OBJECTIVE: The identification of sensitive biomarkers is essential to validate therapeutics for Huntington’s disease (HD). We directly compare structural imaging markers across the largest collective imaging HD dataset, to identify a set of imaging markers robust to multi-centre variation and to derive upper estimates on sample sizes for clinical trials in HD. METHODS: We used one post-processing pipeline to retrospectively analyse T1-weighted magnetic resonance imaging (MRI) scans from 624 participants at three time points, from the PREDICT-HD, TRACK-HD and IMAGE-HD studies. We used mixed effects models to adjust regional brain volumes for covariates, calculate effect sizes, and simulate possible treatment effects in disease-affected anatomical regions. We used our model to estimate the statistical power of possible treatment effects for anatomical regions and clinical markers. RESULTS: We identify a set of common anatomical regions that have similarly large standardised effect sizes (>0.5) between healthy control and pre-manifest (PreHD) groups. These include: sub-cortical, white matter, and cortical regions, and non-ventricular cerebrospinal fluid (CSF). We also observe a consistent spatial distribution of effect size by region across the whole brain. We find that multi-centre studies are necessary to capture treatment effect variance; that for a 20% treatment effect, power > 80% is achieved for the caudate (N=661), pallidum (N=687), and non-ventricular CSF (N=939); and, crucially, that these imaging markers provide greater power than standard clinical markers. INTERPRETATION: Our findings provide the first cross-study validation of structural imaging markers in HD, supporting the use of these measurements as endpoints for both observational studies and clinical trials. This article is protected by copyright. All rights reserved.