ObjectivesTo systematically review the efficacy and safety of bevacizumab combined with STUPP regimen for newly diagnosed glioblastoma.MethodsPubMed, EMbase, the Cochrane Library, CBM, CNKI, VIP and WanFang Data databases were searched to obtain randomized controlled trials (RCTs) of bevacizumab combined with STUPP regimen for newly diagnosed glioblastoma patients from inception to September 2017. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies. Meta-analysis was then performed using RevMan 5.3 software.ResultsA total of 6 RCTs involving 2 835 patients were included. The results of meta-analysis showed that: the bevacizumab combined with STUPP regimen group was superior to the control group on PFS (HR=0.69, 95%CI 0.62 to 0.77, P<0.000 01). But the adverse events rate at the three and above three levels was significantly higher than the control group (P<0.05).ConclusionsCurrent evidence shows that bevacizumab combined with STUPP regimen for newly diagnosed glioblastoma can significantly prolong the PFS. The treatment group performs not as well as the control group on adverse event rate. Due to the limited quality and quantity of the included studies, more high-quality studies are required to verify above conclusions.
ObjectiveTo explore the value of 3.0 T MRI functional imaging in differential diagnosis of radiation brain injury and recurrence of glioblastoma multiforme.MethodsFrom March 2017 to January 2018, 31 patients diagnosed with brain glioblastoma multiforme in Peking University International Hospital were collected continuously, including 14 cases of tumor recurrence and 17 cases of radiation-induced brain injury. All the patients routinely underwent conventional MRI head scan, three-dimension arterial spin labeling (3D-ASL), dynamic susceptibility contrastperfusion weighted imaging (DSC-PWI), and enhanced MRI scan sequence; related parameters were recorded and compared.ResultsCerebral blood flow (CBF) value of abnormal enhanced area in the recurrence group was significantly higher than that in the brain injury group with 3D-ASL scan (t=3.016, P=0.005), and no difference was found in edema area between the two groups (P>0.05). In the recurrence group, CBF value of abnormal enhanced area was significantly higher than that of the normal area (t=2.628, P=0.014); however, there was no significant difference in the CBF value between the abnormal enhancement foci and the normal areas in the radiation brain injury group (P>0.05). Relative cerebral blood volume (rCBV) ratio (t=2.894, P=0.007) and relative cerebral blood volume (rCBF) ratio (t=2.694, P=0.012) of abnormal enhanced area, as well as rCBV ratio (t=2.622, P=0.013) and rCBF ratio (t=2.775, P=0.010) of edema area in the recurrence group were significantly higher than those in the brain injury group with DSC-PWI scan. No differences were found in relative mean transit time (rMTT) ratio and relative time to peak (rTTP) ratio between the two groups (P>0.05). In the brain injury groupr, CBV ratio (t=2.921, P=0.008) and rCBF ratio (t=3.100, P=0.004) of abnormal enhanced area were significantly higher than those of the edema area, and no difference was found in rMTT ratio or rTTP ratio (P>0.05). In the recurrence group, no difference was found in all focal parameters between abnormal enhanced area and edema area (P>0.05). In diagnosis value analysis, the areas under the curve of CBF in 3D-ASL scan, and rCBF ratio, rCBV ratio in DSC-PWI scan were 0.752, 0.675, and 0.645, respectively; the cut-off values were 34.59, 1.48, and 1.67, respectively; the sensitivities were 79.2%, 61.5%, and 58.3%, respectively; and the specificities were 44.4%, 32.8%, and 22.4%, respectively.ConculsionThe diagnostic value of functional MRI imaging in distinguishing glioblastoma multiforme recurrence and radiation-induced brain injury is high recommendated; further research and clinical application should be needed.
ObjectiveTo systematically review the value of radiomics in the diagnosis of glioblastoma. MethodsPubMed, EMbase, Web of Science and The Cochrane Library databases were electronically searched to collect studies on radiomics in the grading of gliomas or the differentiation diagnosis from inception to May 30th, 2021. Two reviewers independently screened literature, extracted data, and assessed the risk of bias and the quality of the included studies. Meta-analysis was then performed using Meta-Disc 1.4 software and RevMan 5.3 software. ResultsA total of 37 studies involving 2 746 subjects were included. The results of meta-analysis showed that the pooled sensitivity, specificity, and diagnostic odds ratio for the diagnosis of glioblastoma by radiomics were 0.91 (95%CI 0.89 to 0.92), 0.88 (95%CI 0.87 to 0.90), and 78.00 (95%CI 50.81 to 119.72), respectively. The area under the summary receiver operating characteristic (SROC) curve was 0.95. The key radiomic features for correct diagnosis of glioblastoma included intensity features and texture features of the lesions. ConclusionThe current evidence shows that radiomics provides good diagnostic accuracy for glioblastoma. Due to the limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusions.
Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.