Background: As pancreatic ductal adenocarcinoma (PDAC) remains highly lethal, biomarkers are needed to identify patients who may benefit from specific therapeutic strategies. We previously described a qualitative computed tomography (CT) based biomarker - delta classification, whereby high delta tumors showed lower stromal content, more aggressive biology and poorer outcomes, than their counterparts. Here, we describe a quantitative method to differentiate these patients and predict outcomes. Methods: We retrospectively identified 101 treatment naïve patients who underwent pancreatectomy as a discovery cohort and 90 patients who underwent preoperative gemcitabine-based chemoradiation for validation. All patients underwent a pre-therapy pancreatic protocol CT and were classified as high or low delta, as described before. We semi-automatically segmented the tumors, chose normal pancreatic (NP) tissue and abdominal fat as references, then measured relative enhancement values using Philips IntelliSpace8 multimodality tumor tracking. We then analyzed the arterial and portal-venous phases separately using ROC and cox proportional hazards. Results: Delta class significantly associated with normalized enhancement values (NEV) in the arterial phase referenced to NP (P<0.0001, AUC =90%). A cutoff of 0.72 was identified that also distinguished high and low delta groups in the validation cohort (P<0.0001). As a continuous variable, the NEV was associated with distant metastasis free survival (DMFS) and overall survival (OS) on uni and multivariate analyses, accounting for traditional survival covariates. Using cutoff of 0.72, patients with high NEV had longer median OS (39 and 35.9 months) compared to those with low NEV (17.5 and 17.6 months, P=<0.0001) in discovery and validation cohorts, respectively. Similarly, patients with high NEV had longer median DMFS (46.6 and 62.2 months) compared to those with low NEV (15.6 and 13.1 months, P=0.005) in discovery and validation cohorts, respectively. Conclusions: The NEV measurement on baseline CT scans may serve as a quantitative imaging biomarker that can objectively reflect tumor biology and provide prognostic insight.