Compression optical coherence elastography versus strain ultrasound elastography for breast cancer detection and differentiation: pilot study.
Ekaterina V GubarkovaAleksander A SovetskyDmitry A VorontsovPavel A BudayMarina A SirotkinaAnton A PlekhanovSergey S KuznetsovAleksander L MatveyevLev A MatveevSergey V GamayunovAlexey Y VorontsovVladimir Y ZaitsevNatalia D GladkovaPublished in: Biomedical optics express (2022)
The aims of this study are (i) to compare ultrasound strain elastography (US-SE) and compression optical coherence elastography (C-OCE) in characterization of elastically linear phantoms, (ii) to evaluate factors that can cause discrepancy between the results of the two elastographic techniques in application to real tissues, and (iii) to compare the results of US-SE and C-OCE in the differentiation of benign and malignant breast lesions. On 22 patients, we first used standard US-SE for in vivo assessment of breast cancer before and then after the lesion excision C-OCE was applied for intraoperative visualization of margins of the tumors and assessment of their type/grade using fresh lumpectomy specimens. For verification, the tumor grades and subtypes were determined histologically. We show that in comparison to US-SE, quantitative C-OCE has novel capabilities due to its ability to locally control stress applied to the tissue and obtain local stress-strain curves. For US-SE, we demonstrate examples of malignant tumors that were erroneously classified as benign and vice versa. For C-OCE, all lesions are correctly classified in agreement with the histology. The revealed discrepancies between the strain ratio given by US-SE and ratio of tangent Young's moduli obtained for the same samples by C-OCE are explained. Overall, C-OCE enables significantly improved specificity in breast lesion differentiation and ability to precisely visualize margins of malignant tumors compared. Such results confirm high potential of C-OCE as a high-speed and accurate method for intraoperative assessment of breast tumors and detection of their margins.
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