Clinical trial NCT00906789: Testing of Computer Aided Detection Software for Riverain Medical Group
Official title: Testing of Computer Aided Detection Software for Riverain Medical Group
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Lung Cancer
Keywords: Lung Cancer
Chest Radiograph
Computer-aided Detection
Image processing
Lead sponsor: Georgetown University
Sponsor class: OTHER
Collaborators: name: Riverain Technologies
First posted: 2009-05-21
Enrollment: 15
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Radiologists in active clinical practice who are not subspecialists in chest radiology

Brief summary: This is a clinical trial using retrospective data of two different software devices developed by Riverain Medical Group: Softview and OnGuard 5.0. The two studies will be run concurrently. Riverain Medical Group's computer systems are designed to assist radiologists in their identification of lung cancer on chest radiographs. The current machine received FDA Pre-Market Approval. This is to test two new software approaches.

Detailed description: In 2000, data was presented to the FDA to demonstrate that a new system for computer analysis could assist radiologists in the detection of small lung cancers on chest radiographs. Radiologists using the system showed a statistically significant improvement in lung cancer detection rate when they used the system, compared to their interpretation of chest radiographs when they did not use the computer system. This study, along with other supporting data, resulted in the FDA giving Pre-Market Approval for the system.

The system has undergone several improvements in software and hardware, and it is now intended to test two different software systems to determine whether radiologists using the systems can improve their detection of lung cancer on chest radiographs.

One of these systems processes the chest radiograph to decrease the emphasis given to the shadow of the ribs and thereby enhances the ability of radiologists to detect disease in the lungs. The second system performs a series of evaluations on chest radiographs and, based on a complex system of analysis, points to locations on the chest radiograph that contain solitary pulmonary nodules having the characteristics of primary lung cancer or solitary metastases of cancer to the lungs.

This will be a test of radiologists to determine the degree of improvement, if any, that results when they interpret chest radiographs that may or may not have cancer, first interpreted without the computer and, second, with the images output by the software.

Eligibility criteria: Inclusion Criteria:

* US American Board of Radiology Certified Radiologists in active clinical practice

Exclusion Criteria:

* Specialists in pulmonary or chest or cardio-pulmonary radiology Prior membership on expert panels for this study who prepared cases Current or recent colleagues or trainees (within 10 years) of the Principal Investigator

Primary outcomes:
measure: Improvement in Cancer Detection as Measured by Localized Receiver Operating Characteristic) LROC Changes Under the LROC Curve.
timeFrame: Three days of experiment over 3-5 months, varied by participant
Secondary outcomes:
measure: Sensitivity and Specificity Using SoftView Software
timeFrame: Three days of experiment over 3-5 months, varied by participant
Other outcomes:
measure: Difference in the Area Under the LROC Curve Comparing OnGuard 1.0 and OnGuard 5.1
timeFrame: 5 months
Locations:
city: Washington
country: United States
facility: ISIS Imaging Science Research Center, Georgetown University
state: District of Columbia
Study officials:
affiliation: Georgetown University
name: Matthew T. Freedman, MD, MBA
role: PRINCIPAL_INVESTIGATOR
affiliation: Georgetown University
name: Ben Lo, Ph.D.
role: STUDY_DIRECTOR
References:
citation: Freedman MT, Lo SC, Seibel JC, Bromley CM. Lung nodules: improved detection with software that suppresses the rib and clavicle on chest radiographs. Radiology. 2011 Jul;260(1):265-73. doi: 10.1148/radiol.11100153. Epub 2011 Apr 14.