High-grade glioma (HGG) are the most aggressive malignant primary brain tumor in adults
with a median survival rate of 12-15 months. It still carries a poor prognosis despite
aggressive treatment, which includes tumor resection followed by chemo-radiotherapy
cycles. The inter-patient and intra-patient tumor heterogeneity is one of the responsible
factors for the high aggressiveness of solid malignant tumors and their resistance
against effective therapies.
Due to the extremely complex and heterogeneous biology of this tumor, the same treatment
for all approach does not work well in this disease, and standard of care is not always
the best option, calling for precision medicine to select the best therapeutic option in
the right moment to each patient. This requires quantitative medical imaging, patient
profiling, prognosis estimation, and expected response to treatment for objective
decision making along with the patient management.
The Hemodynamic Tissue Signature (HTS) methodology, included in the ONCOhabitats site
(www.oncohabitats.upv.es), provides an automated unsupervised method to describe the
heterogeneity of the enhancing tumor and edema areas in terms of the angiogenic process
located at these regions. HTS considers 4 habitats within the tumour: 1) the HAT habitat,
which refers to the high angiogenic enhancing tumor part of the tumour, 2) the LAT
habitat, which refers to the less angiogenic enhancing tumor area of the tumour, 2) the
IPE habitat, which refers to the potentially infiltrated peripheral edema, and 4) the VPE
habitat, which refers to the vasogenic peripheral edema of the tumour (Juan-Albarracin et
al, 2016). Perfusion imaging markers, such as relative cerebral blood volume, can be
calculated from these different vascular habitats, and they have been proven as
clinically relevant for prognosis. The HTS methodology, as well as the prognostic
capacity of these perfusion imaging markers, have been validated with a retrospective
multicenter study that included 184 high-grade glioma patients from 7 European centers.
Furthermore, relevant associations have been found between the perfusion markers and
clinical-routine biomarkers, such as IDH mutation, MGMT methylation (Fuster-Garcia et al,
2020), molecular subtype or microvessel area.
Considering these promising results and, in order to develop a decision support system
based on pixel level Artificial Intelligent models for deciding treatment in high-grade
glioma, it is necessary to develop a prospective study and to validate at biological
level the vascular habitats defined by the HTS methodology.
The proposed objectives are based on the following hypothesis:
I. Since the tumor and edema HTS habitats (HAT, LAT, IPE and VPE) have been proven as
different in relation to their hemodynamic and vascular behavior, the main hypothesis are
that these are habitats are also significantly different at the vascular, tissular,
cellular and molecular level.
II. Significant associations between the perfusion imaging markers calculated with the
HTS methodology and both molecular and histopathological markers (useful in prognosis,
monitoring and evaluation of therapies) have been found in previous studies. Therefore,
the hypothesis are that relevant associations between the imaging markers and
clinical-routine biomarkers, such as molecular and histopathological markers, exist.
III. Preliminary studies have shown associations between the perfusion imaging markers
and molecular markers related with the immune action/suppression. In addition, previous
works have demonstrated that immune and genomic correlates of response to immunotherapy
treatments, such as anti-PD-1, in glioblastoma. Therefore, to find correlations between
these immune and genomic signatures with perfusion imaging markers can be useful for
decision making and evaluation of immunotherapies.
IV. Preliminary retrospective studies have demonstrated robust association between the
perfusion imaging markers calculated at high and low angiogenic habitats and patient
overall survival. These robust associations between the perfusion imaging markers and
survival times will be demonstrated with a prospective study.
