: While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain-age paradigm to assess whether FD patients' brains appear older than normal and to validate brain-predicted age difference (brain-PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index (FASTEX) was recorded as a measure of disease severity. Using minimally preprocessed 3D T1-weighted brain scans of healthy subjects from eight publicly available sources (N = 2160; mean age = 33 years [range 4-86]), we trained a model predicting chronological age based on a DenseNet architecture and used it to generate brain-age predictions in the internal cohort. Within a linear modeling framework, brain-PAD was tested for age/sex-adjusted associations with diagnostic group (FD vs. HC), FASTEX score, and both global and voxel-level neuroimaging measures. We studied 52 FD patients (40.6 ± 12.6 years; 28F) and 58 HC (38.4 ± 13.4 years; 28F). The brain-age model achieved accurate out-of-sample performance (mean absolute error = 4.01 years, R2 = .90). FD patients had significantly higher brain-PAD than HC (estimated marginal means: 3.1 vs. -0.1, p = .01). Brain-PAD was associated with FASTEX score (B = 0.10, p = .02), brain parenchymal fraction (B = -153.50, p = .001), white matter hyperintensities load (B = 0.85, p = .01), and tissue volume reduction throughout the brain. We demonstrated that FD patients' brains appear older than normal. Brain-PAD correlates with FD-related multi-organ damage and is influenced by both global brain volume and white matter hyperintensities, offering a comprehensive biomarker of (neurological) disease severity.

Assessing brain involvement in Fabry disease with deep learning and the brain‐age paradigm / Montella, Alfredo; Tranfa, Mario; Scaravilli, Alessandra; Barkhof, Frederik; Brunetti, Arturo; Cole, James; Gravina, Michela; Marrone, Stefano; Riccio, Daniele; Riccio, Eleonora; Sansone, Carlo; Spinelli, Letizia; Petracca, Maria; Pisani, Antonio; Cocozza, Sirio; Pontillo, Giuseppe. - In: HUMAN BRAIN MAPPING. - ISSN 1065-9471. - 45:5(2024). [10.1002/hbm.26599]

Assessing brain involvement in Fabry disease with deep learning and the brain‐age paradigm

Tranfa, Mario;Scaravilli, Alessandra;Brunetti, Arturo;Gravina, Michela;Marrone, Stefano;Riccio, Daniele;Riccio, Eleonora;Sansone, Carlo;Spinelli, Letizia;Petracca, Maria;Pisani, Antonio;Cocozza, Sirio
;
Pontillo, Giuseppe
2024

Abstract

: While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement are lacking. We used deep learning and the brain-age paradigm to assess whether FD patients' brains appear older than normal and to validate brain-predicted age difference (brain-PAD) as a possible disease severity biomarker. MRI scans of FD patients and healthy controls (HCs) from a single Institution were, retrospectively, studied. The Fabry stabilization index (FASTEX) was recorded as a measure of disease severity. Using minimally preprocessed 3D T1-weighted brain scans of healthy subjects from eight publicly available sources (N = 2160; mean age = 33 years [range 4-86]), we trained a model predicting chronological age based on a DenseNet architecture and used it to generate brain-age predictions in the internal cohort. Within a linear modeling framework, brain-PAD was tested for age/sex-adjusted associations with diagnostic group (FD vs. HC), FASTEX score, and both global and voxel-level neuroimaging measures. We studied 52 FD patients (40.6 ± 12.6 years; 28F) and 58 HC (38.4 ± 13.4 years; 28F). The brain-age model achieved accurate out-of-sample performance (mean absolute error = 4.01 years, R2 = .90). FD patients had significantly higher brain-PAD than HC (estimated marginal means: 3.1 vs. -0.1, p = .01). Brain-PAD was associated with FASTEX score (B = 0.10, p = .02), brain parenchymal fraction (B = -153.50, p = .001), white matter hyperintensities load (B = 0.85, p = .01), and tissue volume reduction throughout the brain. We demonstrated that FD patients' brains appear older than normal. Brain-PAD correlates with FD-related multi-organ damage and is influenced by both global brain volume and white matter hyperintensities, offering a comprehensive biomarker of (neurological) disease severity.
2024
Assessing brain involvement in Fabry disease with deep learning and the brain‐age paradigm / Montella, Alfredo; Tranfa, Mario; Scaravilli, Alessandra; Barkhof, Frederik; Brunetti, Arturo; Cole, James; Gravina, Michela; Marrone, Stefano; Riccio, Daniele; Riccio, Eleonora; Sansone, Carlo; Spinelli, Letizia; Petracca, Maria; Pisani, Antonio; Cocozza, Sirio; Pontillo, Giuseppe. - In: HUMAN BRAIN MAPPING. - ISSN 1065-9471. - 45:5(2024). [10.1002/hbm.26599]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/956484
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