Page 52 - Read Online

Dasgupta et al. J Transl Genet Genom 2018;2:15. I https://doi.org/10.20517/jtgg.2018.21 Page 13 of 15
[7]
in the 2016 update of the WHO classification for an integrated diagnosis of medulloblastoma should ensure
widespread adoption of a practical IHC-based classification in routine clinical practice. While this IHC-
[13]
based classification identifies WNT and SHH subgroups with high accuracy, it cannot reliably discriminate
between group 3 and 4 tumors which are classified collectively as non-WNT/non-SHH medulloblastoma,
with differing prognosis. Imaging characteristics (contrast-enhancement of primary tumor and location,
morphology, and pattern of metastatic disease) can further help subclassify non-WNT/non-SHH group
into group 3 and group 4 tumors with high accuracy [29,30] .

Novel insights in the presence of significant heterogeneity within individual molecular subgroups has
prompted further subclassification of medulloblastoma [42,43] which is going to be very difficult to be matched
even with advanced contemporary imaging methods. Apart from identifying molecular subgroups, imaging
biomarkers may serve as putative predictive and prognostic factors in medulloblastoma. The presence
of homogenous contrast uptake (WNT-subgroup) may imply uniform disruption of blood-brain barrier
leading to better CNS penetration of systemic agents and resultant responsiveness to chemotherapy. Other
radiological features have already been reported to be associated with outcomes, e.g., bright enhancement in
non-WNT/non-SHH tumors is associated with poor overall survival, while superiorly located SHH-subgroup
tumors are associated with higher risk of local recurrence. The advent of deep machine-learning (supervised/
unsupervised) techniques and convoluted artificial neural networks should provide unique opportunities to
further improve the accuracy of such radiogenomic correlation and prediction [44,45] .

CONCLUSION
Medulloblastoma is a heterogeneous disease comprising four molecular subgroups with distinct
developmental origins, unique transcriptional profiles, diverse phenotypes, and varying clinical outcomes.
It has been increasingly recognized that imaging is useful not only for diagnosis and staging, but also may
be a reflection of underlying disease biology. The systematic assessment and correlation of imaging features
with molecular subgrouping in medulloblastoma are increasingly being reported with potential to serve as
independent predictive and prognostic biomarkers in contemporary neuro-oncologic practice.

DECLARATIONS
Authors’ contributions
Literature search and manuscript writing: Dasgupta A, Gupta T

Availability of data and materials
Not applicable.

Financial support and sponsorship
None.

Conflicts of interest
All authors declared that there are no conflicts of interest.

Ethical approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Copyright
© The Author(s) 2018.