Evidence map›Paper›PMID 31953663›Full record

ArticleEuropean radiology2020

Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas?

Amandine Crombé, François Le Loarer, Maxime Sitbon, Antoine Italiano, Eberhard Stoeckle, Xavier Buy, Michèle Kind

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Article in European radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.2field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
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  6. Diagnosis and Treatment of Myxoid Liposarcoma.Current treatment options in oncology · 2024
    Review
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  11. Review
  12. Myxoid Liposarcoma: How to Stage and Follow.Current treatment options in oncology · 2023
    Review
  13. Review
  14. Article
  15. Magnetic resonance imaging of soft tissue sarcoma: features related to prognosis.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2021
    Review
  16. Article
  17. Review
  18. Review
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Amandine CrombéDepartment of Radiology, Institut Bergonie, F-33000, Bordeaux, France. a.crombe@bordeaux.unicancer.fr.ORCID http://orcid.org/0000-0003-0098-6482
François Le LoarerUniversity of Bordeaux, F-33000, Bordeaux, France.
Maxime SitbonDepartment of Radiology, Institut Bergonie, F-33000, Bordeaux, France.
Antoine ItalianoDepartment of Surgery, Institut Bergonie, F-33000, Bordeaux, France.
Eberhard StoeckleDepartment of Medical Oncology, Institut Bergonie, F-33000, Bordeaux, France.
Xavier BuyDepartment of Radiology, Institut Bergonie, F-33000, Bordeaux, France.
Michèle KindDepartment of Radiology, Institut Bergonie, F-33000, Bordeaux, France.
Institut Bergonié · FRCentre National de la Recherche Scientifique · FRUniversité de Bordeaux · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe 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.

methodsThirty-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.

resultsTwelve 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).

conclusionAdding selected radiomics features that quantify tumor heterogeneity and shape at baseline to a conventional radiological analysis improves prediction of MRC-LPS patients' prognosis. KEY POINTS: • 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.

Indexed as

AdultAgedAged, 80 and overBiopsyFemaleHumansLiposarcoma, MyxoidLower ExtremityMagnetic Resonance ImagingMaleMiddle AgedNeoadjuvant TherapyNeoplasm MetastasisNeoplasm Recurrence, LocalPrognosisRecurrenceLiposarcomas, myxoidMagnetic resonance imagingPatient-specific modelingPrognosisSarcoma

Identifiers

PMID31953663
OpenAlexW2999416136

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.