Multiparametric Image Analysis and Correlation With Outcomes in Lung Cancer Screening and Early Stage Lung Cancer

Multi Parametric Image Analysis and Correlation With Outcomes in Lung Cancer Screening and Early Stage Lung Cancer

Determine whether CT-based multiparametric analytical models may improve prediction of biopsy and treatment outcome in patients undergoing screening CT scan and/or treatment for early stage lung cancer

Study Overview

• Status: Recruiting
• Conditions: Lung Cancer
• Intervention / Treatment: Other: Retrospective Study

Detailed Description

The hypothesis is that multiparametric models that incorporate complex image information from screening CT scans will improve prediction of the outcome of subsequent lung biopsy, an invasive diagnostic procedure. In this project, we will construct an image feature-based multiparametric prognostic model for biopsy outcome from screening lung CT scans performed at our institution, and then validate it using theNLST imaging and clinical outcomes dataset.

This study involves no treatment or invasive procedures. Investigator will review all charts of patients who were treated for early stage lung cancer with definitive radiation therapy at UTSW or Parkland Memorial hospital, diagnosed with a malignancy from January 1, 2004 to October 31, 2014, to compile demographic, diagnostic, therapeutic, outcome, and toxicity data. Investigator expect that this will include approximately 200 patient charts. This data will be analyzed statistically and used for future directed research. Investigator will also analyze an anonymized dataset of patients from the National Lung Cancer Screening Trial (NLST) provided by the National Cancer Institute (NCI)

• Study Type: Observational
• Enrollment (Estimated): 2000

Contacts and Locations

• Study Contact: Name: Sarah Neufeld, MS; Phone Number: 214-648-1836; Email: Sarah.hardee@UTSouthwestern.edu
• Study Contact Backup: Name: Kajal Desai, MS; Phone Number: 2146458525; Email: kajal.desai@utsouthwestern.edu

Study Locations

• United States
  • Texas
    • Dallas, Texas, United States, 75390
      • Recruiting
      • UT Southwestern Medical Center
      • Contact: Sarah Neufeld; Phone Number: 214-648-1836; Email: Sarah.Hardee@UTSouthwestern.edu

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 99 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

The medical charts are the subjects. Risk will be minimized by protecting patient data through the use of de-identification of patient identifiers and password protected data collection. The information will be given only to faculty members and statisticians involved in the research project. The data will be disclosed only for analytical purposes.

Confidentiality will be maintained by adhering to HIPAA guidelines. The location of the data will be maintained at the worksite of the PI and the research coordinator in the Moncrief Radiation Oncology Department on the North Campus at UTSW. Risks will be minimized by protecting patient data and using it only for research purposes for retrospective analysis.

Description

Inclusion Criteria:

Patients that have been diagnosed with lung cancer, and are treated at Department of Radiation Oncology, UTSW or Parkland Memorial Hospital.

Exclusion Criteria:

There will be no absolute exclusion criteria as long as the inclusion criteria have been met.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Determine whether CT-based multiparametric analytical models may improve prediction of biopsy and treatment outcome in patients undergoing screening CT scan and/or treatment for early stage lung cancer	We will review all charts of patients who were treated for early stage lung cancer with definitive radiation therapy at UTSW or Parkland Memorial hospital, diagnosed with a malignancy from January 1, 2004 to October 31, 2014, to compile demographic, diagnostic, therapeutic, outcome, and toxicity data. The data will be subject to standard descriptive, parametric, and nonparametric hypothesis testing with biostatistical analyses. We will also analyze an anonymized dataset of patients from the National Lung Cancer Screening Trial (NLST) provided by the National Cancer Institute (NCI) including screening images and diagnostic outcomes to validate models generated using institutional data.	10 years

Collaborators and Investigators

• Sponsor: University of Texas Southwestern Medical Center
• Investigators: Principal Investigator: Jing Wang, MD, UTSW Radiation Oncology

Study record dates

Study Major Dates

• Study Start (Actual): February 18, 2015
• Primary Completion (Estimated): June 30, 2029
• Study Completion (Estimated): June 30, 2031

Study Registration Dates

• First Submitted: May 18, 2018
• First Submitted That Met QC Criteria: June 8, 2018
• First Posted (Actual): June 20, 2018

Study Record Updates

• Last Update Posted (Actual): April 22, 2026
• Last Update Submitted That Met QC Criteria: April 16, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Early Stage Lung Cancer
• Additional Relevant MeSH Terms: Neoplasms by Site; Neoplasms; Respiratory Tract Diseases; Lung Diseases; Respiratory Tract Neoplasms; Thoracic Neoplasms; Lung Neoplasms; Health Care Quality, Access, and Evaluation; Investigative Techniques; Epidemiologic Methods; Health Care Evaluation Mechanisms; Quality of Health Care; Public Health; Environment and Public Health; Epidemiologic Studies; Epidemiologic Study Characteristics; Cohort Studies; Case-Control Studies; Retrospective Studies
• Other Study ID Numbers: STU 122014-052

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No