MPR Image Quality

The quality and utility of MPR images is directly related to the quality of the base images used to create them. In this sense the factors affecting image quality are the same as for any scan. Suitable contrast, SNR, contrast to noise ratio (CNR) and the minimisation of artefacts are most important. Because most MPR work involves the use of short TR GRE 3DFT sequences, obtaining suitable image contrast can be difficult. As will be discussed later, the best solutions are offered by complex and efficient GRE sequences. 
Geometric parameters assume an added importance in this application. Slice thickness cannot be used to provide SNR to compensate for losses inherent in providing high in-plane resolution. Optimum results require slice thickness equal to the in-plane pixel size (isotropic data). When the data is not isotropic, images reformatted using the larger dimension will show reduced spatial resolution. This problem is worst when the large dimension is in the reconstruction plane, but its visibility will depend on the level of anatomical detail that needs to be resolved. 
Artefacts causing geometric distortion of the base image will also degrade the MPR image fidelity. Contrast and signal loss from cross talk becomes a problem when designing thin slice contiguous 2DFT sequences, particularly in multi-slice sequences with low acquisition bandwidths. While attempting to maintain a reasonable number of slices per unit TR, the sequence designer may choose a shorter period RF pulse, to make up for the increased sampling time dictated by a low acquisition bandwidth, sacrificing pulse shaping and slice profile in the process. 
The MPR software will employ specific algorithms to assign the pixel values of a reformatted slice. The image quality will depend on how well these handle multiple voxel values in thick slices, and how the data gaps resulting from inter-slice gaps are interpolated. The interpolation routines of magnification programmes can also significantly affect presented image quality. 
In any given system best results are obtained with small dimension isotropic data sets acquired from 3DFT data. When using 2DFT sequences, keep slice thickness and slice gap as small as possible, and plan to reconstruct planes at small angles to the acquired plane.

For best results use (in order of preference):

High SNR sequences with a: -
3DFT small dimension isotropic data 
3DFT small dimension anisotropic data 
2DFT thin slices with minimal or no inter-slice gap and optimised slice profile.