MRI-based Computer Aided Diagnosis Software (V1) for Glioma

NCT05739500 | Unknown DMC

• 1 other identifier: MINGGE-SW-00001-V1-01
• Study Type: observational
• Target: 250
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this multi-center clinical trial is to evaluate the effectiveness of MRI-based computer-aided diagnosis software (V1) for glioma segmentation, gene prediction, and tumor grading. Machine learning methods such as high-precision tumor segmentation and classification and discrimination modeling can further optimize the non-invasive molecular diagnosis and prognosis prediction. The main question it aims to answer is whether the software can predict the molecular type and the prognosis quickly and correctly. The results will be compared with the real-world clinical data double-blindly. Finally, form a set of user-friendly automatic glioma diagnosis and treatment systems for clinics.

Conditions

Glioma; Primary Brain Tumor

Outcome Measures

Primary Outcomes (1)

• Accuracy rate

  describing the number of correct cases predicted by the software as a proportion of the total participants. The accuracy rate has a value between 0 and 1, with higher values indicating a more reliable tool.

  end of the study (one year after the surgery of the last participants).

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Preliminary diagnosis of glioma patients and patients who plan to undergo surgical treatment

You may qualify if:

• Age front 18 to 70 years old (not including threshold), gender is not limited;
• Preliminary diagnosis of glioma patients and patients who plan to undergo surgical treatment;
• Preoperative cranial MRI (T1, T2, T2 Flair, T1 enhanced GE company magnetic resonance package), tumor pathological examination (H\&E section, Kuoran Gene Company package), acceptable follow-up and brain MRI scan;
• The patient himself voluntarily participated and signed the informed consent in writing.

You may not qualify if:

• Patients who only underwent biopsy rather than surgical tumor resection;
• Postoperative pathologically confirmed non-glioma patients;
• Patients with multiple glioma metastases or multiple gliomas;
• Patients who died of complications in the early postoperative period;
• The researcher believes that this researcher should not be included.

Sponsors & Collaborators

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

Study Sites (1)

Zhen Fan

Shanghai, Shanghai Municipality, 200040, China

Location

Related Publications (4)

• Garcia CR, Slone SA, Dolecek TA, Huang B, Neltner JH, Villano JL. Primary central nervous system tumor treatment and survival in the United States, 2004-2015. J Neurooncol. 2019 Aug;144(1):179-191. doi: 10.1007/s11060-019-03218-8. Epub 2019 Jun 28.

  PMID: 31254264 BACKGROUND

• Reardon DA, Wen PY. Glioma in 2014: unravelling tumour heterogeneity-implications for therapy. Nat Rev Clin Oncol. 2015 Feb;12(2):69-70. doi: 10.1038/nrclinonc.2014.223. Epub 2015 Jan 6.

  PMID: 25560529 BACKGROUND

• Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016 Feb;278(2):563-77. doi: 10.1148/radiol.2015151169. Epub 2015 Nov 18.

  PMID: 26579733 BACKGROUND

• Yu J, Shi Z, Lian Y, Li Z, Liu T, Gao Y, Wang Y, Chen L, Mao Y. Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma. Eur Radiol. 2017 Aug;27(8):3509-3522. doi: 10.1007/s00330-016-4653-3. Epub 2016 Dec 21.

  PMID: 28004160 BACKGROUND

MeSH Terms

Conditions

Glioma; Brain Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms, Neuroepithelial; Neuroectodermal Tumors; Neoplasms, Germ Cell and Embryonal; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Neoplasms, Nerve Tissue; Central Nervous System Neoplasms; Nervous System Neoplasms; Neoplasms by Site; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases

Study Officials

• Zhifeng Shi, MD.

  Huashan Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CROSSOVER
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof.

Study Record Dates

• First Submitted: December 28, 2022
• First Posted: February 22, 2023
• Study Start: December 1, 2022
• Primary Completion: November 23, 2025
• Study Completion: December 31, 2025
• Last Updated: February 22, 2023

Record last verified: 2023-02

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)