Abstract
Accurate assessment and quantification of neoangiogenesis associated with breast cancer could be potentially used to improve the sensitivity and specificity of non-invasive diagnosis, as well as predict outcomes and monitor treatment effects. In this study, we adapted an emerging technology, namely diffuse correlation tomography (DCT), to image microvascular blood flow in breast tissues and evaluate the potential for discriminating between benign and malignant lesions. A custom-made DCT system was designed for breast blood flow imaging, with both the source-detector array and reconstruction algorithm optimized to ensure precise imaging of breast blood flow. The global features and local features of three-dimensional blood flow images were extracted from the relative blood flow index (rBFI), which was obtained from most of the breasts targeted to the lesion. A total of 37 women with 19 benign and 18 malignant lesions were included in the study. Significant differences between malignant and benign groups were found in 12 image features. Moreover, when selecting the lesion mean relative blood flow index (MrBFI) as a single indicator, the malignant and benign tumors were discriminated with an accuracy of 89.2%. The blood flow features were found to successfully identify malignant and benign tumors, suggesting that DCT, as an alternate functional imaging modality, has the potential to be translated into clinical practice for diagnosis and assessment of breast cancers. There is potential to reduce the need for biopsy of benign lesions by improving the specificity of diagnostic imaging, as well as monitoring response to breast cancer treatment.