Brain network characteristics’ potential to serve as a neurological and psychiatric pathology biomarker has been hampered by the so-called thresholding problem. The minimum spanning tree (MST) is increasingly applied to overcome this problem. It is yet unknown whether this approach leads to more consistent findings across studies and converging outcomes of either disease-specific biomarkers or transdiagnostic effects. We performed a systematic review on MST analysis in neurophysiological and neuroimaging studies (N = 43) to study consistency of MST-metrics between different network sizes, and assessed disease specificity and transdiagnostic sensitivity of MST-metrics for neurological and psychiatric conditions. Analysis of data from control groups (12 studies) showed that MST leaf fraction but not diameter decreased with increasing network size. Studies showed a broad range in metric values, suggesting that specific processing pipelines affect MST topology. Contradicting findings remain in the inconclusive literature of MST brain network studies, but some trends were seen: 1) a more line-like organization characterizes neurodegenerative disorders across pathologies, and is associated with symptom severity and disease progression; 2) neurophysiological studies in epilepsy show frequency band specific MST alterations that normalize after successful treatment; and 3) less efficient MST topology in alpha band is found across disorders associated with attention impairments.