Survival Associations Using Perfusion and Diffusion Magnetic Resonance Imaging in Patients With Histologic and Genetic Defined Diffuse Glioma World Health Organization Grades II and III

Diagnostic accuracy of magnetic resonance imaging in detection of intra-axial gliomas

Objective:

To evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in detection of intra-axial gliomas in suspected cases keeping histopathology as gold standard.

Methods:

This cross-sectional study was conducted at Dow Institute of Radiology, DUHS from October 2017 - April 2018. Patients of either gender aged 30-70 years presenting with headache were included. Patients already diagnosed and referred for follow up were excluded. MRI was performed on 1.5T scanner by a trained MRI technician. T1, T2, FLAIR, diffusion weighted and T1 post contrast images were acquired and reviewed by two radiologists having more than five years post fellowship experience. Sensitivity, specificity, PPV, NPV and diagnostic accuracy of MRI for intraaxial gliomas was calculated taking histopathology findings as gold standard.

Results:

Mean age of the patient`s was 51.71 ±10.85 years. Positive intraaxial gliomas on MRI were observed in 123 (79.90%) patients while on histopathology, positive intraaxial gliomas were observed in 131 (85.10%) patients. Diagnostic accuracy of MRI in detection of intra-axial gliomas taking histopathology findings as gold standard showed sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV) and overall diagnostic accuracy as 89.31%, 73.91%, 95.12%, 54.84% and 87.01%.

Conclusions:

MRI has high sensitivity, moderate specificity and high diagnostic accuracy in detection of intraaxial gliomas.

Comparison of Genetic Profiles and Prognosis of High-Grade Gliomas Using Quantitative and Qualitative MRI Features: A Focus on G3 Gliomas

Objective

To evaluate the association of MRI features with the major genomic profiles and prognosis of World Health Organization grade III (G3) gliomas compared with those of glioblastomas (GBMs).

Materials and Methods

We enrolled 76 G3 glioma and 155 GBM patients with pathologically confirmed disease who had pretreatment brain MRI and major genetic information of tumors. Qualitative and quantitative imaging features, including volumetrics and histogram parameters, such as normalized cerebral blood volume (nCBV), cerebral blood flow (nCBF), and apparent diffusion coefficient (nADC) were evaluated. The G3 gliomas were divided into three groups for the analysis: with this isocitrate dehydrogenase (IDH)-mutation, IDH mutation and a chromosome arm1p/19q-codeleted (IDHmut1p/19qdel), IDH mutation, 1p/19q-nondeleted (IDHmut1p/19qnondel), and IDH wildtype (IDHwt). A prediction model for the genetic profiles of G3 gliomas was developed and validated on a separate cohort. Both the quantitative and qualitative imaging parameters and progression-free survival (PFS) of G3 gliomas were compared and survival analysis was performed. Moreover, the imaging parameters and PFS between IDHwt G3 gliomas and GBMs were compared.

Results

IDHmut G3 gliomas showed a larger volume (p = 0.017), lower nCBF (p = 0.048), and higher nADC (p = 0.007) than IDHwt. Between the IDHmut tumors, IDHmut1p/19qdel G3 gliomas had higher nCBV (p = 0.024) and lower nADC (p = 0.002) than IDHmut1p/19qnondel G3 gliomas. Moreover, IDHmut1p/19qdel tumors had the best prognosis and IDHwt tumors had the worst prognosis among G3 gliomas (p < 0.001). PFS was significantly associated with the 95th percentile values of nCBV and nCBF in G3 gliomas. There was no significant difference in neither PFS nor imaging features between IDHwt G3 gliomas and IDHwt GBMs.

Conclusion

We found significant differences in MRI features, including volumetrics, CBV, and ADC, in G3 gliomas, according to IDH mutation and 1p/19q codeletion status, which can be utilized for the prediction of genomic profiles and the prognosis of G3 glioma patients. The MRI signatures and prognosis of IDHwt G3 gliomas tend to follow those of IDHwt GBMs.

Diffusion kurtosis imaging histogram parameter metrics predicting survival in integrated molecular subtypes of diffuse glioma: An observational cohort study

PURPOSE

The aim of the study was to assess the predictive value of preoperatively assessed diffusion kurtosis imaging (DKI) metrics as prognostic factors in the 2016 World Health Organization Classification of Tumors of the Central Nervous System integrated glioma groups.

MATERIAL AND METHODS

Seventy-seven patients with histopathologically confirmed treatment-naïve glioma were retrospectively assessed between 08/2013 and 10/2017 using mean kurtosis (MK) and mean diffusivity (MD) histogram parameters from DKI, overall and progression-free survival, and relevant prognostic molecular data (isocitrate dehydrogenase, [IDH]; alpha-thalassemia/mental retardation syndrome X-linked, [ATRX]; chromosome 1p/19q loss of heterozygosity). Receiver operating characteristic (ROC) analysis was performed on metric variables to determine the optimal cutoff-values. The Kaplan-Meier method was used to assess univariate survival data. A multivariate Cox proportional hazards model was performed on significant results from the univariate analysis.

RESULTS

There were significant differences in overall and progression-free survival between patient age (p = 0.001), resection statuses (p = 0.002), WHO glioma grades (p < 0.0001), and integrated molecular profiles (p < 0.0001). Survival was significantly better in patients with lower MK and higher MD values globally (p = 0.009), in gliomas without chromosome 1p/19q LOH (p < 0.0001), and those with retained ATRX expression (p = 0.008).

CONCLUSIONS

Patient age and MK from DKI from DKI are relevant factors for preoperatively predicting overall and progression-free survival. Regarding the molecular subgroups, they seem to be predictive in gliomas with ATRX retention, representing a feature of IDH wild-type gliomas.