Improving Treatment Response Prediction for Chemoradiation Therapy of Pancreatic Cancer Using a Combination of Delta-Radiomics and the Clinical Biomarker CA19-9. Front Oncol 2019;9:1464
Date
01/24/2020Pubmed ID
31970088Pubmed Central ID
PMC6960122DOI
10.3389/fonc.2019.01464Scopus ID
2-s2.0-85078248047 (requires institutional sign-in at Scopus site) 50 CitationsAbstract
Recently we showed that delta radiomics features (DRF) from daily CT-guided chemoradiation therapy (CRT) is associated with early prediction of treatment response for pancreatic cancer. CA19-9 is a widely used clinical biomarker for pancreatic cancer. The purpose of this work is to investigate if the predictive power of such biomarkers (DRF or CA19-9) can improve by combining both biomarkers. Daily non-contrast CTs acquired during routine CT-guided neoadjuvant CRT for 24 patients (672 datasets, in 28 daily fractions), along with their CA19-9, pathology reports and follow-up data were analyzed. The pancreatic head was segmented on each daily CT and radiomic features were extracted from the segmented regions. The time between the end of treatment and last follow-up was used to build a survival model. Patients were divided into two groups based on their pathological response. Spearman correlations were used to find the DRFs correlated to CA19-9. A regression model was built to examine the effect of combining CA19-9 and DRFs on response prediction. C-index was used to measure model effectiveness. The effect of a decrease in CA19-9 levels during treatment vs. failure of CA19-9 levels to normalize on survival was examined. Univariate- and multivariate Cox-regression analysis were performed to determine the effect of combining CA19-9 and DRFs on survival correlations. Spearman correlation showed that CA19-9 is correlated to DRFs (Entropy, cluster tendency and coarseness). An Increase in CA19-9 levels during treatment were correlated to a bad response, while a decline was correlated to a good response. Incorporating CA19-9 with DRFs increased the c-index from 0.57 to 0.87 indicating a stronger model. The univariate analysis showed that patients with decreasing CA19-9 had an improved median survival (68 months) compared to those with increasing levels (33 months). The 5-years survival was improved for the decreasing CA19-9 group (55%) compared to the increasing group (30%). The Cox-multivariate analysis showed that treatment related decrease in CA19-9 levels (p = 0.031) and DRFs (p = 0.001) were predictors of survival. The hazard-ratio was reduced from 0.73, p = 0.032 using CA19-9 only to 0.58, p = 0.028 combining DRFs with CA19-9. DRFs-CA19-9 combination has the potential to increasing the possibility for response-based treatment adaptation.
Author List
Nasief H, Hall W, Zheng C, Tsai S, Wang L, Erickson B, Li XAAuthors
Beth A. Erickson MD Professor in the Radiation Oncology department at Medical College of WisconsinWilliam Adrian Hall MD Chair, Professor in the Radiation Oncology department at Medical College of Wisconsin
Xiaochuan Allen Li PhD Emeritus Professor in the Radiation Oncology department at Medical College of Wisconsin
Haidy G. Nasief PhD, MS, MSc Assistant Professor in the Radiation Oncology department at Medical College of Wisconsin
