Pancreatic Neuroendocrine Tumor
Conditions
Keywords
Radiomics, Pancretic neuroendocrine neoplasms (panNEN)
Brief summary
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.
Detailed description
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.
Interventions
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.
Sponsors
Study design
Eligibility
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Interobserver variability in delineating panNENs on CT | 6 months | Asses inter-observer variability on CT- scans (with contrast alone) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Use CT texture analysis to predict, histological characteristics of PanNEN on CT scans | 6 months | Evaluate histological characteristics on CT-scans with and without contrast agent in a group of subjects |
Countries
Italy