Intraoperative Rapid Diagnosis of Glioma Based on Fusion of Magnetic Resonance and Ultrasound Imaging

NCT05656053 | Active Not Recruiting

• 1 other identifier: MINGGE-SW-00002-V1-01
• Study Type: observational
• Target: 30
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of this observational study is to enable rapid diagnosis of molecular biomarkers in patients during surgery by medical imaging and artificial intelligence models, to help clinicians with strategies to maximize safe resection of gliomas. The main questions it aims to answer are:

1. 1.To solve the current clinical shortcomings of intraoperative molecular diagnosis, which is time-consuming and complex, and enables rapid and automated molecular diagnosis of glioma, thus providing the possibility of personalized tumor resection plans.
2. 2.To implement a neuro-navigation platform that combines preoperative magnetic resonance images, intraoperative ultrasound signals and intraoperative ultrasound images to address real-time molecular boundary visualisation and molecular diagnosis for glioma, providing an approach to improve glioma treatment.

Conditions

Glioma, Malignant; Computer-Assisted Surgery

Keywords

Gliomas; Computer-Assisted Decision Making

Outcome Measures

Primary Outcomes (1)

• Accuracy rate, describing the number of correct people or correct regions predicted by the computer-aided algorithm as a proportion of the total sample.

  The accuracy rate has a value between 0 and 1, with higher values indicating a more reliable system.

  End of study (24 weeks)

Study Arms (1)

Patients undergoing glioma removal surgery

Patients will undergo magnetic resonance examination before surgery, followed by rapid ultrasound acquisition of the tumor section by the surgeon during surgery and the resection of the tumor tissue for cryopreservation. After surgery, the tissue sample will be used for genetic sequencing and mass spectrometry to obtain molecular information. The data involved in the overall surgical procedure will be saved and used in this observational study.

Eligibility Criteria

• Age: 18 Years - 80 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All enrolled cases were collected and saved from Huashan Hospital of Fudan University, Shanghai, China. There was no restriction of data in terms of region, age, or gender, and only their diagnostic results and data quality were considered to meet the requirements.

You may qualify if:

• Age over 18 years old
• Tumor in non-functional areas of the cerebral hemisphere.
• Preoperative diagnosis of glioma.
• Undergo glioma removal surgery.

You may not qualify if:

• Postoperative confirmation of non-glioma.
• Magnetic resonance or ultrasound data not available.

Sponsors & Collaborators

• Mingge LLC: lead
• Huashan Hospital: collaborator
• Fudan University: collaborator

Study Sites (1)

Fudan University

Shanghai, Shanghai Municipality, 200433, China

Location

Related Publications (1)

• Xie X, Shen C, Zhang X, Wu G, Yang B, Qi Z, Tang Q, Wang Y, Ding H, Shi Z, Yu J. Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning. EBioMedicine. 2023 Dec;98:104899. doi: 10.1016/j.ebiom.2023.104899. Epub 2023 Dec 2.

  PMID: 38041959 DERIVED

Biospecimen

Retention: SAMPLES WITH DNA

tissue

MeSH Terms

Conditions

Glioma

Condition Hierarchy (Ancestors)

Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Nerve Tissue

Study Officials

• Zhifeng Shi, DM

  Huashan Hospital

  STUDY DIRECTOR

• Jinhua Yu, DE

  Fudan University

  STUDY CHAIR

• Yinhui Deng, DE

  Fudan University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 3 Months
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 9, 2022
• First Posted: December 19, 2022
• Study Start: November 15, 2021
• Primary Completion: September 1, 2025
• Study Completion (Estimated): September 1, 2026
• Last Updated: March 17, 2023

Record last verified: 2023-03

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)