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- Li, Sirui, et al.
(författare)
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Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging
- 2021
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 31:11, s. 8197-8207
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. Materials and methods: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (μFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. Results: FA, MD, MKA, MKI, MKT, μFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). Conclusion: DIVIDE is a promising technique for glioma characterization and diagnosis. Key Points: • DIVIDE metrics MKIis related to cell density heterogeneity while MKAand μFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKIwas larger than MKAwhich indicates predominant cell density heterogeneity in gliomas. • MKAand MKIincreased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKAin relation to the cell density heterogeneity metric MKI.
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| 2. |
- Liu, Zhengtao, et al.
(författare)
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Meta-Analysis of Adiponectin as a Biomarker for the Detection of Metabolic Syndrome
- 2018
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Ingår i: Frontiers in Physiology. - : Frontiers Media SA. - 1664-042X. ; 9:SEP
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Forskningsöversikt (refereegranskat)abstract
- Previous studies revealed the potential significance of circulating adiponectin levels with respect to the diagnosis and prediction of metabolic syndrome, but uncertainty has been noted across different cohorts. Systematic evaluation was performed for diagnostic accuracy and predictivity of adiponectin variation for metabolic syndrome in enrolled studies including 1,248 and 6,020 subjects, respectively. Adiponectin can identify metabolic syndrome with moderate accuracy (area under the curve = 0.81, 95% CI: 0.77-0.84). Heterogeneity analysis revealed that an increasing index of insulin resistance was independently associated with improving the performance of adiponectin upon metabolic syndrome diagnosis (ratio of diagnostic odds ratio = 3.89, 95% CI: 1.13-13.9). In addition, reductions in adiponectin were associated with increasing metabolic syndrome incidence in a linear dose-response manner. The risk of hypoadiponectinemia with metabolic syndrome was especially increased in men (P < 0.05). Further Mendelian randomization analysis identified that the amplified risk could be attributed to increased susceptibility (up to 7%) to insulin resistance compared with women. In conclusion, adiponectin measurement might have potential benefits in the detection of metabolic syndrome. Factors that affect insulin resistance should be considered for adjustment in future assessments.
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