Glioma, MalignantNCT05656053
Intraoperative Rapid Diagnosis of Glioma Based on Fusion of Magnetic Resonance and Ultrasound Imaging
An observational study of Glioma, Malignant and Computer-Assisted Surgery, run by Mingge LLC at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Glioma, Malignant, Computer-Assisted Surgery
- How many people
- 30 participants
- Where
- 1 siteChina
- Study dates
- 15 Nov 2021to Sep 2026
- How long will I take part?
- 3 Months
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
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.
Who may be able to join
- Age over 18 years old
- Tumor in non-functional areas of the cerebral hemisphere.
- Preoperative diagnosis of glioma.
- Undergo glioma removal surgery.
Who cannot join
- Postoperative confirmation of non-glioma.
- Magnetic resonance or ultrasound data not available.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Rapid Diagnosis of Molecular Biomarkers and Visualization of IDH Molecular Boundaries in Glioma Using Preoperative Magnetic Resonance Images, Intraoperative Ultrasound Signals and Intraoperative Ultrasound Images
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:
- 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.
- 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.
Participants will read an informed consent agreement before surgery and voluntarily decide whether or not to join the experimental group. they will undergo preoperative magnetic resonance imaging, intraoperative ultrasound, and postoperative genotype identification. Their imaging data, genotype data, clinical history data, and pathology data will be used for the experimental study. The data collection process will not interrupt the normal surgical process.
Read the detailed description
BACKGROUND:
The extent of glioma resection is directly related to patient survival, and a combination of multiple imaging and molecular pathology imaging methods has been developed to achieve maximum safe resection. In this study, three types of data, preoperative magnetic resonance imaging, intraoperative ultrasound and molecular genotype, will be collected and combined to build an artificial intelligence imaging model to achieve maximum safe resection and prolong patient's life.
PLAN:
In order to achieve the goal of maximum safe resection, we plan to sequentially implement imaging-based molecular visualization techniques, and integrated guidance techniques through a combination of intraoperative ultrasound and preoperative magnetic resonance imaging, in order to address the two critical scientific issues of glioma molecular boundary visualization and intraoperative real-time molecular diagnosis. It can also help neurosurgeons to achieve complete glioma resection at the molecular level, maximizing patient survival time and providing another effective approach to improving glioma treatment.
PROCESS:
Participants will read an informed consent agreement before surgery and voluntarily decide whether or not to join the experimental group. They will undergo preoperative magnetic resonance imaging and intraoperative ultrasound to obtain magnetic resonance images, ultrasound images, and ultrasound radio-frequency signals. After surgery, the patient's tumor tissue samples will undergo specialist genetic testing to obtain multiple molecular diagnostic results, such as isocitrate dehydrogenase (IDH), telomerase reverse transcriptase promoter (TERTp), the short arm chromosome 1 and the long arm of chromosome 19 (1p/19q), et al. Also, their imaging data, genotype data, clinical history data, and pathology data will be used for the experimental study.
The data collected from each patient will be performed in three steps as follows.
- Image translation and alignment of intraoperative ultrasound and preoperative MRI navigation across modalities for glioma.
- Multimodality imaging of IDH1/2 gene mutations from structural to molecular boundaries.
- Applied study of molecular boundary visualization. All the above information will be summarized and handed over to Fudan University to build an artificial intelligent model.
Compared with the previous gold standard glioma resection, this study adds intraoperative ultrasound, intraoperative multi-point tumor specimen sampling for IDH genotype identification during the surgery, and will collect relevant molecular imaging data, MRI data, intraoperative ultrasound data, clinical case data and pathology data from patients after the surgery. Intraoperative ultrasound is non-invasive, real-time and rapid, without adding additional operative time or risk of infection.
- Conditions
- Glioma, Malignant, Computer-Assisted Surgery
- Keywords
- Gliomas, Computer-Assisted Decision Making
- Medical subject headings
- Glioma
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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. |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: End of study (24 weeks)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Dec 2022
- Study start15 Nov 2021
- Primary completionSep 2025 (estimated)
- Study completionSep 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Glioma, MalignantStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 30 participants (actual)
- Target duration
- 3 Months
Sponsor and investigators
- Lead sponsor
- Mingge LLC
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Huashan Hospital, Fudan University
- Responsible party
- Sponsor
- Investigators
- Zhifeng Shi, DM, Study director, Huashan HospitalJinhua Yu, DE, Study chair, Fudan UniversityYinhui Deng, DE, Principal investigator, Fudan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05656053
- Sponsor's protocol ID
- MINGGE-SW-00002-V1-01
- Status last verified
- Mar 2023
- First submitted
- 9 Dec 2022
- Last updated
- 17 Mar 2023
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: All patient information collected by the Huashan Hospital will be kept strictly confidential. We will share the results and findings of the study with other researchers.
Publications
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.
