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Article History

Received: 3 March 2022

Revised: 14 June 2022

Accepted: 24 July 2022

First Online: 25 August 2022

Declarations

:

: The scientific guarantor of this publication is Masoom A. Haider.

: The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

: Rahi Jain and Dr. Dominik Deniffel who have significant statistical expertise (both co-authors) provided statistical advice for this manuscript.

: Written informed consent was waived by the Institutional Review Board.

: This retrospective single-center study was approved by the institutional review boards.

: This cohort represents a subset of our prior studies. No pathohistological or transcriptomic information was available for the cohort at the time of the prior analysis. An overlap of study populations is discussed in the cover letter and disclosure paragraph.ReferencesHealy GM, Salinas-Miranda E, Jain R, et al (2021) Pre-operative radiomics model for prognostication in resectable pancreatic adenocarcinoma with external validation. European Radiology 2021 1–14. (n = 122)Khalvati F, Zhang Y, Baig S, et al (2019) Prognostic value of CT radiomic features in resectable pancreatic ductal adenocarcinoma. Scientific Reports 9:5449. (n = 13)Zhang Y, Lobo-Mueller EM, Karanicolas P, et al (2021) Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images. Scientific reports 11:. (n = 38)Zhang Y, Lobo-Mueller EM, Karanicolas P, et al (2020) CNN-based survival model for pancreatic ductal adenocarcinoma in medical imaging. BMC Medical Imaging 20:. (n = 38)

: • Retrospective• diagnostic or prognostic study• performed at one institution