Affiliation:
1. Radiology Stanford University Stanford California USA
2. Electrical Engineering Stanford University Stanford California USA
3. Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles California USA
4. Bioengineering Stanford University Stanford California USA
Abstract
AbstractPurposeComprehensive assessment of image quality requires accounting for spatial variations in (i) intensity artifact, (ii) geometric distortion, (iii) signal‐to‐noise ratio (SNR), and (iv) spatial resolution, among other factors. This work presents an ensemble of methods to meet this need, from phantom design to image analysis, and applies it to the scenario of imaging near metal.MethodsA modular phantom design employing a gyroid lattice is developed to enable the co‐registered volumetric quantitation of image quality near a metallic hip implant. A method for measuring spatial resolution by means of local point spread function (PSF) estimation is presented and the relative fitness of gyroid and cubic lattices is examined. Intensity artifact, geometric distortion, and SNR maps are also computed. Results are demonstrated with 2D‐FSE and MAVRIC‐SL scan protocols on a 3T MRI scanner.ResultsThe spatial resolution method demonstrates a worst‐case error of 0.17 pixels for measuring in‐plane blurring up to 3 pixels (full width at half maximum). The gyroid outperforms a cubic lattice design for the local PSF estimation task. The phantom supports four configurations toggling the presence/absence of both metal and structure with good spatial correspondence for co‐registered analysis of the four quality factors. The marginal scan time to evaluate one scan protocol amounts to five repetitions. The phantom design can be fabricated in 2 days at negligible material cost.ConclusionThe phantom and associated analysis methods can elucidate complex image quality trade‐offs involving intensity artifact, geometric distortion, SNR, and spatial resolution. The ensemble of methods is suitable for benchmarking imaging performance near metal.
Funder
Natural Sciences and Engineering Research Council of Canada
National Institutes of Health