Quantitative MRI T2mapping in the knee joint using deep learning-based reconstruction for Compressed sensing

MRI T2 mapping has been recommended as a noninvasive biomarker of knee cartilage lesions. However, due to the long acquisition time, it hasn’t been widely used in the clinical setting. Recently, deep learning-based acceleration of compressed sensing (CS) has shown promising results without losing image quality. The purpose of this study was to explore the feasibility of quantitative knee T2-mapping accelerated by deep learning-based compressed sensing (CS-AI), and compare the image quality and diagnostic performance with conventional CS. The results demonstrates that quantitative knee T2 mapping with reconstruction by CS-AI was feasible, suggesting better diagnostic performance without extra time consuming.