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Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma.

Journal of clinical medicine | 2021

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.

Pubmed ID: 34640425 RIS Download

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SPSS (tool)

RRID:SCR_002865

Software package used for interactive, or batched, statistical analysis in social science, health sciences and marketing. Software platform offers advanced statistical analysis, a library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and deployment into applications.Versions that were produced by SPSS Inc. before the IBM acquisition (Versions 18 and earlier) would be given origin or publisher of SPSS Inc. in Chicago.

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3D Slicer (tool)

RRID:SCR_005619

A free, open source software package for visualization and image analysis including registration, segmentation, and quantification of medical image data. Slicer provides a graphical user interface to a powerful set of tools so they can be used by end-user clinicians and researchers alike. 3D Slicer is natively designed to be available on multiple platforms, including Windows, Linux and Mac Os X. Slicer is based on VTK (http://public.kitware.com/vtk) and has a modular architecture for easy addition of new functionality. It uses an XML-based file format called MRML - Medical Reality Markup Language which can be used as an interchange format among medical imaging applications. Slicer is primarily written in C++ and Tcl.

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