Abstract Over one third of stroke patients have long-term cognitive impairment. The likelihood of cognitive dysfunction is poorly predicted by the location or size of the infarct. The macroscale damage caused by ischaemic stroke is relatively localised, but the effects of stroke occur across the brain. Structural covariance networks represent voxelwise correlations in cortical morphometry. Atrophy and topographical changes within such distributed brain structural networks may contribute to cognitive decline after ischaemic stroke, but this has not been thoroughly investigated. We examined longitudinal changes in structural covariance networks in stroke patients and their relationship to domain-specific cognitive decline. Seventy-three patients (mean age 67.41 years, SD 12.13) were scanned with high-resolution MRI at subacute (3-months) and chronic (1-year) timepoints after ischaemic stroke. Patients underwent a number of neuropsychological tests assessing five cognitive domains including attention, executive function, language, memory and visuospatial function at each timepoint. Individual-level structural covariance network scores were derived from the subacute grey matter probabilistic maps or changes in grey matter probability maps from subacute to chronic using data-driven partial least squares method seeding at major nodes in six canonical high-order cognitive brain networks (i.e., dorsal attention, executive control, salience, default mode, language-related and memory networks). We then investigated covarying patterns between structural covariance network scores within canonical distributed brain networks and domain-specific cognitive performance after ischaemic stroke, both cross-sectionally and longitudinally, using multivariate behavioural partial least squares correlation approach. We tested our models in an independent validation dataset with matched imaging and behavioural testing and using split-half validation. We found that distributed degeneration in higher-order cognitive networks was associated with attention, executive function, language, memory and visuospatial function impairment in subacute stroke. From the subacute to the chronic timepoint, longitudinal structural covarying patterns mirrored the baseline structural covariance networks, suggesting synchronized grey matter volume decline occurred within established networks over time. The greatest changes, in terms of extent of distributed spatial covarying patterns, were in the default mode and dorsal attention networks while the rest were more focal. Importantly, faster degradation in these major cognitive structural covariance networks was associated with greater decline in attention, memory and language domains frequently impaired after stroke. Our findings suggest that subacute ischaemic stroke is associated with widespread degeneration of higher-order structural brain networks and degradation of these structural brain networks may contribute to longitudinal domain-specific cognitive dysfunction.