Feasibility of similarity coefficient map in improving morphological evaluation of T2* weighted MRI for renal cancer

The purpose of this paper is to investigate the feasibility of similarity coefficient map (SCM) in improving morphological evaluation of T₂^* weighted (T₂^*W) magnatic resonance imaging (MRI) for renal cancer. Simulation studies and in vivo 12-echo T₂^*W experiments for renal cancers were performed for this purpose. The results of the first simulation study suggest that SCM can reveal small structures which are hard to be distinguished from the background tissue in T₂^*W images and the corresponding T₂^* map. The capability of improving morphological evaluation is likely due to the improvement in signal to noise ratio (SNR) and carrier to noise ratio (CNR) by SCM technique. Compared with T₂^*W images, SCM can improve SNR by a factor ranging from 1.87 to 2.47. Compared with T₂^* maps, SCM can improve SNR by a factor ranging from 3.85 to 33.31. Compared with T₂^*W images, SCM can improve CNR by a factor raging from 2.09 to 2.43. Compared with T₂^* maps SCM can improve CNR by a factor raging from 1.94 to 8.14. For a given noise level, the improvements of SNR and CNR depend mainly on the original SNRs and CNRs in T₂^*W images, respectively. In vivo experiments confirmed the results of the first simulation study. The results of the second simulation study suggest that more echoes are used to generate SCM, and higher SNR and CNR can be achieved in SCM. In conclusion, SCM can provide improved morphological evaluation of T₂^*W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T₂^*W MR images and T₂^* maps. What is more, in practical application, for a fixed total sampling time, one should increase the number of echoes as much as possible to achieve SCMs with better SNR and CNR.