An observational study in Pancreatic Neuroendocrine Tumor, sponsored by Francesco De Cobelli. Completed at 2 sites in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-09-23.
Sponsored by Francesco De Cobelli · Observational
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.
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.
102 studies on the registry are indexed under Adenoma, Islet Cell; 26 are open to participants now.
This study's enrollment of 70 is below the median of 85 across 22 observational studies indexed under Adenoma, Islet Cell.
Browse Adenoma, Islet Cell studies →Francesco De Cobelli is the lead sponsor of 6 studies on the registry; 2 are open to participants now.
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Monocentric, retrospective, observational study. Subjects who fulfill the inclusion criteria will be randomly chosen from our Institutional data-base. Thirty patients will be used to evaluate inter-observer variability and forty patients will be used to evaluate histological characteristics on CT-scans with and without contrast agent).
Imaged based and clinical variables will be used to construct an overall status of the patient.
Exclusion Criteria:
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.
Interobserver variability in delineating panNENs on CT
Asses inter-observer variability on CT- scans (with contrast alone)
Time frame: 6 months
Use CT texture analysis to predict, histological characteristics of PanNEN on CT scans
Evaluate histological characteristics on CT-scans with and without contrast agent in a group of subjects
Time frame: 6 months
Plan to share: No
This study is completed, as verified in Dec 2019. You cannot join it, but the record below documents what was studied.
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Francesco De Cobelli