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Aghakhanyan G, Filidei T, Febi M, Fanni SC, Marciano A, Francischello R, Caputo FP, Tumminello L, Cioni D, Neri E, Volterrani D. Advancing Pediatric Sarcomas through Radiomics: A Systematic Review and Prospective Assessment Using Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS). Diagnostics (Basel) 2024; 14:832. [PMID: 38667477 PMCID: PMC11049622 DOI: 10.3390/diagnostics14080832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 04/28/2024] Open
Abstract
Pediatric sarcomas, rare malignancies of mesenchymal origin, pose diagnostic and therapeutic challenges. In this review, we explore the role of radiomics in reshaping our understanding of pediatric sarcomas, emphasizing methodological considerations and applications such as diagnostics and predictive modeling. A systematic review conducted up to November 2023 identified 72 papers on radiomics analysis in pediatric sarcoma from PubMed/MEDLINE, Web of Knowledge, and Scopus. Following inclusion and exclusion criteria, 10 reports were included in this review. The studies, predominantly retrospective, focus on Ewing sarcoma and osteosarcoma, utilizing diverse imaging modalities, including CT, MRI, PET/CT, and PET/MRI. Manual segmentation is common, with a median of 35 features extracted. Radiomics Quality Score (RQS) and Methodological Radiomics Score (METRICS) assessments reveal a consistent emphasis on non-radiomic features, validation criteria, and improved methodological rigor in recent publications. Diagnostic applications dominate, with innovative studies exploring prognostic and treatment response aspects. Challenges include feature heterogeneity and sample size variations. The evolving landscape underscores the need for standardized methodologies. Despite challenges, the diagnostic and predictive potential of radiomics in pediatric oncology is evident, paving the way for precision medicine advancements.
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Affiliation(s)
- Gayane Aghakhanyan
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Tommaso Filidei
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Maria Febi
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Salvatore C. Fanni
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Andrea Marciano
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
| | - Roberto Francischello
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Francesca Pia Caputo
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Lorenzo Tumminello
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Dania Cioni
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Emanuele Neri
- Department of Translational Research and of New Surgical and Medical Technology, Academic Radiology, University of Pisa, 56126 Pisa, Italy (D.C.)
| | - Duccio Volterrani
- Department of Translational Research and of New Surgical and Medical Technology, University of Pisa, 56126 Pisa, Italy
- Regional Center of Nuclear Medicine, University Hospital of Pisa, 56126 Pisa, Italy
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Preclinical In Vivo Modeling of Pediatric Sarcoma-Promises and Limitations. J Clin Med 2021; 10:jcm10081578. [PMID: 33918045 PMCID: PMC8069549 DOI: 10.3390/jcm10081578] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Revised: 04/05/2021] [Accepted: 04/06/2021] [Indexed: 02/07/2023] Open
Abstract
Pediatric sarcomas are an extremely heterogeneous group of genetically distinct diseases. Despite the increasing knowledge on their molecular makeup in recent years, true therapeutic advancements are largely lacking and prognosis often remains dim, particularly for relapsed and metastasized patients. Since this is largely due to the lack of suitable model systems as a prerequisite to develop and assess novel therapeutics, we here review the available approaches to model sarcoma in vivo. We focused on genetically engineered and patient-derived mouse models, compared strengths and weaknesses, and finally explored possibilities and limitations to utilize these models to advance both biological understanding as well as clinical diagnosis and therapy.
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