Autosomal dominant cerebellar ataxias: Imaging biomarkers with high effect sizes

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.

Trial registration: ClinicalTrials.gov NCT01470729.

Keywords: 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.

Graphical abstract

Fig. 1

Change in clinical scores between baseline and follow-up. All SCA groups showed increased SARA scores that reached significance in SCA1, SCA2 and SCA3. CCFS was also significantly increased in patients with SCA3 and SCA7. Error bars represent standard error of mean (SEM). * p < 0.05 and ^#p ≤ 0.01 represent significant differences adjusted for age and corrected with Bonferroni correction.

Fig. 2

Change in regional volume after 24 months. Manual segmentation of the vermis showed a significant change in volume in SCA3 only (A). Instead, Freesurfer segmentation showed a decrease in the volume of the cerebellum (B) and pons (C) in patients with SCA over 24 months. Error bars represent standard error of mean. * p < 0.05, ^#p ≤ 0.01, and ^†p ≤ 0.001 represent significant differences adjusted for age and corrected with Bonferroni correction.

Fig. 3

Rate of motor decline and atrophy of the cerebellum and pons in patients with SCA compared to controls using age as a covariate. The change over time in SARA score was not significant (A) but the change over time of CCFS was significant in patients with SCA3 and SCA7 (B). A faster rate of atrophy was observed in the cerebellum (C) and the pons (D) of patients with SCA compared to controls, with the exception of SCA7 for the cerebellum. * p < 0.05, ^#p ≤ 0.01, ^†p ≤ 0.001 represent significant differences adjusted for age and corrected with step-down Bonferroni correction.

Fig. 4

Tract-based statistical analysis of FA and RD in SCA and controls. Red-yellow highlights show areas of decreased FA in SCA (p < 0.05) (A). Blue-pink regions show areas of increased RD in SCA (p < 0.05) (B).

Fig. 5

Connectivity-based fixel enhancement on FD, FC and FDC. The fixel mask and tractogram used for the statistics (A). FD, FC and FDC are significantly reduced in the CST of SCA (p < 0.05 with family-wise error correction) (B). Fiber colours are directional: blue = superior-inferior direction; red = left-right direction; green = anterior-posterior direction.