초록/요약

Background: Synthetic MRI is a time-efficient imaging technique that provides both quantitative MRI and contrast-weighted images simultaneously. However, a rather long single scan time can be challenging for children. Objective: To evaluate the clinical feasibility of time-saving synthetic MRI protocols adjusted for echo train length and receiver bandwidth in pediatric neuroimaging based on image quality assessment and quantitative data analysis. Materials and methods: In total, we included 33 children ages 1.6–17.4 years who underwent synthetic MRI using three sets of echo train length and receiver bandwidth combinations (echo train length [E]12–bandwidth [B in KHz]22, E16–B22 and E16–B83) at 3 T. The image quality and lesion conspicuity of synthetic contrast-weighted images were compared between the suggested protocol (E12–B22) and adjusted protocols (E16–B22 and E16–B83). We also compared tissue values (T1, T2, proton-density values) and brain volumetry. Results: For the E16–B83 combination, image quality was sufficient except for 15.2% of T1-W and 3% of T2-W fluid-attenuated inversion recovery (FLAIR) images, with remarkable scan time reduction (up to 35%). The E16–B22 combination demonstrated a comparable image quality to E12–B22 (P>0.05) with a scan time reduction of up to 8%. There were no significant differences in lesion conspicuity among the three protocols (P>0.05). Tissue value measurements and brain tissue volumes obtained with the E12–B22 protocol and adjusted protocols showed excellent agreement and strong correlations except for gray matter volume and non-white matter/gray matter/cerebrospinal fluid volume in E12–B22 vs. E16–B83. Conclusion: The adjusted synthetic protocols produced image quality sufficient or comparable to that of the suggested protocol while maintaining lesion conspicuity with reduced scan time. The quantitative values were generally consistent with the suggested MRI-protocol-derived values, which supports the clinical application of adjusted protocols in pediatric neuroimaging. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.