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Massachusetts Institute of Technology

Large-area cell-tracking cytometry for biophysical measurements of single cells

Abstract

dc:description.abstract

Utility of single-cell biophysical markers is often limited due to the low-specificity nature of biophysical markers and lack of existing techniques which can test multiple biophysical characteristics for single cells. To address this challenge, I developed a multiparameter intrinsic cytometry approach which integrates multiple label-free biophysical measurements into a versatile (can combine techniques across domains) and readily extensible (to measure more than two biophysical markers) platform for single cell analysis. The proposed multiparameter cell-tracking intrinsic cytometry utilizes label-free microfluidic techniques to manipulate cells such that information regarding their biophysical properties can be extracted from their spatiotemporal positions. Furthermore, this technique utilizes cell tracking to extract and associate the biophysical markers for single cells. The specific instantiation of the cytometry platform can measure up to five intrinsic markers of cells, and has facilitated the quantitative investigation of label-free cell profiles and classification of cell types and functional states. The applications of this approach were extended by leveraging digital holographic microscopy and deep learning technologies to monitor cells in a large field of view, enabling rapid and high-throughput assessment of biophysical phenotypes.

Degree

thesis:*
Name thesis:degree_name
Doctoral
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Apichitsopa, Nicha.
Advisor dc:contributor.advisor
  • Joel Voldman.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/127012
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/127012

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Apichitsopa, Nicha.. Large-area cell-tracking cytometry for biophysical measurements of single cells. Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/127012