English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Enumerating circulating tumor cells (CTCs) has been demonstrably useful in cancer treatment. Although there are several approaches that have proved effective in isolating CTC-like cells, the crucial identification of CTCs continues to rely on the manual interpretation of immunofluorescence images of all cells that have been isolated. This procedure is time consuming and more importantly, CTC identification relies on subjective criteria that may differ between examiners. In this study, we describe the design, testing, and verification of a microfluidic platform that provides accurate and automated CTC enumeration using a common objective criterion. Methods: The platform consists of a multi-functional microfluidic chip and a unique image processing algorithm. The microfluidic chip integrates blood filtering, cell isolation, and single cell positioning to ensure minimal cell loss, efficient cell isolation, and fixed arraying of single cells to facilitate downstream image processing. By taking advantage of the microfluidic chip design to reduce calculation loads and eliminate measurement errors, our specially designed algorithm has the capability of rapidly interpreting hundreds of images to provide accurate CTC counts. Results: Following intensive optimization of the microfluidic chip, the image processing algorithm, and their collaboration, we verified the complete platform by enumerating CTCs from six clinical blood samples of patients with breast cancer. Compared to tube-based CTC isolation and manual CTC identification, our platform had better accuracy and reduced the time needed from sample loading to result review by 50%. Conclusion: This automated CTC enumeration platform demonstrates not only a sound strategy in integrating a specially designed multi-functional microfluidic chip with a unique image processing algorithm for robust, accurate, and "hands-free" CTC enumeration, but may also lead to its use as a novel in vitro diagnostic device used in clinics and laboratories as readily as a routine blood test.

Precisely Enumerating Circulating Tumor Cells Utilizing a Multi-Functional Microfluidic Chip and Unique Image Interpretation Algorithm