CT-based Radiomic Signature Can Identify Adenocarcinoma Lung Tumor Histology

Maastricht University

Status: Unknown

Conditions: Nonsmall Cell Lung Cancer

Treatments: Diagnostic Test: Virtual biopsy

Study type: Observational

Funder types: Other

Identifiers

NCT03940846

LHist

Details and patient eligibility

About

Lung cancer remains the leading cause of cancer related mortality worldwide, with more than 1.5 million related deaths annually. Lung cancer is divided into two main groups: Small Cell Lung Carcinoma (SCLC) and Non-Small Cell Lung Carcinoma (NSCLC), with prevalence of ~20% and 80% respectively. NSCLC is further subdivided into adenocarcinoma (the most common), squamous cell carcinoma (SCC), and large cell carcinoma. Furthermore, each subtype is likely to have specific mutations, which could be targeted for treatment.

Medical imaging and radiomics feature extraction represent a candidate alternative to conventional tissue biopsy, a theory that is investigated in this study.

Enrollment: 650 estimated patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Availability of diagnostic non-contrast enhanced CT scan.
• Availability of histologic tumor analysis results

Exclusion criteria

Trial design

650 participants in 4 patient groups

Maastro (Lung1)

Description:

Open source dataset available at TCIA.org. The cohort includes CT scans of 422 patients diagnosed with NSCLC.

Treatment:

Diagnostic Test: Virtual biopsy

UCSF

Description:

A cohort of patients diagnosed with NSCLC at UCSF medical center. It includes CT scans of 165 patients.

Treatment:

Diagnostic Test: Virtual biopsy

Radboud

Description:

A cohort of patients diagnosed with NSCLC at Radboud medical center. It includes CT scans of 255 patients.

Treatment:

Diagnostic Test: Virtual biopsy

Stanford

Description:

Open source dataset available at TCIA.org. The cohort includes CT scans of 211 patients diagnosed with NSCLC.

Treatment:

Diagnostic Test: Virtual biopsy