High‐resolution diffusion‐weighted imaging of the breast with multiband 2D radiofrequency pulses and a generalized parallel imaging reconstruction
Year: 2016
Type: article
Abstract: PURPOSE: To develop a technique for high-resolution diffusion-weighted imaging (DWI) and to compare it with standard DWI methods. METHODS: Multiple in-plane bands of magnetization were simultaneously excited by identically phase modulating each subpulse of a two-dimensional (2D) RF pulse. Several excitations with the same multiband pattern progressively shifted in the phase-encode direction were used to cover the prescribed field of view (FOV). The phase-encoded FOV was limited to the width of a single band to reduce off-resonance-induced distortion and blurring. Parallel imaging (PI) techniques were used to resolve aliasing from the other bands and to combine the different excitations. Following validation in phantoms and healthy volunteers, a preliminary study in breast cancer patients (N=14) was performed to compare the proposed method to conventional DWI with PI and to reduced-FOV DWI. RESULTS: The proposed method gave high-resolution diffusion-weighted images with minimal artifacts at the band intersections. Compared to PI alone, higher phase-encoded FOV-reduction factors and reduced noise amplification were obtained, which translated to higher resolution images than conventional (non-multiband) DWI. The same resolution and image quality achievable over targeted regions using existing reduced-FOV methods was obtained, but the proposed method also enables complete bilateral coverage. CONCLUSION: We developed an in-plane multiband technique for high-resolution DWI and compared its performance with other standard DWI methods. Magn Reson Med 77:209-220, 2017. © 2016 Wiley Periodicals, Inc.
Source: Magnetic Resonance in Medicine
DOI: 10.1002/mrm.26110
Institutions: Stanford Medicine, Stanford University
Language: English
Topic: MRI in cancer diagnosis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2273215959
