ArticleJournal of magnetic resonance imaging : JMRI2026
RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization.
Article in Journal of magnetic resonance imaging : JMRI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Editorial for "RadiolGAN: Multicenter Feasibility Study of Synthetic CT From 3D Ultra-Short Echo Time MRI for Enhanced Pulmonary Radiologic Sign Visualization".Journal of magnetic resonance imaging : JMRI · 2026Article
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Authors and funding
16 authors.
Funding
Abstract
backgroundChest CT requires breath-holding and ionizing radiation. 3D ultrashort echo time (UTE) MRI allows radiation-free imaging, but the image quality is suboptimal. PURPOSE: To develop RadiolGAN and evaluate synthetic CT (sCT) from 3D UTE MRI for enhanced pulmonary visualization. STUDY TYPE: Prospective multicenter study. POPULATION: Three hundred and fifty-nine subjects (167 women, 192 men; 52 ± 19 years) from four centers: 244 training, 61 internal test, and 54 external test. FIELD STRENGTH/SEQUENCE: 3 T, 3D UTE gradient-echo sequence. ASSESSMENT: Signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise, peak signal-to-noise ratio (PSNR), mean structural similarity index (MS-SSIM), universal quality index (UQI), and learned perceptual image patch similarity (LPIPS). Three radiologists rated pulmonary structures (bronchi, vessels, fissures, artifacts, diagnostic confidence) and radiologic signs (nodules/masses, ground-glass opacities, patchy shadows/consolidation, emphysema/bullae, bronchiectasis) on a 5-point Likert scale. STATISTICAL TESTING: Repeated-measures ANOVA, paired t-tests, and Friedman tests; p < 0.05 significant.
resultsIn the external test set, RadiolGAN-CT showed higher SNR (32.63 ± 1.21 vs. 26.07 ± 1.53) and CNR (25.36 ± 1.06 vs. 21.64 ± 1.32), and lower noise (15.74 ± 0.85 vs. 19.66 ± 1.01) than 3D UTE. Versus CycleGAN-CT, RadiolGAN-CT achieved higher PSNR (65.32 ± 0.19 vs. 64.68 ± 0.21), MS-SSIM (0.912 ± 0.004 vs. 0.892 ± 0.004), FSIM (0.808 ± 0.007 vs. 0.783 ± 0.006), and UQI (0.854 ± 0.007 vs. 0.843 ± 0.007), and lower LPIPS (0.221 ± 0.010 vs. 0.236 ± 0.009). No differences were found between RadiolGAN-CT and CycleGAN-CT in SNR (p = 0.612), CNR (p = 0.547), or noise (p = 0.595). Diagnostic confidence was higher for RadiolGAN-CT (3.98 ± 1.09) than CycleGAN-CT (3.59 ± 1.06) and 3D UTE (2.84 ± 1.30). Ground-glass opacity depiction did not differ between RadiolGAN-CT and CycleGAN-CT (p = 0.903). DATA
conclusionRadiolGAN enables high-fidelity sCT from 3D UTE, improving structural depiction and perceptual similarity. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: 2.
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