Open Access
14 September 2024 Monte Carlo simulation of spatial frequency domain imaging for breast tumors during compression
Constance M. Robbins, Kuanren Qian, Yongjie Jessica Zhang, Jana M. Kainerstorfer
Author Affiliations +
Abstract

Significance

Near-infrared optical imaging methods have shown promise for monitoring response to neoadjuvant chemotherapy (NAC) for breast cancer, with endogenous contrast coming from oxy- and deoxyhemoglobin. Spatial frequency domain imaging (SFDI) could be used to detect this contrast in a low-cost and portable format, but it has limited imaging depth. It is possible that local tissue compression could be used to reduce the effective tumor depth.

Aim

To evaluate the potential of SFDI for therapy response prediction, we aim to predict how changes to tumor size, stiffness, and hemoglobin concentration would be reflected in contrast measured by SFDI under tissue compression.

Approach

Finite element analysis of compression on an inclusion-containing soft material is combined with Monte Carlo simulation to predict the measured optical contrast.

Results

When the effect of compression on blood volume is not considered, contrast gain from compression increases with the size and stiffness of the inclusion and decreases with the inclusion depth. With a model of reduction of blood volume from compression, compression reduces imaging contrast, an effect that is greater for larger inclusions and stiffer inclusions at shallower depths.

Conclusions

This computational modeling study represents a first step toward tracking tumor changes induced by NAC using SFDI and local compression.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
Constance M. Robbins, Kuanren Qian, Yongjie Jessica Zhang, and Jana M. Kainerstorfer "Monte Carlo simulation of spatial frequency domain imaging for breast tumors during compression," Journal of Biomedical Optics 29(9), 096001 (14 September 2024). https://doi.org/10.1117/1.JBO.29.9.096001
Received: 17 April 2024; Accepted: 19 August 2024; Published: 14 September 2024
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KEYWORDS
Monte Carlo methods

Tumors

Tissues

Breast

Voxels

Optical properties

Biomedical optics

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