Quantifying fluid overload with portable magnetic resonance sensors

The objective of this work was to translate the diagnostic capabilities of magnetic resonance imaging (MRI) to the patient bedside, specifically for the purpose of quantifying fluid overload. MRI is used extensively in clinical medicine, but it is still not used for routine diagnostics due to high cost, limited availability, and long scan times. Many of these impracticalities come from the hardware requirements associated with generating images. Images, however, are not necessary to harness some of magnetic resonance's (MR's) diagnostic potential. This thesis demonstrates that that a single-voxel MR sensor can obtain the same results as a traditional MRI in both phantoms and humans. A clinical study with hemodialysis patients and age-matched healthy controls was performed at MGH. The T2 relaxation times of study participants' legs were quantified at multiple time points with both a 1.5T clinical MRI scanner and a custom 0.27T single-voxel MR sensor. The results showed that the first sign of fluid overload is an increase in the relative fraction of extracellular fluid in the muscle. The relaxation time of the extracellular fluid in the muscle eventually increases after more fluid accumulates. Importantly, these MR findings occur before signs of lower-extremity edema are detectable on physical exam. Two healthy control subjects became dehydrated over the course of the study and the relative fraction of their extracellular fluid decreased. This incidental finding suggests MR can measure the full spectrum of hydration states. Furthermore, a single MRI measurement at a single time point can distinguish fluid overloaded patients from healthy controls. The amplitude associated with extracellular fluid most closely correlates to fluid loss, and these amplitude decreases are detectable with both the MRI and MR sensor. The results of this work point towards a promising future of using cheaper, faster MR sensors for bedside diagnostics.

Department dc:contributor.department

Harvard--MIT Program in Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Colucci, Lina Avancini

Advisor dc:contributor.advisor

• Michael J. Cima.

• Harvard--MIT Program in Health Sciences and Technology.

Statement 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.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/117894

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/117894