Four-quadrant fast compressive tracking of breast ultrasound videos for computer-aided response evaluation of neoadjuvant chemotherapy in mice

Yifei Yan; Lei Tang; Haibo Huang; Qihui Yu; Haohao Xu; Ying Chen; Man Chen; Qi Zhang

doi:10.1016/j.cmpb.2022.106698

Four-quadrant fast compressive tracking of breast ultrasound videos for computer-aided response evaluation of neoadjuvant chemotherapy in mice

Comput Methods Programs Biomed. 2022 Apr:217:106698. doi: 10.1016/j.cmpb.2022.106698. Epub 2022 Feb 9.

Authors

Yifei Yan¹, Lei Tang², Haibo Huang¹, Qihui Yu¹, Haohao Xu¹, Ying Chen¹, Man Chen³, Qi Zhang⁴

Affiliations

¹ The SMART (Smart Medicine and AI-Based Radiology Technology) Lab, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China; School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China.
² Department of Ultrasound, Tongren Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200050, China.
³ Department of Ultrasound, Tongren Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai 200050, China. Electronic address: CM3650@shtrhospital.com.
⁴ The SMART (Smart Medicine and AI-Based Radiology Technology) Lab, Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China; School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China. Electronic address: zhangq@t.shu.edu.cn.

PMID: 35217304
DOI: 10.1016/j.cmpb.2022.106698

Abstract

Background and objective: Neoadjuvant chemotherapy (NAC) is a valuable treatment approach for locally advanced breast cancer. Contrast-enhanced ultrasound (CEUS) potentially enables the assessment of therapeutic response to NAC. In order to evaluate the response accurately, quantitatively and objectively, a method that can effectively compensate motions of breast cancer in CEUS videos is urgently needed.

Methods: We proposed the four-quadrant fast compressive tracking (FQFCT) approach to automatically perform CEUS video tracking and compensation for mice undergoing NAC. The FQFCT divided a tracking window into four smaller windows at four quadrants of a breast lesion and formulated the tracking at each quadrant as a binary classification task. After the FQFCT of breast cancer videos, the quantitative features of CEUS including the mean transit time (MTT) were computed. All mice showed a pathological response to NAC. The features between pre- (day 1) and post-treatment (day 3 and day 5) in these responders were statistically compared.

Results: When we tracked the CEUS videos of mice with the FQFCT, the average tracking error of FQFCT was 0.65 mm, reduced by 46.72% compared with the classic fast compressive tracking method (1.22 mm). After compensation with the FQFCT, the MTT on day 5 of the NAC was significantly different from the MTT before NAC (day 1) (p = 0.013).

Conclusions: The FQFCT improves the accuracy of CEUS video tracking and contributes to the computer-aided response evaluation of NAC for breast cancer in mice.

Keywords: Breast cancer; Contrast-enhanced ultrasound (CEUS); Neoadjuvant chemotherapy (NAC); Video tracking.

MeSH terms

Animals
Breast Neoplasms* / diagnostic imaging
Breast Neoplasms* / drug therapy
Breast Neoplasms* / pathology
Chemotherapy, Adjuvant
Computers
Contrast Media
Female
Humans
Mice
Neoadjuvant Therapy* / methods
Treatment Outcome
Ultrasonography / methods
Ultrasonography, Mammary / methods

Substances

Contrast Media