Purpose: To systematically review evidence regarding the association of multiparametric
biomarkers with clinical outcomes and their capacity to explain relevant subcompartments
Materials and Methods: Scopus database was searched for original journal papers from January
1st, 2007 to February 20th, 2017 according to PRISMA. Four hundred forty-nine abstracts of papers
were reviewed and scored independently by two out of six authors. Based on those papers we
analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical
outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were
highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes.
Similarly, eighteen studies defining subcompartments within the tumor region were also
highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised
according to the QUADAS-2 criteria.
Results: It has been demonstrated that multi-parametric biomarkers are prepared for surrogating
diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular
profiling and response to treatment in gliomas. Quantifications and radiomics features obtained
from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion
(DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to
clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation,
mass effect and pseudo flush, relapse compartments, gross tumor volumes, and highrisk
regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences,
we found no evidence to assert that observed co-occurrences were significantly different
from their expected co-occurrences (Binomial test with False Discovery Rate correction,
α=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual
prevalence and trends in the literature.
Conclusion: Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI
exams have demonstrated their capability to predict clinical outcomes in different management
moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during
the last ten years, new multi-parametric MRI approaches have also been proposed to discover
specific subcompartments of the tumors. MR biomarkers from those subcompartments show the
local behavior within the heterogeneous tumor and may quantify the prognosis and response to
treatment of gliomas.