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.
