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3. Clinical and biological underpinnings of longitudinal atrophy pattern progression in Alzheimer's disease.

Author

Ferraro, Pilar M, Filippi, Laura, Ponzano, Marta, Signori, Alessio, Orso, Beatrice, Massa, Federico, Arnaldi, Dario, Caneva, Stefano, Argenti, Lucia, Losa, Mattia, Lombardo, Lorenzo, Mattioli, Pietro, Costagli, Mauro, Gualco, Lorenzo, Pulze, Martina, Plantone, Domenico, Brugnolo, Andrea, Girtler, Nicola, Diociasi, Andrea, and Garbarino, Sara

Subjects
ALZHEIMER'S disease, MAGNETIC resonance imaging, LOGISTIC regression analysis, DISEASE progression, DATABASES, MILD cognitive impairment
Abstract

Background: Magnetic resonance imaging (MRI) has recently enabled to identify four distinct Alzheimer's disease (AD) subtypes: hippocampal sparing (HpSp), typical AD (tAD), limbic predominant (Lp), and minimal atrophy (MinAtr). To date, however, the natural history of these subtypes, especially regarding the presence of subjects switching to other MRI patterns and their clinical and biological differences, remains poorly understood. Objective: To investigate the clinical and biological underpinnings of longitudinal atrophy pattern progression in AD. Methods: 251 AD patients (16 with significant memory concern, 66 with early mild cognitive impairment (MCI), 125 with late MCI, and 44 with AD dementia) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database were assigned to their baseline MRI atrophy subtype using Freesurfer-derived cortical:hippocampal volumes ratio. Switching to other MRI patterns was investigated on longitudinal scans, and patients were accordingly classified as " switching " and " stable ". Logistic regression models were applied to identify predictors of switching to other MRI patterns. Results: 40% of Lp, 26% of HpSp, and 35% of MinAtr cases switched to other MRI patterns, with tAD representing the destination subtype of all switching HpSp and Lp, and the majority of MinAtr. At baseline significant clinical, cognitive and biomarkers differences were observed across the four subtypes. Only clinical and cognitive variables, however, were significantly associated with switch to other MRI patterns. Conclusions: Our results suggest convergent directions of disease progression across atypical and typical AD forms, at least in a subset of AD subjects, and highlight the importance of deep-phenotyping approaches to understand AD heterogeneity. [ABSTRACT FROM AUTHOR]

Published
2025
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7. Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A of derived brain volume measurements

Author

Ferraro, Pilar Maria, Gualco, Lorenzo, Costagli, Mauro, Schiavi, Simona, Ponzano, Marta, Signori, Alessio, Massa, Federico, Pardini, Matteo, Castellan, Lucio, Levrero, Fabrizio, Zaca, Domenico, Piredda, Gian Franco, Hilbert, Tom, Kober, Tobias, and Roccatagliata, Luca

Subjects
images, cs mp2rage, segmentation, brain volume, mprage, mri, gray, freesurfer
Abstract

Purpose: T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a quantitative 3D anatomical image coupled with T1-map. Here we investigated the agreement between FreeSurfer-derived volume measurements obtained from MPRAGE and CS MP2RAGE acquisitions. Methods: MPRAGE and CS MP2RAGE images of 37 subjects (14 patients with neurodegenerative disorders and 23 healthy controls) were acquired on a 3 T MR scanner and grey matter volumes were extracted using standard FreeSurfer parcellation. Lin's concordance correlation coefficient (Lin's CCC), Bland-Altman analysis, Passing-Bablok regression and DICE similarity coefficient were calculated to assess the agreement between the two. Results: We found a good correspondence for most of the regions examined, with 93.5 % of them showing a mean DICE index >0.70. Poorer results were found with Lin's CCC especially for subcortical labels across patients. The Bland-Altman analysis showed CS MP2RAGE tended to measure lower cortical volumes compared to MPRAGE but in most cases the difference wasn't statistically relevant. The Passing-Bablock regression indicated overall an absence of systematic constant and proportional bias when CS MP2RAGE was used instead of MPRAGE. Conclusions: We found a good concordance for volumes obtained from MPRAGE and CS MP2RAGE images using FreeSurfer, suggesting a possible role of CS MP2RAGE for structural analysis with significant advantages like shorter acquisition time and the possibility to simultaneously obtain quantitative T1-maps of the brain enriching the diagnostic power of this technique.

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