Imaging‐based biomarkers: Changes in the tumor interface of pancreatic ductal adenocarcinoma on computed tomography scans indicate response to cytotoxic therapy

Abstract

BACKGROUNDThe assessment of pancreatic ductal adenocarcinoma (PDAC) response to therapy remains challenging. The objective of this study was to investigate whether changes in the tumor/parenchyma interface are associated with response.METHODSComputed tomography (CT) scans before and after therapy were reviewed in 4 cohorts: cohort 1 (99 patients with stage I/II PDAC who received neoadjuvant chemoradiation and surgery); cohort 2 (86 patients with stage IV PDAC who received chemotherapy), cohort 3 (94 patients with stage I/II PDAC who received protocol‐based neoadjuvant gemcitabine chemoradiation), and cohort 4 (47 patients with stage I/II PDAC who received neoadjuvant chemoradiation and were prospectively followed in a registry). The tumor/parenchyma interface was visually classified as either a type I response (the interface remained or became well defined) or a type II response (the interface became poorly defined) after therapy. Consensus (cohorts 1‐3) and individual (cohort 4) visual scoring was performed. Changes in enhancement at the interface were quantified using a proprietary platform.RESULTSIn cohort 1, type I responders had a greater probability of achieving a complete or near‐complete pathologic response (21% vs 0%; P = .01). For cohorts 1, 2, and 3, type I responders had significantly longer disease‐free and overall survival, independent of traditional covariates of outcomes and of baseline and normalized cancer antigen 19‐9 levels. In cohort 4, 2 senior radiologists achieved a κ value of 0.8, and the interface score was associated with overall survival. The quantitative method revealed high specificity and sensitivity in classifying patients as type I or type II responders (with an area under the receiver operating curve of 0.92 in cohort 1, 0.96 in cohort 2, and 0.89 in cohort 3).CONCLUSIONSChanges at the PDAC/parenchyma interface may serve as an early predictor of response to therapy. Cancer 2018;124:1701‐9. © 2018 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Early detection of pancreatic cancer

“…Toward identification of the primary tumor, Fishman and colleagues have described a radiomics-based machine learning algorithm to differentiate PDAC from benign situations (i.e., normal pancreas and pancreatitis) with high specificity and sensitivity 112 . Other applications of radiomics and quantitative imaging approaches have shown that the enhancement and morphology of the primary tumors have biological underpinnings and clinical relevance [113][114][115] , suggesting that quantitative imaging and further application of AI to these imaging features can provide non-invasive insight into the disease. This insight may have relevance to early detection through better stratification and personalized approaches to screening in high-risk individuals.…”

Response to Preoperative Therapy in Localized Pancreatic Cancer

“…At our institution, Amer et al recently evaluated 4 cohorts of patients and showed that in each, the change in the radiographic interface between tumor and adjacent pancreatic parenchyma that often occurred in association with (chemo)radiation was associated with outcome. Moreover, in one of the cohorts, patients who met criteria for a radiomic response had a greater likelihood of achieving a pMR or pCR (21 vs. 0%, P = 0.01) (54). Our group has also identified an imaging biomarker that can be assessed using routine computer tomographic images and may be used to stratify patient's tumors into distinctive biophysical subtypes (55).…”

Selective EGLN Inhibition Enables Ablative Radiotherapy and Improves Survival in Unresectable Pancreatic Cancer

“…Another limitation is that there is currently no biomarker to determine which patients are ideal for consolidation with radiation and who might benefit from EGLN inhibitors. For the former, there is continuing work on histologic biomarkers such as SMAD4 (38), circulating tumor DNA (39), and radiomic (40,41) approaches. For the latter issue, there is no clinically accepted biomarker for hypoxia.…”