Abstract
This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.
Highlights
One limitation associated with standard ultrasound imaging for breast cancer screening is that ultrasound B-mode images are mainly qualitative and fail to provide reliable quantitative information about underlying tissue microstructure[5]
The mean-value and textural parameters extracted from the effective scatterer diameter (ESD) parametric maps demonstrated average values of 102.6 ± 4.4 μm versus 111.1 ± 4.1 μm, 4.9 ± 0.6 A.U. versus 3.0 ± 0.4 A.U., 0.7 ± 0.02 A.U. versus 0.8 ± 0.01 A.U., 0.61 ± 0.02 A.U. versus 0.66 ± 0.02 A.U., and 0.07 ± 0.01 A.U. versus 0.06 ± 0.01 A.U. for the two lesion types, respectively
This study demonstrated, for the first time, the potential of Quantitative ultrasound (QUS) spectral and textural analysis techniques for characterization of benign versus malignant breast lesions non-invasively
Summary
One limitation associated with standard ultrasound imaging for breast cancer screening is that ultrasound B-mode images are mainly qualitative and fail to provide reliable quantitative information about underlying tissue microstructure[5]. Texture-analysis techniques have been applied to ultrasound B-mode images in order to quantify spatial heterogeneities within tumour in tissue characterization applications, such as discriminating between benign and malignant breast tumours[53,54,55]. The principle behind this approach is that benign and malignant lesions often demonstrate homogeneous and heterogeneous internal echoes, respectively. Several textural features were determined from each parametric map in addition to an average-based mean-value parameter as imaging biomarkers These biomarkers were utilized to classify benign versus malignant lesions using a k-nearest neighbour (K-NN) classifier with leave-one-patient-out cross-validation. The observations in this study suggest that QUS spectral parametric imaging along with texture-analysis methods have a high potential to characterize suspicious breast lesions rapidly, non-invasively, and with high sensitivity and specificity
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