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Industry Research
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Automated phantom analysis for gamma cameras and SPECT: A methodology for use in a clinical setting
Research using QC-Track for automated phantom analysis
in nuclear medicine QC has been published in the Journal of Applied Clinical Medical Physics.
This research demonstrated that QC-Track’s Automated Phantom Analysis module can be used to quantitatively analyze image quality
and resolution of gamma cameras as part of an institution’s routine QC process.
View a narrated summary here.
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Signal and contrast to noise ratio evaluation of fluoroscopic loops for interventional fluoroscope quality control
Research on automated fluoroscopy QC
using QC-Track in an IR lab has been published in the October issue of the Journal of Applied Clinical Medical Physics.
The paper’s first author is Allen Goode, M.S., Chief Diagnostic Medical Physicist, University of Virginia Health System.
Carl Snyder, PhD, Senior Engineer at Atirix, and Angela Snyder, PhD, Atirix VP of Research, are listed as second
and third authors, respectively. The research effort was led by Goode and included his team at the University of
Virginia Health System in collaboration with the research team at Atirix Medical Systems.
Automated Phantom Analysis for Gamma Cameras – An Efficient, Accessible, Consistent, and Sensitive Method
for Quality Control
Research using QC-Track for automated phantom analysis in nuclear medicine QC was presented by Erik Tazegul,
Atirix Research Analyst, as a talk at the 2019 AAPM Annual Meeting. (
View the narrated presentation here.
) The
abstract
describes a robust automated quantitative image analysis package for efficiently
assessing gamma camera image quality in a busy clinical setting.
The research was a collaborative effort between the Atirix Medical Systems and University of
Virginia Health System research teams.
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Use of Signal to Noise Ratio for Daily Quality Control of Fluoroscopes Used for Interventional Radiology Procedures
Research on automated fluoroscopy QC using QC-Track in an IR lab was presented by Allen Goode, M.S.,
Chief Diagnostic Medical Physicist, University of Virginia Health System, as an
ePoster
at the 2018 AAPM Annual Meeting.
The
research effort
was led by Allen Goode, M.S., and included his team at the University of Virginia Health System in collaboration with the
research team at Atirix Medical Systems.
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ACR acknowledges Atirix recommendation of SNR as alternative to spoke counting for MRI QC
The American College of Radiology (ACR) MRI accreditation program has officially acknowledged signal-to-noise ratio (SNR) as an alternative measurement to low contrast detectability
for weekly MRI quality control.
This addition came at the suggestion of Angela Snyder, Ph.D, Director of Research for Atirix Medical Systems,
who advocated for the alternative quality measure.
Using SNR as the daily/weekly measurement of MRI image quality:
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offers greater sensitivity to subtle performance changes,
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has a broader range than spoke counting,
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is quantitative rather than qualitative, and
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for facilities using QC-Track’s automated phantom analysis module, is a faster measure to obtain than spoke count, leading to more efficient MRI QC.
The ACR’s statement on using SNR in place of low contrast detectability can be found in the Annual Medical Physicist/MR Scientist Survey section of the ACR’s Accreditation Support
Quality Control: MRI/Breast MRI
page.
Effective September 2016 - Current
Steve Backes, President and CEO of Atirix, is a consulting member of AAPM Task Group No. 272 - Comprehensive Acceptance Testing and Evaluation of Fluoroscopy
Imaging Systems.
Atirix is using QC-Track to support the research efforts of the
TG272 Quality Control subcommittee.
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Atirix products are covered by issued and pending patents, including US 8,478,610 “Medical Imaging Device Quality Control
System and Method” and US 8,428,969 “System and Method for Tracking Imaging Quality”
©
2021
Atirix Medical Systems, Inc. All Rights Reserved.
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