Radiomics Tool for Pulmonary Nodule Risk Stratification

Study Overview
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Brief Summary
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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.

Detailed Description
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Accurate malignancy risk stratification of pulmonary nodules (PNs) is critical to ensuring that cancer is diagnosed in a timely manner and patients do not undergo unnecessary diagnostic procedures. Preliminary data suggests that a radiomics-based lung cancer prediction (LCP) computer-aided diagnosis (CAD) tool is effective in risk stratifying PNs and may improve clinicians' PN management decisions. This is a pragmatic clinical trial evaluating the effect of this CAD tool on clinicians' management of PNs compared to usual care. Individuals eligible for this study will include adults aged 35-89 years who are scheduled to be evaluated at a Penn Medicine PN clinic for a newly discovered PN 8-30mm in maximal diameter on CT imaging. Exclusion criteria include lack of CT imaging data at the time of index clinic visit, thoracic lymphadenopathy by CT size criteria, presence of pulmonary masses (>3cm in maximal diameter), PNs with popcorn calcification (consistent with benign etiology), subsolid PNs, and a known history of active cancer. Enrolled participants will undergo 1:1 stratified randomization to one of two groups, defined by the PN malignancy risk stratification strategy used by evaluating clinicians: 1) usual care (clinician assessment) or 2) clinician assessment + CAD-based risk stratification using the LCP-CAD tool. The control arm will be usual care, defined as routine clinician assessment of PN malignancy risk. In the experimental arm, at the start of the clinic visit clinicians will be provided a report with the CAD tool estimate of malignancy risk for the PN being evaluated along with information about the CAD tool.

Official Title
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Assessment of a Radiomics-Based Computer-Aided Diagnosis Tool for Cancer Risk Stratification of Pulmonary Nodules

Conditions
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Lung Cancer, Pulmonary Nodule, Solitary

Intervention / Treatment
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* Device: Optellum Virtual Nodule Clinic


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Male or female, aged 35-89 years Scheduled to be evaluated at a pulmonary nodule clinic Newly discovered solid PN 8-30mm in maximal diameter on CT imaging Chest CT imaging compatible with Optellum Virtual Nodule Clinic software and available on or before the date of index clinic visit Exclusion Criteria: Chest CT imaging with mediastinal or hilar lymphadenopathy by CT size criteria (>10mm in maximal short-axis diameter on axial CT images) PNs with popcorn calcification (consistent with benign etiology) Subsolid PNs (may be associated with lower risk of clinically significant malignancy) Known history of active cancer

Ages Eligible for Study
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Minimum Age: 35 Years
Maximum Age: 89 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Usual care (clinician assessment)<br>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<br>In the experimental arm, evaluating clinicians will receive an electronic health record-based alert with the report from an artificial intelligence radiomics-based computer-aided diagnosis tool for risk stratification of pulmonary nodules. | Device: Optellum Virtual Nodule Clinic<br>* The Optellum Virtual Nodule Clinic is an FDA-approved (Class II) device for risk stratification of pulmonary nodules. It uses a convolutional neural network to evaluate CT imaging data to provide an estimate of malignancy risk for indeterminate pulmonary nodules.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Appropriate management of pulmonary nodule | The composite proportion of benign pulmonary nodules managed with imaging surveillance and malignant pulmonary nodules managed with biopsy or empiric treatment. Final pulmonary nodule diagnosis will be categorized as malignant or benign. If the pathology report does not offer a specific pathologic diagnosis or in inconclusive (i.e., the biopsy was non-diagnostic), we will defined pulmonary nodule resolution, shrinkage, or diameter stability at 12 months as a benign diagnosis. | 12 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Timeliness of care | For patients with malignant pulmonary nodules, defined as the number of days between the index clinic visit and diagnosis of malignancy and receipt of treatment for malignancy (i.e., surgical resection, radiation therapy). | 12 months | 
| Adverse events | For patients undergoing biopsy, defined as procedural complications related to pulmonary nodule biopsy. | 12 months | 
| Diagnostic yield | Using information found in pathology reports, defined as the proportion of biopsies with a definitive histopathologic diagnosis, for each type of diagnostic biopsy procedure. | 12 months | 
| Healthcare costs | The costs of all imaging studies and diagnostic testing associated with the pulmonary nodule diagnostic process, based on Medicare allowed amounts (amount paid by Medicare and the amount paid by the beneficiary and/or third parties). | 12 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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clinical effectiveness, clinical utility, artificial intelligence, medical decision-making, risk stratification