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

[1]  A. Crombé,et al.  Natural Changes in Radiological and Radiomics Features on MRIs of Soft‐Tissue Sarcomas Naïve of Treatment: Correlations With Histology and Patients' Outcomes , 2021, Journal of magnetic resonance imaging : JMRI.

[2]  Shulian Wang,et al.  Radiomics Analysis of Fat-Saturated T2-Weighted MRI Sequences for the Prediction of Prognosis in Soft Tissue Sarcoma of the Extremities and Trunk Treated With Neoadjuvant Radiotherapy , 2021, Frontiers in Oncology.

[3]  P. Lambin,et al.  MRI-based Delta-Radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy. , 2021, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

[4]  P. Rodrigues-Santos,et al.  The Role of Natural Killer Cells in Soft Tissue Sarcoma: Prospects for Immunotherapy , 2021, Cancers.

[5]  A. B. Hassan,et al.  Soft tissue and visceral sarcomas: ESMO-EURACAN-GENTURIS Clinical Practice Guidelines for diagnosis, treatment and follow-up. , 2021, Annals of oncology : official journal of the European Society for Medical Oncology.

[6]  P. Lambin,et al.  Prognostic Assessment in High-Grade Soft-Tissue Sarcoma Patients: A Comparison of Semantic Image Analysis and Radiomics , 2021, Cancers.

[7]  Chencui Huang,et al.  Magnetic Resonance Imaging‐Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two‐Center Study , 2020, Journal of magnetic resonance imaging : JMRI.

[8]  O. Husson,et al.  The sarcoma diagnostic interval: a systematic review on length, contributing factors and patient outcomes , 2020, ESMO Open.

[9]  X. Buy,et al.  Can radiomics improve the prediction of metastatic relapse of myxoid/round cell liposarcomas? , 2020, European Radiology.

[10]  Olivier Saut,et al.  High‐Grade Soft‐Tissue Sarcomas: Can Optimizing Dynamic Contrast‐Enhanced MRI Postprocessing Improve Prognostic Radiomics Models? , 2020, Journal of magnetic resonance imaging : JMRI.

[11]  D. Hao,et al.  Radiomics and Machine Learning With Multiparametric Preoperative MRI May Accurately Predict the Histopathological Grades of Soft Tissue Sarcomas , 2019, Journal of magnetic resonance imaging : JMRI.

[12]  M. A. Shouman,et al.  Tumor grading of soft tissue sarcomas using MRI-based radiomics , 2019, EBioMedicine.

[13]  L. Fayad,et al.  Magnetic resonance imaging biomarkers in musculoskeletal soft tissue tumors: Review of conventional features and focus on nonmorphologic imaging , 2019, Journal of magnetic resonance imaging : JMRI.

[14]  X. Buy,et al.  Soft-Tissue Sarcomas: Assessment of MRI Features Correlating with Histologic Grade and Patient Outcome. , 2019, Radiology.

[15]  D. Hippe,et al.  MRI Radiomic Features Are Independently Associated With Overall Survival in Soft Tissue Sarcoma , 2019, Advances in radiation oncology.

[16]  Olivier Saut,et al.  T2‐based MRI Delta‐radiomics improve response prediction in soft‐tissue sarcomas treated by neoadjuvant chemotherapy. , 2019, Journal of magnetic resonance imaging : JMRI.

[17]  X. Buy,et al.  MRI assessment of surrounding tissues in soft-tissue sarcoma during neoadjuvant chemotherapy can help predicting response and prognosis. , 2018, European journal of radiology.

[18]  L. Mainardi,et al.  Radiomic analysis of soft tissues sarcomas can distinguish intermediate from high‐grade lesions , 2018, Journal of magnetic resonance imaging : JMRI.

[19]  P. Lambin,et al.  Radiomics: the bridge between medical imaging and personalized medicine , 2017, Nature Reviews Clinical Oncology.

[20]  A. Sudo,et al.  Infiltrative tumor growth patterns on magnetic resonance imaging associated with systemic inflammation and oncological outcome in patients with high-grade soft-tissue sarcoma , 2017, PloS one.

[21]  N. Paragios,et al.  Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology , 2017, Annals of oncology : official journal of the European Society for Medical Oncology.

[22]  L. Mariani,et al.  Development and external validation of two nomograms to predict overall survival and occurrence of distant metastases in adults after surgical resection of localised soft-tissue sarcomas of the extremities: a retrospective analysis. , 2016, The Lancet. Oncology.

[23]  Ash A. Alizadeh,et al.  Robust enumeration of cell subsets from tissue expression profiles , 2015, Nature Methods.

[24]  Shivani Ahlawat,et al.  Can MR imaging be used to predict tumor grade in soft-tissue sarcoma? , 2014, Radiology.

[25]  Charles Marion,et al.  ITK: enabling reproducible research and open science , 2014, Front. Neuroinform..

[26]  Charity W. Law,et al.  voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.

[27]  David M. Thomas,et al.  Prevailing importance of the hedgehog signaling pathway and the potential for treatment advancement in sarcoma. , 2012, Pharmacology & therapeutics.

[28]  Matthew D. Wilkerson,et al.  ConsensusClusterPlus: a class discovery tool with confidence assessments and item tracking , 2010, Bioinform..

[29]  Brian B. Avants,et al.  N4ITK: Improved N3 Bias Correction , 2010, IEEE Transactions on Medical Imaging.

[30]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[31]  L. White,et al.  Histologic assessment of peritumoral edema in soft tissue sarcoma. , 2005, International journal of radiation oncology, biology, physics.

[32]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[33]  L G Nyúl,et al.  On standardizing the MR image intensity scale , 1999, Magnetic resonance in medicine.

[34]  F. Collin,et al.  Prognostic factors in adult patients with locally controlled soft tissue sarcoma. A study of 546 patients from the French Federation of Cancer Centers Sarcoma Group. , 1996, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[35]  D. Parham,et al.  Muscle edema in musculoskeletal tumors: MR imaging characteristics and clinical significance , 1991, Journal of magnetic resonance imaging : JMRI.

[36]  J. Coindre,et al.  Soft‐tissue sarcomas of adults; study of pathological prognostic variables and definition of a histopathological grading system , 1984, International journal of cancer.