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Distinct patterns of the natural evolution of soft tissue sarcomas on pre-treatment MRIs captured with delta-radiomics correlate with gene expression profiles

  • Oncology
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

Radiomics of soft tissue sarcomas (STS) is assumed to correlate with histologic and molecular tumor features, but radiogenomics analyses are lacking. Our aim was to identify if distinct patterns of natural evolution of STS obtained from consecutive pre-treatment MRIs are associated with differential gene expression (DGE) profiling in a pathway analysis.

Methods

All patients with newly diagnosed STS treated in a curative intent in our sarcoma reference center between 2008 and 2019 and with two available pre-treatment contrast-enhanced MRIs were included in this retrospective study. Radiomics features (RFs) were extracted from fat-sat contrast-enhanced T1-weighted imaging. Log ratio and relative change in RFs were calculated and used to determine grouping of samples based on a consensus hierarchical clustering. DGE and oncogenesis pathway analysis were performed in the delta-radiomics groups identified in order to detect associations between delta-radiomics patterns and transcriptomics features of STS. Secondarily, the prognostic value of the delta-radiomics groups was investigated.

Results

Sixty-three patients were included (median age: 63 years, interquartile range: 52.5–70). The consensus clustering identified 3 reliable delta-radiomics patient groups (A, B, and C). On imaging, group B patients were characterized by increase in tumor heterogeneity, necrotic signal, infiltrative margins, peritumoral edema, and peritumoral enhancement before the treatment start (p value range: 0.0019–0.0244), and, molecularly, by downregulation of natural killer cell–mediated cytotoxicity genes and upregulation of Hedgehog and Hippo signaling pathways. Group A patients were characterized by morphological stability of pre-treatment MRI traits and no local relapse (log-rank p = 0.0277).

Conclusions

This study highlights radiomics and transcriptomics convergence in STS. Proliferation and immune response inhibition were hyper-activated in the STS that were the most evolving on consecutive imaging.

Key Points

• Three consensual and stable delta-radiomics clusters were identified and captured the natural patterns of morphological evolution of STS on pre-treatment MRIs.

• These 3 patterns were explainable and correlated with different well-known semantic radiological features with an ascending gradient of pejorative characteristics from the A group to C group to B group.

• Gene expression profiling stressed distinct patterns of up/downregulated oncogenetic pathways in STS from B group in keeping with its most aggressive radiological evolution.

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Abbreviations

AC:

Absolute change

CE:

Contrast-enhanced

CI:

Confidence interval

DGE:

Differential gene expression

FNCLCC:

French “Fédération Nationale des Centres de Lutte Contre le Cancer”

FS:

Fat sat

HR:

Hazard ratio

IQR:

Interquartile range

IRB:

Institutional Review Board

LD:

Longest diameter

LFS:

Local relapse-free survival

LR:

Log ratio

MFS:

Metastatic relapse-free survival

MRI:

Magnetic resonance imaging

NK:

Natural killer

OS:

Overall survival

RF:

Radiomics feature

RNA:

Ribonucleic acids

SAM:

Significance analysis of microarrays

SI:

Signal intensity

STS:

Soft tissue sarcoma

TSE:

Turbo spin echo

TWAC:

Time-weighted absolute change

TWRC:

Time-weighted relative change

WI:

Weighted imaging

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Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Department of Oncologic Imaging, Institut Bergonié, Comprehensive Cancer Center, F-33076, Bordeaux, France

    Amandine Crombé & Michèle Kind

  2. Models in Oncology (MONC) Team, INRIA Bordeaux Sud-Ouest, CNRS UMR 5251 & Bordeaux University, F-33400, Talence, France

    Amandine Crombé

  3. Department of Musculoskeletal Imaging, Pellegrin University Hospital, 2, place Amélie Raba Léon, F-33000, Bordeaux, France

    Amandine Crombé & David Fadli

  4. Bioinformatics Department, Institut Bergonié, Comprehensive Cancer Center, F-33076, Bordeaux, France

    Frédéric Bertolo & Carlo Lucchesi

  5. Department of Pathology, Institut Bergonié, Comprehensive Cancer Center, F-33076, Bordeaux, France

    François Le Loarer, Raul Perret & Vanessa Chaire

  6. Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, 40136, Bologna, Italy

    Paolo Spinnato

  7. Department of Medical Oncology, Institut Bergonié, Comprehensive Cancer Center, F-33076, Bordeaux, France

    Antoine Italiano

Authors
  1. Amandine Crombé
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  2. Frédéric Bertolo
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  3. David Fadli
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  4. Michèle Kind
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  5. François Le Loarer
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  8. Paolo Spinnato
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  9. Carlo Lucchesi
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  10. Antoine Italiano
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Corresponding author

Correspondence to Amandine Crombé.

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Guarantor

The scientific guarantor of this publication is Prof. Antoine Italiano.

Conflict of interest

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.

Statistics and biometry

Three of the authors have significant statistical expertise (C.L. and F.B. are bioinformaticians; A.C. has a PhD in applied mathematics).

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in the study by Fadli et al [20].

Methodology

• retrospective

• diagnostic or prognostic study/observational/experimental

• performed at one institution

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Crombé, A., Bertolo, F., Fadli, D. et al. Distinct patterns of the natural evolution of soft tissue sarcomas on pre-treatment MRIs captured with delta-radiomics correlate with gene expression profiles. Eur Radiol 33, 1205–1218 (2023). https://doi.org/10.1007/s00330-022-09104-8

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