K‐space substitution: A novel dynamic imaging technique

Abstract

A rapid dynamic imaging sequence has been developed in which only the 32 phase encoding steps that encode low spatial frequencies are collected for each dynamic image. These are substituted into a previously acquired, 128 x 128 raw data set prior to image reconstruction. In this way the dynamic information is retained while the overall appearance is improved in comparison with images obtained by zero filling to 128 x 128, leading to better qualitative evaluation. The limited k-space sampling means that the technique is most effective for large homogeneous areas of signal change since fine changes in contrast are imperfectly recorded.

Noninvasive Evaluation of Cerebral Arteriovenous Malformations by 4D-MRA for Preoperative Planning and Postoperative Follow-Up in 56 Patients: Comparison with DSA and Intraoperative Findings

“…The following parameters were constant within all examinations: TR, 2.2 ms; TE, 0.9 ms; flip angle, 15°; FOV, 256 mm; parallel imaging (sensitivity encoding 16 ) with an acceleration factor of 8 (phase encoding, 4; section encoding, 2); and half-Fourier imaging with 25% k-space reduction (acceleration factor ϭ 1.33). Patients in group 1 (19/56) were examined with CENTRA keyhole [17][18][19] with a keyhole diameter of 16% (6-fold acceleration), and patients in group 2 (37/56) were examined by using CENTRA keyhole with a keyhole diameter of 20% and a view-sharing compression factor of 80 (total, 9-fold acceleration). [17][18][19][20] Group 1 was imaged by using a matrix of 224 ϫ 178, acquiring 50 dynamic datasets consisting of 140 sections each with a section thickness of 1.4 mm, resulting in a reconstructed voxel size of 1.1 ϫ 1.1 ϫ 1.4 mm 3 .…”

“…Patients in group 1 (19/56) were examined with CENTRA keyhole [17][18][19] with a keyhole diameter of 16% (6-fold acceleration), and patients in group 2 (37/56) were examined by using CENTRA keyhole with a keyhole diameter of 20% and a view-sharing compression factor of 80 (total, 9-fold acceleration). [17][18][19][20] Group 1 was imaged by using a matrix of 224 ϫ 178, acquiring 50 dynamic datasets consisting of 140 sections each with a section thickness of 1.4 mm, resulting in a reconstructed voxel size of 1.1 ϫ 1.1 ϫ 1.4 mm 3 . Group 2 was imaged by using a matrix of 232 ϫ 232, acquiring 50 dynamic datasets consisting of 168 sections each with a section thickness of 1.1 mm, resulting in a reconstructed voxel size of 1.1 ϫ 1.1 ϫ 1.1 mm 3 .…”

Reconstruction of Cardiac Cine MR Images from Partial k-Space

“…These techniques have been used for dynamic imaging as well. In an attempt to further increase the acquisition rate by reducing the amount of acquired data by a given factor, referred to as the reduction factor, several methods dedicated to dynamic MR images reconstruction have been reported in the literature [9][10][11][12][13][14][15]. Even though parallel imaging is commonly used to acquire cine MRI, few reconstruction methods have been proposed for reconstructing cardiac cine images [16].…”

Reconstruction of undersampled dynamic images by modeling the motion of object elements

“…Therefore, each pixel is considered in a constant position over time. These methods include keyhole (8,9), reduced encoding MR imaging with generalized-series reconstruction (RIGR) (10), reduced field of view (rFOV) (11), hybrid technique for dynamic imaging (12), unaliasing by Fourier-encoding the overlaps using the temporal dimension (UNFOLD) (13), sensitivity encoding incorporating temporal filtering (TSENSE) (14), k-t broad-use linear acquisition speed-up technique (k-t BLAST) (15), and reconstruction employing temporal registration (16). In contrast, in this work we are concerned not with the image pixels, but with the continuous position of the object elements (obels) through the dynamic sequence (17,18).…”