Diagnostic performance of a single breath-hold lung MRI scan with AI-powered compressed sensing for nodule detection in comparison to photon counting detector-CT

OBJECTIVE: The aim was to evaluate the performance of a single-breath-hold accelerated 3D-T1w-FFE 3-T MRI sequence for screening lung nodules, compared with photon-counting detector CT (PCD-CT), which served as the reference standard. MATERIALS AND METHODS: In this single-center prospective study, 148 healthy adults underwent lung 3-T MRI between June 2024 and June 2025 using a single-breath-hold, AI-aided compressed sensing (AI-CS)- accelerated 3D-T1-FFE sequence (acceleration factor of 9) to evaluate for the presence of lung nodules. Patients scanned within 24 h using PCD-CT, for comparison, were enrolled. Lung-RADS scores were evaluated per patient, and all nodules were assessed for size and composition. The diagnostic performance of MRI was compared with PCD-CT, including interobserver and intermodality agreement, using Lin's Concordance Correlation Coefficient (CCC). RESULTS: 97 patients were enrolled (65 men, 67%; mean age 58 ± 12 years old) and 33 (34%) were active smokers. MRI and CT showed complete agreement in the Lung-RADS 4A and 4B categories. MRI demonstrated an overall sensitivity of 83.1% (95% CI: 73.2-89.9) for solid nodules, increasing to 98.1% (95% CI: 90.2-99.7) for nodules ≥ 4 mm. Lin's CCC for nodule size was 0.985, indicating excellent agreement, with MRI showing a slight underestimation of 1.02 mm (95% CI: [-1.16, 3.20]) in Bland-Altman analysis. MRI failed to detect calcified nodules < 4 mm, which accounted for 51.2% of undetected nodules. CONCLUSIONS: A single breath-hold AI-CS accelerated 3D-T1-FFE MRI scan can be a valuable tool for solid lung nodule screening, showing very good agreement with CT. KEY POINTS: Question May lung MRI using an optimized AI-CS accelerated 3D-T1-FFE sequence acquired in a single breath hold be a radiation-free alternative to CT in lung cancer screening? Findings Lung MRI using AI-CS 3D-T1-FFE sequence achieved an overall accuracy of 87.3% for detecting solid nodules overall, increasing to 97.7% for nodules ≥ 4 mm. Clinical relevance Lung MRI using an optimized AI-CS 3D-T1-FFE is a promising alternative to chest CT in lung nodules screening, offering high diagnostic accuracy, especially for clinically relevant nodules, excellent Lung-RADS classification agreement, and short acquisition time (17.2 s [IQR, 17.2-17.3]).