Objective:

To investigate the role of texture parameters obtained from the commonly used quantitative parameter maps derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting and evaluating the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer.

Methods:

A total of 63 breast cancer patients with pathologically confirmed in the Shanxi Province Tumor Hospital from Sep. 2014 to Oct. 2018 were retrospectively analyzed. All these patients underwent DCE-MRI before and after NAC. According to the pathological results

the patients were divided into the effective group (40 cases) and the ineffective group (23 cases). Then we used omni-kinetics software to extract 52 texture parameters from each of the four maps derived from DCE-MRI before NAC and after 4-8 cycles of treatment. The independent-sample t test or Mann-Whitney

U

test were used to statistical analysis between the texture parameters of the two groups. The parameters with statistical differences were analyzed by single factor logistic regression

and the texture parameters related to the efficacy of NAC were selected. The receiver operating characteristic (ROC) curves were drawn. According to the area under the curve (AUC)

the diagnostic efficacy of texture parameters in DCE-MRI image for the curative effect of NAC of breast cancer was obtained.

Results:

In this study

a total of 208 texture parameters were extracted from four commonly used quantitative maps (K

trans

K

ep

V

e

V

p

) of patients DCE-MRI. In K

trans

K

ep

and V

p

maps of DCE-MRI before NAC in the effective and ineffective groups of patients

there were 13

17

and 10 texture parameters with statistically significant differences

respectively (

P

＜0.05). Univariate logistic regression analysis showed th

at there were 1

7

and 3 texture parameters associated with the efficacy of NAC. No statistically significant texture parameters were found in the V

e

map (

P

＜0.05). But the AUC of the above parameters were all less than 0.8. Post-NAC texture parameters and parameter change rates could evaluate the efficacy of NAC. The parameters with better performance mainly included volume count

run length non-uniformity

volume count

run length non-uniformity in the four maps. The grey level non-uniformity and grey level non-uniformity in the K

trans

maps

and the voxel value sum and grey level non-uniformity in the K

ep

maps also had good evaluation performance. All of them had higher AUC

and had high sensitivity and specificity.

Conclusion:

Among the texture parameters based on the DCE-MRI quantitative parameter maps

there are parameters that can predict and evaluate the efficacy of NAC in breast cancer.