Prediction of pathological complete response of breast cancer patients undergoing neoadjuvant chemotherapy: usefulness of breast MRI computer-aided detection

Abstract

Objective: To evaluate the usefulness of MR computeraided detection (CAD) in patients undergoing neoadjuvant chemotherapy for prediction of the pathological complete response of tumours. Methods: 148 patients with breast cancer (mean age, 47.3 years; range, 29-72 years) who underwent neoadjuvant chemotherapy were included in our study. They underwent MRI before and after neoadjuvant chemotherapy, and we reviewed the pathological result as the gold standard. The computer-generated kinetic features for each lesion were recorded, and the features analysed included "threshold enhancement" at 50% and 100% minimum thresholds; degree of initial peak enhancement; and enhancement profiles comprising lesion percentages of washout, plateau and persistent enhancement. The final pathological size and character of tumours were correlated with postchemotherapy mammography, ultrasonography and MR CAD findings. Kruskal-Wallis test and intraclass correlation coefficient were used to analyse the findings.

Automated Semi-Quantitative Analysis of Breast MRI: Potential Imaging Biomarker for the Prediction of Tissue Response to Neoadjuvant Chemotherapy

“…Their study collective was much smaller (57 lesions) compared to that of Kim et al [9] (n = 148) and the present investigation (n = 108). Similar to our data and different from Kim et al [9], Lyoung et al [17] documented the degree of TR on a much more detailed, 4-tailed, ordinal scale.…”

“…The use of CAD can overcome this source of error as previously demonstrated [17,18]. Surprisingly, only few papers have applied this approach in assessing TR to NAC (for instance [9,17,18]). …”

“…Multiple studies have investigated the potential of bMRI to predict the degree of TR to NAC compared to mammography and ultrasound [3,9,17,18]. As this topic remained controversial, a recent meta-analysis summarized the current evidence [3]:…”

“…Kim et al [9] investigated whether TR can be predicted by CAD. They simplified the CG score and dichotomized patients into categories of 'complete response' and 'non-complete-response' to NAC.…”

“…As shown in previous research, such data reflect the tumor biology, are connected to patient outcomes [6][7][8], and could be used as surrogate parameters of TR (for instance [9]). Yet, the major drawback of bMRI is its complex interpretation [10,11].…”