1103. Multiparametric Detection and Outcome Prediction of Pancreatic Cancer Involving Dual-Energy CT, Diffusion-Weighted MRI, and Radiomics
Authors* Denotes Presenting Author
Vitali Koch *;
Goethe University Frankfurt
Leon Gruenewald;
Goethe University Frankfurt
Simon Martin;
Goethe University Frankfurt
Jennifer Gotta;
Goethe University Frankfurt
Thomas Vogl;
Goethe University Frankfurt
Objective:
The advent of next-generation computed tomography (CT)- and magnetic resonance imaging (MRI) opened many new perspectives in the evaluation of tumor characteristics. An increasing body of evidence suggests the incorporation of quantitative imaging biomarkers into clinical decision-making to provide mineable tissue information. The present study sought to evaluate the diagnostic and predictive value of a multiparametric approach involving radiomics texture analysis, dual-energy CT-derived iodine concentration (DECT-IC), and diffusion-weighted MRI (DWI) in participants with histologically proven pancreatic cancer.
Materials and Methods:
In this study, a total of 143 participants (63 years ± 13, 48 females) who underwent third-generation dual-source DECT and DWI between November 2014 and October 2022 were included. Among these, 83 received a final diagnosis of pancreatic cancer, 20 had pancreatitis and 40 had no evidence of pancreatic pathologies. Data comparisons were performed using chi-square statistic tests, one-way ANOVA, or two-tailed Student’s t-test. For the assessment of the association of texture features with overall survival, receiver operating characteristics analysis and Cox regression tests were used.
Results:
Malignant pancreatic tissue differed significantly from normal or inflamed tissue regarding radiomics features (overall <em>P</em> < .001, respectively) and iodine uptake (overall <em>P</em> < .001, respectively). The performance for the distinction of malignant from normal or inflamed pancreatic tissue ranged between an AUC of >0.995 (95% CI, 0.955–1.0; <em>P</em> < .001) for radiomics features, >0.852 (95% CI, 0.767–0.914; <em>P</em> < .001) for DECT-IC, and >0.690 (95% CI, 0.587–0.780; <em>P</em> = .01) for DWI, respectively. During a follow-up of 14 ± 12 months (range, 10-44 months), the multiparametric approach showed a moderate prognostic power to predict all-cause mortality (c-index = 0.778 [95% CI, 0.697–0.864], <em>P</em> = .01).
Conclusion:
In conclusion, this study showed that a multiparametric approach allows for accurate diagnosis of pancreatic mass lesions, as well as prediction of all-cause mortality. Therefore, merging radiomics with established imaging modalities may have the potential to identify patients with cancer by computational allocation in specific survival models.
