1
|
Cheng Z, Du Y, Yu L, Yuan Z, Tian J. Application of Noninvasive Imaging to Combined Immune Checkpoint Inhibitors for Breast Cancer: Facts and Future. Mol Imaging Biol 2022; 24:264-279. [PMID: 35102468 DOI: 10.1007/s11307-021-01688-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 11/13/2021] [Accepted: 11/24/2021] [Indexed: 12/19/2022]
Abstract
With the application of mono-immunotherapy in cancer, particularly immune checkpoint inhibitors, improved outcomes have been achieved. However, there are several limitations to immunotherapy, such as a poor response to the drugs, immune resistance, and immune-related adverse events. In recent years, studies of preclinical animal models and clinical trials have demonstrated that immune checkpoint inhibitors for breast cancer can significantly prolong the overall survival and quality of patients' lives. Meanwhile, combined immune checkpoint inhibitor treatment has attracted researchers' attention and showed great potential in the comprehensive treatment of breast cancer patients. Additionally, noninvasive imaging enables physicians to predict response to combined immunotherapeutic drugs, achieve treatment efficacy, and lead to better clinical management. Herein, we review the background of combined immune checkpoint inhibitor therapy and summarize its targeted imaging as well as progress in noninvasive imaging aimed at evaluating therapeutic outcomes. Finally, we describe several factors that may influence the outcome of this combined immunotherapy, the future direction of medical imaging, and the potential application of artificial intelligence in breast cancer. With further development of noninvasive imaging for the guidance of combined immune checkpoint inhibitors, cures for this disease may be achieved.
Collapse
Affiliation(s)
- Zhongquan Cheng
- Department of General Surgery, Capital Medical University, Beijing Friendship Hospital, Beijing, 100050, China
- CAS Key Laboratory of Molecular Imaging, Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Sciences, BeijingBeijing, 100190, China
| | - Yang Du
- CAS Key Laboratory of Molecular Imaging, Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Sciences, BeijingBeijing, 100190, China.
- University of Chinese Academy of Sciences, Beijing, 100080, China.
| | - Leyi Yu
- Department of General Surgery, Capital Medical University, Beijing Friendship Hospital, Beijing, 100050, China
| | - Zhu Yuan
- Department of General Surgery, Capital Medical University, Beijing Friendship Hospital, Beijing, 100050, China.
| | - Jie Tian
- CAS Key Laboratory of Molecular Imaging, Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex System, Institute of Automation, Chinese Academy of Sciences, BeijingBeijing, 100190, China.
- University of Chinese Academy of Sciences, Beijing, 100080, China.
- Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine Science and Engineering, Beihang University, Beijing, 100191, China.
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi, 710071, China.
| |
Collapse
|
2
|
Sathekge MM, Bouchelouche K. Letter from the Editors. Semin Nucl Med 2019; 49:337-338. [PMID: 31470929 DOI: 10.1053/j.semnuclmed.2019.06.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
|