PubMed 38041959
Study at a glance
From the registry record, last updated by the sponsor on 17 Mar 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Rapid Diagnosis of Molecular Biomarkers and Visualization of IDH Molecular Boundaries in Glioma Using Preoperative Magnetic Resonance Images, Intraoperative Ultrasound Signals and Intraoperative Ultrasound Images
- ClinicalTrials.gov ID
- NCT05656053
- Acronym / sponsor ID
- MINGGE-SW-00002-V1-01
- Conditions
- Glioma, Malignant, Computer-Assisted Surgery
- Keywords
- Gliomas, Computer-Assisted Decision Making
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 30 participants (actual)
- Lead sponsor
- Mingge LLCIndustry (pharma, biotech, devices)
- Collaborators
- Huashan Hospital, Fudan University
- Study start
- 15 Nov 2021 (actual)
- Primary completion
- Sep 2025 (estimated)
- Study completion
- Sep 2026 (estimated)
- First posted
- 19 Dec 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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:
- 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.
- 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.
Participants will read an informed consent agreement before surgery and voluntarily decide whether or not to join the experimental group. they will undergo preoperative magnetic resonance imaging, intraoperative ultrasound, and postoperative genotype identification. Their imaging data, genotype data, clinical history data, and pathology data will be used for the experimental study. The data collection process will not interrupt the normal surgical process.
Detailed description
BACKGROUND:
The extent of glioma resection is directly related to patient survival, and a combination of multiple imaging and molecular pathology imaging methods has been developed to achieve maximum safe resection. In this study, three types of data, preoperative magnetic resonance imaging, intraoperative ultrasound and molecular genotype, will be collected and combined to build an artificial intelligence imaging model to achieve maximum safe resection and prolong patient's life.
PLAN:
In order to achieve the goal of maximum safe resection, we plan to sequentially implement imaging-based molecular visualization techniques, and integrated guidance techniques through a combination of intraoperative ultrasound and preoperative magnetic resonance imaging, in order to address the two critical scientific issues of glioma molecular boundary visualization and intraoperative real-time molecular diagnosis. It can also help neurosurgeons to achieve complete glioma resection at the molecular level, maximizing patient survival time and providing another effective approach to improving glioma treatment.
PROCESS:
Participants will read an informed consent agreement before surgery and voluntarily decide whether or not to join the experimental group. They will undergo preoperative magnetic resonance imaging and intraoperative ultrasound to obtain magnetic resonance images, ultrasound images, and ultrasound radio-frequency signals. After surgery, the patient's tumor tissue samples will undergo specialist genetic testing to obtain multiple molecular diagnostic results, such as isocitrate dehydrogenase (IDH), telomerase reverse transcriptase promoter (TERTp), the short arm chromosome 1 and the long arm of chromosome 19 (1p/19q), et al. Also, their imaging data, genotype data, clinical history data, and pathology data will be used for the experimental study.
The data collected from each patient will be performed in three steps as follows.
- Image translation and alignment of intraoperative ultrasound and preoperative MRI navigation across modalities for glioma.
- Multimodality imaging of IDH1/2 gene mutations from structural to molecular boundaries.
- Applied study of molecular boundary visualization. All the above information will be summarized and handed over to Fudan University to build an artificial intelligent model.
Compared with the previous gold standard glioma resection, this study adds intraoperative ultrasound, intraoperative multi-point tumor specimen sampling for IDH genotype identification during the surgery, and will collect relevant molecular imaging data, MRI data, intraoperative ultrasound data, clinical case data and pathology data from patients after the surgery. Intraoperative ultrasound is non-invasive, real-time and rapid, without adding additional operative time or risk of infection.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Target follow-up
- 3 Months
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (4 listed)
- Age over 18 years old
- Tumor in non-functional areas of the cerebral hemisphere.
- Preoperative diagnosis of glioma.
- Undergo glioma removal surgery.
Key exclusion criteria (2 listed)
- Postoperative confirmation of non-glioma.
- Magnetic resonance or ultrasound data not available.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Accuracy rate, describing the number of correct people or correct regions predicted by the computer-aided algorithm as a proportion of the total sample.
Time frame: End of study (24 weeks)
The accuracy rate has a value between 0 and 1, with higher values indicating a more reliable system.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Mar 2023.
- Derived from this study: PubMed 38041959Xie 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.
- Individual participant dataSharing planned: No. All patient information collected by the Huashan Hospital will be kept strictly confidential. We will share the results and findings of the study with other researchers.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Zhifeng Shi, DM study director
Huashan Hospital
Jinhua Yu, DE study chair
Fudan University
Yinhui Deng, DE principal investigator
Fudan University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Glioma, Malignant and Computer-Assisted Surgery, run by Mingge LLC at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 17 Mar 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy rate, describing the number of correct people or correct regions predicted by the computer-aided algorithm as a proportion of the total sample. (time frame: End of study (24 weeks)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05656053, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Mar 2023; AzTrials last refreshed its copy on 8 Nov 2026.