Cargando…

Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?

BACKGROUND: Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In thi...

Descripción completa

Detalles Bibliográficos
Autores principales: Yoshida, Mitsuteru, Yuasa, Masao, Ogawa, Hirohisa, Miyamoto, Naoki, Kawakami, Yukikiyo, Kondo, Kazuya, Tangoku, Akira
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons Australia, Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017252/
https://www.ncbi.nlm.nih.gov/pubmed/33599059
http://dx.doi.org/10.1111/1759-7714.13838
_version_ 1783674025044606976
author Yoshida, Mitsuteru
Yuasa, Masao
Ogawa, Hirohisa
Miyamoto, Naoki
Kawakami, Yukikiyo
Kondo, Kazuya
Tangoku, Akira
author_facet Yoshida, Mitsuteru
Yuasa, Masao
Ogawa, Hirohisa
Miyamoto, Naoki
Kawakami, Yukikiyo
Kondo, Kazuya
Tangoku, Akira
author_sort Yoshida, Mitsuteru
collection PubMed
description BACKGROUND: Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In this study, we investigated whether histological diagnosis of AIS and MIA using quantitative three‐dimensional CT imaging analysis could be predicted. METHODS: We retrospectively analyzed the images and histopathological findings of patients with lung cancer who were diagnosed with AIS or MIA between January 2017 and June 2018. We used Synapse Vincent (v. 4.3) (Fujifilm) software to analyze the CT attenuation values and performed a histogram analysis. RESULTS: There were 22 patients with AIS and 22 with MIA. The ground‐glass nodule (GGN) rate was significantly higher in patients with AIS (p < 0.001), whereas the solid volume (p < 0.001) and solid rate (p = 0.001) were significantly higher in those with MIA. The mean (p = 0.002) and maximum (p = 0.025) CT values were significantly higher in patients with MIA. The 25th, 50th, 75th, and 97.5th percentiles (all p < 0.05) for the CT values were significantly higher in patients with MIA. CONCLUSIONS: We demonstrated that quantitative analysis of 3D‐CT imaging data using software can help distinguish AIS from MIA. These analyses are useful for guiding decision‐making in the surgical management of early lung cancer, as well as subsequent follow‐up.
format Online
Article
Text
id pubmed-8017252
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher John Wiley & Sons Australia, Ltd
record_format MEDLINE/PubMed
spelling pubmed-80172522021-04-02 Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma? Yoshida, Mitsuteru Yuasa, Masao Ogawa, Hirohisa Miyamoto, Naoki Kawakami, Yukikiyo Kondo, Kazuya Tangoku, Akira Thorac Cancer Original Articles BACKGROUND: Given the subtle pathological signs of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA), effective differentiation between the two entities is crucial. However, it is difficult to predict these conditions using preoperative computed tomography (CT) imaging. In this study, we investigated whether histological diagnosis of AIS and MIA using quantitative three‐dimensional CT imaging analysis could be predicted. METHODS: We retrospectively analyzed the images and histopathological findings of patients with lung cancer who were diagnosed with AIS or MIA between January 2017 and June 2018. We used Synapse Vincent (v. 4.3) (Fujifilm) software to analyze the CT attenuation values and performed a histogram analysis. RESULTS: There were 22 patients with AIS and 22 with MIA. The ground‐glass nodule (GGN) rate was significantly higher in patients with AIS (p < 0.001), whereas the solid volume (p < 0.001) and solid rate (p = 0.001) were significantly higher in those with MIA. The mean (p = 0.002) and maximum (p = 0.025) CT values were significantly higher in patients with MIA. The 25th, 50th, 75th, and 97.5th percentiles (all p < 0.05) for the CT values were significantly higher in patients with MIA. CONCLUSIONS: We demonstrated that quantitative analysis of 3D‐CT imaging data using software can help distinguish AIS from MIA. These analyses are useful for guiding decision‐making in the surgical management of early lung cancer, as well as subsequent follow‐up. John Wiley & Sons Australia, Ltd 2021-02-17 2021-04 /pmc/articles/PMC8017252/ /pubmed/33599059 http://dx.doi.org/10.1111/1759-7714.13838 Text en © 2021 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Yoshida, Mitsuteru
Yuasa, Masao
Ogawa, Hirohisa
Miyamoto, Naoki
Kawakami, Yukikiyo
Kondo, Kazuya
Tangoku, Akira
Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title_full Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title_fullStr Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title_full_unstemmed Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title_short Can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
title_sort can computed tomography differentiate adenocarcinoma in situ from minimally invasive adenocarcinoma?
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8017252/
https://www.ncbi.nlm.nih.gov/pubmed/33599059
http://dx.doi.org/10.1111/1759-7714.13838
work_keys_str_mv AT yoshidamitsuteru cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT yuasamasao cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT ogawahirohisa cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT miyamotonaoki cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT kawakamiyukikiyo cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT kondokazuya cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma
AT tangokuakira cancomputedtomographydifferentiateadenocarcinomainsitufromminimallyinvasiveadenocarcinoma