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Peter van Zijl

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6 papers

1 author row

YNIMG Journal 2026 Journal Article

Deep-learning saturation transfer magnetic resonance fingerprinting (ST-MRF) in patients with Parkinson’s disease

Jannik Prasuhn
Munendra Singh
Sultan Z Mahmud
Nirbhay N Yadav
Ted M. Dawson
Kelly A. Mills
Peter van Zijl
Hye-Young Heo

Parkinson’s disease (PD) is marked by progressive neurodegeneration in the substantia nigra (SN). This study evaluated deep-learning saturation-transfer magnetic resonance fingerprinting (ST-MRF) to quantify molecular and microstructural changes in PD. We examined 23 patients with PD (PwPD) and 22 matched healthy controls (HCs) using multimodal imaging, including ST-MRF. ST-MRF detected significant molecular and microstructural alterations in the SN of PwPD compared to HCs, including increases in magnetization transfer ratio at 3. 5 ppm (MTR(3. 5ppm, 1. 5 µT); 0. 612 ± 0. 022 vs. 0. 597 ± 0. 021, p = 0. 014), MTR(-3. 5ppm, 1. 5 µT); 0. 614 ± 0. 021 vs. 0. 586 ± 0. 019, p = 0. 008)), and decreases in T2 w (51. 9 ± 3. 4 vs. 54. 5 ± 1. 3 ms, p = 0. 005), suggesting disrupted protein homeostasis and iron accumulation. ST-MRF provides multiparametric insights into PD-related pathology and may serve as a candidate tool for future biomarker studies. Validation in larger, longitudinal cohorts will be essential to establish its clinical utility.

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YNIMG Journal 2009 Journal Article

Landmark-referenced voxel-based analysis of diffusion tensor images of the brainstem white matter tracts

Weihong Zhang
Xin Li
Jiangyang Zhang
Andreas Luft
Daniel F. Hanley
Peter van Zijl
Michael I. Miller
Laurent Younes

Although DTI can provide detailed information about white matter anatomy, it is not yet straightforward enough to quantify the anatomical information it visualizes. In this study, we developed and tested a new tool to perform brain normalization and voxel-based analysis of DTI data. For the normalization part, manually placed landmarks ensured that the visualized white matter tracts were well-registered among the populations. A standard landmark set in ICBM-152 space and an interface to remap them to subject data were integrated in the procedure. After landmark placement, highly elastic non-linear Large Deformation Diffeomorphic Metric Mapping (LDDMM) was driven by the landmarks to normalize the brainstem anatomy of normal subjects. The approach was then applied to delineate brainstem tract abnormalities in patients with left chronic middle cerebral artery (MCA) stroke. The voxel-based comparison between control and patient groups identified abnormalities in the ipsilesional corticospinal tract and contralesional cerebellar peduncles. We believe that this tool is useful for regional brain normalization of patients with severe anatomical alterations, such as stroke, brain tumor, and lobectomy, for whom standard automated normalization tools may not work properly.

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YNIMG Journal 2008 Journal Article

Automated fiber tracking of human brain white matter using diffusion tensor imaging

Weihong Zhang
Alessandro Olivi
Samuel J. Hertig
Peter van Zijl
Susumu Mori

Reconstruction of white matter tracts based on diffusion tensor imaging (DTI) is currently widely used in clinical research. This reconstruction allows us to identify coordinates of specific white matter tracts and to investigate their anatomy. Fiber reconstruction, however, relies on manual identification of anatomical landmarks of a tract of interest, which is based on subjective judgment and thus a potential source of experimental variability. Here, an automated tract reconstruction approach is introduced. A set of reference regions of interest (rROIs) known to select a tract of interest was marked in our DTI brain atlas. The atlas was then linearly transformed to each subject, and the rROI set was transferred to the subject for tract reconstruction. Agreement between the automated and manual approaches was measured for 11 tracts in 10 healthy volunteers and found to be excellent (kappa>0. 8) and remained high up to 4–5 mm of the linear transformation errors. As a first example, the automated approach was applied to brain tumor patients and strategies to cope with severe anatomical abnormalities are discussed.

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YNIMG Journal 2008 Journal Article

Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template

Susumu Mori
Kenichi Oishi
Hangyi Jiang
Li Jiang
Xin Li
Kazi Akhter
Kegang Hua
Andreia V. Faria

Brain registration to a stereotaxic atlas is an effective way to report anatomic locations of interest and to perform anatomic quantification. However, existing stereotaxic atlases lack comprehensive coordinate information about white matter structures. In this paper, white matter-specific atlases in stereotaxic coordinates are introduced. As a reference template, the widely used ICBM-152 was used. The atlas contains fiber orientation maps and hand-segmented white matter parcellation maps based on diffusion tensor imaging (DTI). Registration accuracy by linear and non-linear transformation was measured, and automated template-based white matter parcellation was tested. The results showed a high correlation between the manual ROI-based and the automated approaches for normal adult populations. The atlases are freely available and believed to be a useful resource as a target template and for automated parcellation methods.

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YNIMG Journal 2007 Journal Article

Reproducibility of quantitative tractography methods applied to cerebral white matter

Setsu Wakana
Arvind Caprihan
Martina M. Panzenboeck
James H. Fallon
Michele Perry
Randy L. Gollub
Kegang Hua
Jiangyang Zhang

Tractography based on diffusion tensor imaging (DTI) allows visualization of white matter tracts. In this study, protocols to reconstruct eleven major white matter tracts are described. The protocols were refined by several iterations of intra- and inter-rater measurements and identification of sources of variability. Reproducibility of the established protocols was then tested by raters who did not have previous experience in tractography. The protocols were applied to a DTI database of adult normal subjects to study size, fractional anisotropy (FA), and T 2 of individual white matter tracts. Distinctive features in FA and T 2 were found for the corticospinal tract and callosal fibers. Hemispheric asymmetry was observed for the size of white matter tracts projecting to the temporal lobe. This protocol provides guidelines for reproducible DTI-based tract-specific quantification.

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YNIMG Journal 2005 Journal Article

Mapping postnatal mouse brain development with diffusion tensor microimaging

Jiangyang Zhang
Michael I. Miller
Celine Plachez
Linda J. Richards
Paul Yarowsky
Peter van Zijl
Susumu Mori

While mouse brain development has been extensively studied using histology, quantitative characterization of morphological changes is still a challenging task. This paper presents how developing brain structures can be quantitatively characterized with magnetic resonance diffusion tensor microimaging coupled with techniques of computational anatomy. High resolution diffusion tensor images of ex vivo postnatal mouse brains provide excellent contrasts to reveal the evolutions of mouse forebrain structures. Using anatomical landmarks defined on diffusion tensor images, tissue level growth patterns of mouse brains were quantified. The results demonstrate the use of these techniques to three-dimensionally and quantitatively characterize brain growth.

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