Clinical trial NCT03439332: Multicentre Validation of How Vascular Biomarkers From Tumor Can Predict the Survival of the Patient With Glioblastoma
Official title: Multicentre Validation of Hemodynamic Multiparametric Tissue Signature (MTS) Biomarkers From Preoperative and Postradiotherapy MRI in Patients With Glioblastoma: Predictors of Overall Survival
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Glioblastoma
Keywords: Highly infiltrative
Deeply invasive
Strong vascular proliferation
Robust angiogenesis
Vascular heterogeneity
Perfusion Biormarker
Non-Invasive Biomarker
Predictor of overall survival
Predictor of progression-free survival
Lead sponsor: Universitat Politècnica de València
Sponsor class: OTHER
Collaborators: name: University of Liege
name: Hospital de Manises
name: Hospital de la Ribera
name: Hospital Vall d'Hebron
name: Hospital Clinic of Barcelona
name: Azienda Ospedaliero-Universitaria di Parma
name: Oslo University Hospital
First posted: 2018-02-20
Enrollment: 305
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: CASE_ONLY
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The population of the target group is formed by patients diagnosed with Glioblastoma grade IV World Health Organization (WHO) with histopathological confirmation

Brief summary: Despite an aggressive therapeutic approach, the prognosis for most patients with glioblastoma (GBM) remains poor. The relationship between non-invasive Magnetic Resonance Imaging (MRI) biomarkers at preoperative, postradiotherapy and follow-up stages, and the survival time in GBM patients will be useful to plan an optimal strategy for the management of the disease.

The Hemodynamic Multiparametric Tissue Signature (HTS) biomarker 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. This allows to automatically draw 4 reproducible habitats that describe the tumor vascular heterogeneity:

* The High Angiogenic enhancing Tumor (HAT)
* The Less Angiogenic enhancing Tumor (LAT)
* The potentially tumor Infiltrated Peripheral Edema (IPE)
* The Vasogenic Peripheral Edema (VPE)

The conceptual hypothesis is that there is a significant correlation between the perfusion biomarkers located at several HTS habitats and the patient's overall survival.

The primary purpose of this clinical study is to determine if preoperative vascular heterogeneity of glioblastoma is predictive of overall survival of patients undergoing standard-of-care treatment by using the HTS biomarker.

Detailed description: This is a multicenter observational retrospective study with data collected from Hospital Information System (HIS) and Picture Archiving and Communication System (PACS) of each center involved in the study. The cohort is built with patients diagnosed with glioblastoma (GBM) with a Magnetic Resonance Imaging (MRI) pre-treatment since 1st of January of 2012 until the Study Start Date.

The main objective of the study is to determine if the habitats obtained by the Hemodynamic Multiparametric Tissue Signature (HTS) biomarker, which describe the tumor vascular heterogeneity of the enhancing tumor and edema areas, are predictive of the overall survival of patients undergoing standard-of-care treatment.

The specific objectives of the study are:

* To identify four habitats within the GBM using MRI and HTS
* To analyse the relation between the HTS habitats obtained from the first preoperative MRI and the overall survival of the patient
* To analyse the relation between HTS habitats obtained from the first preoperative MRI and the progression-free survival of the patient
* To analyse the relation between the HTS habitats obtained from the postradiotherapy MRI and the overall survival of the patient
* To analyse the relation between HTS habitats obtained from the postradiotherapy MRI and the progression-free survival of the patient
* To discover other interesting relations between the HTS habitats obtained from preoperative, postradiotherapy and follow-up images and the clinical conditions of the patients

Cox regression, Kaplan-Meier estimator and multiple linear regression analysis will be used to assess survival significance of each biomarker at each HTS habitat. The predictive value will be compared with models based on clinical and volumetric image variables: Age, Karnofsky Performance Status (KPS) Scale and Visually AcceSAble Rembrandt Images (VASARI) features. Moreover, the HTS-based models will be compared to models based on hemodynamic biomarkers, such as Cerebral Blood Flow (CBF), Cerebral Blood Volume (CBV), capillary permeability (Ktrans) and fractional Volume of Extravascular-Extracellular space (Ve), and diffusion biomarkers, such as Apparent Diffusion Coefficient (ADC), extracted from automatic segmentations of the edema and the enhancing tumor. Finally, Sørensen-Dice coefficient will be used to measure the correlation between MTS habitats in longitudinal studies.

