CT Radiomic Features of Pancreatic Neuroendocrine Neoplasms

The aim of this study is to quantify inter-observer variability in delineating pancreatic neuroendocrine neoplasm (PanNEN) on Computerized Tomography (CT) images and its impact on radiomic features (RF), subsequently to this determination, to use CT texture analysis to predict, histological characteristics of PanNEN on CT scans.

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Key information

Conditions

Pancreatic Neuroendocrine Tumor Adenoma Adenoma, Islet Cell Digestive System Diseases Digestive System Neoplasms Endocrine Gland Neoplasms Endocrine System Diseases Neoplasms Neoplasms by Histologic Type Neoplasms by Site Neoplasms, Glandular and Epithelial Pancreatic Diseases Pancreatic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Deaprtment of Radiology, IRCCS Ospadale San Raffaele, Milan, Italy

About this study

CT imaging is the most widely used modality for studying radiomic features due to its ability to assess tissue density, shape, texture and size before, during and after therapy. To the best of the investigator's knowledge, the impact of inter-observer delineation variability on the reliability of CT RF for PanNEN patients, including Hounsfield unit (HU) values-, shape-, and texture-based features, has not yet been assessed. One this has been determined, an additional evaluation will be conducted to correlate the morphologically observed images with their histopathological characteristics.

The ultimate potential objective of this research is to identify and predict characteristics of aggressiveness of PanNEN in CT scans.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

> 18 years of age
pancreatic neuroendocrine neoplasm with intervention and biopsy
availability of pre-operatory CT scan with or without IV contrast agent- inInstitution from 2009-2017

Exclusion criteria

pregnant women

Treatment and study plan

CT radiomic feature evaluation

Other

Radiomic features will be calculated and extracted from all contrast and non-contrast CT-scans. First order features will be evaluated and high order features will be grouped in parent matrices. Parent matrices of second and third order will be chosen and evaluated.

In the second part, based on the results of inter-correlation of the operator analysis, the most significant radiomic features will be chosen. Morphological and histopathological features will be evaluated will be.

Histopathology will be performed on a biopsy specimen; percentage of Ki67 and grading will be evaluated.

Primary outcomes

Interobserver variability in delineating panNENs on CT

Time frame: 6 months

Asses inter-observer variability on CT- scans (with contrast alone)

Secondary outcomes

Use CT texture analysis to predict, histological characteristics of PanNEN on CT scans

Time frame: 6 months

Evaluate histological characteristics on CT-scans with and without contrast agent in a group of subjects

Sponsors and collaborators

Lead sponsor

Francesco De Cobelli

Other

Registry information

Important dates

Study start: 2019
Primary completion: 2019
Study completion: 2019
First posted: May 30, 2019
Registry last updated: Dec 26, 2019

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed