CT Radiomic Features of Pancreatic Neuroendocrine Neoplasms

NCT ID: NCT03967951

Last Updated: 2019-12-26

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

70 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-03-23

Study Completion Date

2019-05-06

Brief Summary

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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

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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.

Conditions

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Pancreatic Neuroendocrine Tumor

Keywords

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Radiomics Pancretic neuroendocrine neoplasms (panNEN)

Study Design

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Observational Model Type

OTHER

Study Time Perspective

RETROSPECTIVE

Interventions

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CT radiomic feature evaluation

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.

Intervention Type OTHER

Eligibility Criteria

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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
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Francesco De Cobelli

OTHER

Sponsor Role lead

Responsible Party

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Francesco De Cobelli

Professor of Radiology, Head of Clinical and Experimental Radiology

Responsibility Role SPONSOR_INVESTIGATOR

Locations

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Deaprtment of Radiology, IRCCS Ospadale San Raffaele

Milan, , Italy

Site Status

IRCCS Ospedale San Raffaele

Milan, , Italy

Site Status

Countries

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Italy

References

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Belli ML, Mori M, Broggi S, Cattaneo GM, Bettinardi V, Dell'Oca I, Fallanca F, Passoni P, Vanoli EG, Calandrino R, Di Muzio N, Picchio M, Fiorino C. Quantifying the robustness of [18F]FDG-PET/CT radiomic features with respect to tumor delineation in head and neck and pancreatic cancer patients. Phys Med. 2018 May;49:105-111. doi: 10.1016/j.ejmp.2018.05.013. Epub 2018 May 23.

Reference Type BACKGROUND
PMID: 29866335 (View on PubMed)

Benedetti G, Mori M, Panzeri MM, Barbera M, Palumbo D, Sini C, Muffatti F, Andreasi V, Steidler S, Doglioni C, Partelli S, Manzoni M, Falconi M, Fiorino C, De Cobelli F. CT-derived radiomic features to discriminate histologic characteristics of pancreatic neuroendocrine tumors. Radiol Med. 2021 Jun;126(6):745-760. doi: 10.1007/s11547-021-01333-z. Epub 2021 Feb 1.

Reference Type DERIVED
PMID: 33523367 (View on PubMed)

Other Identifiers

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panNEN

Identifier Type: -

Identifier Source: org_study_id