Zhang Ruizhi, Lu Jianju, Di Wenqi, Gui Zhiguo, Chan Shun Wan, Yang Fengbao, Shang Yu
State Key Laboratory of Dynamic Measurement Technology, North University of China, Taiyuan 030051, China.
Department of Breast Surgery, The First Hospital of Jiaxing, Affiliated hospital of Jiaxing University, Jiaxing 314000, China.
Biomed Opt Express. 2024 Oct 9;15(11):6259-6276. doi: 10.1364/BOE.535330. eCollection 2024 Nov 1.
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.
准确评估和量化与乳腺癌相关的新生血管生成，可能有助于提高非侵入性诊断的敏感性和特异性，以及预测预后和监测治疗效果。在本研究中，我们采用了一种新兴技术，即扩散相关断层扫描（DCT），对乳腺组织中的微血管血流进行成像，并评估鉴别良性和恶性病变的潜力。设计了一种定制的DCT系统用于乳腺血流成像，对源探测器阵列和重建算法进行了优化，以确保乳腺血流的精确成像。从相对血流指数（rBFI）中提取三维血流图像的全局特征和局部特征，rBFI是从大多数靶向病变的乳腺中获得的。本研究共纳入37名患有19个良性病变和18个恶性病变的女性。在12个图像特征中发现了恶性组和良性组之间的显著差异。此外，当选择病变平均相对血流指数（MrBFI）作为单一指标时，鉴别恶性和良性肿瘤的准确率为89.2%。发现血流特征能够成功鉴别恶性和良性肿瘤，这表明DCT作为一种替代功能成像方式，有潜力转化为临床实践用于乳腺癌的诊断和评估。通过提高诊断成像的特异性以及监测乳腺癌治疗反应，有可能减少对良性病变进行活检的需求。
