Soft tissue tumor imaging in adults: whole-body staging in sarcoma, non-malignant entities requiring special algorithms, pitfalls and special imaging aspects. Guidelines 2024 from the European Society of Musculoskeletal Radiology (ESSR)

The revised European Society of Musculoskeletal Radiology (ESSR) consensus guidelines on soft tissue tumor imaging represent an update of 2015 after technical advancements, further insights into specific entities, and revised World Health Organization (2020) and AJCC (2017) classifications. This sec...

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Published inEuropean radiology
Main Authors Noebauer-Huhmann, Iris-Melanie, Vanhoenacker, Filip M, Vilanova, Joan C, Tagliafico, Alberto S, Weber, Marc-André, Lalam, Radhesh K, Grieser, Thomas, Nikodinovska, Violeta Vasilevska, de Rooy, Jacky W J, Papakonstantinou, Olympia, Mccarthy, Catherine, Sconfienza, Luca Maria, Verstraete, Koenraad, Martel-Villagrán, José, Szomolanyi, Pavol, Lecouvet, Frédéric E, Afonso, Diana, Albtoush, Omar M, Aringhieri, Giacomo, Arkun, Remide, Aström, Gunnar, Bazzocchi, Alberto, Botchu, Rajesh, Breitenseher, Martin, Chaudhary, Snehansh, Dalili, Danoob, Davies, Mark, de Jonge, Milko C, Mete, Berna D, Fritz, Jan, Gielen, Jan L M A, Hide, Geoff, Isaac, Amanda, Ivanoski, Slavcho, Mansour, Ramy M, Muntaner-Gimbernat, Lorenzo, Navas, Ana, O Donnell, Paul, Örgüç, Şebnem, Rennie, Winston J, Resano, Santiago, Robinson, Philip, Sanal, Hatice T, Ter Horst, Simone A J, van Langevelde, Kirsten, Wörtler, Klaus, Koelz, Marita, Panotopoulos, Joannis, Windhager, Reinhard, Bloem, Johan L
Format Journal Article
LanguageEnglish
Published Germany 20.07.2024
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Summary:The revised European Society of Musculoskeletal Radiology (ESSR) consensus guidelines on soft tissue tumor imaging represent an update of 2015 after technical advancements, further insights into specific entities, and revised World Health Organization (2020) and AJCC (2017) classifications. This second of three papers covers algorithms once histology is confirmed: (1) standardized whole-body staging, (2) special algorithms for non-malignant entities, and (3) multiplicity, genetic tumor syndromes, and pitfalls. A validated Delphi method based on peer-reviewed literature was used to derive consensus among a panel of 46 specialized musculoskeletal radiologists from 12 European countries. Statements that had undergone interdisciplinary revision were scored online by the level of agreement (0 to 10) during two iterative rounds, that could result in 'group consensus', 'group agreement', or 'lack of agreement'. The three sections contain 24 statements with comments. Group consensus was reached in 95.8% and group agreement in 4.2%. For whole-body staging, pulmonary MDCT should be performed in all high-grade sarcomas. Whole-body MRI is preferred for staging bone metastasis, with [ F]FDG-PET/CT as an alternative modality in PET-avid tumors. Patients with alveolar soft part sarcoma, clear cell sarcoma, and angiosarcoma should be screened for brain metastases. Special algorithms are recommended for entities such as rhabdomyosarcoma, extraskeletal Ewing sarcoma, myxoid liposarcoma, and neurofibromatosis type 1 associated malignant peripheral nerve sheath tumors. Satisfaction of search should be avoided in potential multiplicity. Standardized whole-body staging includes pulmonary MDCT in all high-grade sarcomas; entity-dependent modifications and specific algorithms are recommended for sarcomas and non-malignant soft tissue tumors. These updated ESSR soft tissue tumor imaging guidelines aim to provide support in decision-making, helping to avoid common pitfalls, by providing general and entity-specific algorithms, techniques, and reporting recommendations for whole-body staging in sarcoma and non-malignant soft tissue tumors. An early, accurate, diagnosis is crucial for the prognosis of patients with soft tissue tumors. These updated guidelines provide best practice expert consensus for standardized imaging algorithms, techniques, and reporting. Standardization can improve the comparability examinations and provide databases for large data analysis.
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ISSN:1432-1084
1432-1084
DOI:10.1007/s00330-024-10897-z