Speed and efficiency: evaluating pulmonary nodule detection with AI-enhanced 3D gradient echo imaging.

ABSTRACT:

Objectives

Evaluating the diagnostic feasibility of accelerated pulmonary MR imaging for detection and characterisation of pulmonary nodules with artificial intelligence-aided compressed sensing.

Materials and methods

In this prospective trial, patients with benign and malignant lung nodules admitted between December 2021 and December 2022 underwent chest CT and pulmonary MRI. Pulmonary MRI used a respiratory-gated 3D gradient echo sequence, accelerated with a combination of parallel imaging, compressed sensing, and deep learning image reconstruction with three different acceleration factors (CS-AI-7, CS-AI-10, and CS-AI-15). Two readers evaluated image quality (5-point Likert scale), nodule detection and characterisation (size and morphology) of all sequences compared to CT

SUBMITTER: Ziegelmayer S 

PROVIDER: S-EPMC11914225 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature