Stereotactic Body Radiation Therapy Planning With Artificial Intelligence-Directed Dose Recommendation for Treatment of Primary or Metastatic Lung Tumors, RAD-AI Study

PRIMARY OBJECTIVE: I. To obtain preliminary evidence of efficacy (reduction in local failure free survival) in patients receiving SBRT to the lung with personalized artificial intelligence dose guidance (Deep Profiler + iGray). SECONDARY OBJECTIVES: I. To evaluate progression free survival (PFS) per Response Evaluation Criteria in Solid Tumors (RECIST) version (v.) 1.1 in patients receiving individualized radiation doses to the lung as recommended by Deep Profiler + iGray. II. To evaluate the feasibility, defined as 85% receiving within 10% of the projected dose, of implementing the individualized radiation doses recommended by machine learning software (Deep Profiler + iGray) in a clinical practice. III. To assess toxicity per Common Terminology Criteria for Adverse Events (CTCAE) v. 5.0 in patients receiving individualized radiation doses to the lung as recommended by Deep Profiler + iGray. IV. To evaluate respiratory function per the RTOG Pulmonary Function Scale. OUTLINE: Patients undergo radiation planning with AI-directed analysis for dose recommendations with Deep Profiler + iGray software on study. Patients then undergo SBRT on study. Patients also undergo positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), and/or x-ray imaging during screening and follow-up.