Early prediction of neoadjuvant treatment outcome in locally advanced breast cancer using parametric response mapping and radial heterogeneity from breast MRI

Abstract

Background: Early prediction of nonresponse is essential in order to avoid inefficient treatments.

Purpose: To evaluate if parametrical response mapping (PRM)-derived biomarkers could predict early morphological response (EMR) and pathological complete response (pCR) 24-72 hours after initiation of chemotherapy treatment and whether concentric analysis of nonresponding PRM regions could better predict response.

Study type: This was a retrospective analysis of prospectively acquired cohort, nonrandomized, monocentric, diagnostic study.

Population: Sixty patients were initially recruited, with 39 women participating in the final cohort.

Field strength/sequence: A 1.5T scanner was used for MRI examinations.

Assessment: Dynamic contrast-enhanced (DCE)-MR images were acquired at baseline (timepoint 1, TP1), 24-72 hours after the first chemotherapy (TP2), and after the end of anthracycline treatment (TP3). PRM was performed after fusion of T₁ subtraction images from TP1 and TP2 using an affine registration algorithm. Pixels with an increase of more than 10% of their value (PRMdce+) were corresponding nonresponding regions of the tumor. Patients with a decrease of maximum diameter (%dDmax) between TP1 and TP3 of more than 30% were defined as EMR responders. pCR patients achieved a residual cancer burden score of 0.

Statistical tests: T-test, receiver operating characteristic (ROC) curves, and logistic regression were used for the analysis.

Results: PRM showed a statistical difference between pCR response groups (P < 0.01) and AUC of 0.88 for the prediction of non-pCR. Logistic regression analysis demonstrated that PRMdce+ and Grade II were significant (P < 0.01) for non-pCR prediction (AUC = 0.94). Peripheral tumor region demonstrated higher performance for the prediction of non-pCR (AUC = 0.85) than intermediate and central zones; however, statistical comparison showed no significant difference.

Data conclusion: PRM could be predictive of non-pCR 24-72 hours after initiation of chemotherapy treatment. Moreover, the peripheral region showed increased AUC for non-pCR prediction and increased signal intensity during treatment for non-pCR tumors, information that could be used for optimal tissue sampling.

Level of evidence: 1 Technical Efficacy Stage: 4 J. Magn. Reson. Imaging 2020;51:1403-1411.

Keywords: breast cancer; lesion heterogeneity; magnetic resonance; neoadjuvant chemotherapy; pathological response.