Compressed sensing reconstruction for undersampled breath-hold radial cine imaging with auxiliary free-breathing data.

To improve compressed sensing (CS) reconstruction of accelerated breath-hold (BH) radial cine magnetic resonance imaging (MRI) by exploiting auxiliary data acquired between different BHs.Cardiac function is usually assessed using segmented cine acquisitions over multiple BHs to cover the entire left ventricle (LV). Subjects are given a resting period between adjacent BHs, when conventionally no data are acquired and subjects rest in the scanner. In this study the resting periods between BHs were used to acquire additional free-breathing (FB) data, which are subsequently used to generate a sparsity constraint for each cardiac phase. Images reconstructed using the proposed sparsity constraint were compared with conventional CS using a composite image generated by averaging different cardiac phases. The efficacy of the proposed reconstruction was compared using indices of LV function and blood-myocardium sharpness.The proposed method provided accurate LV ejection fraction measurements for 33% and 20% sampled datasets compared with fully sampled reference images, and showed 14% and 11% higher blood-myocardium border sharpness scores compared to the conventional CS.The FB data acquired during resting periods can be efficiently used to improve the image quality of the undersampled BH data without increasing the total scan time.

Duke Scholars

Author Vahid Tarokh Electrical and Computer Engineering