This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. / Thesis: Ph. D., Harvard-MIT Program in Health Sciences and Technology, 2020 / Cataloged from student-submitted PDF version of thesis. / Includes bibliographical references (pages 171-185). / Magnetic Particle Imaging (MPI) is an emerging tracer-based imaging modality that uniquely images the nonlinear magnetization of superparamagnetic iron oxide nanoparticles (SPIOs). MPI boasts high sensitivity, zero background signal, positive contrast, fast temporal resolution, and quantitative detection. The field of MPI is currently preclinical, and this work aims to scale MPI to human sizes by developing and validating it for two clinical applications: tumor detection and imaging for intraoperative margin assessment during breast-conserving surgery (BCS), and functional neuroimaging. For margin assessment in BCS, a hand-held Magnetic Particle detector and a small-bore MPI imager are assessed for intraoperative use along with an injected SPIO agent. The goal is to detect positive margins during surgery and thus reduce the need for future reexcision. Both hardware systems are validated using clinically relevant phantoms. For functional Magnetic Particle Imaging (fMPI) of the brain, a continuous time-series MPI imager is developed and validated for imaging of cerebral blood volume (CBV) changes during functional activation. The goal is improved sensitivity beyond the capabilities of current functional imaging modalities. We present initial results of in vivo rodent fMPI in a small-bore imager, and the design of a human head-sized system, with implementation underway. Through the collective development of these MPI hardware systems and validation of their potential for these two clinical applications, this work aims to catalyze the expansion of MPI into the clinical setting. / by Erica Ellis Mason. / Ph. D. / Ph.D. Harvard-MIT Program in Health Sciences and Technology
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/128037 |
| Date | January 2020 |
| Creators | Mason, Erica Ellis. |
| Contributors | Lawrence L. Wald., Harvard--MIT Program in Health Sciences and Technology., Harvard University--MIT Division of Health Sciences and Technology |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 185 pages, application/pdf |
| 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., http://dspace.mit.edu/handle/1721.1/7582 |
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