Early prediction of pathological complete response to neoadjuvant chemotherapy combining DCE-MRI and apparent diffusion coefficient values in breast Cancer

Abstract

Introduction: Improving the early prediction of neoadjuvant chemotherapy (NAC) efficacy in breast cancer can lead to an improved prediction of the final prognosis of patients, which would be useful for promoting individualized treatment. This study aimed to explore the value of the combination of dynamic contrast-enhanced (DCE)-MRI parameters and apparent diffusion coefficient (ADC) values in the early prediction of pathological complete response (pCR) to NAC for breast cancer.

Methods: A total of 119 (range, 28-69 years) patients with biopsy-proven breast cancer who received two cycles of NAC before breast surgery were retrospectively enrolled from our hospital database. Patients were divided into pCR and non pCR groups according to their pathological responses; a total of 24 patients achieved pCR, while 95 did not. The quantitative (K^trans; K_ep; V_e; IAUC) and semiquantitative parameters (W-in; W-out; TTP) of DCE-MRI that were significantly different between groups were combined with ADC values to explore their value in the early prediction of pCR to NAC for breast cancer. The independent T test was performed to compare the differences in DCE-MRI parameters and ADC values between the two groups. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC), sensitivity and specificity were calculated to evaluate the performance of the prediction.

Results: The K^trans, K_ep, IAUC, ADC, W-in and TTP values were significantly different between the pCR and non pCR groups after NAC. The AUC (0.845) and specificity (95.79%) of the combined K^trans, K_ep, IAUC and ADC values were both higher than those of the individual parameters. The combination of W-in, TTP and ADC values had the highest AUC value (0.886) in predicting pCR, with a sensitivity and specificity of 87.5% and 82.11%, respectively.

Conclusions: The results suggested that the combination of ADC values and quantitative and semiquantitative DCE-MRI parameters, especially the combination of W-in, TTP, and ADC values, may improve the early prediction of pCR in breast cancer.

Keywords: DCE-MRI; Neoadjuvant chemotherapy; apparent diffusion coefficient values; breast cancer; treatment response.

Fig. 1

MR images of a 65-year-old woman with invasive ductal carcinoma of the left breast before NAC. A TWIST-DCE image. B–H Pseudocolor images for determining K^trans (B), K_ep (C), IAUC (D), W-in (E), W-out (F), TTP (G), and ADC (H). Red represents high values, yellow intermediate values, and blue low values. The values for K^trans, K_ep, IAUC, W-in, W-out, and TTP were 0.309 min^-1, 1.136 min^-1, 0.336, 0.499 min^-1, 0.013 min^-1, 0.582 minutes and 0.849×10^-3 mm²/s, respectively

Fig. 2

MR images of the same patient after two cycles of NAC. The patient underwent surgery after six cycles of NAC. Surgical specimens indicated a complete response (Miller-Payne grade 5). A TWIST-DCE image. B–H Pseudocolor images for K^trans (B), K_ep (C), IAUC (D), W-in (E), W-out (F), TTP (G), and ADC (H). Red represents high values, yellow intermediate values, and blue low values. The values for K^trans, K_ep, IAUC, W-in, W-out, and TTP were 0.069 min^-1, 0.339 min^-1, 0.083, 0.181 min^-1, 0.022 min^-1, 0.868 minutes and 1.036×10^-3 mm ²/s, respectively

Fig. 3

Box plot graphs revealing statistically significant differences in values between CR and non pCR groups

Fig. 4

ROC curves of DCE-MRI quantitative parameters, ADC value, and combination of multiple parameters in predicting pCR after two cycles of NAC

Fig. 5

ROC curves of DCE-MRI semiquantitative parameters, ADC values and combinations of multiple parameters in predicting pCR after NAC

Fig. 6

The nomogram to predict pCR with quantitative DCE- MRI parameters and ADC values after two cycles of NAC for breast cancer patients