Lung Nodule Characterization by Artificial Intelligence Techniques

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT03843164

Acronym

CARANOD-IA

Enrollment

Registered

2019-02-15

Start date

2019-03-12

Completion date

2021-03-31

Last updated

2019-04-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Incidental Lung Nodule

Keywords

Solitary Pulmonary Nodule, Multidetector Computed Tomography, Artificial Intelligence

Brief summary

Management of incidental lung nodule is difficult and mainly based on simple morphometric characteristics such as maximum size and shape. Radiomics could play a role in simplifying this management by orientating towards a benign or a malignant origin, by comparing advanced characteristics to a large database of lung nodules. The primary purpose is to evaluate the performances of a novel tool based on radiomics to characterize incidental lung nodules, discovered on computed tomography. The secondary objectives are: * to evaluate the variation in the performances of the software based on various technical aspects of the CT, such as radiation dose, reconstruction algorithm, type of scanner,… * to compare the performances of this software to those of expert readers, * to analyze the potential impact of this software on patient's management.

Interventions

None listed

Study design

Observational model

CASE_ONLY

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Inclusion criteria

* Adult patient (at least 18 years old); * With a chest CT acquired between Jan 1 2012 and Oct 1 2018 at the Strasbourg University Hospital; * CT being available over the PACS and exhibiting at least one lung nodule; * Patient having given its authorization for the exploitation of his medical data for this research.

Exclusion criteria

* Patient having expressed direct opposition to participation in this study; * Patient under juridical protection; * Patient under tutelage or guardianship.

Design outcomes

Primary

Measure	Time frame	Description
Evaluate the performances of a novel tool based on radiomics to characterize incidental lung nodules, discovered on computed tomography.	he period from January 1st, 2012 to October 01, 2018 will be examined	The study concerns patients who performed a chest CT scan at Strasbourg University Hospitals between 01/01/2012 and 01/10/2018

Countries

France

Contacts

Primary ContactMickaël OHANA, MD

mickael.ohana@chru-strasbourg.fr33 3 69 55 11 17

Backup ContactAissam LABANI, MD

aissam.labani@chru-strasbourg.fr33 3 69 55 11 17

Outcome results