Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment

F-FDG PET/CT enable sensitive detection of metastatic disease, with PET providing metabolic biomarkers correlated with prognosis and chemotherapy response. Imaging features, including tumor volume, diffusion metrics, and changes in contrast enhancement, increasingly allow non-invasive prediction of histologic response, a key determinant of survival. Lastly, recent quantitative methods, such as radiomics and artificial intelligence, show promise for differentiating Ewing sarcoma from other sarcomas, predicting metastases, and anticipating local recurrence. By reviewing modality-specific findings, staging strategies, and response assessment tools, this article provides a practical, updated, structured framework for radiologists and oncologists to optimize diagnosis, risk stratification, and treatment planning in Ewing sarcoma, ultimately improving patient care.

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Publication Details

Journal
Skeletal Radiology
Published
2026-04-30
DOI
https://doi.org/10.1007/s00256-026-05238-8
Primary Topic
Sarcoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment

Hisaki Aiba, Amandine Crombé, George R. Matcuk, Costantino Errani et al.
Skeletal Radiology
Sarcoma Diagnosis and Treatment
article

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment

Hisaki Aiba, Amandine Crombé, George R. Matcuk, Costantino Errani, Paolo Spinnato, Tanya Tivorsak, Christopher T Watterson
article en

Abstract

F-FDG PET/CT enable sensitive detection of metastatic disease, with PET providing metabolic biomarkers correlated with prognosis and chemotherapy response. Imaging features, including tumor volume, diffusion metrics, and changes in contrast enhancement, increasingly allow non-invasive prediction of histologic response, a key determinant of survival. Lastly, recent quantitative methods, such as radiomics and artificial intelligence, show promise for differentiating Ewing sarcoma from other sarcomas, predicting metastases, and anticipating local recurrence. By reviewing modality-specific findings, staging strategies, and response assessment tools, this article provides a practical, updated, structured framework for radiologists and oncologists to optimize diagnosis, risk stratification, and treatment planning in Ewing sarcoma, ultimately improving patient care.

Skeletal Radiology
Cedars-Sinai Medical Center (US), Université de Bordeaux (FR), Inserm (FR), Institut Gustave Roussy (FR), Nagoya City University (JP), Bordeaux Population Health (FR), Hôpital Pellegrin (FR), Nagoya City University Hospital (JP), S. Mark Taper Foundation (US), Istituto Ortopedico Rizzoli (IT), Imaging Center (US)
Cedars-Sinai Medical Center
Good health and well-being
Openalex Percentile: Top 11%
Sarcoma Diagnosis and Treatment
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