A transfer function approach for predicting rare cell capture microdevice performance
Rare cells have the potential to improve our understanding of biological systems and the treatment of a variety of diseases; each of those applications requires a different balance of throughput, capture efficiency, and sample purity. Those challenges, coupled with the limited availability of patien...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer US
2016
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| Online Access: | http://hdl.handle.net/1721.1/105241 |
| _version_ | 1811076518319751168 |
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| author | Smith, James P. Kirby, Brian J. |
| author2 | Lincoln Laboratory |
| author_facet | Lincoln Laboratory Smith, James P. Kirby, Brian J. |
| author_sort | Smith, James P. |
| collection | MIT |
| description | Rare cells have the potential to improve our understanding of biological systems and the treatment of a variety of diseases; each of those applications requires a different balance of throughput, capture efficiency, and sample purity. Those challenges, coupled with the limited availability of patient samples and the costs of repeated design iterations, motivate the need for a robust set of engineering tools to optimize application-specific geometries. Here, we present a transfer function approach for predicting rare cell capture in microfluidic obstacle arrays. Existing computational fluid dynamics (CFD) tools are limited to simulating a subset of these arrays, owing to computational costs; a transfer function leverages the deterministic nature of cell transport in these arrays, extending limited CFD simulations into larger, more complicated geometries. We show that the transfer function approximation matches a full CFD simulation within 1.34 %, at a 74-fold reduction in computational cost. Taking advantage of these computational savings, we apply the transfer function simulations to simulate reversing array geometries that generate a “notch filter” effect, reducing the collision frequency of cells outside of a specified diameter range. We adapt the transfer function to study the effect of off-design boundary conditions (such as a clogged inlet in a microdevice) on overall performance. Finally, we have validated the transfer function’s predictions for lateral displacement within the array using particle tracking and polystyrene beads in a microdevice. |
| first_indexed | 2024-09-23T10:23:27Z |
| format | Article |
| id | mit-1721.1/105241 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T10:23:27Z |
| publishDate | 2016 |
| publisher | Springer US |
| record_format | dspace |
| spelling | mit-1721.1/1052412022-09-30T20:49:04Z A transfer function approach for predicting rare cell capture microdevice performance Smith, James P. Kirby, Brian J. Lincoln Laboratory Smith, James P. Rare cells have the potential to improve our understanding of biological systems and the treatment of a variety of diseases; each of those applications requires a different balance of throughput, capture efficiency, and sample purity. Those challenges, coupled with the limited availability of patient samples and the costs of repeated design iterations, motivate the need for a robust set of engineering tools to optimize application-specific geometries. Here, we present a transfer function approach for predicting rare cell capture in microfluidic obstacle arrays. Existing computational fluid dynamics (CFD) tools are limited to simulating a subset of these arrays, owing to computational costs; a transfer function leverages the deterministic nature of cell transport in these arrays, extending limited CFD simulations into larger, more complicated geometries. We show that the transfer function approximation matches a full CFD simulation within 1.34 %, at a 74-fold reduction in computational cost. Taking advantage of these computational savings, we apply the transfer function simulations to simulate reversing array geometries that generate a “notch filter” effect, reducing the collision frequency of cells outside of a specified diameter range. We adapt the transfer function to study the effect of off-design boundary conditions (such as a clogged inlet in a microdevice) on overall performance. Finally, we have validated the transfer function’s predictions for lateral displacement within the array using particle tracking and polystyrene beads in a microdevice. National Cancer Institute (U.S.). Physical Sciences-Oncology Center (Cornell Center on the Microenvironment and Metastasis. Award U54CA143876) 2016-11-07T21:50:25Z 2016-11-07T21:50:25Z 2015-05 2016-08-18T15:44:27Z Article http://purl.org/eprint/type/JournalArticle 1387-2176 1572-8781 http://hdl.handle.net/1721.1/105241 Smith, James P., and Brian J. Kirby. “A Transfer Function Approach for Predicting Rare Cell Capture Microdevice Performance.” Biomedical Microdevices 17.3 (2015): n. pag. en http://dx.doi.org/10.1007/s10544-015-9956-7 Biomedical Microdevices Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Springer Science+Business Media New York application/pdf Springer US Springer US |
| spellingShingle | Smith, James P. Kirby, Brian J. A transfer function approach for predicting rare cell capture microdevice performance |
| title | A transfer function approach for predicting rare cell capture microdevice performance |
| title_full | A transfer function approach for predicting rare cell capture microdevice performance |
| title_fullStr | A transfer function approach for predicting rare cell capture microdevice performance |
| title_full_unstemmed | A transfer function approach for predicting rare cell capture microdevice performance |
| title_short | A transfer function approach for predicting rare cell capture microdevice performance |
| title_sort | transfer function approach for predicting rare cell capture microdevice performance |
| url | http://hdl.handle.net/1721.1/105241 |
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