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Peer-reviewedCC BY 4.0NeuroImage: Clinical

Characterizing post-stroke changes in brain microstructure using the mean apparent propagator model

  • Ricardo J. Vega1
  • Wesely T. Richerson2
  • Max O. Krucoff3,1,4
  • Brian D. Schmit1
4 affiliations
  1. 1Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
  2. 2Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
  3. 3Department of Neurosurgery, Medical College of Wisconsin and Froedtert Hospital, Milwaukee, Wisconsin, USA
  4. 4Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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Abstract

This study investigated regional and whole-brain microstructural alterations following stroke using diffusion tensor imaging (DTI) and Mean Apparent Propagator MRI (MAP-MRI). Multi-shell diffusion and T1-weighted MRI data were analyzed from participants with chronic stroke and healthy controls. DTI-derived fractional anisotropy (FA) and mean diffusivity (MD), and MAP-MRI-derived return-to-origin (RTOP), return-to-axis (RTAP), and return-to-plane (RTPP) probabilities were quantified across 13 predefined regions in native diffusion space. Regional group differences were assessed using participant-level median values with Benjamini–Hochberg false discovery rate (BH-FDR) correction across all 65 ROI × diffusion-metric comparisons and age- and sex-adjusted sensitivity analyses. Complementary lesion-relative whole-brain analyses used nonparametric permutation testing with threshold-free cluster enhancement and family-wise error correction.

MAP-MRI demonstrated widespread regional abnormalities, with significant group differences in 11 of 13 regions for RTOP, 12 of 13 for RTAP, and 10 of 13 for RTPP, compared with 8 of 13 for FA and all 13 regions for MD. After adjustment for age and sex, significant differences remained in 11, 10, and 9 regions for RTOP, RTAP, and RTPP, respectively, compared with 6 for FA and all 13 for MD. Whole-brain analyses demonstrated significant corrected abnormalities across all five diffusion metrics, with RTOP and RTAP showing the most spatially extensive Control > Stroke effects, followed by RTPP and FA, whereas MD showed extensive effects in the opposite, Stroke > Control direction. Regional discrimination varied by anatomical region and metric, without a uniform advantage of MAP-MRI over DTI. Exploratory diffusion–function analyses identified several nominal associations, but none survived correction across all comparisons.

These findings demonstrate complementary, region- and metric-specific sensitivity of MAP-MRI and DTI to chronic stroke-related microstructural abnormalities. MAP-MRI identified distributed abnormalities across regional and whole-brain analyses, while MD remained highly sensitive to widespread tissue differences. The differing spatial distributions and regional discriminative performance of MAP-MRI and DTI suggest that these approaches capture partially distinct features of the post-stroke diffusion environment. Together, these findings support their complementary use for characterizing distributed microstructural abnormalities following chronic stroke.

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Cite

BibTeXRIS
BibTeX
@article{vega2026characterizing,
  title = {{Characterizing post-stroke changes in brain microstructure using the mean apparent propagator model}},
  author = {Ricardo J. Vega and Wesely T. Richerson and Max O. Krucoff and Brian D. Schmit},
  journal = {NeuroImage: Clinical},
  year = {2026},
  month = oct,
  doi = {10.1016/j.nicl.2026.104076},
  url = {https://doi.org/10.1016/j.nicl.2026.104076},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Characterizing post-stroke changes in brain microstructure using the mean apparent propagator model
AU  - Ricardo J. Vega
AU  - Wesely T. Richerson
AU  - Max O. Krucoff
AU  - Brian D. Schmit
PY  - 2026
DA  - 2026/10/21
JO  - NeuroImage: Clinical
DO  - 10.1016/j.nicl.2026.104076
UR  - https://doi.org/10.1016/j.nicl.2026.104076
AB  - This study investigated regional and whole-brain microstructural alterations following stroke using diffusion tensor imaging (DTI) and Mean Apparent Propagator MRI (MAP-MRI). Multi-shell diffusion and T1-weighted MRI data were analyzed from participants with chronic stroke and healthy controls. DTI-derived fractional anisotropy (FA) and mean diffusivity (MD), and MAP-MRI-derived return-to-origin (RTOP), return-to-axis (RTAP), and return-to-plane (RTPP) probabilities were quantified across 13 predefined regions in native diffusion space. Regional group differences were assessed using participant-level median values with Benjamini–Hochberg false discovery rate (BH-FDR) correction across all 65 ROI × diffusion-metric comparisons and age- and sex-adjusted sensitivity analyses. Complementary lesion-relative whole-brain analyses used nonparametric permutation testing with threshold-free cluster enhancement and family-wise error correction.  MAP-MRI demonstrated widespread regional abnormalities, with significant group differences in 11 of 13 regions for RTOP, 12 of 13 for RTAP, and 10 of 13 for RTPP, compared with 8 of 13 for FA and all 13 regions for MD. After adjustment for age and sex, significant differences remained in 11, 10, and 9 regions for RTOP, RTAP, and RTPP, respectively, compared with 6 for FA and all 13 for MD. Whole-brain analyses demonstrated significant corrected abnormalities across all five diffusion metrics, with RTOP and RTAP showing the most spatially extensive Control > Stroke effects, followed by RTPP and FA, whereas MD showed extensive effects in the opposite, Stroke > Control direction. Regional discrimination varied by anatomical region and metric, without a uniform advantage of MAP-MRI over DTI. Exploratory diffusion–function analyses identified several nominal associations, but none survived correction across all comparisons.  These findings demonstrate complementary, region- and metric-specific sensitivity of MAP-MRI and DTI to chronic stroke-related microstructural abnormalities. MAP-MRI identified distributed abnormalities across regional and whole-brain analyses, while MD remained highly sensitive to widespread tissue differences. The differing spatial distributions and regional discriminative performance of MAP-MRI and DTI suggest that these approaches capture partially distinct features of the post-stroke diffusion environment. Together, these findings support their complementary use for characterizing distributed microstructural abnormalities following chronic stroke.
SN  - 2213-1582
ER  -