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Updated: May 24, 2025
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Magnetic resonance diffusion-derived vessel density (DDVD) as a valuable tissue perfusion biomarker for isocitrate
Chen-Xi Ni1,2, Ruo-Lan Lin1,2, Dian-Qi Yao3
1Department of Radiology, Fujian Medical University Union Hospital, NO.29 Xinquan Road, Fuzhou, 350001, Fujian, P. R. China.
Background:
Determining isocitrate dehydrogenase (IDH) mutation is crucial for glioma clinical management. MR diffusion-derived 'vessel density' (DDVD) offers non-invasive tissue perfusion evaluation within the tumor microenvironment. The study attempts to distinguish IDH genotypes of diffuse gliomas using DDVD in whole tumor parenchyma and its habitats.
Methods:
This study enrolled 63 patients with diffuse gliomas (30 IDH-mutant and 33 IDH-wildtype) who underwent diffusion-weighted (DW) imaging at 3T. DDVDb0b10 was the signal difference between the b = 0 and b = 10 s/mm2 DW images. DDVDb0b10_b10b20 is DDVDb0b10 minus DDVDb10b20. nDDVD was DDVD divided by signal intensity at b = 0 s/mm2 DW image. Correlations between DDVD metrics/intravoxel incoherent motion (IVIM) imaging metrics (D and f) and IDH genotypes/Ki-67 status were studied.
Results:
In tumor parenchyma, DDVDb0b10_b10b20 and nDDVDb0b10_b10b20 were lower, whereas D was higher in IDH-mutant gliomas [median (interquartile range): 12.76 (9.79-14.60); 15.14 (11.61-19.29); 1.31 (1.19-1.39)] compared to IDH-wildtype gliomas [14.48 (2.93-18.60), p = 0.008; 20.55 (15.89-24.02), p < 0.001; 1.16 (0.98-1.27), p = 0.003]. Habitat analysis improved the diagnostic performance for IDH genotyping, with the highest AUC of 0.823 found for the nDDVDb0b10_b10b20 derived from the high DDVDb0b10 value habitat. Diagnostic efficacy of the combined model of nDDVDb0b10_b10b20 with D was superior to that of combined model of f with D. The habitat model incorporating age, sex, and Karnofsky Performance Status further significantly enhanced the diagnostic efficacy, with an AUC reaching 0.979. Additionally, DDVD and f showed a positive correlation with Ki-67, while D exhibited a negative correlation with Ki-67 (all p < 0.05).
Conclusion:
DDVD, as a novel biomarker of microvascular perfusion, effectively differentiates IDH genotypes in gliomas. The habitat analysis improves the diagnostic accuracy for IDH genotyping.
