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. 2013 Apr 15;19(8):2163-74.
doi: 10.1158/1078-0432.CCR-12-2965. Epub 2013 Feb 20.

Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

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Quantitative Ultrasound Evaluation of Tumor Cell Death Response in Locally Advanced Breast Cancer Patients Receiving Chemotherapy

Ali Sadeghi-Naini et al. Clin Cancer Res. .
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Abstract

Purpose: Quantitative ultrasound techniques have been recently shown to be capable of detecting cell death through studies conducted on in vitro and in vivo models. This study investigates for the first time the potential of early detection of tumor cell death in response to clinical cancer therapy administration in patients using quantitative ultrasound spectroscopic methods.

Experimental design: Patients (n = 24) with locally advanced breast cancer received neoadjuvant chemotherapy treatments. Ultrasound data were collected before treatment onset and at 4 times during treatment (weeks 1, 4, and 8, and preoperatively). Quantitative ultrasound parameters were evaluated for clinically responsive and nonresponding patients.

Results: Results indicated that quantitative ultrasound parameters showed significant changes for patients who responded to treatment, and no similar alteration was observed in treatment-refractory patients. Such differences between clinically and pathologically determined responding and nonresponding patients were statistically significant (P < 0.05) after 4 weeks of chemotherapy. Responding patients showed changes in parameters related to cell death with, on average, an increase in mid-band fit and 0-MHz intercept of 9.1 ± 1.2 dBr and 8.9 ± 1.9 dBr, respectively, whereas spectral slope was invariant. Linear discriminant analysis revealed a sensitivity of 100% and a specificity of 83.3% for distinguishing nonresponding patients by the fourth week into a course of chemotherapy lasting several months.

Conclusion: This study reports for the first time that quantitative ultrasound spectroscopic methods can be applied clinically to evaluate cancer treatment responses noninvasively. The results form a basis for monitoring chemotherapy effects and facilitating the personalization of cancer treatment.

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