Inferring malignancy grade of soft tissue sarcomas from magnetic resonance imaging features: A systematic review

被引:2
|
作者
Schmitz, Fabian [1 ]
Sedaghat, Sam [1 ]
机构
[1] Univ Hosp Heidelberg, Dept Diagnost & Intervent Radiol, Neuenheimer Feld 420, D-69120 Heidelberg, Germany
关键词
Soft tissue sarcoma; MRI; Grade; FNCLCC; Predictor; Systematic review; SYNOVIAL SARCOMA; NEEDLE-BIOPSY; MRI; DIAGNOSIS; TUMORS; POPULATION; APPEARANCE;
D O I
10.1016/j.ejrad.2024.111548
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Purpose: Systematic reviews on the grading of STS using MRI are lacking. This review analyses the role of different MRI features in inferring the histological grade of STS. Materials and methods: A systematic review was conducted and is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) checklist. The electronic databases of PubMed/MEDLINE were systematically searched for literature addressing the correlation of MRI findings in soft tissue sarcoma with tumor grade. As keywords "MRI", "magnetic resonance imaging", "sarcoma", "grade", "grading", and "FNCLCC" have been selected. Results: 14 studies have been included in this systematic review. Tumor size (p = 0.015 (51 patients) to p = 0.81 (36 patients)), tumor margin (p < 0.001 (95 patients) to 0.93 (36 patients)), necrosis (p = 0.004 (50 patients) to p = 0.65 (95 patients)), peritumoral edema (p = 0.002 (130 patients) to p = 0.337 (40 patients)), contrast enhancement (p < 0.01 (50 patients) to 0.019 (51 patients)) and polycyclic/multilobulated tumor configuration (p = 0.008 (71 patients)) were significantly associated with STS malignancy grade in most of the included studies. Heterogeneity in T2w images (p = 0.003 (130 patients) to 0.202 (40 patients)), signal intensity in T1w images/ hemorrhage (p = 0.02 (130 patients) to 0.5 (31 patients)), peritumoral contrast enhancement (p < 0.001 (95 patients) to 0.253 (51 patients)) and tumoral diffusion restriction (p = 0.01 (51 patients) to 0.53 (52 patients)) were regarded as significantly associated with FNCLCC grade in some of the studies which investigated these features. Most other MRI features were not significant. Conclusion: Several MRI features, such as tumor size, necrosis, peritumoral edema, peritumoral contrast enhancement, intratumoral contrast enhancement, and polycyclic/multilobulated tumor configuration may indicate the malignancy grade of STS. However, further studies are needed to gain consensus.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Clinical outcomes of brain metastasectomy from soft tissue and bone sarcomas: a systematic review
    Wang, Ying
    Delisle, Megan
    Smith, Denise
    Alshamsan, Bader
    Srikanthan, Amirrtha
    INTERNATIONAL JOURNAL OF CLINICAL ONCOLOGY, 2022, 27 (11) : 1767 - 1779
  • [22] Clinical outcomes of brain metastasectomy from soft tissue and bone sarcomas: a systematic review
    Ying Wang
    Megan Delisle
    Denise Smith
    Bader Alshamsan
    Amirrtha Srikanthan
    International Journal of Clinical Oncology, 2022, 27 : 1767 - 1779
  • [23] Accuracy of real time noninvasive temperature measurements using magnetic resonance thermal imaging in patients treated for high grade extremity soft tissue sarcomas
    Craciunescua, Oana I.
    Stauffer, Paul R.
    Soher, Brian J.
    Wyatt, Cory R.
    Arabe, Omar
    Maccarini, Paolo
    Das, Shiva K.
    Cheng, Kung-Shan
    Wong, Terence Z.
    Jones, Ellen L.
    Dewhirst, Mark W.
    Vujaskovic, Zeljko
    MacFall, James R.
    MEDICAL PHYSICS, 2009, 36 (11) : 4848 - 4858
  • [24] Tumor grade in soft-tissue sarcoma Prediction with magnetic resonance imaging texture analysis
    Hong, Ji Hyun
    Jee, Won-Hee
    Jung, Chan-Kwon
    Chung, Yang-Guk
    MEDICINE, 2020, 99 (27) : E20880
  • [25] Candidate Biomarkers for Specific Intraoperative Near-Infrared Imaging of Soft Tissue Sarcomas: A Systematic Review
    Rijs, Zeger
    Shifai, A. Naweed
    Bosma, Sarah E.
    Kuppen, Peter J. K.
    Vahrmeijer, Alexander L.
    Keereweer, Stijn
    Bovee, Judith V. M. G.
    van de Sande, Michiel A. J.
    Sier, Cornelis E. M.
    van Driel, Pieter B. A. A.
    CANCERS, 2021, 13 (03) : 1 - 29
  • [26] Development and Validation of Nomograms for Malignancy Prediction in Soft Tissue Tumors Using Magnetic Resonance Imaging Measurements
    Ji Hyun Lee
    Young Cheol Yoon
    Wook Jin
    Jang Gyu Cha
    Seonwoo Kim
    Scientific Reports, 9
  • [27] Development and Validation of Nomograms for Malignancy Prediction in Soft Tissue Tumors Using Magnetic Resonance Imaging Measurements
    Lee, Ji Hyun
    Yoon, Young Cheol
    Jin, Wook
    Cha, Jang Gyu
    Kim, Seonwoo
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [28] Soft tissue sarcomas of the buttock: A systematic review and meta-analysis
    Sacco, Riccardo
    Lalevee, Matthieu
    Pellegrino, Pietro
    Ferro, Andrea
    Yasmine, Bendoukha
    Andre, Gillibert
    Matthieu, Gilleron
    Hamza, Amine
    Piana, Raimondo
    Dujardin, Franck
    SURGICAL ONCOLOGY-OXFORD, 2022, 45
  • [29] THERAPY MONITORING IN HUMAN AND CANINE SOFT-TISSUE SARCOMAS USING MAGNETIC-RESONANCE-IMAGING AND SPECTROSCOPY
    PRESCOTT, DM
    CHARLES, HC
    SOSTMAN, HD
    DODGE, RK
    THRALL, DE
    PAGE, RL
    TUCKER, JA
    HARRELSON, JM
    LEOPOLD, KA
    OLESON, JR
    DEWHIRST, MW
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 1994, 28 (02): : 415 - 423
  • [30] Musculoskeletal Soft-Tissue Masses: A Review of Sonographic, Magnetic Resonance, and Pathologic Features
    Backer, M.
    Patel, B.
    Larrison, M.
    AMERICAN JOURNAL OF ROENTGENOLOGY, 2010, 194 (05)