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Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography

Abstract

Purpose

The purpose of the study was to assess the utility of tumor biomarkers, ultrasound (US) and US-guided diffuse optical tomography (DOT) in early prediction of breast cancer response to neoadjuvant therapy (NAT).

Methods

This prospective HIPAA compliant study was approved by the institutional review board. Forty one patients were imaged with US and US-guided DOT prior to NAT, at completion of the first three treatment cycles, and prior to definitive surgery from February 2017 to January 2020. Miller-Payne grading was used to assess pathologic response. Receiver operating characteristic curves (ROCs) were derived from logistic regression using independent variables, including: tumor biomarkers, US maximum diameter, percentage reduction of the diameter (%US), pretreatment maximum total hemoglobin concentration (HbT) and percentage reduction in HbT (%HbT) at different treatment time points. Resulting ROCs were compared using area under the curve (AUC). Statistical significance was tested using two-sided two-sample student t-test with P < 0.05 considered statistically significant. Logistic regression was used for ROC analysis.

Results

Thirty-eight patients (mean age = 47, range 24–71 years) successfully completed the study, including 15 HER2 + of which 11 were ER + ; 12 ER + or PR + /HER2−, and 11 triple negative. The combination of HER2 and ER biomarkers, %HbT at the end of cycle 1 (EOC1) and %US (EOC1) provided the best early prediction, AUC = 0.941 (95% CI 0.869–1.0). Similarly an AUC of 0.910 (95% CI 0.810–1.0) with %US (EOC1) and %HbT (EOC1) can be achieved independent of HER2 and ER status. The most accurate prediction, AUC = 0.974 (95% CI 0.933–1.0), was achieved with %US at EOC1 and %HbT (EOC3) independent of biomarker status.

Conclusion

The combined use of tumor HER2 and ER status, US, and US-guided DOT may provide accurate prediction of NAT response as early as the completion of the first treatment cycle.

Clinical Trial Registration number: NCT02891681. https://clinicaltrials.gov/ct2/show/NCT02891681, Registration time: September 7, 2016

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Fig. 1
Fig. 2

source laser diodes of 730 nm, 785 nm, 808 nm and 830 nm optical wavelengths were sequentially switched to nine source positions (pointed by an arrow) on the probe, while the reflected light was coupled by the 14 light guides (pointed by an arrow) to 14 parallel detectors

Fig. 3
Fig. 4
Fig. 5
Fig. 6

Data availability

The patients’ clinicopathologic characteristics are given in Table 1. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Code availability

The code is available from the corresponding author on reasonable request.

Abbreviations

NIR:

Near infrared

pCR:

Pathological complete response

ROI:

Region of interest

ER:

Estrogen receptor

PR:

Progesterone receptor

HER2:

Human epidermal growth factor receptor 2

TNBC:

Triple-negative breast cancer

MP:

Miller-Payne grade

RCB:

Residual cancer burden

NAT:

Neoadjuvant therapy

HbT:

Total hemoglobin

ROC:

Receiver operating characteristic curve

AUC:

Area under receiving operating characteristic curve

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Acknowledgements

The authors appreciate the help of Clinical Trial Office of the Oncology Department of Washington University School of Medicine for patient consenting and scheduling. Drs. Catherine Young, Catherine Appleton, Matthew F. Covington, were faculty members of Radiology Department of Washington University in St Louis from the beginning of the study to July 2019. Dr. Steven Poplack was a faculty member of Radiology Department of Washington University in St Louis from the beginning of the study to June 2020.

Funding

This study was funded by National Institutes of Health (R01EB002136, R01 CA228047). SPP acknowledges funding support from the Foundation for Barnes Jewish Hospital Ronald and Hanna Evens Endowed Chair in Women’s Health.

Author information

Authors and Affiliations

Authors

Contributions

QZ: designed and conducted all aspects of the ultrasound-guided optical tomography data acquisition, image reconstruction and data analysis and contributed to the manuscript preparation and literature review. SPP: designed and conducted patient imaging studies, data analysis, and contributed to the manuscript preparation and literature review. FOA and CM: coordinated and recruited patients to the study, and contributed to the manuscript review and literature review. CY, CA, MFC: contributed to the imaging studies, imaging interpretations, and manuscript review. SS and ISH: contributed to the pathological data evaluations, interpretations, manuscript review. AM and K.M.S.U: contributed to the development of optical tomography system hardware and software as well as imaging algorithm. IG: coordinated, consented all study patients, and data analysis. AEF and LFH: contributed to patient recruitments. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Quing Zhu.

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Conflict of interest

QZ is the inventor of the patents related to ultrasound-guided near-infrared tomography technologies and patents owned by the University of Connecticut and/or Washington University in St Louis. She has no conflicts of interest. All authors declare that they have no conflicts of interests.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Research involving human and animal rights

This article does not contain any studies with animals performed by any of the authors.

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All authors have read the manuscript and agreed with the submission.

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Supplementary Information

Below is the link to the electronic supplementary material.

10549_2021_6239_MOESM1_ESM.docx

We developed treatment prediction models using data of 38 patients from this manuscript and data of 22 patients from an earlier study. Results are similar to the regression analysis reported in the manuscript. Please see the supplement materials for details. (DOCX 174 kb)

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Zhu, Q., Ademuyiwa, F.O., Young, C. et al. Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography. Breast Cancer Res Treat 188, 615–630 (2021). https://doi.org/10.1007/s10549-021-06239-y

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Keywords

  • Predicting neoadjuvant therapy
  • Personalized medicine
  • Near Infrared imaging
  • Ultrasound