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This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

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On page 1 showing 1 ~ 2 papers out of 2 papers

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

  • Alice Bellini‎ et al.
  • 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.


Radiomics of spinal muscles: toward a radiological biomarker for allograft rejection in lung transplant.

  • Chiara Giraudo‎ et al.
  • La Radiologia medica‎
  • 2023‎

To assess the role of muscle composition and radiomics in predicting allograft rejection in lung transplant.


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