Quantitatively evaluate the efficacy of advanced diffusion weighted imaging (NODDI and DKI) in grading gliomas

This poster is published under an open license. Please read the disclaimer for further details.

Congress:

ECR 2017

Poster Number:

C-2979

Type:

Scientific Exhibit

Keywords:

CNS, Oncology, Head and neck, MR-Diffusion/Perfusion, Diagnostic procedure, Neoplasia

Authors:

J. Zhao¹, J. P. Chu², J.-Y. Wang², Y. L. Wang², X. B. Li², Y. Song², X. Yan³; ¹GuangZhou, GuangZhou/CN, ²GuangZhou/CN, ³Shang Hai/CN

DOI:

10.1594/ecr2017/C-2979

DOI-Link:

https://dx.doi.org/10.1594/ecr2017/C-2979

Fig. 1: There were two cases with left frontal lobe brain tumor (upper) and left...

Fig. 2: ROC curve showed that the AUC of the model which included ADC, MK and ficvf for...

Table 1: The statistic findings of the NODDI and DKI metrics for grading gliomas

Aims and objectives

Preoperative accurate brain tumor diagnosis plays an essential role in the selection of the optimum treatment strategy, as their management and prognosis are different. Advanced MRI techniques, such as DWI, PWI, MRS and DKI, have been wildly used to grading gliomas and the diagnostic efficiency for grading gliomas has been gradually improved.1-3Newly developed neurite orientation dispersion and density imaging (NODDI) and DKI is an advanced diffusion weighted imaging. DKI has show potential to grading gliomas.4NODDI has been applied to analyze multiple sclerosis5, focal cerebral corital...

Methods and materials

29 patients (male: 18, female: 11, mean age: 45.4 y) were prospectively recruited and they underwent whole-brain DWI which were collected at three b values (0, 1000 and 2000 s/mm2) and each non-zero b value has 30 directions. Both the b = 1000 s/mm2 and b = 2000 s/mm2 data were used for the NODDI and DKI analysis. The parameter maps of DKI (MK, Ka, Kr, FA and ADC) and NODDI (ficvf and ODI) were generated. Ten same ROIs were manually drawn on each maps...

Results

All diffusion parameters can significantly differentiate HGG and LGG (p<0.000). MK, Ka, Kr, FA, ficvf and ODI were significantly higher in HGG while MD and ADC were significantly lower in HGG.(Fig.1) ROC analysis showed that ficvf had the highest diagnostic value (AUC: 0.80, sensitivity: 71%; specificity: 80%; cut-off value: 0.33) in predicting HGG while ADC demonstrated the lowest diagnostic value. Combining analysis of ADC, MK and ficvf by linear regression showed that the AUC for predicting LGG was much higher (89%)(Fig.2) and the sensitivity and...

Conclusion

Advanced diffusion weighted imaging (NODDI and DKI) may help in gliomas grading and ficvf showed the highest diagnostic value. Combining use of different diffusion models could substantially improve our diagnosis.

Personal information

References

1. Sadeghi N, D'Haene N, Decaestecker C, et al. Apparent diffusion coefficient and cerebral blood volume in brain gliomas: relation to tumor cell density and tumor microvessel density based on stereotactic biopsies[J]. AJNR Am J Neuroradiol,2008,29(3):476-482. 2. Calvar J A, Meli F J, Romero C, et al. Characterization of brain tumors by MRS, DWI and Ki-67 labeling index[J]. J Neurooncol,2005,72(3):273-280. 3. Zonari P, Baraldi P, Crisi G. Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and...