MRI ‐ DTI Biomarkers Along the Continuum of Behavioral Variant Frontotemporal Dementia
Article Swipe
Hans‐Jürgen Huppertz
,
Heiko Volkmann
,
Daniele Urso
,
Benedetta Tafuri
,
Salvatore Nigro
,
Jan Kassubek
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/ene.70438
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/ene.70438
Background We investigated whether diffusion tensor imaging (DTI) and atlas‐based volumetry (ABV) could track specific patterns of brain white matter (WM) microstructure and gray matter (GM) volumes in behavioral variant frontotemporal dementia (bvFTD) and amyotrophic lateral sclerosis with frontotemporal dementia (ALS‐FTD). Methods MRI datasets from 65 bvFTD (including 19 with longitudinal MRI), 18ALS‐FTD, and 39 controls were analyzed. White matter fractional anisotropy (FA) differences were assessed using unbiased Whole Brain‐based Spatial Statistics (WBSS) and a hypothesis‐driven complementary approach consisting of Tract‐Wise FA Statistics (TFAS) in Tracts of Interest (TOIs) and ABV in Structures of Interest (SOIs). FA maps were correlated with disease severity (FTLD‐CDR sum of boxes). A random forest algorithm classified participants employing TOI and SOI data. Results At baseline, both bvFTD and ALS‐FTD exhibited WM changes in several tracts including the uncinate fasciculi, tracts originating in the corpus callosum, and the inferior and superior longitudinal fasciculi. Atrophy was most pronounced in the frontal lobes and caudate nuclei. Longitudinally, bvFTD demonstrated an antero‐posterior spread of WM degeneration, particularly along the corpus callosum and inferior longitudinal fasciculus, with relatively modest cortical atrophy progression. Random forest analysis identified the most discriminative TOIs and SOIs including the uncinate fasciculus and the amygdala. Conclusions Our findings demonstrate a similar pattern of structural and microstructural changes in bvFTD and ALS‐FTD, with a specific involvement of the corticospinal tract for ALS‐FTD, and support the utility of combined DTI and ABV in tracking disease progression across the FTLD spectrum.
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- Landing Page
- https://doi.org/10.1111/ene.70438
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https://doi.org/10.1111/ene.70438Digital Object Identifier
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MRI ‐DTI Biomarkers Along the Continuum of Behavioral Variant Frontotemporal DementiaWork title - Type
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-11-30Full publication date if available
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Hans‐Jürgen Huppertz, Heiko Volkmann, Daniele Urso, Benedetta Tafuri, Salvatore Nigro, Jan KassubekList of authors in order
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https://doi.org/10.1111/ene.70438Publisher landing page
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goldOpen access status per OpenAlex
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https://doi.org/10.1111/ene.70438Direct OA link when available
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| abstract_inverted_index.datasets | 44 |
| abstract_inverted_index.dementia | 32, 40 |
| abstract_inverted_index.findings | 203 |
| abstract_inverted_index.inferior | 144, 175 |
| abstract_inverted_index.patterns | 16 |
| abstract_inverted_index.severity | 103 |
| abstract_inverted_index.specific | 15, 219 |
| abstract_inverted_index.superior | 146 |
| abstract_inverted_index.tracking | 237 |
| abstract_inverted_index.unbiased | 68 |
| abstract_inverted_index.uncinate | 134, 196 |
| abstract_inverted_index.ALS‐FTD | 125 |
| abstract_inverted_index.algorithm | 111 |
| abstract_inverted_index.amygdala. | 200 |
| abstract_inverted_index.analyzed. | 58 |
| abstract_inverted_index.baseline, | 121 |
| abstract_inverted_index.callosum, | 141 |
| abstract_inverted_index.diffusion | 5 |
| abstract_inverted_index.employing | 114 |
| abstract_inverted_index.exhibited | 126 |
| abstract_inverted_index.including | 132, 194 |
| abstract_inverted_index.sclerosis | 37 |
| abstract_inverted_index.spectrum. | 243 |
| abstract_inverted_index.volumetry | 11 |
| abstract_inverted_index.(including | 48 |
| abstract_inverted_index.ALS‐FTD, | 216, 226 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.Statistics | 72, 83 |
| abstract_inverted_index.Structures | 93 |
| abstract_inverted_index.anisotropy | 62 |
| abstract_inverted_index.behavioral | 29 |
| abstract_inverted_index.classified | 112 |
| abstract_inverted_index.consisting | 79 |
| abstract_inverted_index.correlated | 100 |
| abstract_inverted_index.fasciculi, | 135 |
| abstract_inverted_index.fasciculi. | 148 |
| abstract_inverted_index.fasciculus | 197 |
| abstract_inverted_index.fractional | 61 |
| abstract_inverted_index.identified | 187 |
| abstract_inverted_index.pronounced | 152 |
| abstract_inverted_index.relatively | 179 |
| abstract_inverted_index.structural | 209 |
| abstract_inverted_index.(FTLD‐CDR | 104 |
| abstract_inverted_index.Conclusions | 201 |
| abstract_inverted_index.amyotrophic | 35 |
| abstract_inverted_index.demonstrate | 204 |
| abstract_inverted_index.differences | 64 |
| abstract_inverted_index.fasciculus, | 177 |
| abstract_inverted_index.involvement | 220 |
| abstract_inverted_index.originating | 137 |
| abstract_inverted_index.progression | 239 |
| abstract_inverted_index.(ALS‐FTD). | 41 |
| abstract_inverted_index.18ALS‐FTD, | 53 |
| abstract_inverted_index.Tract‐Wise | 81 |
| abstract_inverted_index.demonstrated | 162 |
| abstract_inverted_index.investigated | 3 |
| abstract_inverted_index.longitudinal | 51, 147, 176 |
| abstract_inverted_index.participants | 113 |
| abstract_inverted_index.particularly | 169 |
| abstract_inverted_index.progression. | 183 |
| abstract_inverted_index.Brain‐based | 70 |
| abstract_inverted_index.atlas‐based | 10 |
| abstract_inverted_index.complementary | 77 |
| abstract_inverted_index.corticospinal | 223 |
| abstract_inverted_index.degeneration, | 168 |
| abstract_inverted_index.discriminative | 190 |
| abstract_inverted_index.frontotemporal | 31, 39 |
| abstract_inverted_index.microstructure | 22 |
| abstract_inverted_index.Longitudinally, | 160 |
| abstract_inverted_index.microstructural | 211 |
| abstract_inverted_index.antero‐posterior | 164 |
| abstract_inverted_index.hypothesis‐driven | 76 |
| cited_by_percentile_year | |
| countries_distinct_count | 3 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile |