Imaging-based Prediction of Eligibility for ChemoImmunotherapy in Resectable NSCLC, iPRECISE

What this Trial Is About

Researchers are investigating imaging features from chest computed tomography (CT) scans to better predict how adults with resectable non-small cell lung cancer (NSCLC) respond to neoadjuvant chemoimmunotherapy given before surgery. This observational study aims to find CT scan characteristics that correlate with how well the cancer responds pathologically and to assess links with treatment side effects and long-term outcomes like disease progression and survival. The study also explores whether advanced deep learning-based CT reconstruction improves imaging biomarker development. Participants will receive standard clinical care involving neoadjuvant chemoimmunotherapy followed by surgery. Chest CT scans are obtained before starting chemoimmunotherapy and again after completing it, just before surgery. Additional CT scans may be done if disease progression is suspected. The study applies both conventional and high-resolution deep learning-based CT reconstruction to the images to evaluate tumor features, lymph node involvement, and possible immune-related lung inflammation. During the study, participants undergo standardized CT imaging and clinical monitoring. Researchers will compare imaging findings with clinical data, molecular markers, and surgical pathology results including pathologic complete and major responses. Outcomes like progression-free and overall survival will also be evaluated. The study involves follow-up through surgery and up to six months for primary outcome assessment, with longer-term monitoring for disease progression and survival. This may help develop noninvasive methods to guide treatment planning for NSCLC patients.

Imaging-based PRediction of Eligibility for ChemoImmunotherapy in reSEctable NSCLC, iPRECISE