small number of mice to demonstrate the ability of SFDI to track treatment effects. Optical scattering and oxygen saturation increased as much as 70% and 25% respectively in treated tumors, suggesting SFDI may be useful for preclinical tracking of cancer therapies.

Diffuse and nonlinear imaging of multiscale vascular parameters for in vivo monitoring of preclinical mammary tumors

“…The choice of SFDI f x pairs affects both the depth sensitivity of SFDI (as demonstrated in the previous section), as well as the ability to accurately extract optical properties . To assess tradeoffs between these two factors, we quantified optical property uncertainties for DC and 0.1 mm −1 , and 0.05 and 0.1 mm −1 given that the former has been identified as a f x pair that minimizes optical property extraction errors , and the latter was found to provide good agreement in depth sensitivity between SFDI and MPM. We found that there was good agreement in extracting optical properties between the two spatial frequency pairs for a range of optical properties (Figure ).…”

Two-layer inverse model for improved longitudinal preclinical tumor imaging in the spatial frequency domain

“…For example, we have shown in a previous study that spatial frequency domain imaging (SFDI) can be used to monitor the in vivo tumor state of a subcutaneous tumor xenograft model grown in mouse over a period of 45 days. 11 SFDI is a widefield DOI modality, capable of tracking the same noninvasive and label-free metrics measured using clinical DOI modalities and is well suited for preclinical oncology work given its shallower penetration depth (typically mm). 11,12 Much of the prior published works using SFDI for both small animal and clinical research have utilized the assumption of homogeneity in depth when extracting optical properties from tissue.…”

“…11 SFDI is a widefield DOI modality, capable of tracking the same noninvasive and label-free metrics measured using clinical DOI modalities and is well suited for preclinical oncology work given its shallower penetration depth (typically mm). 11,12 Much of the prior published works using SFDI for both small animal and clinical research have utilized the assumption of homogeneity in depth when extracting optical properties from tissue. [13][14][15][16] For example, in our prior preclinical monitoring study, we modeled mouse tumor tissue as a semi-infinite homogeneous medium and used the results of a Monte Carlo (MC) simulation to create a look-up-table (LUT) inversion algorithm to recover optical property estimates from SFDI measurements of diffuse reflectance.…”

“…[13][14][15][16] For example, in our prior preclinical monitoring study, we modeled mouse tumor tissue as a semi-infinite homogeneous medium and used the results of a Monte Carlo (MC) simulation to create a look-up-table (LUT) inversion algorithm to recover optical property estimates from SFDI measurements of diffuse reflectance. 11 However, tissue geometry is complex, and in the case of subcutaneous tumors in mice, a thin skin layer is located above the tumor, which remains unaccounted for in a homogeneous model. Although there are several prior studies that have described inversion algorithms that utilize a layered-tissue structure [17][18][19][20][21] or utilize tomographic reconstructions with SFDI, 22,23 we describe, in this work, the first use of MC simulations conducted natively in the spatial frequency domain to make a two-layer LUT inversion algorithm that closely matches the true physiology and optical characteristics of preclinical tumor models.…”

Compressed single pixel imaging in the spatial frequency domain

“…SFDI techniques have been utilized widely to characterize tissue composition and function in humans, 3,4 animal models, and ex vivo tissue specimens. 5,6 There is generally a tradeoff between spectral and spatial information content in SFDI instruments. This is due to the fact that wide-field imaging is typically performed serially at several discrete wavelengths using selective illumination and/or optical filters.…”