Introduction

Grade II and III glioma comprises of most common histologic subtypes such as astrocytoma (AT) and oligodendroglioma (OD). The prognosis of AT and OD are different. Accurate determination of tumor and its subtype in patients is therefore clinically relevant. The histopathology is the current reference standard for glioma grading. In the context of a shift towards histological and molecular markers in classifying subtype of AT and OD, a reappraisal of noninvasive imaging biomarkers is warranted. Previous reported studies1,2 have evaluated conventional MRI features such as calcifications, cortical involvement, hemorrhage, location and T2/FLAIR mismatch in differentiating OD’s from AT’s. Despite the identification of several characteristic features, MR imaging is not sufficiently specific for differentiation between glioma subtypes. Dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast-enhanced (DSC) perfusion MRI have been extensively used to characterize the tumor on the basis of tumor biology and the degree of neoangiogenesis3,4. A Few studies have reported the usefulness of DSC-perfusion MRI in differentiating OD from AT based on relative CBV (rCBV) values5,6. On the other hand, a recent study has reported that DSC perfusion MRI shows no change in relative CBV (rCBV) whereas, DCE-derived kinetic parameters especially Ktrans, Kep and Ve showed higher values in OD than AT of similar grades7. However, these studies are limited to small number of patients and have demonstrated inconsistent results. To the best our knowledge, the comparative evaluation of OD and AT with similar grades in large participants is still limited. The present study is designed to compare perfusion parameter and conventional MRI features in large histological proven participants across similar grades of OD and AT to look for any differentiating biomarkers.

Materials and Methods

In the current study, 79 patients were included (51 men, 28 women; mean age= 34.7; age range=03-69 years). Patients were classified into two groups: OD group (n=40; grade II, n=17; grade III, n=23; mean-age=37 years, age range=13-61 years) and AT group (n=39; grade II, n=08; grade III, n=31; mean-age=32.5 years, age range=03-69 years) with tumor histopathological characterization done using WHO 2016 classification. Conventional MRI and T1-perfusion MRI was performed at 3.0T MRI (Philips Health Systems, the Netherlands) with 15 channel head coil. Structural MRI of the brain included T2-W, T1-W, 3D-fluid attenuated inversion recovery (FLAIR), pre-contrast 2D T1-W and susceptibility-weighted imaging (SWI) sequences. 12 slices for T1-W and dual PD-T2-W images were obtained which covered the entire tumor. DCE perfusion imaging was performed using a T1-fast field echo (T1-FFE) sequence (TR/TE= 4.45/2.01ms; FA=10 degree; slice thickness=6 mm; FOV= 240 × 240 mm2; acquisition matrix size = 128x128). A series of 384 images, 32-time points for each of the 12 slices, with a temporal resolution of 3.9 sec with total dynamic acquisition time of 2 min and 7 seconds was acquired followed by acquisition of a Post-contrast 3D T1-W turbo spin echo (TSE) sequence. Two experienced radiologists evaluated the conventional MRI features in all the patients. The T1-perfusion MRI data analysis was done using in-house built Matlab programs (MathWorks, Natick, MA). Briefly, data analysis comprises of the following steps: 1) Quantification of T1 perfusion parameters (CBF_NormWM, CBV_NormWM_corr, Ktrans, Ve, Vp). 2) Extraction of tumor subparts (contrast enhancing, necrosis, SVM classifier based non-enhancing and vasogenic edema). 3) Statistical analysis of features from selected ROIs8.

Results

The comparison of the conventional MRI features between the OD and AT of similar grades is summarized in (Table 1). The OD’s showed higher prevalence of intratumoral calcifications, higher cortex involvement and haemorrhage than the AT’s. T2/FLAIR mismatch was slightly higher in AT’s as compared to OD’s. Figure 1 depicts an atypical example from one of the AT’s cases. Statistical analysis was performed on the perfusion parameters using SPSS 16.0 software. Student T test analysis showed no significant differences across the similar grades of OD and AT, on all the perfusion and kinetic parameters. However, there was a tendency towards higher values in AT than OD in almost all the parameters except Ktrans (Table 2). The OD group (grade II+III) and AT group (grade II+III) demonstrated no significant differences between any of the perfusion parameters (Table 2).

Discussion and Conclusion

In our study the characteristic conventional imaging findings, such as the higher cortex involvement, presence of calcification, hemorrhage and T2/FLAIR mismatch could not clearly differentiate similar grades of OD and AT. T1-perfusion based DCE-MRI imaging also showed no significant difference in all the perfusion parameters across the similar grades of OD and AT. In this study the mean rCBVmax values of AT’s were higher as compared to OD’s across similar grades. This finding is in disagreement with a report by Saito et al.9, which showed that the mean rCBVmax of AT was significantly lower than that of OD. We assumed that this discrepancy could be because of the T2* based DSC perfusion MRI technique used in this study which is known to overestimate the rCBV values in the presence of increased calcification and hemorrhage that is more commonly seen in OD10. Our results suggest that even with advanced MR imaging techniques the image biomarkers for differentiation and grading of OD and AT subtypes in large data remain elusive.

Acknowledgements

No acknowledgement found.

References

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