====== Frontal glioma ======

Although every [[glioma]] [[patient]] varies in [[tumor size]], [[location]], [[histological grade]], and [[molecular biomarker]]s, non-tumoral morphological abnormalities are commonly detected by a statistical comparison among patient groups, missing the information of individual morphological alterations. 

Zhang et al. introduced an individual-level structural [[anomaly detection]] method for [[glioma]] patients and proposed several [[abnormality]] indexes to depict individual [[atrophy]] patterns. Forty-five patients with a glioma in the [[frontal lobe]] and fifty-one age-matched healthy controls participated in the study. Individual structural abnormality maps (SAM) were generated using patients' preoperative [[T1]] images, by calculating the degree of deviation of [[voxel]] [[volume]] in each patient with the normative model built from healthy controls. Based on SAM, a series of individual abnormality indexes were computed, and their relationship with glioma characteristics was explored. The results demonstrated that glioma patients showed unique non-tumoral atrophy patterns with overlapping atrophy regions mainly located in the [[hippocampus]], [[parahippocampus]], [[amygdala]], [[insula]], [[middle temporal gyrus]] and [[inferior temporal gyrus]], which are closely related to the human [[cognitive function]]s. The abnormality indexes were associated with several [[molecular biomarker]]s including [[isocitrate dehydrogenase]] (IDH) mutation, [[1p/19q co-deletion]] and telomerase reverse transcriptase ([[TERT]]) promoter mutation. The study provides an effective way to access the individual-level non-tumoral structural abnormalities in glioma patients, which has the potential to significantly improve individualized [[precision medicine]]
((Zhang G, Zhang X, Huang H, Wang Y, Li H, Duan Y, Chen H, Liu Y, Jing B, Tie Y, Lin S. Probing individual-level structural [[atrophy]] in [[frontal glioma]] patients. Neurosurg Rev. 2022 May 4. doi: 10.1007/s10143-022-01800-9. Epub ahead of print. PMID: 35508819.)).