Schizophrenia is a mental disorder in which functional and structural brain networks are disrupted. Classical network analysis has been used by many researchers to quantify brain networks and to study the network changes in schizophrenia, but unfortunately metrics used in this classical method highly depend on the networks' density and weight; the comparisons made by this method are biased. The minimum spanning tree (MST) is an alternative method to solve this problem, but its usefulness in studying the schizophrenic brain network has not been examined yet. In the present study, we quantified structural brain networks using MST metrics to conduct group analysis between age and sex matched schizophrenic patients and healthy controls. Many MST metrics including Kappa, gamma, max, Betweenness centrality (BC), leaf number, and diameter were found to have significantly changed between two groups that implied a disruption in the whole brain integrity. This was unlike the brain segregation, which was not altered in the schizophrenia group. These results have consistency with Classical network analysis works and demonstrate the MST potential as a powerful method to be used in researches, studying schizophrenic brain connectome.