Evaluating pathologic response of breast cancer to neoadjuvant chemotherapy with computer-extracted features from contrast-enhanced ultrasound videos.

Abstract

PURPOSE:

To extract quantitative perfusion and texture features with computer assistance from contrast-enhanced ultrasound (CEUS) videos of breast cancer before and after neoadjuvant chemotherapy (NAC), and to evaluate pathologic response to NAC with these features.

METHODS:

Forty-two CEUS videos with 140,484 images were acquired from 21 breast cancer patients pre- and post-NAC. Time-intensity curve (TIC) features were calculated including the difference between area under TIC within a tumor and that within a computer-detected reference region (AUT_T-R). Four texture features were extracted including Homogeneity and Contrast. All patients were identified as pathologic responders by Miller and Payne criteria. The features between pre- and post-treatment in these responders were statistically compared, and the discrimination between pre- and post-treatment cancers was assessed with a receiver operating characteristic (ROC) curve.

RESULTS:

Compared with the pre-treatment cancers, the post-treatment cancers had significantly lower Homogeneity (p<0.001) and AUT_T-R (p=0.014), as well as higher Contrast (p<0.001), indicating the intratumoral contrast enhancement decreased and became more heterogeneous after NAC in responders. The combination of Homogeneity and AUT_T-R achieved an accuracy of 90.5% and area under ROC curve of 0.946 for discrimination between pre- and post-chemotherapy cancers without cross validation. The accuracy still reached as high as 85.7% under leave-one-out cross validation.

CONCLUSIONS:

The computer-extracted CEUS features show reduced and more heterogeneous neovascularization of cancer after NAC. The features achieve high accuracy for discriminating between pre- and post-chemotherapy cancers in responders and thus are potentially valuable for tumor response evaluation in clinical practice.

• Authors: Qi Zhang, Congcong Yuan, Wei Dai, Lei Tang, Jun Shi, Zuoyong Li, Man Chen
• Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) (Phys Med) Vol. 39 Pg. 156-163 (Jul 2017) ISSN: 1724-191X [Electronic] Italy
• PMID: 28690116 (Publication Type: Journal Article)
• Copyright: Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Chemical References

• Contrast Media

Topics

• Breast Neoplasms (diagnostic imaging, drug therapy)
• Contrast Media
• Female
• Humans
• Neoadjuvant Therapy
• Neovascularization, Pathologic (diagnostic imaging)
• ROC Curve
• Treatment Outcome
• Ultrasonography