We propose to validate the potential role of our novel near-infrared (NIR) diffuse optical tomography guided by ultrasound (NIR/US) imaging system in assessing patient pathological response to neoadjuvant chemotherapy (NAC). NIR/US is implemented by simultaneously deploying NIR optical sensors and a commercial ultrasound transducer on a hand-held probe, and utilizing co-registered ultrasound to provide lesion structure information and guide optical tomography reconstruction. As a result, the optical tomography has overcome problems associated with intense light scattering and has provided reliable tumor hemoglobin distributions, which are directly related to tumor angiogenesis. Pilot data obtained from 32 patients who underwent NAC, which was assessed by NIR/US, have demonstrated that pretreatment tumor total hemoglobin (tHb) content predicts patient final pathological response with 79% sensitivity and 80% specificity. In addition, the percentage of total hemoglobin changes normalized to the pretreatment level (%tHb) can be used to further identify responders from non-responders at the end of cycle 1 (2-3 weeks) after the initiation of NAC. Furthermore, combining widely used tumor pathologic variables and receptor status with hemoglobin functional parameters obtained before the initiation of NAC can achieve 100% prediction sensitivity and specificity when baseline scatter data are included, or treatment regimens are categorized based on human epidermal growth factor receptor 2 (HER-2/neu) or the addition of %tHb at the end of treatment cycle 1 is assessed. In this proposal, we will: 1) Upgrade NIR imaging systems and validate NIR imaging algorithms optimized for imaging large lesions;2) Validate the initial findings through the recruitment of approximately 80 patients who are undergoing NAC at the Hartford Hospital, the University of Connecticut Health Center, and the Waterbury Hospital;and 3) Perform data analysis a) to determine the best time-window to assess response based on cycle 1 %tHb for different treatment regimens;b) to validate the prediction model developed from pilot data based on tumor pathological variables (tumor type, grade and mitotic count), tumor molecular markers of estrogen receptor (ER), progesterone receptor (PR), and HER-2/neu, and pretreatment NIR functional parameters as well as scatter data and response rate based on one cycle of %tHb. The successful completion of the project will result in a powerful tool to manage personalized breast cancer treatment. In the genomic era of personalized medicine where predicting and monitoring of early responses for outcome prediction becomes crucial, our NIR/US technology will prove to be invaluable.

Public Health Relevance

In this project, an ultrasound-guided near infrared tomography technique will be refined and validated for imaging locally advanced breast cancers in patients who are undergoing neoadjuvant chemotherapy. Approximately, 80 patients will be recruited from three hospitals and their responses to neoadjuvant treatment will be assessed pretreatment, at early treatment cycles, and prior to surgery. This larger patient pool will be use a) to determine the best time- window to assess response based on cycle 1 %tHb for different treatment regimens;b) to validate the prediction model developed from pilot data based on tumor pathological variables (tumor type, grade and mitotic count), tumor molecular markers of estrogen receptor (ER), progesterone receptor (PR), and HER-2/neu, and pretreatment NIR functional parameters as well as response rate based on one cycle of %tHb. The successful completion of the project will provide a means to improve the current clinical practice by accurately predicting an individual patient's response.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
2R01EB002136-09A1
Application #
8636133
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Lopez, Hector
Project Start
2002-09-01
Project End
2017-08-31
Budget Start
2013-09-30
Budget End
2014-08-31
Support Year
9
Fiscal Year
2013
Total Cost
$382,694
Indirect Cost
$108,463
Name
University of Connecticut
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
614209054
City
Storrs-Mansfield
State
CT
Country
United States
Zip Code
06269
Tavakoli, Behnoosh; Zhu, Quing (2013) Two-step reconstruction method using global optimization and conjugate gradient for ultrasound-guided diffuse optical tomography. J Biomed Opt 18:16006
Zanganeh, Saeid; Li, Hai; Kumavor, Patrick D et al. (2013) Photoacoustic imaging enhanced by indocyanine green-conjugated single-wall carbon nanotubes. J Biomed Opt 18:096006
Xu, Yan; Zanganeh, Saeid; Mohammad, Innus et al. (2013) Targeting tumor hypoxia with 2-nitroimidazole-indocyanine green dye conjugates. J Biomed Opt 18:66009
Tavakoli, Behnoosh; Zhu, Quing (2011) Depth-correction algorithm that improves optical quantification of large breast lesions imaged by diffuse optical tomography. J Biomed Opt 16:056002
Biswal, Nrusingh C; Xu, Yan; Zhu, Quing (2011) Imaging tumor oxyhemoglobin and deoxyhemoglobin concentrations with ultrasound-guided diffuse optical tomography. Technol Cancer Res Treat 10:417-29
Ardeshirpour, Yasaman; Biswal, Nrusingh; Aguirre, Andres et al. (2011) Artifact reduction method in ultrasound-guided diffuse optical tomography using exogenous contrast agents. J Biomed Opt 16:046015
Xu, Yan; Xu, Chen; Zhu, Quing (2011) Clustered targets imaged by optical tomography guided by ultrasound. J Biomed Opt 16:076018
Gamelin, John K; Aguirre, Andres; Zhu, Quing (2011) Fast, limited-data photoacoustic imaging for multiplexed systems using a frequency-domain estimation technique. Med Phys 38:1503-18
Kumavor, Patrick D; Tavakoli, Behnoosh; Donkor, Eric et al. (2011) Time-gating scheme based on a photodiode for single-photon counting. Opt Lett 36:2501-3
Kumavor, Patrick D; Xu, Chen; Aguirre, Andres et al. (2011) Target detection and quantification using a hybrid hand-held diffuse optical tomography and photoacoustic tomography system. J Biomed Opt 16:046010

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