Quantitative ultrasound characterization of locally advanced breast cancer by estimation of its scatterer properties

Abstract

Overall, the binary classification results (tumor versus normal tissue) were more promising than tumor grade assessment. Combinations of advanced parameters can further improve the separation of tumors from normal tissue compared to the use of linear regression parameters. While the linear regression parameters were sufficient for characterizing breast tumors and normal breast tissues, advanced parameters and their textural features were required to better characterize tumor subtypes.

Multiparametric Monitoring of Chemotherapy Treatment Response in Locally Advanced Breast Cancer Using Quantitative Ultrasound and Diffuse Optical Spectroscopy

“…DOSI parameters have been useful in demonstrating biochemical, hematological and morphological changes with treatment [23,38,39], while QUS parameters have demonstrated cell death in samples from chemotherapy [20,26]. These parameters have also been tied to pathologic characteristics and outcomes [20,22,29,33]. Recent work by Cerussi et al, used DOSI to measure tumor water content, and tumor hemoglobin concentration at multiple times during chemotherapy treatment [33].…”

“…Theoretical frameworks in these early QUS studies for cancer imaging have driven efforts to study chemotherapy response in breast cancer in vivo [20,29]. To date, QUS has been demonstrated for functional imaging to monitor treatment response in photodynamic therapy, chemotherapy, and radiation therapy; both in animal and human studies [20,25,[29][30][31][32].…”

“…In order to reduce spectral-noise artifacts, a sliding window algorithm was used with the settings of a Hamming window function for gating, where there was an 80% overlap between adjacent windows in the axial direction. A reference phantom technique was used to remove system transfer effects from the data using a tissue-mimicking agar-embedded glassbead phantom, with measured acoustic properties [29]. The normalized power spectrum (dBr) was calculated by dividing the power spectrum for samples by the reference power spectrum of the phantom.…”

Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment

“…This heterogeneity in tumor tissue scatterers could span different scatterer densities. Regions within the tumor tissue that respond to treatment exhibit different statistical properties to that of the non-respondent counterpart [2][3][4]6]. Thus it is essential to improve the discriminative abilities of the employed statistical distribution model for better characterization of tumor heterogeneity.…”

“…A number of contributions employed the backscattered statistics from RF ultrasound signal for evaluating the early death of tumor cells in response to chemotherapy treatment; such as using the scatterer spacing and diameter, and acoustic concentration in combination with texture features from the gray-level co-occurrence matrix [3]. Others relied on calculating the power spectrum from the Fourier transform of raw RF data, and subsequently deriving the spectral slope, 0-MHz intercept, and mid-band fit quantitative parameters [2].…”