Oncotarget

Research Papers:

Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture

Ali Sadeghi-Naini _, Lakshmanan Sannachi, Kathleen Pritchard, Maureen Trudeau, Sonal Gandhi, Frances C. Wright, Judit Zubovits, Martin J. Yaffe, Michael C. Kolios and Gregory J. Czarnota

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Oncotarget. 2014; 5:3497-3511. https://doi.org/10.18632/oncotarget.1950

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Abstract

Ali Sadeghi-Naini1,2,3,4, Lakshmanan Sannachi1,2,3,4, Kathleen Pritchard5, Maureen Trudeau5, Sonal Gandhi5, Frances C. Wright6,7, Judit Zubovits8, Martin J. Yaffe1,3, Michael C. Kolios3,9, Gregory J. Czarnota1,2,3,4

1 Imaging Research - Physical Sciences, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

2 Department of Radiation Oncology, Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

3 Department of Medical Biophysics, Faculty of Medicine, University of Toronto, Toronto, ON, Canada

4 Department of Radiation Oncology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada

5 Department of Medical Oncology, Sunnybrook Health Sciences Centre, and Faculty of Medicine, University of Toronto, Toronto, ON, Canada

6 Division of General Surgery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada

7 Department of Surgery, Faculty of Medicine, University of Toronto, Toronto, ON, Canada

8 Department of Pathology, Sunnybrook Health Sciences Centre, and Faculty of Medicine, University of Toronto, Toronto, ON, Canada

9 Department of Physics, Ryerson University, Toronto, ON, Canada

Correspondence:

Gregory J. Czarnota, email:

Keywords: Personalized medicine, Therapy response monitoring, Breast Cancer, Neo-adjuvant chemotherapy, Tumor response heterogeneity, Textural analysis, Quantitative ultrasound.

Received: March 12, 2014 Accepted: May 6, 2014 Published: May 7, 2014

Abstract

Early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, in conjunction with changes in their mean values, are demonstrated here, for the first time, to be capable of predicting ultimate clinical/pathologic responses of breast cancer patients to chemotherapy. Mechanisms of cell death, induced by chemotherapy within tumor, introduce morphological alterations in cancerous cells, resulting in measurable changes in tissue echogenicity. We have demonstrated that the development of such changes is reflected in early alterations in textural characteristics of quantitative ultrasound spectral parametric maps, followed by consequent changes in their mean values. The spectral/textural biomarkers derived on this basis have been demonstrated as non-invasive surrogates of breast cancer chemotherapy response. Particularly, spectral biomarkers sensitive to the size and concentration of acoustic scatterers could predict treatment response of patients with up to 80% of sensitivity and specificity (p=0.050), after one week within 3-4 months of chemotherapy. However, textural biomarkers characterizing heterogeneities in distribution of acoustic scatterers, could differentiate between treatment responding and non-responding patients with up to 100% sensitivity and 93% specificity (p=0.002). Such early prediction permits offering effective alternatives to standard treatment, or switching to a salvage therapy, for refractory patients.


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