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Enhancing Lymphoma Diagnosis, Treatment, and Follow-Up Using 18F-FDG PET/CT Imaging: Contribution of Artificial
Setareh Hasanabadi1, Seyed Mahmud Reza Aghamiri1, Ahmad Ali Abin2
1Department of Medical Radiation Engineering, Shahid Beheshti University, Tehran 1983969411, Iran.
Artificial intelligence (AI) and radiomics show promise in analyzing 18F-FDG PET/CT scans for lymphoma management. Further trials are needed to confirm their reliability and standardize AI applications in nuclear medicine.
Area of Science:
- Nuclear Medicine
- Oncology
- Radiology
Background:
- Lymphoma diagnosis and management are complex due to its heterogeneity and mimicry of other conditions.
- Current molecular imaging like 18F-FDG PET/CT aids in lymphoma assessment but faces limitations.
- Identifying reliable biomarkers for lymphoma prognosis and treatment selection remains a challenge.
Purpose of the Study:
- To review the current literature on the application of artificial intelligence (AI) and radiomics using 18F-FDG PET/CT in lymphoma patient management.
- To explore the potential of AI and radiomics in overcoming challenges in lymphoma diagnosis, prognostication, and treatment response assessment.
Main Methods:
- Review of existing studies on AI and radiomics applied to 18F-FDG PET/CT in lymphoma.
- Analysis of how these technologies extract subtle imaging features for clinical insights.
- Synthesis of findings regarding the utility of AI and radiomics in various lymphoma management scenarios.
Main Results:
- Radiomics and AI can detect subtle imaging features in 18F-FDG PET/CT scans, potentially improving lymphoma assessment.
- These technologies offer new opportunities in nuclear medicine for lymphoma patients.
- The application of AI and radiomics shows promise across diverse clinical aspects of lymphoma management.
Conclusions:
- AI and radiomics hold significant promise for enhancing lymphoma management through advanced analysis of 18F-FDG PET/CT data.
- Standardization and validation through extensive prospective trials are crucial for widespread clinical adoption.
- The integration of AI and radiomics into nuclear medicine workflows could revolutionize lymphoma care.
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