Retrospective Study
Copyright ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Sep 24, 2021; 12(9): 808-822
Published online Sep 24, 2021. doi: 10.5306/wjco.v12.i9.808
Role of mammogram and ultrasound imaging in predicting breast cancer subtypes in screening and symptomatic patients
Tay Wei Ming Ian, Ern Yu Tan, Niketa Chotai
Tay Wei Ming Ian, Department of Diagnostic Radiology, Singapore General Hospital, Singapore 101070, Singapore
Ern Yu Tan, Department of General Surgery, Tan Tock Seng Hospital, Singapore 308433, Singapore
Niketa Chotai, Department of Diagnostic Radiology, Tan Tock Seng Hospital, Singapore 308433, Singapore
Author contributions: Ian TWM contributed to data collection, statistical analysis, and manuscript writing; Tan EY contributed to data collection and ethics committee approval application; Chotai N contributed to data collection and manuscript editing.
Institutional review board statement: The Institutional review board was approved by the NHG DSRB, DSRB Reference Number: 2019/00058.
Informed consent statement: The Informed consent statement was waived by the Institutional review board.
Conflict-of-interest statement: The authors have stated that they have no conflicts of interest.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at niketachotai@gmail.com. Participants gave informed consent for data sharing as part of their inclusion into the hospital breast cancer registry.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Niketa Chotai, MBBS, MD, Academic Research, Attending Doctor, Department of Diagnostic Radiology, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, Singapore 308433, Singapore. niketachotai@gmail.com
Received: February 23, 2021
Peer-review started: February 23, 2021
First decision: June 16, 2021
Revised: June 24, 2021
Accepted: August 3, 2021
Article in press: August 3, 2021
Published online: September 24, 2021
Processing time: 205 Days and 18.2 Hours
ARTICLE HIGHLIGHTS
Research background

There is evidence in the literature that breast cancer (BC) molecular subtypes often have characteristic imaging features on mammogram (MG), ultrasound (US) and magnetic resonance imaging. These imaging features on MG and US are of particular interest as they are cost-effective and widely available even in many developing countries.

Research motivation

Thus far, research into the correlation between MG and US imaging features and BC subtypes has been based on populations of symptomatic patients, with the lack of data on an asymptomatic (screening) population highlighted as an area for future research. We wanted to thus use our data which consists of both screening and symptomatic patients to add to the body of knowledge on this issue. Also, our population includes patients with ductal carcinoma-in-situ (DCIS) which only a few papers have examined.

Research objectives

To correlate the MG and US imaging features with the molecular subtypes of BC (hormone receptor positive vs hormone receptor negative, triple-negative vs non-triple negative and HER2 positive vs HER2 negative) and DCIS in our population of screening and symptomatic patients.

Research methods

Our study is retrospective, with a population of 328 consecutive patients in 2017-18 with histologically confirmed BC. 237 (72%) were symptomatic, and 91 (28%) were detected via a screening program. All the patients underwent MG and US imaging prior to biopsy. The images were retrospectively interpreted by two breast-imaging radiologists with 5-10 years of experience who were blinded to the histology results to ensure statistical independence. To test the hypothesis that imaging features are correlated with tumor subtypes, univariate binomial and multinomial logistic regression models were performed. Also, multivariate logistic regression (with and without interaction terms) was utilized to identify combinations of MG and US imaging characteristics predictive of molecular subtypes.

Research results

Circumscribed margins, posterior enhancement, and large size are correlated with triple-negative BC (TNBC). High-risk microcalcifications and microlobulated margins is predictive of HER2-enriched cancers. DCIS is characterized by small size on US, absence of posterior acoustic features, and the presence of architectural distortion on MG. Hormone receptor positive subtypes tend to be small, with spiculated margins and posterior acoustic shadowing. These results are broadly consistent with findings from prior studies. In addition, we also find that US lesion size signals a higher odds ratio for TNBC if presented during screening.

Research conclusions

Several MG and US imaging features were shown to independently predict molecular subtypes of BC, in a population of both screening and symptomatic patients. Knowledge of such correlations could help clinicians stratify BC patients, possibly enabling earlier treatment for patients with triple negative cancer. This could also aid therapeutic decisions in countries where receptor testing is not readily available.

Research perspectives

To further research in this field, machine learning algorithms may be trained to recognize both the imaging characteristics as well as the radionomic characteristics of BC molecular subtypes, to see if this can further improve the predictive accuracy of imaging. More studies with asymptomatic populations of patients, and with differing ethnicities would also be useful to corroborate the results in our study.