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Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes

BACKGROUND: Axillary lymph node (ALN) status is an important prognostic factor for breast cancer. We retrospectively used contrast-enhanced computed tomography (CE-CT) to evaluate the presence of ALN, metastasis based on size, shape, and contrasting effects. METHODS: Of 131 consecutive patients who...

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Autores principales: Urata, Masakazu, Kijima, Yuko, Hirata, Munetsugu, Shinden, Yoshiaki, Arima, Hideo, Nakajo, Akihiro, Koriyama, Chihaya, Arigami, Takaaki, Uenosono, Yoshikazu, Okumura, Hiroshi, Maemura, Kosei, Ishigami, Sumiya, Yoshinaka, Heiji, Natsugoe, Shoji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193134/
https://www.ncbi.nlm.nih.gov/pubmed/25266250
http://dx.doi.org/10.1186/1471-2407-14-730
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author Urata, Masakazu
Kijima, Yuko
Hirata, Munetsugu
Shinden, Yoshiaki
Arima, Hideo
Nakajo, Akihiro
Koriyama, Chihaya
Arigami, Takaaki
Uenosono, Yoshikazu
Okumura, Hiroshi
Maemura, Kosei
Ishigami, Sumiya
Yoshinaka, Heiji
Natsugoe, Shoji
author_facet Urata, Masakazu
Kijima, Yuko
Hirata, Munetsugu
Shinden, Yoshiaki
Arima, Hideo
Nakajo, Akihiro
Koriyama, Chihaya
Arigami, Takaaki
Uenosono, Yoshikazu
Okumura, Hiroshi
Maemura, Kosei
Ishigami, Sumiya
Yoshinaka, Heiji
Natsugoe, Shoji
author_sort Urata, Masakazu
collection PubMed
description BACKGROUND: Axillary lymph node (ALN) status is an important prognostic factor for breast cancer. We retrospectively used contrast-enhanced computed tomography (CE-CT) to evaluate the presence of ALN, metastasis based on size, shape, and contrasting effects. METHODS: Of 131 consecutive patients who underwent CE-CT followed by surgery for breast cancer between 2005 and 2012 in our institution, 49 were histologically diagnosed with lymph node metastasis. Maximum Hounsfield units (HU) and mean HU were measured in non-contrasting CT (NC-CT) and CE-CT of ALNs. RESULTS: Of 12 examined measurements, we found significant differences between negative and metastatic ALNs in mean and maximum NC-CT HU, and mean and maximum CE-CT HU (P < 0.05). We used a receiver operating curve, to determine cut-off values of four items in which significant differences were observed. The highest accuracy rate was noted for the cut-off value of 54 as maximum NC-CT HU for which sensitivity, specificity, and accuracy rate were 79.6%, 80.5% and 80.2%, respectively. CONCLUSIONS: CT HU of a patient with breast cancer are absolute values that offer objective disease management data that are not influenced by the screener’s ability.
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spelling pubmed-41931342014-10-11 Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes Urata, Masakazu Kijima, Yuko Hirata, Munetsugu Shinden, Yoshiaki Arima, Hideo Nakajo, Akihiro Koriyama, Chihaya Arigami, Takaaki Uenosono, Yoshikazu Okumura, Hiroshi Maemura, Kosei Ishigami, Sumiya Yoshinaka, Heiji Natsugoe, Shoji BMC Cancer Research Article BACKGROUND: Axillary lymph node (ALN) status is an important prognostic factor for breast cancer. We retrospectively used contrast-enhanced computed tomography (CE-CT) to evaluate the presence of ALN, metastasis based on size, shape, and contrasting effects. METHODS: Of 131 consecutive patients who underwent CE-CT followed by surgery for breast cancer between 2005 and 2012 in our institution, 49 were histologically diagnosed with lymph node metastasis. Maximum Hounsfield units (HU) and mean HU were measured in non-contrasting CT (NC-CT) and CE-CT of ALNs. RESULTS: Of 12 examined measurements, we found significant differences between negative and metastatic ALNs in mean and maximum NC-CT HU, and mean and maximum CE-CT HU (P < 0.05). We used a receiver operating curve, to determine cut-off values of four items in which significant differences were observed. The highest accuracy rate was noted for the cut-off value of 54 as maximum NC-CT HU for which sensitivity, specificity, and accuracy rate were 79.6%, 80.5% and 80.2%, respectively. CONCLUSIONS: CT HU of a patient with breast cancer are absolute values that offer objective disease management data that are not influenced by the screener’s ability. BioMed Central 2014-09-30 /pmc/articles/PMC4193134/ /pubmed/25266250 http://dx.doi.org/10.1186/1471-2407-14-730 Text en © Urata et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Urata, Masakazu
Kijima, Yuko
Hirata, Munetsugu
Shinden, Yoshiaki
Arima, Hideo
Nakajo, Akihiro
Koriyama, Chihaya
Arigami, Takaaki
Uenosono, Yoshikazu
Okumura, Hiroshi
Maemura, Kosei
Ishigami, Sumiya
Yoshinaka, Heiji
Natsugoe, Shoji
Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title_full Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title_fullStr Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title_full_unstemmed Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title_short Computed tomography Hounsfield units can predict breast cancer metastasis to axillary lymph nodes
title_sort computed tomography hounsfield units can predict breast cancer metastasis to axillary lymph nodes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4193134/
https://www.ncbi.nlm.nih.gov/pubmed/25266250
http://dx.doi.org/10.1186/1471-2407-14-730
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