Assessment of a Radiomics-based Computer-Aided Diagnosis Tool for Cancer Risk Stratification of Pulmonary Nodules

Status: Recruiting
Location: See all (3) locations...
Intervention Type: Device
Study Type: Interventional
Study Phase: Not Applicable
SUMMARY

This is a pragmatic clinical trial that will study the effect of a radiomics-based computer-aided diagnosis (CAD) tool on clinicians' management of pulmonary nodules (PNs) compared to usual care. Adults aged 35-89 years with 8-30mm PNs evaluated at Penn Medicine PN clinics will undergo 1:1 randomization to one of two groups, defined by the PN malignancy risk stratification strategy used by evaluating clinicians: 1) usual care or 2) usual care + use of a radiomics-based CAD tool.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 35
Maximum Age: 89
Healthy Volunteers: f
View:

• Male or female, aged 35-89 years

• Scheduled to be evaluated at a UPHS PN clinic

• Newly discovered solid or part-solid indeterminate PN 8-30mm in maximal diameter on CT imaging within 60 days of index clinic visit

• Chest CT imaging meeting the technical requirements for compatibility with Optellum Virtual Nodule Clinic software

Locations
United States
Pennsylvania
Penn Medicine University City
RECRUITING
Philadelphia
Penn Medicine Washington Square
RECRUITING
Philadelphia
Perelman Center for Advanced Medicine
RECRUITING
Philadelphia
Contact Information
Primary
Roger Y. Kim, MD, MSCE
roger.kim@pennmedicine.upenn.edu
215-662-3677
Backup
Anil Vachani, MD, MSCE
avachani@pennmedicine.upenn.edu
215-573-7931
Time Frame
Start Date: 2024-01-09
Estimated Completion Date: 2027-12-31
Participants
Target number of participants: 300
Treatments
No_intervention: Usual care (clinician assessment)
In the usual care arm, clinicians will evaluate individuals with indeterminate pulmonary nodules as part of routine clinical care. No specific guidance regarding pulmonary nodule risk stratification will provided to evaluating clinicians.
Experimental: Clinician assessment + CAD-based risk stratification
In the experimental arm, evaluating clinicians will receive a Lung Cancer Prediction report from an artificial intelligence radiomics-based computer-aided diagnosis tool for risk stratification of pulmonary nodules.
Related Therapeutic Areas
Sponsors
Leads: Abramson Cancer Center at Penn Medicine

This content was sourced from clinicaltrials.gov