Low-frequency ultrasound radiosensitization and therapy response monitoring of tumors: An in vivo study

A new framework has been introduced in this paper for tumor radiosensitization and therapy response monitoring using low-frequency ultrasound. Human fibrosarcoma xenografts grown in severe combined immunodeficiency (SCID) mice (n = 108) were treated using ultrasound-stimulated microbubbles at various concentration and exposed to different doses of radiation. Low-frequency ultrasound radiofrequency (RF) data were acquired from tumors prior to and at different times after treatment. Quantitative ultrasound (QUS) techniques were applied to generate spectral parametric maps of tumors. Textural analysis were performed to quantify spatial heterogeneities within QUS parametric maps. A hybrid model was developed using multiple regression analysis to predict extent of histological tumor cell death non-invasively based on QUS spectral and textural biomarkers. Results of immunohistochemistry on excised tumor sections demonstrated increases in cell death with higher concentration of microbubbles and radiation dose. Quantitative ultrasound results indicated changes that paralleled increases in histological cell death. Specifically, the hybrid QUS biomarker demonstrated a good correlation with extent of tumor cell death observed from immunohistochemistry. A linear discriminant analysis applied in conjunction with the receiver operating characteristic (ROC) curve analysis indicated that the hybrid QUS biomarker can classify tumor cell death fractions with an area under the curve of 91.2. The results obtained in this research suggest that low-frequency ultrasound can concurrently be used to enhance radiation therapy and evaluate tumor response to treatment.

[1]  Yassin Labyed,et al.  Estimate of the attenuation coefficient using a clinical array transducer for the detection of cervical ripening in human pregnancy. , 2011, Ultrasonics.

[2]  Michael C. Kolios,et al.  Low-frequency quantitative ultrasound imaging of cell death in vivo. , 2013, Medical Physics (Lancaster).

[3]  Martin J. Yaffe,et al.  Early prediction of therapy responses and outcomes in breast cancer patients using quantitative ultrasound spectral texture , 2014, Oncotarget.

[4]  Gregory J. Czarnota,et al.  Noninvasive Characterization of Locally Advanced Breast Cancer Using Textural Analysis of Quantitative Ultrasound Parametric Images , 2014, Translational oncology.

[5]  Michael C. Kolios,et al.  Conventional frequency ultrasonic biomarkers of cancer treatment response in vivo. , 2013, Translational oncology.

[6]  Gregory J. Czarnota,et al.  Non-invasive evaluation of breast cancer response to chemotherapy using quantitative ultrasonic backscatter parameters , 2015, Medical Image Anal..

[7]  Raffi Karshafian,et al.  Bioeffects of ultrasound-stimulated microbubbles on endothelial cells: gene expression changes associated with radiation enhancement in vitro. , 2012, Ultrasound in medicine & biology.

[8]  J W Hunt,et al.  © 1999 Cancer Research Campaign Article no. bjoc.1999.0724 Ultrasound imaging of apoptosis: high-resolution noninvasive , 2022 .

[9]  Michael C. Kolios,et al.  Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy , 2013, Clinical Cancer Research.

[10]  Ali Sadeghi-Naini,et al.  Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties. , 2014, Medical physics.

[11]  Gregory J. Czarnota,et al.  Tumor radiation response enhancement by acoustical stimulation of the vasculature , 2012, Proceedings of the National Academy of Sciences.

[12]  Omar Falou,et al.  Quantitative ultrasound spectral parametric maps: Early surrogates of cancer treatment response , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[13]  David A. Freedman,et al.  Statistical Models: Theory and Practice: References , 2005 .

[14]  G. Czarnota,et al.  Effects of biophysical parameters in enhancing radiation responses of prostate tumors with ultrasound-stimulated microbubbles. , 2013, Ultrasound in medicine & biology.

[15]  Gregory J. Czarnota,et al.  Quantification of Ultrasonic Scattering Properties of In Vivo Tumor Cell Death in Mouse Models of Breast Cancer1 , 2015, Translational oncology.

[16]  Martin J. Yaffe,et al.  Imaging innovations for cancer therapy response monitoring , 2012 .

[17]  Kevin Brindle,et al.  New approaches for imaging tumour responses to treatment , 2008, Nature Reviews Cancer.

[18]  Michael C. Kolios,et al.  Ultrasound imaging of apoptosis in tumor response: novel preclinical monitoring of photodynamic therapy effects. , 2008, Cancer research.