Can apparent diffusion coefficient predict the grade, genotype, or proliferation index of oligodendrogliomas

Laghari Ali; Khalid Usman; Mubarak Fatima; Alvi Amna; Ali Saeed; Shaikh Qadeer; Shamim Shahzad; Enam Ather

doi:10.4103/ajns.AJNS_520_20

Asian Journal of Neurosurgery, Table of Contents

CC BY-NC-ND 4.0 · Asian J Neurosurg 2021; 16(04): 752-758
DOI: 10.4103/ajns.AJNS_520_20

Original Article

Can apparent diffusion coefficient predict the grade, genotype, or proliferation index of oligodendrogliomas

Laghari Ali

Department of Surgery, Aga Khan University Hospital, Stadium Road, Karachi

,

Khalid Usman

Department of Surgery, Aga Khan University Hospital, Stadium Road, Karachi

,

Mubarak Fatima

¹Department of Radiology, Aga Khan University Hospital, Stadium Road, Karachi

,

Alvi Amna

¹Department of Radiology, Aga Khan University Hospital, Stadium Road, Karachi

,

Ali Saeed

²School of Nursing and Midwifery, The Aga Khan University, Karachi

,

Shaikh Qadeer

Department of Surgery, Aga Khan University Hospital, Stadium Road, Karachi

,

Shamim Shahzad

Department of Surgery, Aga Khan University Hospital, Stadium Road, Karachi

,

Enam Ather

Department of Surgery, Aga Khan University Hospital, Stadium Road, Karachi

› Author Affiliations

Abstract

Background: Genetic subsets of oligodendrogliomas (OD) have distinct chromosomal and biophysical profiles. Pretherapeutic tumor grade and genotype analysis is a challenging aspect of management, with 1p/19q codeletion status and grade of oligodendroglioma among the most important considerations for clinical decision making. Methodology: Seventy-three patients with histopathological diagnosis of oligodendroglioma were selected, and their preoperative 1.5T magnetic resonance imaging (MRI) scans were reviewed through parameters including diffusion weighted image, susceptibility-weighted imaging, and apparent diffusion coefficient (ADC). These images were correlated with patients' histopathological and chromosomal testing. Tumor border irregularity, homogeneity, contrast enhancement, and other MRI characteristics were also studied. For analysis, descriptive statistics were generated, and normality was evaluated for ADC value, age, and Ki-67 tumor proliferation index. Objectives: The study aimed to determine the correlation of ADC with Ki-67, grade, and 1p/19q co-deletion in oligodendroglioma at a tertiary care hospital within a low-middle income country. Results: Ki-67 tumor proliferation index was high in 33 tumors. It was found to be statistically significant (P = 0.048) with respect to ADC, showing that 1p/19q co-deleted tumors have a difference in their Ki-67 index. Ki-67 also showed a significant relationship (P < 0.05) with grade of OD. However, there was no statistically significant relationship between 1p19q chromosomal co-deletion and ADC. Linear regression was carried out as the data set was continuous. Univariate analysis showed no significant result with all P values above 0.10. Conclusion: Mean ADC is a viable tool to predict Ki-67 and assist prognostic clinical decisions. However, mean ADC alone cannot predict 1p/19q codeletion and tumor grades in OD. Further supplementation with other radiological modalities may provide greater yield and positive results.

Key-words:

Apparent diffusion coefficient - glioblastoma - magnetic resonance imaging

Full Text

References

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