Advancements in Circulating Tumor Cell Detection for Early Cancer Diagnosis: An Integration of Machine Learning Algorithms with Microfluidic Technologies DOI Creative Commons

Ling An,

Yi Liu, Yaling Liu

et al.

Biosensors, Journal Year: 2025, Volume and Issue: 15(4), P. 220 - 220

Published: March 29, 2025

Circulating tumor cells (CTCs) are vital indicators of metastasis and provide a non-invasive method for early cancer diagnosis, prognosis, therapeutic monitoring. However, their low prevalence heterogeneity in the bloodstream pose significant challenges detection. Microfluidic systems, or “lab-on-a-chip” devices, have emerged as revolutionary tool liquid biopsy, enabling efficient isolation analysis CTCs. These systems offer advantages such reduced sample volume, enhanced sensitivity, ability to integrate multiple processes into single platform. Several microfluidic techniques, including size-based filtration, dielectrophoresis, immunoaffinity capture, been developed enhance CTC The integration machine learning (ML) with has further improved specificity accuracy detection, significantly advancing speed efficiency diagnosis. ML models enabled more precise CTCs by automating detection enhancing identify rare heterogeneous cell populations. advancements already demonstrated potential improving diagnostic personalized treatment approaches. In this review, we highlight latest progress technologies algorithms, emphasizing how combination changed diagnosis contributed field.

Language: Английский

Advancements in Circulating Tumor Cell Detection for Early Cancer Diagnosis: An Integration of Machine Learning Algorithms with Microfluidic Technologies DOI Creative Commons

Ling An,

Yi Liu, Yaling Liu

et al.

Biosensors, Journal Year: 2025, Volume and Issue: 15(4), P. 220 - 220

Published: March 29, 2025

Circulating tumor cells (CTCs) are vital indicators of metastasis and provide a non-invasive method for early cancer diagnosis, prognosis, therapeutic monitoring. However, their low prevalence heterogeneity in the bloodstream pose significant challenges detection. Microfluidic systems, or “lab-on-a-chip” devices, have emerged as revolutionary tool liquid biopsy, enabling efficient isolation analysis CTCs. These systems offer advantages such reduced sample volume, enhanced sensitivity, ability to integrate multiple processes into single platform. Several microfluidic techniques, including size-based filtration, dielectrophoresis, immunoaffinity capture, been developed enhance CTC The integration machine learning (ML) with has further improved specificity accuracy detection, significantly advancing speed efficiency diagnosis. ML models enabled more precise CTCs by automating detection enhancing identify rare heterogeneous cell populations. advancements already demonstrated potential improving diagnostic personalized treatment approaches. In this review, we highlight latest progress technologies algorithms, emphasizing how combination changed diagnosis contributed field.

Language: Английский

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