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Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma

Preoperative identification of unresectable pleural mesothelioma could spare unnecessary surgical intervention and accelerate the initiation of medical treatments. The aim of this study is to determine predictors of unresectability, testing our impression that the contraction of the ipsilateral hemi...

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Autores principales: Bellini, Alice, Dell’Amore, Andrea, Giraudo, Chiara, Modugno, Antonella, Bernardinello, Nicol, Terzi, Stefano, Zambello, Giovanni, Pasello, Giulia, Zuin, Andrea, Rea, Federico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8509574/
https://www.ncbi.nlm.nih.gov/pubmed/34640425
http://dx.doi.org/10.3390/jcm10194407
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author Bellini, Alice
Dell’Amore, Andrea
Giraudo, Chiara
Modugno, Antonella
Bernardinello, Nicol
Terzi, Stefano
Zambello, Giovanni
Pasello, Giulia
Zuin, Andrea
Rea, Federico
author_facet Bellini, Alice
Dell’Amore, Andrea
Giraudo, Chiara
Modugno, Antonella
Bernardinello, Nicol
Terzi, Stefano
Zambello, Giovanni
Pasello, Giulia
Zuin, Andrea
Rea, Federico
author_sort Bellini, Alice
collection PubMed
description Preoperative identification of unresectable pleural mesothelioma could spare unnecessary surgical intervention and accelerate the initiation of medical treatments. The aim of this study is to determine predictors of unresectability, testing our impression that the contraction of the ipsilateral hemithorax is often associated with exploratory thoracotomy. Between 1994 and 2020, 291 patients undergoing intended macroscopic complete resection for mesothelioma after chemotherapy were retrospectively investigated. Eligible patients (n = 58) presented a preoperative 3 mm slice-thickness chest computed tomography without pleural effusion or hydropneumothorax. Lung volumes (segmented using a semi-automated method), modified-Response Evaluation Criteria in Solid Tumors (RECIST) measurements, and spirometries were collected after chemotherapy. Multivariable analysis was performed to determine the predictors of unresectability. An unresectable disease was found at the time of operation in 25.9% cases. By multivariable analysis, the total lung capacity (p = 0.03) and the disease burden (p = 0.02) were found to be predictors of unresectability; cut-off values were <77.5% and >120.5 mm, respectively. Lung volumes were not confirmed to be associated with unresectability at multivariable analysis, probably due to the correlation with the disease burden (p < 0.001; r = −0.4). Our study suggests that disease burden and total lung capacity could predict MPM unresectability, helping surgeons in recommending surgery or not in a multimodality setting.
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spelling pubmed-85095742021-10-13 Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma Bellini, Alice Dell’Amore, Andrea Giraudo, Chiara Modugno, Antonella Bernardinello, Nicol Terzi, Stefano Zambello, Giovanni Pasello, Giulia Zuin, Andrea Rea, Federico J Clin Med Article Preoperative identification of unresectable pleural mesothelioma could spare unnecessary surgical intervention and accelerate the initiation of medical treatments. The aim of this study is to determine predictors of unresectability, testing our impression that the contraction of the ipsilateral hemithorax is often associated with exploratory thoracotomy. Between 1994 and 2020, 291 patients undergoing intended macroscopic complete resection for mesothelioma after chemotherapy were retrospectively investigated. Eligible patients (n = 58) presented a preoperative 3 mm slice-thickness chest computed tomography without pleural effusion or hydropneumothorax. Lung volumes (segmented using a semi-automated method), modified-Response Evaluation Criteria in Solid Tumors (RECIST) measurements, and spirometries were collected after chemotherapy. Multivariable analysis was performed to determine the predictors of unresectability. An unresectable disease was found at the time of operation in 25.9% cases. By multivariable analysis, the total lung capacity (p = 0.03) and the disease burden (p = 0.02) were found to be predictors of unresectability; cut-off values were <77.5% and >120.5 mm, respectively. Lung volumes were not confirmed to be associated with unresectability at multivariable analysis, probably due to the correlation with the disease burden (p < 0.001; r = −0.4). Our study suggests that disease burden and total lung capacity could predict MPM unresectability, helping surgeons in recommending surgery or not in a multimodality setting. MDPI 2021-09-26 /pmc/articles/PMC8509574/ /pubmed/34640425 http://dx.doi.org/10.3390/jcm10194407 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bellini, Alice
Dell’Amore, Andrea
Giraudo, Chiara
Modugno, Antonella
Bernardinello, Nicol
Terzi, Stefano
Zambello, Giovanni
Pasello, Giulia
Zuin, Andrea
Rea, Federico
Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title_full Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title_fullStr Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title_full_unstemmed Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title_short Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma
title_sort computed tomography and spirometry can predict unresectability in malignant pleural mesothelioma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8509574/
https://www.ncbi.nlm.nih.gov/pubmed/34640425
http://dx.doi.org/10.3390/jcm10194407
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