NeuroImage (Jul 2022)

Rigid real-time prospective motion-corrected three-dimensional multiparametric mapping of the human brain

  • Shohei Fujita,
  • Akifumi Hagiwara,
  • Naoyuki Takei,
  • Issei Fukunaga,
  • Yasuhiro Hagiwara,
  • Takashi Ogawa,
  • Taku Hatano,
  • Dan Rettmann,
  • Suchandrima Banerjee,
  • Ken-Pin Hwang,
  • Shiori Amemiya,
  • Koji Kamagata,
  • Nobutaka Hattori,
  • Osamu Abe,
  • Shigeki Aoki

Journal volume & issue
Vol. 255
p. 119176

Abstract

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Purpose: To develop a rigid real-time prospective motion-corrected multiparametric mapping technique and to test the performance of quantitative estimates. Methods: Motion tracking and correction were performed by integrating single-shot spiral navigators into a multiparametric imaging technique, three-dimensional quantification using an interleaved Look-Locker acquisition sequence with a T2 preparation pulse (3D-QALAS). The spiral navigator was optimized, and quantitative measurements were validated using a standard system phantom. The effect of motion correction on whole-brain T1 and T2 mapping under different types of head motion during the scan was evaluated in 10 healthy volunteers. Finally, six patients with Parkinson's disease, which is known to be associated with a high prevalence of motion artifacts, were scanned to evaluate the effectiveness of our method in the real world. Results: The phantom study demonstrated that the proposed motion correction method did not introduce quantitative bias. Improved parametric map quality and repeatability were shown in volunteer experiments with both in-plane and through-plane motions, comparable to the no-motion ground truth. In real-life validation in patients, the approach showed improved parametric map quality compared to images obtained without motion correction. Conclusions: Real-time prospective motion-corrected multiparametric relaxometry based on 3D-QALAS provided robust and repeatable whole-brain multiparametric mapping.

Keywords