The progress of magnetic resonance imaging in predicting biomarkers of ovarian cancer

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ZHOU Hongyu BAO Haihua WEN Shengbao WANG Yu ZHAO Yalong ZHANG Zixuan

ZHOU H Y, BAO H H, WEN S B, et al. The progress of magnetic resonance imaging in predicting biomarkers of ovarian cancer[J]. Chin J Magn Reson Imaging, 2023, 14(9): 171-175, 191. DOI:10.12015/issn.1674-8034.2023.09.031.

Abstract

[Abstract] Ovarian cancer has an insidious onset, low early diagnosis rate and poor prognosis. The discovery of biomarkers is increasingly important for the treatment monitoring and guidance of targeted drug use in ovarian cancer, but most of them are invasive. MRI technology, such as diffusion weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI), and molecular MRI, can be used to non-invasive prediction of biomarkers of ovarian cancer and targeted monitoring of therapeutic efficacy in order to provide new diagnostic and ideas for clinical treatment decisions and reduce invasive damage to patients. In addition, due to the rapid development of the pathogenesis and targeted drug research of ovarian cancer, targeted molecular imaging is becoming increasingly important for the clinical diagnosis and treatment of ovarian cancer. Therefore, it is necessary and urgent to develop and use targeted molecular imaging technology and targeted molecular probes in the future. We reviewed the research progress of different MRI techniques, including DWI, DCE-MRI, molecular MRI, imaging omics and artificial intelligence in predicting the biomarkers of ovarian cancer, providing new ideas for monitoring clinical treatment response and guiding the use of targeted drugs of ovarian cancer.

[Keywords] ovarian cancer；magnetic resonance imaging；targeted molecular magnetic resonance imaging；diffusion weighted imaging；dynamic contrast-enhanced magnetic resonance imaging；biomarker；noninvasive prediction

Contributor Information

ZHOU Hongyu¹ BAO Haihua² WEN Shengbao^2* WANG Yu¹ ZHAO Yalong¹ ZHANG Zixuan¹

¹ Clinical Medicine Department of Qinghai University, Xining 810000, China

² Imaging Center of Qinghai University Affiliated Hospital, Xining 810000, China

Corresponding author: Wen SB, E-mail: qdfyyxzxwsb@126.com

Conflicts of interest None.

Publication Information

ACKNOWLEDGMENTS Provincial Clinical Key Specialty Construction Project in Qinghai Province [No. Qing Cai She Zi (2020) 1301]; The ICON Research Fund Project of the China Red Cross Foundation's 'Yingrui Northwest Public Welfare Project' (No. XM_HR_ICON_2020_10).

Received 2023-04-20

Accepted 2023-07-21

DOI: 10.12015/issn.1674-8034.2023.09.031

Text

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