ABSTRACT Purpose Combined spin‐ and gradient‐echo EPI (SAGE‐EPI) offers advantages in tissue quantification and dynamic imaging but suffers from low spatial resolution and geometric distortions. This study aims to develop a multiple overlapping‐echo detachment‐based SAGE acquisition (SAGE‐MOLED) to enable efficient, distortion‐corrected T 2 , , and M 0 mapping for perfusion MRI. Methods SAGE‐MOLED was designed as an optimized MOLED variant by refining echo time sampling and integrating multi‐train blip‐reversed EPI to enhance distortion correction and temporal SNR, enabling reliable extraction of subject‐specific arterial input functions (AIFs). To support dynamic imaging, a steady‐state Bloch simulation‐based synthetic data framework was developed to simultaneously model T 1 , T 2 , and ‐related effects, providing training data for an end‐to‐end deep learning model that enables efficient multiparametric quantification. In addition, a signal‐to‐concentration model tailored for dynamic MOLED signals was formulated for accurate estimation of permeability and leakage‐corrected perfusion parameters. The proposed technique was validated in water phantom experiments, healthy volunteers, and a pilot clinical study. Results Single‐shot SAGE‐MOLED demonstrated high consistency with standard methods in both phantom and in vivo experiments, with Pearson correlation coefficient = 0.991 for T 2 and 0.988 for mapping in the brain. Compared to conventional SAGE‐EPI, SAGE‐MOLED mitigated geometric distortions and intravoxel dephasing‐related signal loss. In perfusion MRI, dynamic SAGE‐MOLED enabled simultaneous permeability and leakage‐corrected perfusion parameter estimation with a single‐dose contrast injection. Conclusion SAGE‐MOLED overcomes key limitations of SAGE‐EPI, providing high‐fidelity, distortion‐corrected T 2 , , and M 0 maps for simultaneous quantification of permeability and perfusion parameters.
Yang et al. (Sun,) studied this question.