TY - GEN
T1 - An Investigation of Quasi-Vertex Views in Brain SPECT Imaging-Initial Results
AU - Goding, Justin C.
AU - Auer, Benjamin
AU - Kalluri, Kesava S.
AU - Konik, Arda
AU - Zeraatkar, Navid
AU - Fromme, Timothy J.
AU - He, Yulun
AU - Zubal, George I.
AU - Furenlid, Lars R.
AU - King, Michael A.
N1 - Funding Information:
Manuscript received November 7, 2017. Research reported herein was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Number R01 EB022521. The contents are the sole responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/11/12
Y1 - 2018/11/12
N2 - A next-generation, adaptive, brain-imaging, single photon emission computed tomography system is currently under development at the Universities of Arizona and Massachusetts. The proposed multi-pinhole based modular gamma camera configuration enables the acquisition of 'quasi-vertex' views i.e., views close to the vertex. This study is concerned with understanding how activity inferior to the brain will influence these views and ultimately, the reconstruction of the volume of interest. Analytical models can provide some measure of the detected primary gamma radiation originating in an organ or tissue outside the region of interest. Scattered gamma radiation will be detected as well but given the difficulty in modeling such phenomena, Monte Carlo simulations are used to quantify its effect. Using computer generated phantoms, the influence of activity from organs and tissues in the thorax, neck and lower head as compared to that from brain structures in the quasivertex views, will be detected, identified and quantified. The simulation consists of two components: detectors and sources. The detectors were simulated gamma camera modules consisting of a tungsten pinhole collimator, an air gap, and a NaI(Tl) scintillator surrounded by lead shielding. The sources were phantoms with activity (I-123, primary gamma photons at 159 keV) set in the liver, lungs, striatum, salivary glands and the thyroid.
AB - A next-generation, adaptive, brain-imaging, single photon emission computed tomography system is currently under development at the Universities of Arizona and Massachusetts. The proposed multi-pinhole based modular gamma camera configuration enables the acquisition of 'quasi-vertex' views i.e., views close to the vertex. This study is concerned with understanding how activity inferior to the brain will influence these views and ultimately, the reconstruction of the volume of interest. Analytical models can provide some measure of the detected primary gamma radiation originating in an organ or tissue outside the region of interest. Scattered gamma radiation will be detected as well but given the difficulty in modeling such phenomena, Monte Carlo simulations are used to quantify its effect. Using computer generated phantoms, the influence of activity from organs and tissues in the thorax, neck and lower head as compared to that from brain structures in the quasivertex views, will be detected, identified and quantified. The simulation consists of two components: detectors and sources. The detectors were simulated gamma camera modules consisting of a tungsten pinhole collimator, an air gap, and a NaI(Tl) scintillator surrounded by lead shielding. The sources were phantoms with activity (I-123, primary gamma photons at 159 keV) set in the liver, lungs, striatum, salivary glands and the thyroid.
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U2 - 10.1109/NSSMIC.2017.8532719
DO - 10.1109/NSSMIC.2017.8532719
M3 - Conference contribution
AN - SCOPUS:85058482855
T3 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
BT - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
Y2 - 21 October 2017 through 28 October 2017
ER -