Brain Tumor Intraoperative Ultrasound Database

Glioblastoma Clinical Trial

— BraTioUS-DB  

Official title:

Predicting Overall Survival in Glioblastomas Using Radiomic Features of Intraoperative Ultrasound. A Proposal for the Creation of an International Database of Brain Tumor Ultrasound Images

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05062772
• Other study ID #: 21-PI085
• Status: Recruiting
• Start date: May 25, 2022
• Est. completion date: December 30, 2023

Study information

• Verified date: May 2023
• Source: Hospital del Río Hortega
• Contact: Santiago Cepeda, MD, PhD
• Phone: +34651035158
• Email: scepedac[@]saludcastillayleon.es
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

Predicting the survival of patients diagnosed with glioblastoma (GBM) is essential to guide surgical strategy and subsequent adjuvant therapies. Intraoperative ultrasound (ioUS) is a low-cost, versatile technique available in most neurosurgical departments. The images from ioUS contain biological information possibly correlated to the tumor's behavior, aggressiveness, and oncological outcomes. Today's advanced image processing techniques require a large amount of data. Therefore, the investigators propose creating an international database aimed to share intraoperative ultrasound images of brain tumors. The acquired data must be processed to extract radiomic or texture characteristics from ioUS images. The rationale is that ultrasound images contain much more information than the human eye can process. Our main objective is to find a relationship between these imaging characteristics and overall survival (OS) in GBM. The predictive models elaborated from this imaging technique will complement those already based on other sources such as magnetic resonance imaging (MRI), genetic and molecular analysis, etc. Predicting survival using an intraoperative imaging technique affordable for most hospitals would greatly benefit the patients' management.

Description:

The investigators plan to carry out a multicentre retrospective study of patients operated with GBM diagnosis between January 2018 and January 2020, in order to set the base for future prospective collection of patients. All cases with an ioUS study will be included. All patients must count with B-mode modality. After an pseudonymization process, the images will be uploaded to a private cloud server. Demographic, clinical, conventional radiological, and molecular variables (IDH, MGMT) will also be collected. OS will be defined as the time elapsed between the histopathological diagnosis and the patient's death. The acquired data must be processed to obtain a series of radiomic markers to perform the study. A pre-processing stage will be necessary (noise cleaning, despeckling, intensity normalization, filtering) to calculate radiomics measurements (histogram, volumetric, shape, texture, etc.). In the previous stage, a very high number of radiological features per subject will be calculated. Because the number of features is much higher than the data set, to avoid the curse of dimensionality, it will be necessary to reduce their number using feature selection and extraction techniques (standard in pattern recognition and radiomics) that allow choosing those characteristics (or transformations of them) that have greater discriminating power. A predictive model of survival will then be elaborated based on the features selected.

Hypotheses

Intraoperative ultrasound images in B-mode harbour tumor texture features correlated with overall survival in glioblastomas.

Objectives:

• To determine the relationship between the radiomic features of intraoperative ultrasound B-mode and overall survival in glioblastomas.

• Develop a predictive survival model using the texture features with the highest discriminatory power.

• Validate the model against an external dataset and compare it with currently available predictive models.

• Build a data set that allows exploring various image harmonization techniques that allow the reproducibility of our predictions.

• Establish an international cooperation network (BraTioUS-DB) whose objective will be to interchange ultrasound images and clinical data of patients operated on for a brain tumor prospectively from its creation and start-up.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 100
• Est. completion date: December 30, 2023
• Est. primary completion date: August 30, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 15 Years and older

Eligibility

Inclusion Criteria:

• Adult patients operated between January 2018 and January 2020 with a pathological diagnosis of WHO grade IV astrocytoma (Glioblastoma).

• Intraoperative ultrasound study that includes B-mode images

Exclusion Criteria:

• Other histopathological diagnoses. Even though the international database will be established in such a way that other tumor types can be included prospectively.

• Artifacts in ultrasound images that make their analysis impossible

• Stereotactic biopsies.

Related Conditions & MeSH terms

• Brain Cancer
• Brain Neoplasms
• Brain Tumor
• Glioblastoma
• Glioma

Intervention

Diagnostic Test:
• Ultrasound
Intraoperative ultrasound imaging

Locations

Country	Name	City	State
India	Tata Memorial Centre	Mumbai	Parel
Italy	Fondazione Irccs Istituto Neurologico "Carlo Besta"	Milan
Italy	Unit of Neurosurgery, Department of Biomedicine Neurosciences and Advanced Diagnsotics, University of Palermo	Palermo
Spain	University Hospital Rio Hortega	Valladolid

Sponsors (1)

Lead Sponsor	Collaborator
Hospital del Río Hortega

Countries where clinical trial is conducted

India,  Italy,  Spain, 

References & Publications (7)

Cepeda S, Arrese I, Garcia-Garcia S, Velasco-Casares M, Escudero-Caro T, Zamora T, Sarabia R. Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers. World Neurosurg. 2021 Feb;146:e1147-e1159. doi: 10.1016/j.wneu.2020.11.113. Epub 2020 Nov 28. — View Citation

Cepeda S, Barrena C, Arrese I, Fernandez-Perez G, Sarabia R. Intraoperative Ultrasonographic Elastography: A Semi-Quantitative Analysis of Brain Tumor Elasticity Patterns and Peritumoral Region. World Neurosurg. 2020 Mar;135:e258-e270. doi: 10.1016/j.wneu.2019.11.133. Epub 2019 Nov 30. — View Citation

Cepeda S, Garcia-Garcia S, Arrese I, Fernandez-Perez G, Velasco-Casares M, Fajardo-Puentes M, Zamora T, Sarabia R. Comparison of Intraoperative Ultrasound B-Mode and Strain Elastography for the Differentiation of Glioblastomas From Solitary Brain Metastases. An Automated Deep Learning Approach for Image Analysis. Front Oncol. 2021 Feb 2;10:590756. doi: 10.3389/fonc.2020.590756. eCollection 2020. — View Citation

Cepeda S, Garcia-Garcia S, Arrese I, Velasco-Casares M, Sarabia R. Acute changes in diffusion tensor-derived metrics and its correlation with the motor outcome in gliomas adjacent to the corticospinal tract. Surg Neurol Int. 2021 Feb 10;12:51. doi: 10.25259/SNI_862_2020. eCollection 2021. — View Citation

Cepeda S, Garcia-Garcia S, Arrese I, Velasco-Casares M, Sarabia R. Relationship between the overall survival in glioblastomas and the radiomic features of intraoperative ultrasound: a feasibility study. J Ultrasound. 2022 Mar;25(1):121-128. doi: 10.1007/s40477-021-00569-9. Epub 2021 Feb 16. — View Citation

Cepeda S, Garcia-Garcia S, Velasco-Casares M, Fernandez-Perez G, Zamora T, Arrese I, Sarabia R. Is There a Relationship between the Elasticity of Brain Tumors, Changes in Diffusion Tensor Imaging, and Histological Findings? A Pilot Study Using Intraoperative Ultrasound Elastography. Brain Sci. 2021 Feb 21;11(2):271. doi: 10.3390/brainsci11020271. — View Citation

Cepeda S, Sarabia R. Letter to the Editor. Intraoperative ultrasound elastography applied in meningioma surgery. Neurosurg Focus. 2021 May;50(5):E23. doi: 10.3171/2021.1.FOCUS2115. No abstract available. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Overall survival	Overall survival in glioblastoma	1 year

External Links

•   Institution Website