The Chinese Glioma Cooperative Group (CGCG) Guideline Panel for adult diffuse gliomas provided recommendations for diagnostic and therapeutic procedures. The Panel covered all fields of expertise in neuro-oncology, i.e. neurosurgeons, neurologists, neuropathologists, neuroradiologists, radiation and medical oncologists and clinical trial experts. The task made clearer and more transparent choices about outcomes considered most relevant through searching the references considered most relevant and evaluating their value. The scientific evidence of papers collected from the literature was evaluated and graded based on the Oxford Centre for Evidence-based Medicine Levels of Evidence and recommendations were given accordingly. The recommendations will provide a framework and assurance for the strategy of diagnostic and therapeutic measures to reduce complications from unnecessary treatment and cost. The guideline should serve as an application for all professionals involved in the management of patients with adult diffuse glioma and also as a source of knowledge for insurance companies and other institutions involved in the cost regulation of cancer care in China.

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Our quantitative neuroimaging analyses support the concept that the anatomic location of an LGG is a contributing factor in tumor-related seizure.

ObjectiveThe aim of this study was to develop a radiomics signature for prediction of progression-free survival (PFS) in lower-grade gliomas and to investigate the genetic background behind the radiomics signature.MethodsIn this retrospective study, training (n = 216) and validation (n = 84) cohorts were collected from the Chinese Glioma Genome Atlas and the Cancer Genome Atlas, respectively. For each patient, a total of 431 radiomics features were extracted from preoperative T2-weighted magnetic resonance images. A radiomics signature was generated in the training cohort, and its prognostic value was evaluated in both the training and validation cohorts. The genetic characteristics of the group with high-risk scores were identified by radiogenomic analysis, and a nomogram was established for prediction of PFS.ResultsThere was a significant association between the radiomics signature (including 9 screened radiomics features) and PFS, which was independent of other clinicopathologic factors in both the training (P < 0.001, multivariable Cox regression) and validation (P = 0.045, multivariable Cox regression) cohorts. Radiogenomic analysis revealed that the radiomics signature was associated with the immune response, programmed cell death, cell proliferation, and vasculature development. A nomogram established using the radiomics signature and clinicopathologic risk factors demonstrated high accuracy and good calibration for prediction of PFS in both the training (C-index, 0.684) and validation (C-index, 0.823) cohorts.ConclusionsPFS can be predicted non-invasively in patients with LGGs by a group of radiomics features that could reflect the biological processes of these tumors.