Eligibility criteria: Inclusion Criteria:

* Patients diagnosed with Glioblastoma grade IV WHO with histopathological confirmation
* Age \>18 years at diagnosis
* Patients with access to the preoperative and postradiotherapy MRI studies using 1.5 Tesla (T) or 3T scanners, including: pre and post gadolinium T1-weighted MRI, T2-weighted MRI, FLAIR MRI, Dynamic Susceptibility Contrast (DSC) T2\*-weighted perfusion, Dynamic Contrast Enhancement (DCE) T1-weighted perfusion (optional) and Diffusion Weighted Imaging (DWI) (optional)
* WHO performance score between 0 and 2
* Patients with Karnofsky Performance Score (KPS) of ≥ 70%

Exclusion Criteria:

* Patients with congestive heart failure within 6 months prior to study entry (New York Heart Association ≥ Grade 3)
* Uncontrolled or significant cardiovascular disease, including: myocardial infarction and transient ischemic attack or stroke within 6 months prior to enrollment, uncontrolled angina within 6 months, diagnosed or suspected congenital long QT syndrome, any history of clinically significant ventricular arrhythmia (such as ventricular tachycardia, ventricular fibrillation or Torsades de pointes) and clinically significant abnormality on electrocardiogram (ECG)
* Pulmonary disease including or greater than grade 2 dyspnea or laryngeal edema, grade 3 pulmonary edema or pulmonary hypertension according to CTCAE 4.03

Primary outcomes:
measure: Correlation between overall survival (in days) of patients undergoing standard-of-care treatment and the tumor vascular heterogeneity described by the four habitats obtained by the Hemodynamic Multiparametric Tissue Signature (HTS) biomarker
timeFrame: From the date of the first MRI acquisition until the date of death from any cause, assessed up to 80 months
Secondary outcomes:
measure: Correlation between progression-free survival (in days) of patients undergoing standard-of-care treatment and the tumor vascular heterogeneity described by the four habitats obtained by the HTS biomarker
timeFrame: From the date of the first MRI acquisition until the date of first documented progression, assessed up to 80 months
measure: Correlation between MTS habitats in longitudinal studies
timeFrame: From the date of the first MRI acquisition until the date of death from any cause, assessed up to 80 months
Other outcomes:
Locations:
city: Valencia
country: Spain
facility: Universitat Politècnica de València
Study officials:
affiliation: Universitat Politècnica de València
name: Juan M Garcia Gomez, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Juan-Albarracin J, Fuster-Garcia E, Perez-Girbes A, Aparici-Robles F, Alberich-Bayarri A, Revert-Ventura A, Marti-Bonmati L, Garcia-Gomez JM. Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology. 2018 Jun;287(3):944-954. doi: 10.1148/radiol.2017170845. Epub 2018 Jan 19.
citation: Juan-Albarracin J, Fuster-Garcia E, Manjon JV, Robles M, Aparici F, Marti-Bonmati L, Garcia-Gomez JM. Automated glioblastoma segmentation based on a multiparametric structured unsupervised classification. PLoS One. 2015 May 15;10(5):e0125143. doi: 10.1371/journal.pone.0125143. eCollection 2015.
citation: Del Mar Alvarez-Torres M, Juan-Albarracin J, Fuster-Garcia E, Bellvis-Bataller F, Lorente D, Reynes G, Font de Mora J, Aparici-Robles F, Botella C, Munoz-Langa J, Faubel R, Asensio-Cuesta S, Garcia-Ferrando GA, Chelebian E, Auger C, Pineda J, Rovira A, Oleaga L, Molla-Olmos E, Revert AJ, Tshibanda L, Crisi G, Emblem KE, Martin D, Due-Tonnessen P, Meling TR, Filice S, Saez C, Garcia-Gomez JM. Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging. 2020 May;51(5):1478-1486. doi: 10.1002/jmri.26958. Epub 2019 Oct 26.