Association of Multi-Parametric MRI Texture Features and a Clinical Biomarker for Chemoradiation Therapy of Pancreatic Cancer

Abstract

Identification of patients with pancreatic adenocarcinoma pre-treatment that optimally benefit from radiotherapy (RT) presents a common clinical challenge. We sought to identify pre-treatment MRI radiomics features associated with treatment response to chemoradiation therapy (CRT) by correlating pre-treatment MRI texture features with decline in the clinical biomarker CA19-9. The pre-CRT MRI data and pre- and post-CRT CA19-9 levels collected from 45 patients treated with pre-operative CRT for their resectable or borderline resectable pancreatic head cancers were analyzed. Pre-CRT MRIs included breath hold, multi-phase (pre, arterial, venous, portal-venous phase) dynamic contrast T1-weighted and ADC images. T1 images were standardized (bias corrected and normalized) prior to analysis. Registrations of these multi-parametric MRIs were used to delineate gross tumor volume (GTV) by experienced radiologist and radiation oncologists and to generate maps of signal enhancement ratio (SER), ratio of maximum intensity to pre-contrast intensity, and uptake rate difference (URD), difference in maximum intensity and pre-contrast intensity over time. A series of image texture features, including mean, standard deviation (SD), skewness, kurtosis, minimum, maximum, and entropy, were calculated from pre-contrast, arterial, venous, portal-venous, SER and URD images. Texture features were compared to pre-CRT CA19-9 levels using a two-tailed t-test to compare the cohort of patients with CA19-9 levels less than to greater than 35 U/mL. In addition, texture features were compared to percent changes of pre- and post-CRT using ROC analysis to find a threshold with a significant difference in textures and t-test. A two tailed t-test was then applied to investigate possible significant differences in the textures. A threshold was established based on the ROC of the data with a decrease in CA19-9 of 40% from pre-CRT level. The t-test showed using the normalized intensity of pre-contrast phase, there was a significant difference between a decrease greater than 40% and less than 40% in CA19-9 using pre-CRT texture metrics (entropy, p=0.016, mean, p=0.004, and skewness, p=0.008). Evaluating CA19-9 levels directly to texture features resulted in p-values of p= 0.001 for SD of normalized intensity of the pre-contrast phase, p= 0.001 for SD of normalized intensity of the arterial phase, p= 0.002 for entropy of SER maps. Image texture metrics from pre-treatment multiphase dynamic contrast MRI are associated with changes in CA19-9 levels over CRT of pancreatic cancer. These data present a potential promising methodology to identify patients pre-treatment that may optimally benefit from RT. Further comprehensive multivariate analysis is required to validate the presented pre-treatment MRI radiomic features as a biomarker for CRT of pancreatic cancer.