Complementary role of computed tomography texture analysis for differentiation of pancreatic ductal adenocarcinoma from
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PANCREAS
Complementary role of computed tomography texture analysis for differentiation of pancreatic ductal adenocarcinoma from pancreatic neuroendocrine tumors in the portal‑venous enhancement phase Christian Philipp Reinert1 · Karolin Baumgartner1 · Tobias Hepp1 · Michael Bitzer2 · Marius Horger1
© Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Purpose To assess the role of CT-texture analysis (CTTA) for differentiation of pancreatic ductal adenocarcinoma (PDAC) from pancreatic neuroendocrine neoplasm (PNEN) in the portal-venous phase as compared with visual assessment and tumor-to-pancreas attenuation ratios. Methods 53 patients (66.1 ± 8.6y) with PDAC and 42 patients (65.5 ± 12.2y) with PNEN who underwent contrast-enhanced CT for primary staging were evaluated. Volumes of interests (VOIs) were set in the tumor tissue at the portal-venous phase excluding adjacent structures. Based on pyradiomics library, 92 textural features were extracted including 1st, 2nd, and higher order features, and then compared between PNEN and PDAC. The visual assessment classified tumors into hypo-, iso-, or hyperdense to pancreas parenchyma or into homogeneous/heterogeneous. Additionally, attenuation ratios between the tumors and the non-involved pancreas were calculated. Results 8/92 (8.6%) highly significant (p double) in G1
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PNEN versus G2/G3 PNEN. Focusing on the statistically significant textural feature of the 2nd order (co-occurrence matrix), results are suggesting a higher magnitude of highergray-level values and joint distribution in PNEN versus PDAC. Interestingly, we found no significant differences in terms of radiomics features among PDAC of different gradings. Finally, our results showed great overlap between the two tumor entities in terms of visual assessment and even quantification of tumor-to-parenchyma ratios with no signal significant finding. Consequently, we believe that in such cases the additional use of CTTA could improve diagnostic quality delivering complementary information without the need for subsequent additional imaging which might improve patient management (e.g., staging procedures). Our study has some limitations. First, our image data were collected on different multi-slice scanner, but using a similar examination and contrast agent injection protocol. Nevertheless, some variations in image quality are inherently expected. This aspect should stress also the applicability of textural analysis on different image data sets with comparable results in our cohort. Second, morphologic imaging features (e.g., form, size, contours) were not evaluated in this cohort as we considered that there is already enough evidence on this topic in the current specialty literature. In conclusion, our data indicate that CT-texture analysis is a feasible tool for differentiation of PNEN from PDAC and also of G1 from G2/3 PNEN in the portal-venous phase. Most textural features reflect lower tissue attenuation and uniformity in PDAC as compared to PNEN. Notably, CTTA seems to outm
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