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Adanyeguh IM, Perlbarg V, Henry PG, Rinaldi D, Petit E, Valabregue R, Brice A, Durr A, Mochel F. Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes. Neuroimage Clin 2018; 19:858-867. [PMID: 29922574 PMCID: PMC6005808 DOI: 10.1016/j.nicl.2018.06.011] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 05/19/2018] [Accepted: 06/07/2018] [Indexed: 12/13/2022]
Abstract
Objective As gene-based therapies may soon arise for patients with spinocerebellar ataxia (SCA), there is a critical need to identify biomarkers of disease progression with effect sizes greater than clinical scores, enabling trials with smaller sample sizes. Methods We enrolled a unique cohort of patients with SCA1 (n = 15), SCA2 (n = 12), SCA3 (n = 20) and SCA7 (n = 10) and 24 healthy controls of similar age, sex and body mass index. We collected longitudinal clinical and imaging data at baseline and follow-up (mean interval of 24 months). We performed both manual and automated volumetric analyses. Diffusion tensor imaging (DTI) and a novel tractography method, called fixel-based analysis (FBA), were assessed at follow-up. Effect sizes were calculated for clinical scores and imaging parameters. Results Clinical scores worsened as atrophy increased over time (p < 0.05). However, atrophy of cerebellum and pons showed very large effect sizes (>1.2) compared to clinical scores (<0.8). FBA, applied for the first time to SCA, was sensitive to microstructural cross-sectional differences that were not captured by conventional DTI metrics, especially in the less studied SCA7 group. FBA also showed larger effect sizes than DTI metrics. Conclusion This study showed that volumetry outperformed clinical scores to measure disease progression in SCA1, SCA2, SCA3 and SCA7. Therefore, we advocate the use of volumetric biomarkers in therapeutic trials of autosomal dominant ataxias. In addition, FBA showed larger effect size than DTI to detect cross-sectional microstructural alterations in patients relative to controls. Biomarkers are needed to test upcoming therapies for spinocerebellar ataxia. As spinocerebellar ataxias are rare, biomarkers with high effect sizes are needed. We identified imaging biomarkers with higher effect sizes than clinical scores.
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Key Words
- Apparent fiber density
- CCFS, composite cerebellar functional severity score
- CFE, connectivity-based fixel enhancement
- CSD, constrained spherical deconvolution
- CST, corticospinal tract
- DTI, diffusion tensor imaging
- Diffusion imaging.
- FA, fractional anisotropy
- FBA, fixel-based analysis
- FC, fiber cross-section
- FD, fiber density
- FDC, fiber density and cross-section
- FOD, fiber orientation distribution
- FOV, Field of view
- Fixel analysis
- GRAPPA, generalized autocalibrating partial parallel acquisition
- Imaging biomarkers
- MPRAGE, magnetization-prepared rapid gradient-echo
- MRI, magnetic resonance imaging
- RD, radial diffusivity
- SARA, scale for the assessment and rating of ataxia
- SCA, spinocerebellar ataxias
- SNR, signal-to-noise ratio
- Spinocerebellar ataxia
- TBSS, tract-based spatial statistics
- TE, echo time
- TR, repetition time
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Affiliation(s)
- Isaac M Adanyeguh
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France
| | - Vincent Perlbarg
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France; Bioinformatics and Biostatistics Core Facililty, iCONICS, Institut du Ceveau et de la Moelle épinière, ICM, F-75013 Paris, France
| | - Pierre-Gilles Henry
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, United States
| | - Daisy Rinaldi
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France
| | - Elodie Petit
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France
| | - Romain Valabregue
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France; Center for NeuroImaging Research (CENIR), Institut du Cerveau et de la Moelle épinière, 75013 Paris, France
| | - Alexis Brice
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France
| | - Alexandra Durr
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France; AP-HP, Pitié-Salpêtrière University Hospital, Department of Genetics, Paris, France
| | - Fanny Mochel
- INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, UPMC Univ Paris 06 UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, F-75013 Paris, France; AP-HP, Pitié-Salpêtrière University Hospital, Department of Genetics, Paris, France; University Pierre and Marie Curie, Neurometabolic Research Group, Paris, France.
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