Digital Waveform Acquisition and Adaptive Collimation Methods for SPECT

Single Photon Emission Computed Tomography (SPECT) is a minimally invasive, functional imaging modality mainly used clinically in cardiology, oncology, and neurology. SPECT has also been particularly useful in preclinical settings because of the ability to perform longitudinal studies on animal models of human disease with a variety of commercial and custom radiotracers tailored to measure biological variables. The attachment of a gamma-emitting isotope to a functional molecule allows for the probing and study of basic biological processes, the investigation and diagnosis of diseases and therapies, and pharmacokinetic studies of candidate drugs. SPECT involves the acquisition of multiple projection images at dierent angles and computer-based reconstruction to recover the three dimensional distribution of the radioactive tracer. In this work, we present the reverse engineering and conversion of a classic clinical SPECT system for use in rabbit cardiac studies. The raw camera signals were tapped into by custom active buffer amplier circuits and rerouted out of the camera and into modern waveform digitizers. Waveform digitization captures time samples of the scintillation light pulse, allowing for the inclusion of more data into ML estimation than in conventional systems. Methods for including this data, as well as strategies for handling the increased computational load were developed. The potential improvements in performance with waveform capture compared to conventional estimation with scalar ML and/or Anger logic are discussed. First images using the cardiac perfusion tracer 99mTc-sestamibi are presented. The image forming optic used in SPECT is typically a parallel-hole collimator or a pinhole aperture. The pinhole allows for varying magnications and can achieve high resolution. However, high-resolution SPECT traditionally suffers from poor geometric sensitivity. To overcome the trade-off between sensitivity and resolution, we have designed an adaptive, adjustable aperture with the capability of changing the aperture diameter during an acquisition, allowing for the collection of datasets with variable resolutions and sensitivities. Combining multiple adjustable apertures allows for acquisition of both unmultiplexed and multiplexed projections, which will help overcome the artifacts that can otherwise occur during tomographic reconstructions, while preserving the advantage of greatly increased sensitivity. This has been incorporated as a key feature in a separate project to develop a clinical brain imager.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Graduate College

Grantor dc:publisher

The University of Arizona.

Year dc:date.issued

2020

Author dc:creator

• Momsen, Neil Charles

Advisor dc:contributor.advisor

• Furenlid, Lars R.

Committee members dc:contributor.committeemember

• Kupinski, Matthew A.
• Kuo, Phillip H.

Statement dc:rights

• Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.

Language dc:language.iso

en

Handle dc:identifier.uri

http://hdl.handle.net/10150/642121

OAI identifier oai:identifier

oai:repository.arizona.edu:10150/642121