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Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need?
OBJECTIVES: To compare the effectiveness of two different patient size metrics based on water equivalent diameter (D (w)), the mid‐scan water equivalent diameter D (w_c), and the mean (average) water equivalent diameter in the imaged region, D (w_ave), for automatic detection of accidental changes i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768030/ https://www.ncbi.nlm.nih.gov/pubmed/29265700 http://dx.doi.org/10.1002/acm2.12240 |
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author | Sarmento, Sandra Mendes, Bruno Gouvêa, Margarida |
author_facet | Sarmento, Sandra Mendes, Bruno Gouvêa, Margarida |
author_sort | Sarmento, Sandra |
collection | PubMed |
description | OBJECTIVES: To compare the effectiveness of two different patient size metrics based on water equivalent diameter (D (w)), the mid‐scan water equivalent diameter D (w_c), and the mean (average) water equivalent diameter in the imaged region, D (w_ave), for automatic detection of accidental changes in computed tomography (CT) acquisition protocols. METHODS: Patient biometric data (height and weight) were available from a previous survey for 80 adult chest examinations, and 119 adult single‐acquisition chest–abdomen–pelvis (CAP) examinations for two 16 slice scanners (GE LightSpeed and Toshiba Aquilion RXL) equipped with automatic tube current modulation (ATCM). D (w_c) and D (w_ave) were calculated from the archived CT images. Size‐specific dose estimates (SSDE) were obtained from volume CT dose index (CTDI (vol)), using the conversion factors for a patient diameter of D (w_c). RESULTS: CTDI (vol) and SSDE correlate better with D (w_ave) than with D (w_c). R‐squared values of linear fits to CTDI (vol) of CAP examinations were 0.81–0.89 for D (w_c) and 0.93–0.94 for D (w_ave) (SSDE: 0.69–080 for D (w_c), 0.87–0.92 for D (w_ave)). Percentage differences between D (w_c) and D (w_ave) were −4 ± 4% for chest and +5 ± 4% for CAP examinations (in % of D (w_ave)). However, small D (w) variations translated as larger variations in CTDI (vol) for these ATCM systems (e.g., a 24% increase in D (w) doubled CTDI (vol)). The dependence of CTDI (vol) on D (w_ave) was similar for chest and CAP examinations performed with similar ATCM parameters, while use of D (w_c) resulted in a clear separation of the same data according to examination type. Maximum D (w) variation in the imaged region was 5.6 ± 1.6 cm for chest and 6.5 ± 1.4 cm for CAP examinations. CONCLUSIONS: D (w_ave) is a better metric than D (w_c) for binning similar‐sized patients in dose comparison studies, despite the additional computational effort required for its calculation Therefore, when implementing automatic determination of D (w) for SSDE calculations, automatic calculation of D (w_ave) should be considered. |
format | Online Article Text |
id | pubmed-5768030 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57680302018-04-02 Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? Sarmento, Sandra Mendes, Bruno Gouvêa, Margarida J Appl Clin Med Phys Medical Imaging OBJECTIVES: To compare the effectiveness of two different patient size metrics based on water equivalent diameter (D (w)), the mid‐scan water equivalent diameter D (w_c), and the mean (average) water equivalent diameter in the imaged region, D (w_ave), for automatic detection of accidental changes in computed tomography (CT) acquisition protocols. METHODS: Patient biometric data (height and weight) were available from a previous survey for 80 adult chest examinations, and 119 adult single‐acquisition chest–abdomen–pelvis (CAP) examinations for two 16 slice scanners (GE LightSpeed and Toshiba Aquilion RXL) equipped with automatic tube current modulation (ATCM). D (w_c) and D (w_ave) were calculated from the archived CT images. Size‐specific dose estimates (SSDE) were obtained from volume CT dose index (CTDI (vol)), using the conversion factors for a patient diameter of D (w_c). RESULTS: CTDI (vol) and SSDE correlate better with D (w_ave) than with D (w_c). R‐squared values of linear fits to CTDI (vol) of CAP examinations were 0.81–0.89 for D (w_c) and 0.93–0.94 for D (w_ave) (SSDE: 0.69–080 for D (w_c), 0.87–0.92 for D (w_ave)). Percentage differences between D (w_c) and D (w_ave) were −4 ± 4% for chest and +5 ± 4% for CAP examinations (in % of D (w_ave)). However, small D (w) variations translated as larger variations in CTDI (vol) for these ATCM systems (e.g., a 24% increase in D (w) doubled CTDI (vol)). The dependence of CTDI (vol) on D (w_ave) was similar for chest and CAP examinations performed with similar ATCM parameters, while use of D (w_c) resulted in a clear separation of the same data according to examination type. Maximum D (w) variation in the imaged region was 5.6 ± 1.6 cm for chest and 6.5 ± 1.4 cm for CAP examinations. CONCLUSIONS: D (w_ave) is a better metric than D (w_c) for binning similar‐sized patients in dose comparison studies, despite the additional computational effort required for its calculation Therefore, when implementing automatic determination of D (w) for SSDE calculations, automatic calculation of D (w_ave) should be considered. John Wiley and Sons Inc. 2017-12-19 /pmc/articles/PMC5768030/ /pubmed/29265700 http://dx.doi.org/10.1002/acm2.12240 Text en © 2017 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 Creative Commons Attribution (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 Sarmento, Sandra Mendes, Bruno Gouvêa, Margarida Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title | Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title_full | Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title_fullStr | Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title_full_unstemmed | Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title_short | Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need? |
title_sort | automatic calculation of patient size metrics in computed tomography: what level of computational accuracy do we need? |
topic | Medical Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5768030/ https://www.ncbi.nlm.nih.gov/pubmed/29265700 http://dx.doi.org/10.1002/acm2.12240 |
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