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<b><i>Introduction:</i></b> Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCNs) are represented as graphs with brain regions as nodes and correlations between nodes as edges. <b><i>Methods:</i></b> We built SCNs for PTSD and control groups using 148 CT and SA measures that were harmonized for site in <i>n</i> = 3439 subjects from Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA)-Psychiatric Genomics Consortium (PGC) PTSD. We compared centrality between PTSD and controls as well as interactions of diagnostic group with age, sex, and comorbid major depressive disorder (MDD) status. We investigated associations between network modularity and diagnostic grouping. <b><i>Results:</i></b> Nodes with higher CT-based centrality in PTSD compared with controls included the left inferior frontal sulcus, left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. Children (<10 years) and adolescents (10-21) with PTSD showed greater centrality in frontotemporal areas compared with young (22-39) and middle-aged adults (40-59) with PTSD, who showed higher centrality in occipital areas. The PTSD diagnostic group interactions with sex and comorbid MDD showed altered centrality in occipital regions, along with greater visual network (VN) modularity in PTSD subjects compared with controls. <b><i>Conclusion:</i></b> Structural covariance in PTSD is associated with centrality differences in occipital areas and VN modularity differences in a large well-powered sample. In the context of extensive structural covariance remodeling taking place before and during adolescence, the present findings suggest a process of cortical remodeling that commences with trauma and/or the onset of PTSD but may also predate these events. Impact statement Centrality is a graph theory measure that offers insights into a node's relationship with all other nodes in the brain. Centrality pinpoints the drivers of brain communication within networks and nodes and may be a promising target for treatments such as neuromodulation. Modularity can pinpoint modules that exist within larger networks and quantify the connections between these modules. Centrality and modularity complement functional and structural connectivity measurements within specific brain networks.