Multiparametric detection and outcome prediction of pancreatic cancer involving dual-energy CT, diffusion-weighted MRI, and radiomics

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Abstract

Background: 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. 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 P

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Koch, V., Weitzer, N., Dos Santos, D. P., Gruenewald, L. D., Mahmoudi, S., Martin, S. S., … Albrecht, M. H. (2023). Multiparametric detection and outcome prediction of pancreatic cancer involving dual-energy CT, diffusion-weighted MRI, and radiomics. Cancer Imaging, 23(1). https://doi.org/10.1186/s40644-023-00549-8

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