Progress in imaging and artificial intelligence in the quantitative assessment of multiple myeloma
10.3760/cma.j.cn431274-20240508-00759
- VernacularTitle:影像学和人工智能在多发性骨髓瘤定量评估中的研究进展
- Author:
Yongshun LIU
1
;
Wenpeng HUANG
;
Zhaonan SUN
Author Information
1. 北京大学第一医院医学影像科，北京 100034
- Publication Type:Journal Article
- Keywords:
Multiple myeloma;
Artificial intelligence;
Computed tomography;
Magnetic resonance imaging;
Positron emission tomography
- From:
Journal of Chinese Physician
2025;27(5):795-800
- CountryChina
- Language:Chinese
-
Abstract:
Multiple myeloma (MM) is a malignant blood disease, but there have been significant improvements in the prognosis due to advancements in quantitative assessment, immunotherapy, and targeted therapy in recent years. The quantitative assessment of MM bone marrow infiltration and prognosis prediction is influenced by imaging and artificial intelligence (AI) quantitative parameters. At present, the primary imaging methods include computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET). These methods are now crucial for diagnosing MM and evaluating myeloma cell infiltration, extramedullary disease, treatment effectiveness, and prognosis. In addition, the utilization of AI, especially in combination with machine learning and radiomics, has shown great potential in diagnosing and distinguishing MM from solubility transfer. This review discusses the advancements in imaging methods, including CT, MRI, and PET, as well as AI for quantitatively assessing MM. We have summarized the key concepts, advantages, limitations, and diagnostic performance of each technology. Finally, we discussed the challenges related to clinical implementation and presented our views on advancing this field, with the aim of providing guidance for clinical research.
