The central vein sign (CVS) has been suggested as a potential biomarker for multiple sclerosis (MS) lesion detection and differential diagnosis. A major hurdle for clinical investigation of CVS of MS lesion is the lack of high-quality visualization on current MRI. In this work, we propose a Susceptibility Relaxation based Optimization (SRO) method that uses routinely acquired multi-echo gradient echo magnitude and phase data to generate an image with optimal CVS contrast while preserving lesion signal. Preliminary qualitative and quantitative results demonstrate that SRO provides superior MS lesion and CVS detection compared to prior methods.
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