Study on Multimodal Imaging and Molecular Imaging Techniques in Degenerative Dementia

Last updated: July 30, 2024
Sponsor: Ruijin Hospital
Overall Status: Active - Recruiting

Phase

N/A

Condition

Dementia

Treatment

N/A

Clinical Study ID

NCT06534658
BP-MIMI
  • Ages 50-85
  • All Genders

Study Summary

This project is a multicenter observational study that establishes a longitudinal cohort of patients with Alzheimer's disease and other dementias based on neuroimaging, molecular imaging, biological and digital markers to explore new solutions such as dementia disease mechanism, diagnosis, condition evaluation, and prognosis assessment.

Eligibility Criteria

Inclusion

Inclusion Criteria:

  • Patients aged ≥50 and ≤85 years old, male or female;

  • Meet the diagnostic criteria for dementia or MCI;

  • Neuropsychological score: MMSE 15-28 points, CDR ≤ 1 point; ④ Patients and theirfamilies are informed and sign the informed consent form

Exclusion

Exclusion Criteria:

  • The presence of other neurological diseases that may cause brain dysfunction (suchas depression, brain tumors, Parkinson's disease, metabolic encephalopathy,encephalitis, multiple sclerosis, epilepsy, brain trauma, normal intracranialpressure hydrocephalus, etc.);

  • The presence of other systemic diseases that may cause cognitive impairment (such asliver dysfunction, renal dysfunction, thyroid dysfunction, severe anemia, folic acidor vitamin B12 deficiency, syphilis, HIV infection, alcohol and drug abuse, etc.);

  • Suffering from a disease that makes it impossible to cooperate with cognitiveexaminations;

  • The presence of contraindications to MRI;

  • The presence of mental and neurological retardation;

  • Refusing to draw blood;

  • Refusing to sign the informed consent form.

Study Design

Total Participants: 1000
Study Start date:
July 30, 2020
Estimated Completion Date:
August 30, 2029

Study Description

This project will build a longitudinal database based on multimodal MRI imaging information of dementia subjects, various body fluid or digital markers, and a cohort. The convolutional neural network algorithm will be used to explore the imaging characteristics of healthy controls, AD, FTD, and DLB, develop an early prediction model for degenerative dementia, and achieve early differential diagnosis of different dementia subtypes. This study further performed GE180, ASEM, and exendin-4 radionuclide imaging on some subjects who completed conventional PET (AV45, Tauvir, and FDG) imaging to explore the diagnostic efficacy of these three probes as new diagnostic probes for early AD. In addition, through longitudinal follow-up of Aβ-positive MCI patients, multimodal MRI and PET image fusion technology were used to explore the changes in fused images during their conversion to AD in order to obtain early and accurate diagnostic markers.

Connect with a study center

  • Chinese People's Liberation Army General Hospital

    Beijing, Beijing
    China

    Active - Recruiting

  • First Affiliated Hospital of Zhejiang University School of Medicine

    Hanzhong, Hangzhou
    China

    Active - Recruiting

  • Cangzhou Hospital of Integrated Traditional Chinese and Western Medicine

    Cangzhou, Hebei
    China

    Active - Recruiting

  • The Second Hospital of Hebei Medical University

    Shijiazhuang, Hebei
    China

    Active - Recruiting

  • Qilu Hospital of Shandong University, Qingdao Branch

    Qingdao, Shandong
    China

    Active - Recruiting

  • Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

    Shanghai, Shanghai 200025
    China

    Active - Recruiting

  • Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine

    Shanghai, Shanghai 200025
    China

    Active - Recruiting

  • The First Affiliated Hospital of China Medical University

    Shenyang, Shenyang
    China

    Active - Recruiting

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