A comparison of five standard methods for evaluating image intensity uniformity in partially parallel imaging MRI. Issue 8 (1st August 2013)

• Record Type: Journal Article
• Authors: Goerner, Frank L.; Duong, Timothy; Stafford, R. Jason; Clarke, Geoffrey D.
• Is Part Of: Medical physics. Volume 40:Issue 8(2013)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2013-08-01
• Subjects: Magnetic resonance imaging -- Reconstruction; biomedical MRI -- image reconstruction -- medical image processing; MRI -- parallel imaging -- image uniformity -- mSENSE -- GRAPPA -- image quality; Involving electronic [emr] or nuclear [nmr] magnetic resonance, e.g. magnetic resonance imaging -- Digital computing or data processing equipment or methods, specially adapted for specific applications -- Image data processing or generation, in general; Medical imaging -- Medical image quality -- Magnetic resonance imaging -- Medical image artifacts -- Medical image reconstruction -- Medical image noise -- Image reconstruction -- Sequence analysis -- Noise propagation -- Medical magnetic resonance imaging; Medical physics -- Periodicals; Medical physics; Geneeskunde; Natuurkunde; Toepassingen; Biophysics; Periodicals; Periodicals; Electronic journals; 610.153
• DOI: 10.1118/1.4816306
• Languages: English
• ISSNs: 0094-2405

Abstract

Abstract : Purpose: : To investigate the utility of five different standard measurement methods for determining image uniformity for partially parallel imaging (PPI) acquisitions in terms of consistency across a variety of pulse sequences and reconstruction strategies. Methods: : Images were produced with a phantom using a 12‐channel head matrix coil in a 3T MRI system (TIM TRIO, Siemens Medical Solutions, Erlangen, Germany). Images produced using echo‐planar, fast spin echo, gradient echo, and balanced steady state free precession pulse sequences were evaluated. Two different PPI reconstruction methods were investigated, generalized autocalibrating partially parallel acquisition algorithm (GRAPPA) and modified sensitivity‐encoding (mSENSE) with acceleration factors ( R ) of 2, 3, and 4. Additionally images were acquired with conventional, two‐dimensional Fourier imaging methods ( R = 1). Five measurement methods of uniformity, recommended by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) were considered. The methods investigated were (1) an ACR method and a (2) NEMA method for calculating the peak deviation nonuniformity, (3) a modification of a NEMA method used to produce a gray scale uniformity map, (4) determining the normalized absolute average deviation uniformity, and (5) a NEMA method that focused on 17 areas of the image to measure uniformity. Changes in uniformity as a function of reconstruction method at the same R ‐value were also investigated. Two‐way analysis of variance (ANOVA) was used to determine whether R ‐value or reconstruction method had a greater influence on signal intensity uniformity measurements for partially parallel MRI. Results: : Two of the methods studied had consistently negative slopes when signal intensity uniformity was plotted against R ‐value. The results obtained comparing mSENSE against GRAPPA found no consistent difference between GRAPPA and mSENSE with regard to signal intensity uniformity. The results of the two‐way ANOVA analysis suggest that R ‐value and pulse sequence type produce the largest influences on uniformity and PPI reconstruction method had relatively little effect. Conclusions: : Two of the methods of measuring signal intensity uniformity, described by the (NEMA) MRI standards, consistently indicated a decrease in uniformity with an increase in R ‐value. Other methods investigated did not demonstrate consistent results for evaluating signal uniformity in MR images obtained by partially parallel methods. However, because the spatial distribution of noise affects uniformity, it is recommended that additional uniformity quality metrics be investigated for partially parallel MR images.