Literature DB >> 29317048

Imaging skeletal muscle volume, density, and FDG uptake before and after induction therapy for non-small cell lung cancer.

M D Goncalves1, S Taylor2, D F Halpenny3, E Schwitzer3, S Gandelman3, J Jackson3, A Lukose3, A J Plodkowski3, K S Tan3, M Dunphy3, L W Jones3, R J Downey4.   

Abstract

AIM: To assess whether changes in body composition could be assessed serially using conventional thoracic computed tomography (CT) and positron-emission tomography (PET)/CT imaging in patients receiving induction chemotherapy for non-small cell lung cancer (NSCLC).
MATERIALS AND METHODS: CT-based skeletal muscle volume and density were measured retrospectively from thoracic and lumbar segment CT images from 88 patients with newly diagnosed and untreated NSCLC before and after induction chemotherapy. Skeletal muscle 2-[18F]-fluoro-2-deoxy-d-glucose (FDG) uptake was measured from PET/CT images from a subset of patients (n=42). Comparisons of each metric before and after induction chemotherapy were conducted using the non-parametric Wilcoxon signed-rank test for paired data. The association between clinical factors and percentage change in muscle volume was examined using univariate linear regression models, with adjustment for baseline muscle volume.
RESULTS: Following induction chemotherapy, thoracic (-3.3%, p=0.0005) and lumbar (-2.6%, p=0.0101) skeletal muscle volume were reduced (adiposity remained unchanged). The proportion of skeletal muscle with a density <0 HU increased (7.9%, p<0.0001), reflecting a decrease in skeletal muscle density and skeletal muscle FDG uptake increased (10.4-31%, p<0.05). No imaging biomarkers were correlated with overall survival.
CONCLUSION: Changes in body composition can be measured from routine thoracic imaging. During chemotherapy skeletal muscle volume and metabolism are altered; however, there was no impact on survival in this retrospective series, and further validation in prospective, well-controlled studies are required.
Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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Year:  2018        PMID: 29317048      PMCID: PMC6785997          DOI: 10.1016/j.crad.2017.12.004

Source DB:  PubMed          Journal:  Clin Radiol        ISSN: 0009-9260            Impact factor:   2.350


  54 in total

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  4 in total

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