Primary systemic (neoadjuvant) therapy is routinely used for locally advanced breast cancer patients before surgery to down-stage the disease and increase the chances of a successful outcome. Many patients though do not respond to neoadjuvant therapy, and may be better off switching to a different treatment regime, or progressing to surgery immediately. However, therapy monitoring is difficult because current clinical examination and x-ray/ultrasound mammography follow-ups correlate poorly with final therapy pathological outcome. Both magnetic resonance imaging (MRI) and positron emission tomography (PET) have been evaluated as early predictors of response, with studies showing that 18F-FDG PET as well as diffusion weighted (DW) MRI and choline-compounds MR spectroscopy (tCho-MRS) measurements correspond well with therapy success within a few weeks from the beginning of treatment. Unfortunately, availability (PET), complexity (tCho-MRS), and specificity (MRI) limit the applicability of these methods. Consequently, there is a need to develop non-invasive specific early prediction approaches that more easily integrate into medical practice. A potential answer may be offered by near infrared spectroscopy and tomography (NIRS-DOT). NIRS-DOT is a novel functional imaging technique that can offer images of tissue chromophores such as oxy (HbO) and deoxy hemoglobin (HbR), water and lipids, and small studies have hinted at its potential to predict therapy outcome with high accuracy as early as one week after the start of treatment. Further, recent technological advancements have permitted DOT to reach high time resolution (>1Hz), allowing new types of functional information to be probed by dynamic imaging. In particular, our group has obtained promising initial results monitoring the response of breast tissue to external compression. Tissue viscoelastic response to compression causes hemodynamic (blood volume) changes with bi-phasic temporal profiles likely to differentiate healthy tissues from breast lesions. Further, the interplay of hemodynamics and tissue oxygen metabolism leads to hemoglobin oxygenation transients that offer the opportunity to estimate tissue oxygen consumption (OC) and blood flow (BF) from time-resolved optical data. The overall goal of this proposal is to combine MRI and NIRS-DOT to characterize the predictive value of compression-enabled measurements of tissue hemodynamics, blood flow and oxygen consumption as new biomarkers sensitive to therapy progress and quantify their relationship to final pathological outcome. Structural information from the MRI scans will be used as prior information for the optical reconstructions and dynamic optical and HbR-related MR blood oxygen level dependent (BOLD) images will be simultaneously acquired enabling a fusion approach for reconstructing time-resolved hemodynamic maps and BF/OC distributions. Difference BOLD images will be cross-validated against corresponding HbR maps. The work will culminate with a clinical trial to assess the early therapy outcome predictive ability of the new biomarkers.

Public Health Relevance

We propose to use fast optical tomography during breast compression to investigate biomechanical and metabolic characteristics of normal and lesion tissues, with the goal of improving specificity for cancer diagnosis and non-invasively monitoring chemotherapy progress.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Transition Award (R00)
Project #
5R00EB011889-05
Application #
8665421
Study Section
Special Emphasis Panel (NSS)
Program Officer
Conroy, Richard
Project Start
2010-06-10
Project End
2015-05-31
Budget Start
2014-06-01
Budget End
2015-05-31
Support Year
5
Fiscal Year
2014
Total Cost
$241,530
Indirect Cost
$98,718
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Deng, Bin; Lundqvist, Mats; Fang, Qianqian et al. (2018) Impact of errors in experimental parameters on reconstructed breast images using diffuse optical tomography. Biomed Opt Express 9:1130-1150
Zimmermann, Bernhard B; Deng, Bin; Singh, Bhawana et al. (2017) Multimodal breast cancer imaging using coregistered dynamic diffuse optical tomography and digital breast tomosynthesis. J Biomed Opt 22:46008
Zimmermann, Bernhard B; Fang, Qianqian; Boas, David A et al. (2016) Frequency domain near-infrared multiwavelength imager design using high-speed, direct analog-to-digital conversion. J Biomed Opt 21:16010
Selb, Juliette; Boas, David A; Chan, Suk-Tak et al. (2014) Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia. Neurophotonics 1:
Carp, Stefan A; Sajjadi, Amir Y; Wanyo, Christy M et al. (2013) Hemodynamic signature of breast cancer under fractional mammographic compression using a dynamic diffuse optical tomography system. Biomed Opt Express 4:2911-24