Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment.
Authors
Affiliations (8)
Affiliations (8)
- Department of Imaging, S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Ste M-335, Los Angeles, CA, 90048, USA. [email protected].
- Department of Imaging, S. Mark Taper Foundation Imaging Center, Cedars-Sinai Medical Center, 8700 Beverly Blvd, Ste M-335, Los Angeles, CA, 90048, USA.
- Department of Orthopedic Oncology, IRCCS Istituto Ortopedico Rizzoli, 40136, Bologna, Italy.
- Department of Orthopedic Surgery, Nagoya City University, Nagoya, Aichi, 467-8601, Japan.
- Department of Diagnostic Oncologic Imaging, Gustave Roussy Institute, 94805, Villejuif, France.
- Department of Musculoskeletal Imaging, Pellegrin University Hospital, 33076, Bordeaux, France.
- SARCOTARGET Team, Bordeaux Research Institute in Oncology (BRIC) INSERM U1312 and University of Bordeaux, 33076, Bordeaux, France.
- Diagnostic and Interventional Radiology, IRCCS Istituto Ortopedico Rizzoli, 40136, Bologna, Italy.
Abstract
Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adolescents. Imaging plays a central role from diagnosis to staging, treatment response assessment, and follow-up. This review synthesizes current evidence across the various imaging modalities involved at each stage of patient management, including conventional radiography, CT, MRI, and nuclear imaging, emphasizing their complementary roles. Radiographs and CT delineate bone destruction patterns, cortical breaches, and periosteal reactions, while MRI provides superior visualization of intramedullary and soft tissue extension, as well as skip lesions. Whole-body MRI and <sup>18</sup>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.