Article ; Online: Virtual touch tissue imaging and quantification
Scientific Reports, Vol 7, Iss 1, Pp 1-
value in malignancy prediction for complex cystic and solid breast lesions
2017 Volume 10
Abstract: Abstract This study was aimed to evaluatethe usefulness of conventional ultrasound (US) and US elastography, including the latest virtual touch tissue imaging and quantification (VTIQ), in malignancy prediction for complex cystic and solid breast lesions. ...
| Abstract | Abstract This study was aimed to evaluatethe usefulness of conventional ultrasound (US) and US elastography, including the latest virtual touch tissue imaging and quantification (VTIQ), in malignancy prediction for complex cystic and solid breast lesions. Eighty-nine complex cystic and solid breast lesions were subject to conventional US and US elastography, including strain elastography (SE), virtual touch tissue imaging (VTI) and VTIQ. Among the 89 lesions, thirty-four (38.2%) lesions were malignant and 55 (61.8%) lesions were benign. Sixteen variables were subject to multivariate logistic regression analysis. Pattern 4b in VTI (odds ratio, OR:15.278), not circumscribed margin of lesion (OR:12.346), SWS mean >4.6 m/s in VTIQ (OR:11.896), and age elder than 50 years (OR:6.303) were identified to be independent predictors for malignancy. In receiver operating characteristic (ROC) curve analyses, associated areas under the ROC curve (Az) for conventional US could be significantly elevated, from 0.649 to 0.918, by combining with US elastography (p < 0.0001). The combined diagnostic method was able to improve the specificity (32.7% vs. 87.3%, p < 0.0001) without sacrificing the sensitivity (97.1% vs. 85.3%, p = 0.075). Both conventional US and US elastography contribute substantially to malignancy prediction in complex cystic and solid lesions. The diagnostic efficacy of conventional US in terms of Az and specificity could be significantly improved by combining with US elastography. |
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| Keywords | Medicine ; R ; Science ; Q |
| Subject code | 616 |
| Language | English |
| Publishing date | 2017-08-01T00:00:00Z |
| Publisher | Nature Portfolio |
| Document type | Article ; Online |
| Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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