dc.contributor.advisor | Michael J. Cima. | en_US |
dc.contributor.author | Frangieh, Chris J.(Christopher John) | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2019-11-04T20:22:44Z | |
dc.date.available | 2019-11-04T20:22:44Z | |
dc.date.copyright | 2019 | en_US |
dc.date.issued | 2019 | en_US |
dc.identifier.uri | https://hdl.handle.net/1721.1/122757 | |
dc.description | Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 | en_US |
dc.description | Cataloged from PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 47-51). | en_US |
dc.description.abstract | Portable, non-invasive sensors of tissue fluid distribution would aid in diagnosis of fluid volume disorders and inform therapeutic decisions across diverse patient populations. Existing techniques are inaccurate, invasive, or easily confounded by patient physiology. Single-sided magnetic resonance (MR) devices could provide a portable, low-cost platform for localized measurements of fluid distribution. This thesis demonstrates a single-sided MR sensor that can quantify fluid distribution of heterogeneous samples via depth-resolved, diffusion-weighted, multicomponent T2 relaxometry. Validation using synthetic tissue phantoms, ex vivo tissue samples, and an in vivo edema model is presented. Estimation of tissue fractions in heterogeneous samples with 2% error and tissue layer thickness with 0.1 mm error is demonstrated. The sensor can identify onset, progression, and recovery of muscle edema despite the presence of a confounding subcutaneous tissue layer. These methods can provide point-of-care diagnostics for fluid distribution disorders such as end-stage renal disease and dehydration. | en_US |
dc.description.statementofresponsibility | by Chris J. Frangieh. | en_US |
dc.format.extent | 51 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. | en_US |
dc.rights.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | Nuclear magnetic resonance sensors methods for volume status monitoring | en_US |
dc.type | Thesis | en_US |
dc.description.degree | S.M. | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.identifier.oclc | 1124923763 | en_US |
dc.description.collection | S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
dspace.imported | 2019-11-04T20:22:43Z | en_US |
mit.thesis.degree | Master | en_US |
mit.thesis.department | EECS | en_US |