1. Can radiomics help to predict skeletal muscle response to chemotherapy in stage IV non-small cell lung cancer?
- Author
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E.E.C. De Jong, Timo M. Deist, Juliette H R J Degens, J. van Timmeren, Anne-Marie C. Dingemans, Karin J. C. Sanders, W. Van Elmpt, Ralph T.H. Leijenaar, Annemie M. W. J. Schols, Philippe Lambin, Arthur Jochems, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Promovendi ODB, Radiotherapie, Pulmonologie, RS: NUTRIM - R3 - Respiratory & Age-related Health, Precision Medicine, MUMC+: MA Med Staf Artsass Interne Geneeskunde (9), and MUMC+: MA Med Staf Spec Longziekten (9)
- Subjects
0301 basic medicine ,Oncology ,Male ,Cancer Research ,Cachexia ,Lung Neoplasms ,FEATURES ,law.invention ,Carboplatin ,Cohort Studies ,Nitroglycerin ,0302 clinical medicine ,Non-small cell lung cancer ,Randomized controlled trial ,law ,Carcinoma, Non-Small-Cell Lung ,Antineoplastic Combined Chemotherapy Protocols ,Computed tomography ,Area under the curve ,Middle Aged ,Bevacizumab ,Survival Rate ,medicine.anatomical_structure ,OBESITY ,030220 oncology & carcinogenesis ,Area Under Curve ,SURVIVAL ,Muscle ,CLINICAL-IMPLICATIONS ,Female ,Muscle tissue ,medicine.medical_specialty ,BODY-COMPOSITION ,Paclitaxel ,METABOLISM ,MASS ,03 medical and health sciences ,Internal medicine ,Post-hoc analysis ,medicine ,Humans ,Muscle, Skeletal ,Neoplasm Staging ,Radiomics ,business.industry ,Skeletal muscle ,Cancer ,medicine.disease ,Confidence interval ,030104 developmental biology ,Cross-Sectional Studies ,TISSUE ,business ,Tomography, X-Ray Computed ,LIPOLYSIS ,Follow-Up Studies - Abstract
Background: Muscle depletion negatively impacts treatment efficacy and survival rates in cancer. Prevention and timely treatment of muscle loss require prediction of patients at risk. We aimed to investigate the potential of skeletal muscle radiomic features to predict future muscle loss.Methods: A total of 116 patients with stage IV non-small cell lung cancer included in a randomised controlled trial (NCT01171170) studying the effect of nitroglycerin added to paclitaxel-carboplatin-bevacizumab were enrolled. In this post hoc analysis, muscle cross-sectional area and radiomic features were extracted from computed tomography images obtained before initiation of chemotherapy and shortly after administration of the second cycle. For internal cross-validation, the cohort was randomly split in a training set and validation set 100 times. We used least absolute shrinkage and selection operator method to select features that were most significantly associated with muscle loss and an area under the curve (AUC) for model performance.Results: Sixty-nine patients (59%) exhibited loss of skeletal muscle. One hundred ninety-three features were used to construct a prediction model for muscle loss. The average AUC was 0.49 (95% confidence interval [CI]: 0.36, 0.62). Differences in intensity and texture radiomic features over time were seen between patients with and without muscle loss.Conclusions: The present study shows that skeletal muscle radiomics did not predict future muscle loss during chemotherapy in non-small cell lung cancer. Differences in radiomic features over time might reflect myosteatosis. Future imaging analysis combined with muscle tissue analysis in patients and in experimental models is needed to unravel the biological processes linked to the radiomic features. (C) 2019 The Authors. Published by Elsevier Ltd.
- Published
- 2019