skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Signal-to-noise ratio in neuro activation PET studies

Abstract

It has become commonplace to compare scanner sensitivity characteristics by comparing noise equivalent count rate curves. However, because a 20-cm diameter uniform phantom is drastically difference from a human brain, these curves give misleading information when planning a neuro activation PET experiment. Signal-to-noise ratio (SNR) calculations have been performed using measured data (Siemens 921 scanner) from the three-dimensional (3-D) Hoffman brain phantom for the purpose of determining the optimal injection and scanning protocol for [{sup 15}O] labeled activation experiments. Region of interest (ROI) values along with the variance due to prompt (trues plus randoms) and random events were determined for various regions and radioactivity concentrations. Calculated attenuation correction was used throughout. Scatter correction was not used when calculating the SNR in activation studies because the number of scattered events is almost identical in each data acquisition and hence cancels. The results indicate that randoms correction should not be performed and that rather than being limited by the scanner capabilities, neuro activation experiments are limited by the amount of radioactivity that can be injected and the length of time the patient can stay in the scanner.

Authors:
 [1]
  1. Emory Center for Positron Emission Tomography, Atlanta, GA (United States). Div. of Nuclear Medicine
Publication Date:
OSTI Identifier:
227873
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Medical Imaging
Additional Journal Information:
Journal Volume: 15; Journal Issue: 2; Other Information: PBD: Apr 1996
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; POSITRON COMPUTED TOMOGRAPHY; SIGNAL-TO-NOISE RATIO; BRAIN; PHANTOMS; THREE-DIMENSIONAL CALCULATIONS; IMAGE PROCESSING; OXYGEN 15; LABELLED COMPOUNDS

Citation Formats

Votaw, J R. Signal-to-noise ratio in neuro activation PET studies. United States: N. p., 1996. Web. doi:10.1109/42.491421.
Votaw, J R. Signal-to-noise ratio in neuro activation PET studies. United States. https://doi.org/10.1109/42.491421
Votaw, J R. 1996. "Signal-to-noise ratio in neuro activation PET studies". United States. https://doi.org/10.1109/42.491421.
@article{osti_227873,
title = {Signal-to-noise ratio in neuro activation PET studies},
author = {Votaw, J R},
abstractNote = {It has become commonplace to compare scanner sensitivity characteristics by comparing noise equivalent count rate curves. However, because a 20-cm diameter uniform phantom is drastically difference from a human brain, these curves give misleading information when planning a neuro activation PET experiment. Signal-to-noise ratio (SNR) calculations have been performed using measured data (Siemens 921 scanner) from the three-dimensional (3-D) Hoffman brain phantom for the purpose of determining the optimal injection and scanning protocol for [{sup 15}O] labeled activation experiments. Region of interest (ROI) values along with the variance due to prompt (trues plus randoms) and random events were determined for various regions and radioactivity concentrations. Calculated attenuation correction was used throughout. Scatter correction was not used when calculating the SNR in activation studies because the number of scattered events is almost identical in each data acquisition and hence cancels. The results indicate that randoms correction should not be performed and that rather than being limited by the scanner capabilities, neuro activation experiments are limited by the amount of radioactivity that can be injected and the length of time the patient can stay in the scanner.},
doi = {10.1109/42.491421},
url = {https://www.osti.gov/biblio/227873}, journal = {IEEE Transactions on Medical Imaging},
number = 2,
volume = 15,
place = {United States},
year = {Mon Apr 01 00:00:00 EST 1996},
month = {Mon Apr 01 00:00:00 EST 1996}
}