Viscoelastic biomarker for differentiation of benign and malignant breast lesion in ultra- low frequency range

• Published in: Scientific reports Vol. 9; no. 1; p. 5737
• Main Authors: Nabavizadeh, Alireza, Bayat, Mahdi, Kumar, Viksit, Gregory, Adriana, Webb, Jeremy, Alizad, Azra, Fatemi, Mostafa
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.04.2019; Nature Publishing Group
• Subjects: 639/166/985; 692/53/2421; Adult; Aged; Aged, 80 and over; Benign; Biomarkers; Biomarkers, Tumor; Breast; Breast - diagnostic imaging; Breast - pathology; Breast cancer; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - pathology; Data processing; Female; Humanities and Social Sciences; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Microenvironments; Middle Aged; multidisciplinary; Performance assessment; Science; Science (multidisciplinary); Tumor Microenvironment; Tumors; Viscoelasticity
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-41885-9

Benign and malignant tumors differ in the viscoelastic properties of their cellular microenvironments and in their spatiotemporal response to very low frequency stimuli. These differences can introduce a unique viscoelastic biomarker in differentiation of benign and malignant tumors. This biomarker may reduce the number of unnecessary biopsies in breast patients. Although different methods have been developed so far for this purpose, none of them have focused on in vivo and in situ assessment of local viscoelastic properties in the ultra-low (sub-Hertz) frequency range. Here we introduce a new, noninvasive model-free method called Loss Angle Mapping (LAM). We assessed the performance results on 156 breast patients. The method was further improved by detection of out-of-plane motion using motion compensation cross correlation method (MCCC). 45 patients met this MCCC criterion and were considered for data analysis. Among this population, we found 77.8% sensitivity and 96.3% specificity (p < 0.0001) in discriminating between benign and malignant tumors using logistic regression method regarding the pre known information about the BIRADS number and size. The accuracy and area under the ROC curve, AUC, was 88.9% and 0.94, respectively. This method opens new avenues to investigate the mechanobiology behavior of different tissues in a frequency range that has not yet been explored in any in vivo patient studies.