The strongest adverse prognostic factor in myxoid/round cell liposarcomas (MRC-LPS) is the presence of a round cell component above 5% within the tumor bulk. Its identification is underestimated on biopsies and in the neoadjuvant setting. The aim was to improve the prediction of patients’ prognosis through a radiomics approach.
Thirty-five out of 89 patients with MRC-LPS managed at our sarcoma reference center from 2008 to 2017 were included in this IRB-approved retrospective study as they presented with a pre-treatment contrast-enhanced MRI (median age, 49 years old). Two radiologists reported usual conventional/semantic radiological variables. After signal intensity (SI) normalization, voxel size standardization of T2-WI, and whole tumor volume segmentation, 44 3D-radiomics features were extracted. Using least absolute shrinkage and selection operator penalized Cox regression on prefiltered features, a radiomics score based on 3 weighted radiomics features was generated. Four prognostic multivariate models for MRFS were compared using concordance index: (1) clinical model, (2) semantic radiological model, (3) radiomics model, and (4) radiomics + semantic radiological model.
Twelve patients showed a metastatic relapse. The radiomics score included FOS_Skewness, GLRLM_LRHGE, and SHAPE_Volume and correlated with MRFS (hazard ratio = 19.37, p = 0.0009) and visual heterogeneity on T2-WI (p < 0.0001). A high score indicated a poorer prognosis. After adjustment, the best predictive performances were obtained with model (4) (concordance index = 0.937) and the lowest with model (1) (concordance index = 0.637).
Adding selected radiomics features that quantify tumor heterogeneity and shape at baseline to a conventional radiological analysis improves prediction of MRC-LPS patients’ prognosis.
• Fourteen radiomics features quantifying shape and heterogeneity of myxoid/round cell liposarcomas on T2-WI were associated with metastatic relapse in univariate analysis.
• A radiomics score based on 3 selected and weighted radiomics features was a strong and independent prognostic factor for metastatic relapse-free survival.
• The best prediction of metastatic relapse-free survival for myxoid/round cell liposarcomas was achieved by combining the radiomics score to relevant radiological features.
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95% confidence interval
Least absolute shrinkage and selection operator
Myxoid round cell liposarcoma
Metastatic relapse-free survival
Turbo spin echo
World Health Organization performance status
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The authors would like to thank Erwan Le Masson (MSc) for his help regarding the normalization of MRIs, as well as Mrs Camille Martinerie for medical writing services.
The authors state that this work has not received any funding.
The scientific guarantor of this publication is Dr Xavier Buy, MD, head of the department of radiology at Bergonie Insitut, Bordeaux, France
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The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
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One of the authors has significant statistical expertise (A.C., PhD student in applied mathematics and in statistical modelling at INRIA Bordeaux). No complex statistical methods were necessary for this paper. The R script for the main findings and figures can be available from the corresponding author on reasonable request.
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Electronic supplementary material
Inter-observer agreements for the semantic radiological variables. Supplementary Data 2. Correlation plot of the radiomics features associated with metastatic relapse-free survival in univariate analysis. (DOCX 420 kb)
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Crombé, A., Le Loarer, F., Sitbon, M. et al. Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?. Eur Radiol (2020). https://doi.org/10.1007/s00330-019-06562-5
- Patient-specific modeling
- Liposarcomas, myxoid
- Magnetic resonance imaging