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Microfluidic Platforms in Diagnostic of Ovarian Cancer Publisher Pubmed



Dabbagh Moghaddam F1 ; Dadgar D2 ; Esmaeili Y3 ; Babolmorad S2 ; Ilkhani E2 ; Rafiee M4 ; Wang XD5 ; Makvandi P6
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Authors Affiliations
  1. 1. Institute for Photonics and Nanotechnologies, National Research Council, Via Fosso del Cavaliere, 100, Rome, 00133, Italy
  2. 2. Faculty of Veterinary Medicine, Science and Research Branch, Islamic Azad University, Tehran, Iran
  3. 3. Biosensor Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
  4. 4. Department of Veterinary Sciences University of Wyoming, 1174 Snowy Range Road, Laramie, 82070, WY, United States
  5. 5. Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University Shanghai Medical College, Shanghai, 200032, China
  6. 6. The Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Zhejiang, Quzhou, 324000, China

Source: Environmental Research Published:2023


Abstract

The most important reason for death from ovarian cancer is the late diagnosis of this disease. The standard treatment of ovarian cancer includes surgery and chemotherapy based on platinum, which is associated with side effects for the body. Due to the nonspecific nature of clinical symptoms, developing a platform for early detection of this disease is needed. In recent decades, the advancements of microfluidic devices and systems have provided several advantages for diagnosing ovarian cancer. Designing and manufacturing new platforms using specialized technologies can be a big step toward improving the prevention, diagnosis, and treatment of this group of diseases. Organ-on-a-chip microfluidic devices are increasingly used as a promising platform in cancer research, with a focus on specific biological aspects of the disease. This review focusing on ovarian cancer and microfluidic application technologies in its diagnosis. Additionally, it discusses microfluidic platforms and their potential future perspectives in advancing ovarian cancer diagnosis. © 2023 The Authors
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