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Medical physics 3.0 versus 1.0: A case study in digital radiography quality control
PURPOSE: The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail. METHODS: MP1.0 tests included traditional annual tests plus the ma...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123149/ https://www.ncbi.nlm.nih.gov/pubmed/30117273 http://dx.doi.org/10.1002/acm2.12425 |
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author | Carver, Diana E. Willis, Charles E. Stauduhar, Paul J. Nishino, Thomas K. Wells, Jered R. Samei, Ehsan |
author_facet | Carver, Diana E. Willis, Charles E. Stauduhar, Paul J. Nishino, Thomas K. Wells, Jered R. Samei, Ehsan |
author_sort | Carver, Diana E. |
collection | PubMed |
description | PURPOSE: The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail. METHODS: MP1.0 tests included traditional annual tests plus the manufacturer's automated Quality Assurance Procedures (QAP) of a DR system before and after a radiologist's image quality (IQ) complaint repeated after service intervention. Further analysis was conducted using nontraditional MP3.0 tests including longitudinal review of QAP results from a 15‐yr database, exposure‐dependent signal‐to‐noise (SNR (2)), clinical IQ, and correlation with the institutional service database. Clinical images were analyzed in terms of IQ metrics by the Duke University Clinical Imaging Physics Group using previously validated software. RESULTS: Traditional metrics did not indicate discrepant system performance at any time. QAP reported a decrease in contrast‐to‐noise ratio (CNR) after detector replacement, but remained above the manufacturer's action limit. Clinical images showed increased lung noise (Ln), mediastinum noise (Mn), and subdiaphragm‐lung contrast (SLc), and decreased lung gray level (Lgl) following detector replacement. After detector recalibration, QAP CNR improved, but did not return to previous levels. Lgl and SLc no longer significantly differed from before detector recalibration; however, Ln and Mn remained significantly different. Exposure‐dependent SNR (2) documented the detector operating within acceptable limits 9 yr previously but subsequently becoming miscalibrated sometime before four prior annual tests. Service records revealed catastrophic failure of the computer containing the original detector calibration from 11 yr prior. It is likely that the incorrect calibration backup file was uploaded at that time. CONCLUSIONS: MP1.0 tests failed to detect substandard system performance, but MP3.0 methods determined the root cause of the problem. MP3.0 exploits the wealth of data with more sensitive performance indicators. Data analytics are powerful tools whose proper application could facilitate early intervention in degraded system performance. |
format | Online Article Text |
id | pubmed-6123149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-61231492018-09-10 Medical physics 3.0 versus 1.0: A case study in digital radiography quality control Carver, Diana E. Willis, Charles E. Stauduhar, Paul J. Nishino, Thomas K. Wells, Jered R. Samei, Ehsan J Appl Clin Med Phys Medical Imaging PURPOSE: The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail. METHODS: MP1.0 tests included traditional annual tests plus the manufacturer's automated Quality Assurance Procedures (QAP) of a DR system before and after a radiologist's image quality (IQ) complaint repeated after service intervention. Further analysis was conducted using nontraditional MP3.0 tests including longitudinal review of QAP results from a 15‐yr database, exposure‐dependent signal‐to‐noise (SNR (2)), clinical IQ, and correlation with the institutional service database. Clinical images were analyzed in terms of IQ metrics by the Duke University Clinical Imaging Physics Group using previously validated software. RESULTS: Traditional metrics did not indicate discrepant system performance at any time. QAP reported a decrease in contrast‐to‐noise ratio (CNR) after detector replacement, but remained above the manufacturer's action limit. Clinical images showed increased lung noise (Ln), mediastinum noise (Mn), and subdiaphragm‐lung contrast (SLc), and decreased lung gray level (Lgl) following detector replacement. After detector recalibration, QAP CNR improved, but did not return to previous levels. Lgl and SLc no longer significantly differed from before detector recalibration; however, Ln and Mn remained significantly different. Exposure‐dependent SNR (2) documented the detector operating within acceptable limits 9 yr previously but subsequently becoming miscalibrated sometime before four prior annual tests. Service records revealed catastrophic failure of the computer containing the original detector calibration from 11 yr prior. It is likely that the incorrect calibration backup file was uploaded at that time. CONCLUSIONS: MP1.0 tests failed to detect substandard system performance, but MP3.0 methods determined the root cause of the problem. MP3.0 exploits the wealth of data with more sensitive performance indicators. Data analytics are powerful tools whose proper application could facilitate early intervention in degraded system performance. John Wiley and Sons Inc. 2018-08-17 /pmc/articles/PMC6123149/ /pubmed/30117273 http://dx.doi.org/10.1002/acm2.12425 Text en © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Medical Imaging Carver, Diana E. Willis, Charles E. Stauduhar, Paul J. Nishino, Thomas K. Wells, Jered R. Samei, Ehsan Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title | Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title_full | Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title_fullStr | Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title_full_unstemmed | Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title_short | Medical physics 3.0 versus 1.0: A case study in digital radiography quality control |
title_sort | medical physics 3.0 versus 1.0: a case study in digital radiography quality control |
topic | Medical Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6123149/ https://www.ncbi.nlm.nih.gov/pubmed/30117273 http://dx.doi.org/10.1002/acm2.12425 |
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