Accuracy of the Compressed Sensing Accelerated 3D-FLAIR Sequence for the Detection of MS Plaques at 3T

Abstract

Twenty-three patients with relapsing-remitting MS underwent both conventional 3D-FLAIR and compressed sensing 3D-FLAIR on a 3T scanner (reduction in scan time 1 minute 25 seconds, 27%; compressed sensing factor of 1.3). Two blinded readers independently evaluated both conventional and compressed sensing FLAIR for image quality and the number of MS lesions visible in the periventricular, intra-juxtacortical, infratentorial, and optic nerve regions. Image quality and the number of MS lesions detected by the readers were similar between the 2 FLAIR acquisitions. Almost perfect agreement was found between the two FLAIR acquisitions for total MS lesion count. The authors conclude that at 3T, and with a compressed sensing factor of 1.3, 3D-FLAIR is 27% faster and preserves diagnostic performance for the detection of MS plaques. The use of 3D FLAIR improves the detection of brain lesions in MS patients, but requires long acquisition times. Compressed sensing reduces acquisition time by using the sparsity of MR images to randomly undersample the k-space. Our aim was to compare the image quality and diagnostic performance of 3D-FLAIR with and without compressed sensing for the detection of multiple sclerosis lesions at 3T. Twenty-three patients with relapsing-remitting MS underwent both conventional 3D-FLAIR and compressed sensing 3D-FLAIR on a 3T scanner (reduction in scan time 1 minute 25 seconds, 27%; compressed sensing factor of 1.3). Two blinded readers independently evaluated both conventional and compressed sensing FLAIR for image quality (SNR and contrast-to-noise ratio) and the number of MS lesions visible in the periventricular, intra-juxtacortical, infratentorial, and optic nerve regions. The volume of white matter lesions was measured with automatic postprocessing segmentation software for each FLAIR sequence. Image quality and the number of MS lesions detected by the readers were similar between the 2 FLAIR acquisitions ( P = .74 and P = .094, respectively). Almost perfect agreement was found between both FLAIR acquisitions for total MS lesion count (Lin concordance correlation coefficient = 0.99). Agreement between conventional and compressed sensing FLAIR was almost perfect for periventricular and infratentorial lesions and substantial for intrajuxtacortical and optic nerve lesions. Postprocessing with the segmentation software did not reveal a significant difference between conventional and compressed sensing FLAIR in total MS lesion volume ( P = .63) or the number of MS lesions ( P = .15). With a compressed sensing factor of 1.3, 3D-FLAIR is 27% faster and preserves diagnostic performance for the detection of MS plaques at 3T.