Abstract
Worldwide, prostate cancer sits only behind lung cancer as the most commonly diagnosed form of the disease in men. Even the best diagnostic standards lack precision, presenting issues with false positives and unneeded surgical intervention for patients. This lack of clear cut early diagnostic tools is a significant problem. We present a microfluidic platform, the Time-Resolved Hydrodynamic Stretcher (TR-HS), which allows the investigation of the dynamic mechanical response of thousands of cells per second to a non-destructive stress. The TR-HS integrates high-speed imaging and computer vision to automatically detect and track single cells suspended in a fluid and enables cell classification based on their mechanical properties. We demonstrate the discrimination of healthy and cancerous prostate cell lines based on the whole-cell, timeresolved mechanical response to a hydrodynamic load. Additionally, we implement a finite element method (FEM) model to characterise the forces responsible for the cell deformation in our device. Finally, we report the classification of the two different cell groups based on their time-resolved roundness using a decision tree classifier. This approach introduces a modality for high-throughput assessments of cellular suspensions and may represent a viable application for the development of innovative diagnostic devices.
Original language | English |
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Article number | 5742 |
Number of pages | 9 |
Journal | Scientific Reports |
Volume | 9 |
DOIs | |
Publication status | Published - 5 Apr 2019 |
Keywords
- Diagnostic markers
- High-throughput screening
- Lab-on-a-chip
- Prostate
ASJC Scopus subject areas
- General
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Dive into the research topics of 'High-Throughput, Time-Resolved Mechanical Phenotyping of Prostate Cancer Cells'. Together they form a unique fingerprint.Student theses
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Sequential Recognition of Manipulation Actions Using Superpixel Group Mining
Huang, T. (Author), McKenna, S. (Supervisor) & Zhang, J. (Supervisor), 2019Student thesis: Doctoral Thesis › Doctor of Philosophy
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Profiles
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Nabi, Ghulam
- Cancer Research - Clinical Professor (Teaching and Research) of Surgical Uro-Oncology
Person: Academic