Radiomics Multifactorial Biomarker for Pulmonary Nodules

Neoplasms Clinical Trial

— RMBPN  

Official title:

Radiomics and Clinical Variables Can Differentiate Malignant Nodules and Detect Invasive Adenocarcinoma in Pulmonary Nodules: a Multi-center Study

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03872362
• Other study ID #: UM2019DLABGY1
• Status: Completed
• Start date: July 11, 2018
• Est. completion date: February 1, 2019

Study information

• Verified date: January 2019
• Source: Maastricht University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The investigators aim to investigate the utility of radiomics to differentiate malignant nodules from benign nodules and invasive adenocarcinoma from non-invasive adenocarcinoma.

Description:

With the development of computed tomography (CT) equipment and the increasing use of lung cancer screening programs with low-dose CT, a growing number of early-stage lung cancers were detected so that a large number of patients have undergone surgery.

Although a number of radiological studies have been used morphological signs so-called semantic features to make a differential diagnosis, it is still hard to apply by clinician because pulmonary nodules especially ground-glass nodules and small size nodules have atypical radiology signs and have strong subjectivity from different observers. Recently, CT-based radiomics, extracting the quantitative high-throughput features from medical images and facilitating clinical decision-making system, showed a good performance to predict diagnosis and prognosis of diverse cancer.

Therefore, the proposed project aims to develop and validate radiomics models based on CT images to identify malignant nodules and then to discriminate the different types of lung adenocarcinoma in patients with pulmonary nodules.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 800
• Est. completion date: February 1, 2019
• Est. primary completion date: January 11, 2019
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• intraoperative frozen section diagnosis and final pathology diagnosis are available

• preoperative standard non-enhanced CT is available

• Pathologically confirmed

Exclusion Criteria:

• with a previous history of radiation therapy, chemotherapy or biopsy

• the time interval between the CT examination and surgery was more than two weeks

Related Conditions & MeSH terms

• Carcinoma, Non-Small-Cell Lung
• Lung Diseases
• Lung Neoplasms
• Multiple Pulmonary Nodules
• Neoplasms
• Pathology

Intervention

Diagnostic Test:
• radiomics
The high-throughput extraction of large amounts of quantitative image features from medical images

Locations

Country	Name	City	State
China	Affiliated Zhongshan Hospital of Dalian University	Dalian	Liaoning

Sponsors (4)

Lead Sponsor	Collaborator
Maastricht University	The Affiliated Zhongshan Hospital of Dalian University, The Fifth Hospital of Dalian, The Second Affiliated Hospital of Dalian Medical University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Malignant nodules classifier	Model based on Radiomic that can differentiate malignant nodules from benign nodules.	30 days
Primary	Invasive adenocarcinoma classifier	Model based on Radiomic that can differentiate invasive adenocarcinoma from non-invasive adenocarcinoma.	30 days