Deep Learning Reconstruction: Capability for Image Quality and Staging Accuracy Improvements on Chest MRI in NSCLC Patients

Deep learning reconstruction (DLR) has been applied in routine clinical practice and started to demonstrate its’ potential in different MR examinations. However, no one have evaluated the utility of DLR for chest MRI, yet. We hypothesize that DLR method is useful for chest MRI and improve image quality and diagnostic performance for T and N factor evaluations in non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine the influence of DLR method on image quality and diagnostic performance for T and N factor evaluations at chest MRI in NSCLC patients.