Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma

Our plain-English summary of Computed Tomography and Spirometry Can Predict Unresectability in Malignant Pleural Mesothelioma, by A. Bellini, A. Dell'Amore, C. Giraudo, et al (Journal of Clinical Medicine, 2021).

The study

• Authors: A. Bellini, A. Dell'Amore, C. Giraudo, A. Modugno, N. Bernardinello, S. Terzi, G. Zambello, G. Pasello, A. Zuin, F. Rea
• Journal: Journal of Clinical Medicine
• Published: 2021;10(19)
• Cited by: 2 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

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.

In plain English

This retrospective study from Padova University Hospital, Italy, reviewed 291 patients with malignant pleural mesothelioma. They were operated on between July 1994 and August 2020, after induction chemotherapy, with the aim of removing all visible tumor. Of these, 58 had a suitable preoperative CT scan without pleural effusion or hydropneumothorax. All visible and palpable tumor was removed in 43 patients. In 15 (25.9%) it was found unresectable at operation, 13 of them because of diffuse chest wall invasion. The authors compared CT lung volumes, a summed tumor-thickness score called "disease burden", and lung function tests. In multivariable analysis, total lung capacity (odds ratio 0.920, 95% CI 0.853 to 0.992) and disease burden (odds ratio 1.020, 95% CI 1.003 to 1.038) were independent predictors of unresectability. The suggested cut-offs were total lung capacity below 77.5% of predicted and disease burden above 120.5 mm. Lung volumes were linked to unresectability only in univariable analysis. The study did not examine asbestos exposure. The authors concluded these measures could predict unresectability, and they called for larger prospective studies.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Retrospective single-center study of surgical patients, comparing those who had macroscopic complete resection with those found unresectable at operation, using univariable and multivariable regression analysis
• Who was studied: 291 patients with malignant pleural mesothelioma at Padova University Hospital, Italy, operated on between July 1994 and August 2020 after induction chemotherapy, with the aim of macroscopic complete resection. Of these, 58 were eligible because they had a preoperative 3 mm slice-thickness chest CT without pleural effusion or hydropneumothorax. Of the 58, 43 had macroscopic complete resection (removal of all visible and palpable tumor) and 15 had an unresectable tumor.
• Exposure: Asbestos exposure was not studied; the introduction only describes mesothelioma as asbestos-related. The possible predictors of unresectability were measured after induction chemotherapy (platinum with pemetrexed or gemcitabine, two to six cycles). They were CT-measured aerated lung volumes, pleural thickness summed as 'disease burden' under modified RECIST criteria, and lung function tests expressed as percentage of predicted, including total lung capacity (TLC%).
• Main results:
  • Of the 58 eligible patients, 43 had macroscopic complete resection: 33 by pleurectomy/decortication and 10 by extrapleural pneumonectomy. Fifteen had unresectable disease (25.9% of cases): 13 due to diffuse chest wall invasion, 1 due to aortic adventitia infiltration and 1 due to diaphragmatic pillar infiltration.
  • Median total lung capacity (percentage of predicted) was 89% (IQR 79 to 97) in the macroscopic complete resection group and 75% (IQR 71 to 80) in the unresectable group (p = 0.003).
  • Median disease burden was 57 mm (IQR 36 to 99) in the macroscopic complete resection group and 133 mm (IQR 70 to 181) in the unresectable group (p = 0.001).
  • In multivariable analysis, only TLC% (p = 0.03, OR 0.920, 95% CI 0.853 to 0.992) and disease burden (p = 0.02, OR 1.020, 95% CI 1.003 to 1.038) were independent predictors of unresectability.
  • Optimal cut-offs were TLC below 77.5% of predicted (AUC 0.81, sensitivity 73.3%, specificity 80%) and disease burden above 120.5 mm (AUC 0.77, sensitivity 60%, specificity 90.7%).
  • In the unresectable group, 11 of 15 (73%) had TLC below 77.5%, 9 of 15 (60%) had disease burden above 120.5 mm, and 5 (33%) had both.
  • In the macroscopic complete resection group, 36 of 43 (84%) had TLC of 77.5% or more, 39 (91%) had disease burden of 120.5 mm or less, and 34 (79%) had both.
  • CT-measured aerated lung volumes were associated with unresectability only in univariable analysis. The authors attributed this probably to their correlation with disease burden.
• The authors' conclusion: The authors concluded that disease burden and TLC% could predict unresectability of malignant pleural mesothelioma. They added that the findings should be validated by prospective studies with larger samples.
• Limitations the authors state:
  • The study was retrospective.
  • Lung function test results depend strongly on patient compliance and could be impaired by inadequate pain control.
  • Most patients had received talc pleurodesis, and the authors could not evaluate its influence on lung function tests and radiological assessment.
  • Patients with pleural effusion or hydropneumothorax were excluded because these could interfere with the measurements.
  • MRI, which the authors say is better than CT for predicting chest wall invasion, was not routinely performed.

Topics

Medical terms in this study, explained in our Lexicon: Spirometry, Pleural Mesothelioma, Unresectable Pleural Mesothelioma, Hemithorax, Thoracotomy, Mesothelioma, Chemotherapy, Pleural Effusion.

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• Sarcopenia as a Predictor of Short- and Long-Term Outcomes in Patients Surgically Treated for Malignant Pleural Mesothelioma — E. Faccioli, S. Terzi, et al. (2022)
• Relapse Patterns and Tailored Treatment Strategies for Malignant Pleural Mesothelioma Recurrence after Multimodality Therapy — A. Bellini, A. Dell'Amore, et al. (2021)
• Predictive accuracy of the Liverpool Lung Project risk model for stratifying patients for computed tomography screening for lung cancer: a case-control and cohort validation study — O.Y. Raji, S.W. Duffy, et al. (2012)
• High resolution computed tomography and lung function in asbestos-exposed workers with normal chest radiographs — C.A. Staples, G. Gamsu, et al. (1989)
• Computed tomography features in malignant pleural mesothelioma and other commonly seen pleural diseases — M. Metintas, I. Ucgun, et al. (2002)

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