Cargando…

Predicting recurrence of non-small cell lung cancer based on mean computed tomography value

BACKGROUND: The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence. METHODS: A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was...

Descripción completa

Detalles Bibliográficos
Autores principales: Tamura, Masaya, Matsumoto, Isao, Tanaka, Yusuke, Saito, Daisuke, Yoshida, Shuhei, Takata, Munehisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117299/
https://www.ncbi.nlm.nih.gov/pubmed/33980268
http://dx.doi.org/10.1186/s13019-021-01476-0
_version_ 1783691566008762368
author Tamura, Masaya
Matsumoto, Isao
Tanaka, Yusuke
Saito, Daisuke
Yoshida, Shuhei
Takata, Munehisa
author_facet Tamura, Masaya
Matsumoto, Isao
Tanaka, Yusuke
Saito, Daisuke
Yoshida, Shuhei
Takata, Munehisa
author_sort Tamura, Masaya
collection PubMed
description BACKGROUND: The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence. METHODS: A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict tumor recurrence. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence. RESULTS: The m-CT values were − 213.7 ± 10.2 Hounsfield Units (HU) for the recurrence group and − 594.1 ± 11.6 HU for the non-recurrence group (p < 0.0001). Recurrence occurred in 45 patients (9.1%). The tumor recurrence group was strongly associated with a high CT attenuation value, high C/T ratio, large solid tumor size, and SUV. The diagnostic value of mCT value was more accurate than the C/T ratio, excluding the pure ground-glass opacity and pure solid (0 < C/T ratio < 100) groups. The SUV and mCT are independent predictive factors of tumor recurrence. CONCLUSIONS: The evaluation of mCT values was useful for predicting recurrence after the limited resection of small-sized NSCLC, and may potentially contribute to the selection of suitable treatment strategies.
format Online
Article
Text
id pubmed-8117299
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-81172992021-05-13 Predicting recurrence of non-small cell lung cancer based on mean computed tomography value Tamura, Masaya Matsumoto, Isao Tanaka, Yusuke Saito, Daisuke Yoshida, Shuhei Takata, Munehisa J Cardiothorac Surg Research Article BACKGROUND: The aim of this study was to assess the ability of using mean computed tomography (mCT) values to predict non-small cell lung cancer (NSCLC) tumor recurrence. METHODS: A retrospective study was conducted on 494 patients with stage IA NSCLC. Receiver operating characteristics analysis was used to assess the ability to use mCT value, C/T ratio, tumor size, and SUV to predict tumor recurrence. Multiple logistic regression analyses were performed to determine the independent variables for the prediction of tumor recurrence. RESULTS: The m-CT values were − 213.7 ± 10.2 Hounsfield Units (HU) for the recurrence group and − 594.1 ± 11.6 HU for the non-recurrence group (p < 0.0001). Recurrence occurred in 45 patients (9.1%). The tumor recurrence group was strongly associated with a high CT attenuation value, high C/T ratio, large solid tumor size, and SUV. The diagnostic value of mCT value was more accurate than the C/T ratio, excluding the pure ground-glass opacity and pure solid (0 < C/T ratio < 100) groups. The SUV and mCT are independent predictive factors of tumor recurrence. CONCLUSIONS: The evaluation of mCT values was useful for predicting recurrence after the limited resection of small-sized NSCLC, and may potentially contribute to the selection of suitable treatment strategies. BioMed Central 2021-05-12 /pmc/articles/PMC8117299/ /pubmed/33980268 http://dx.doi.org/10.1186/s13019-021-01476-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Tamura, Masaya
Matsumoto, Isao
Tanaka, Yusuke
Saito, Daisuke
Yoshida, Shuhei
Takata, Munehisa
Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title_full Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title_fullStr Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title_full_unstemmed Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title_short Predicting recurrence of non-small cell lung cancer based on mean computed tomography value
title_sort predicting recurrence of non-small cell lung cancer based on mean computed tomography value
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8117299/
https://www.ncbi.nlm.nih.gov/pubmed/33980268
http://dx.doi.org/10.1186/s13019-021-01476-0
work_keys_str_mv AT tamuramasaya predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue
AT matsumotoisao predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue
AT tanakayusuke predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue
AT saitodaisuke predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue
AT yoshidashuhei predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue
AT takatamunehisa predictingrecurrenceofnonsmallcelllungcancerbasedonmeancomputedtomographyvalue