Evaluation of adaptive combination of 30-channel head receive coil array data in 23Na MR imaging.

Abstract

The aim was to optimally combine multichannel coil array data in sodium ((23) Na) MRI. (23) Na MRI was conducted on a 3 Tesla MR system using a 30-channel head receive coil array. The parameters used for the adaptive combination (ADC) reconstruction of the low signal-to-noise ratio (SNR) dataset have been optimized by finding the maximum mean SNR. A pseudo multiple-replica approach has been used to obtain SNR maps of the combined images. To prove reproducibility of the combination algorithm, the procedure was repeated for several measurements. For low SNR data, sum-of-squares (SOS) reconstruction leads to high background noise and a signal bias in the imaged object. The ADC reconstruction clearly reduces noise in the image and leads to an increase of the mean SNR in the range of 8% to 50%, compared to weighted SOS depending on the absolute SNR of the image. The evaluation of the effects of different noise scans showed that a small number of projections can be used to estimate noise statistics of the coil array without substantially decreasing the resulting SNR. (23) Na MRI can be markedly improved by using a 30-channel receive array and ADC reconstruction. The ADC reconstruction showed robust results for all measurements without the need for sensitivity maps.