Establishment and Evaluation of Multimodal Image Recognition System of Glioma Based on Deep Learning

NCT04407039 | Unknown FDA Device

• 1 other identifier: YXLL-KY-2020 (009)
• Study Type: observational
• Target: 350
• Locations: 0 countries
• Sites: N/A

Brief Summary

Research purposes:

1. 1.To obtain the metabolic characteristics of glioma molecular imaging through a multimodal image recognition system.
2. 2.To determine whether molecular imaging metabolic parameters can characterize the molecular typing of glioma by analyzing the relationship between metabolic parameters and tumor subtypes
3. 3.To get metabolic classification based on metabolic parameters of glioma molecular imaging, and to identify the relationship between metabolic subtypes and surgical resection, radiotherapy and chemotherapy, and prognosis and further refine the molecular classification of glioma.

Conditions

Glioma

Outcome Measures

Primary Outcomes (2)

• The data of multimodal image recognition system

  1. Cho (mmol/kg), Cr (mmol/kg), NAA (mmol/kg), Cho/Cr, Cho/NAA and NAA/Cr values Record the Cho (mmol/kg), Cr (mmol/kg), NAA (mmol/kg), Cho/Cr, Cho/NAA and NAA/Cr values in the lesion area, and calculate the ratio (relative reference value) to the metabolites of the healthy brain tissue area, namely r Cho, r Cr, r NAA, r Cho/Cr, r Cho/NAA and r NAA/Cr. 2. 18 F-FDG uptake values The uptake of 18 F-FDG was analyzed based on the anatomical morphology of the lesions provided by MRI images. Finally, according to the 18F-FDG uptake of the lesion, it is divided into 5 levels: level 1 is no intake, level 2 is slightly lower than the contralateral normal brain tissue, level 3 is similar to the contralateral normal brain tissue, and level 4 is the intake The degree is slightly higher than that of the contralateral normal brain tissue. Level 5 is the level of uptake significantly higher than that of the contralateral normal brain tissue.

  one week

• Molecular subsets in in diffuse gliomas

  (1) G-CIMP-low; (2) G-CIMP-high; (3) codel; (4) classic-like; (5) mesenchymal-like; (6) LGM6-GBM; (7) PA-like

  five months

Secondary Outcomes (1)

• Overall survival

  two years

Study Arms (7)

Glioma molecular subtype: G-CIMP-low

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: G-CIMP-high

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: codel

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: classic-like

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: mesenchymal-like

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: LGM6-GBM

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Glioma molecular subtype: PA-like

one of molecular subtypes according to gene expression, DNA copy number, DNA methylation, exome sequencing and protein expression of glioma

Device: PET/CT, H-MRS and MRI

Interventions

PET/CT, H-MRS and MRI DEVICE

Use imaging methods to get metabolic parameters.

Glioma molecular subtype: G-CIMP-high; Glioma molecular subtype: G-CIMP-low; Glioma molecular subtype: LGM6-GBM; Glioma molecular subtype: PA-like; Glioma molecular subtype: classic-like; Glioma molecular subtype: codel; Glioma molecular subtype: mesenchymal-like

Eligibility Criteria

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

Study Population

outpatients from Shandong Province Qianfoshan Hospital

You may qualify if:

• glioma patients confirmed by postoperatively pathology ;
• the lesion is non-diffuse, and the tumor body, edema and surrounding normal tissue are clearly delimited;
• capacity to give informed consent and follow study procedures.

You may not qualify if:

• patients with previous treatment of glioma;
• lack of clinical and image data or data inability to meet research needs;
• severe cardiac dysfunction: acute decompensated heart failure and/or chronic heart failure functional class III or IV (New York Heart Association classification);
• patients who gave up halfway

Sponsors & Collaborators

• Tao Xin: lead

Related Publications (4)

• Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J. Cancer statistics in China, 2015. CA Cancer J Clin. 2016 Mar-Apr;66(2):115-32. doi: 10.3322/caac.21338. Epub 2016 Jan 25.

  PMID: 26808342 BACKGROUND

• Ceccarelli M, Barthel FP, Malta TM, Sabedot TS, Salama SR, Murray BA, Morozova O, Newton Y, Radenbaugh A, Pagnotta SM, Anjum S, Wang J, Manyam G, Zoppoli P, Ling S, Rao AA, Grifford M, Cherniack AD, Zhang H, Poisson L, Carlotti CG Jr, Tirapelli DP, Rao A, Mikkelsen T, Lau CC, Yung WK, Rabadan R, Huse J, Brat DJ, Lehman NL, Barnholtz-Sloan JS, Zheng S, Hess K, Rao G, Meyerson M, Beroukhim R, Cooper L, Akbani R, Wrensch M, Haussler D, Aldape KD, Laird PW, Gutmann DH; TCGA Research Network; Noushmehr H, Iavarone A, Verhaak RG. Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma. Cell. 2016 Jan 28;164(3):550-63. doi: 10.1016/j.cell.2015.12.028.

  PMID: 26824661 BACKGROUND

• Chaumeil MM, Lupo JM, Ronen SM. Magnetic Resonance (MR) Metabolic Imaging in Glioma. Brain Pathol. 2015 Nov;25(6):769-80. doi: 10.1111/bpa.12310.

  PMID: 26526945 BACKGROUND

• la Fougere C, Suchorska B, Bartenstein P, Kreth FW, Tonn JC. Molecular imaging of gliomas with PET: opportunities and limitations. Neuro Oncol. 2011 Aug;13(8):806-19. doi: 10.1093/neuonc/nor054. Epub 2011 Jul 13.

  PMID: 21757446 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

DNA is extracted from frozen glioma tissues

MeSH Terms

Conditions

Glioma

Interventions

Positron Emission Tomography Computed Tomography

Condition Hierarchy (Ancestors)

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

Intervention Hierarchy (Ancestors)

Positron-Emission Tomography; Tomography, Emission-Computed; Image Interpretation, Computer-Assisted; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis; Tomography, X-Ray Computed; Multimodal Imaging; Radiographic Image Enhancement; Image Enhancement; Photography; Radiography; Tomography, X-Ray; Radionuclide Imaging; Tomography; Diagnostic Techniques, Radioisotope

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Director of Neurosurgery

Study Record Dates

• First Submitted: May 25, 2020
• First Posted: May 29, 2020
• Study Start: December 30, 2021
• Primary Completion: August 30, 2022
• Study Completion: December 30, 2022
• Last Updated: September 9, 2021

Record last verified: 2021-09