Resumen de Characterization of vascular heterogeneity of astrocytomas grade 4 for supporting patient prognosis estimation, and treatment response assessment
Brain tumors are one of the most devastating diseases today because of the significant cognitive impairment suffered by patients, high mortality rates, and poor prognosis. Astrocytomas grade 4 bring five-year survival in approximately 5% of diagnosed patients, being the most aggressive and lethal tumors of the Central Nervous System (CNS).
Astrocytomas grade 4 continue to be an unresolved complex medical problem. Despite accounting for more than 60% of malignant brain tumors in adults, these tumors have a low relative prevalence and are considered an orphan disease, making difficult developing new drugs or treatments that might benefit patients.
The aggressiveness of these tumors is due to different characteristics, such as strong angiogenesis, necrosis, vascular microproliferation, the capacity of the tumor cells to invade and infiltrate, and a particular immune microenvironment. In addition, due to the rapid progression of astrocytomas grade 4, different specific regions coexist in the lesion area which change over time. This complex nature, along with the marked interpatient, intratumor, and longitudinal heterogeneity, makes complicate the success of a single efficient treatment for all patients.
Magnetic Resonance Imaging (MRI) represents a useful technique to characterize tumor morphology and vascularity. Using advanced and robust methods to analyze MR images collected from initial stages of patient management allows the delineation of different regions of astrocytomas grade 4, becoming useful tools for researchers, radiologists and neurosurgeons. In addition, the calculation of imaging vascular biomarkers, such as those proposed in this thesis, would facilitate tumor characterization, prognosis estimation and more personalized treatment approaches.
This thesis proposes four fundamental pillars to advance the management of astrocytomas grade 4. These include I) the multilevel characterization of the tumor to improve classifications of high-grade CNS gliomas; II) the search and development of robust biomarkers for estimating patient prognosis from the presurgical moment; III) as well as for evaluating the response to treatments and the selection of patients who may benefit from specific therapies; and IV) the design and implementation of clinical studies and protocols for long-term collecting data from internationally remarkable cohorts of patients.
To address these four pillars, an interdisciplinary approach has been used that combines medical imaging analysis, advanced artificial intelligence techniques, and molecular, histopathological, and clinical variables.
Concluding, we have addressed the influence of both interpatient and intratumor heterogeneity of astrocytoma grade 4 for tumor characterization and classification, patient prognosis estimation and predicting treatment responses. In addition, different clinical studies have been designed and implemented allowing the collection of multilevel data from international cohorts of patients with astrocytoma grade 4.
