Journal Article

DZNE-2026-01010

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Human In Vivo Validation of Frequency-Dependent QTI.

Niesen, S. (First author)DZNE* ; Veldmann, M.DZNE* ; Ajouz, A. ; Stöcker, T. (Last author)DZNE*

2026
Wiley-Liss New York, NY [u.a.]

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Please use a persistent id in citations: doi:10.1002/mrm.70529

Abstract: The aim of this work is to investigate if q-space trajectory imaging (QTI) waveforms can be designed to probe QTI metrics at a single centroid frequency under realistic experimental conditions for in vivo human brain imaging.Realistic diffusion encoding waveforms based on double-rotation gradient waveform and magic-angle spinning of the q-vector with varying encoding bandwidth, alignment of encoding spectra across encodings (tuning) and across axes (spectral isotropy) were designed to investigate the accuracy of the centroid frequency approximation. QTI metrics were computed for idealized as well as realistic oscillating and pulsed gradient waveforms using analytical diffusion spectra with 1D and 2D short-range disorder along and perpendicular to axons. For in vivo validation, the waveforms were integrated into a multiband spiral spin-echo sequence.The simulations demonstrate frequency-dependent QTI metrics. The combination of tuning and spectral isotropy led to metrics close to the simulated ground-truth at the centroid frequency of the encoding spectrum. Realistic waveforms with broader bandwidth compared to idealized waveforms introduce little additional error in QTI metrics due to truncation of the cumulant expansion. In agreement with literature, omitting tuning and spectral isotropy reduces isotropic variance and increases microscopic fractional anisotropy when LTE contains lower frequencies, and vice versa for PTE. This observation is confirmed qualitatively by the in vivo measurements.The accuracy of the centroid frequency approximation depends on the combination of encoding spectra and investigated tissue. Using similar encoding spectra for tuning and spectral isotropy leads to metrics, characteristic to the centroid frequency.

Keyword(s): Humans (MeSH) ; Brain: diagnostic imaging (MeSH) ; Algorithms (MeSH) ; Reproducibility of Results (MeSH) ; Image Processing, Computer-Assisted: methods (MeSH) ; Computer Simulation (MeSH) ; Diffusion Magnetic Resonance Imaging: methods (MeSH) ; Image Interpretation, Computer-Assisted: methods (MeSH) ; QTI ; microstructure ; spiral imaging ; tensor‐valued encoding ; time dependent diffusion

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Contributing Institute(s):

1. MR Physics (AG Stöcker)

Research Program(s):

1. 354 - Disease Prevention and Healthy Aging (POF4-354) (POF4-354)

Appears in the scientific report 2026

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Database coverage:
; ; ; BIOSIS Previews ; Biological Abstracts ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Life Sciences ; DEAL Wiley ; Essential Science Indicators ; IF < 5 ; JCR ; Nationallizenz ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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