Non-invasive Evaluation of Lymphoma Patients Based on Artificial Intelligence and PET/MRI
- Conditions
- Follicular LymphomaLymphomaNon Hodgkin Lymphoma
- Interventions
- Diagnostic Test: PET/MR scan
- Registration Number
- NCT04154228
- Lead Sponsor
- Tel-Aviv Sourasky Medical Center
- Brief Summary
18F-FDG PET/MR imaging protocol integrating advanced MR vascular imaging sequences, along with computerized quantitative methods for data analysis, is expected to serve as an objective tool for assessment of lymphoma patients. The aim of this prospective study is to develop an automatic artificial intelligence-based tool for the assessment of early response to treatment and evaluation of residual masses in patients with lymphoma. Specific objectives are:
1. To evaluate the added value of 18F-FDG PET/MRI compared with PET/CT in imaging lymphoma.
2. To optimize PET/MR imaging protocol for lymphoma assessment.
3. To develop an automated tool for staging patients with lymphoma.
4. To develop an automated method for early prediction of response to therapy and prognosis in patients with lymphoma.
5. To develop an automated non-invasive tool for discriminating benign from active residual masses at end of treatment in patients with lymphoma.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 100
- patients with newly diagnosed hodgkin's, aggressive non-hodgkin's and follicular lymphoma (for whom the PET/CT is the imaging modality of choice)/
- Patients aged 18 years or older of both sexes.
- Patients treated at Tel-Aviv Sourasky Medical center.
- pregnancy,
- contraindication to MRI or to intravenous gadolinium injection.
Study & Design
- Study Type
- INTERVENTIONAL
- Study Design
- SINGLE_GROUP
- Arm && Interventions
Group Intervention Description Lymphoma Patients PET/MR scan -
- Primary Outcome Measures
Name Time Method Patients that preform 18F-FDG PET/MRI and the routinely PET/CT 1 year Patients that preform 18F-FDG PET/MRI and the routinely PET/CT, and the investigators optimize PET/MRI imaging protocol, and to develop an automated artificial intelligence-based tool for assessment of early response to treatment in patients with lymphoma.
- Secondary Outcome Measures
Name Time Method