Quantitative susceptibility mapping using principles of echo shifting with a train of observations sequence on 1.5 T MRI

Hirohito Kan, Nobuyuki Arai, Harumasa Kasai, Hiroshi Kunitomo, Yasujiro Hirose, Yuta Shibamoto

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

Purpose To evaluate the accuracy of susceptibility estimated from the principles of echo shifting with a train of observations (PRESTO) sequence using a 1.5 T MRI system, we conducted experiments on the human brain using the PRESTO sequence and compared our results with the susceptibility obtained from spoiled gradient-recalled echo (GRE) sequence with flow compensation using quantitative susceptibility mapping (QSM) reconstruction. Materials and methods Experiments on the human brain were conducted on 12 healthy volunteers (27 ± 4 years) using PRESTO and spoiled GRE sequences on a 1.5 T scanner. The PRESTO sequence is an echo-shifted gradient echo sequence that allows high susceptibility sensitivity and rapid acquisition because of TE > TR compared with the spoiled GRE sequence. QSM analysis was performed on the obtained phase images using the iLSQR method. Estimated susceptibility maps were used for region of interest analyses and estimation of line profiles through iron-rich tissue and major vessels. Results Our results demonstrated that susceptibility maps were accurately estimated, without error, by QSM analysis of PRESTO and spoiled GRE sequences. Acquisition time in the PRESTO sequence was reduced by 43% compared with that in the spoiled GRE sequence. Differences did exist between susceptibility maps in PRESTO and spoiled GRE sequences for visualization and quantitative values of major blood vessels and the areas around them Conclusion The PRESTO sequence enables correct estimation of tissue susceptibility with rapid acquisition and may be useful for QSM analysis of clinical use of 1.5 T scanners.

Original languageEnglish
Pages (from-to)37-42
Number of pages6
JournalMagnetic Resonance Imaging
Volume42
DOIs
Publication statusPublished - 10-2017
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Biophysics
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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