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Scaphoid fractures are difficult to diagnose with current imaging modalities. It is unknown whether the shape of the scaphoid bone, assessed by statistical shape modeling, can be used to differentiate between fractured and non-fractured bones. Therefore, the aim of this study was to investigate whether the presence of a scaphoid fracture is associated with shape modes of a statistical shape model (SSM). Forty-one high-resolution peripheral quantitative computed tomography (HR-pQCT) scans were available from patients with a clinically suspected scaphoid fracture of whom 15 patients had a scaphoid fracture. The scans showed no motion artefacts affecting bone shape. The scaphoid bones were semi-automatically contoured, and the contours were converted to triangular meshes. The meshes were registered, followed by principal component analysis to determine mean shape and shape modes describing shape variance. The first five out of the forty shape modes cumulatively explained 87.8% of the shape variance. Logistic regression analysis was used to study the association between shape modes and fracture presence. The regression models were used to classify the 41 scaphoid bones as fractured or non-fractured using a cut-off value that maximized the sum of sensitivity and specificity. The classification of the models was compared with fracture diagnosis on HR-pQCT. A regression model with four shape modes had an area under the ROC-curve of 72.3% and correctly classified 75.6% of the scaphoid bones (fractured: 60.0%, non-fractured: 84.6%). To conclude, fracture presence in patients with a clinically suspected scaphoid fracture appears to be associated with the shape of the scaphoid bone.