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Sandra D'Alfonso

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2 papers

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YNICL Journal 2022 Journal Article

Clinical relevance of single-subject brain metabolism patterns in amyotrophic lateral sclerosis mutation carriers

Giacomo Tondo
Letizia Mazzini
Silvia Paola Caminiti
Maria Francesca Sarnelli
Lucia Corrado
Roberta Matheoud
Sandra D'Alfonso
Roberto Cantello

BACKGROUND AND OBJECTIVES: F-FDG-PET single-subject analysis in a sample of familial ALS patients carrying different gene mutations, investigating the genotype-phenotype correlations and exploring metabolism correlations with clinical and neuropsychological data. METHODS: F-FDG-PET regional hypometabolism was correlated with clinical and neuropsychological features. RESULTS: Classifying the patients with C9orf72-ALS based on the rate of disease progression from symptoms onset to the time of scan, we observed two different patterns of brain hypometabolism: an extensive motor and prefrontal hypometabolism in patients classified as fast progressors, and a more limited brain hypometabolism in patients grouped as slow progressors. Patients with SOD1-ALS showed a hypometabolic pattern involving the motor cortex and prefrontal association regions, with a minor involvement of the limbic regions. The patient with TBK1-ALS showed an extended hypometabolism, in limbic systems, along with typical motor involvement, while the hypometabolism in the patient with KIF5A-ALS involved almost exclusively the motor regions, supporting the predominantly motor impairment linked to this gene mutation. Additionally, we observed strong correlations between the hypometabolism in the motor, prefrontal association and limbic meta-ROI and the specific neuropsychological performances. CONCLUSIONS: F-FDG-PET in revealing pattern of neuronal dysfunction, aiding the diagnostic workup in genetic ALS patients.

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YNIMG Journal 2016 Journal Article

Power estimation for non-standardized multisite studies

Anisha Keshavan
Friedemann Paul
Mona K. Beyer
Alyssa H. Zhu
Nico Papinutto
Russell T. Shinohara
William Stern
Michael Amann

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.

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