Concordance of histopathological and radiological grading in soft tissue sarcomas

Year 2022, Volume: 5 Issue: 5, 1484 - 1490, 25.09.2022

Begumhan Baysal Fikret Berkan Anarat Mahmut Bilal Dogan Tulay Zenginkinet Aykut Celik Ayse Nur Toksoz Tarık Sarı Korhan Özkan

https://doi.org/10.32322/jhsm.1153412

Abstract

Aim: The grade of the tumor is essential for planning the treatment strategy in soft-tissue sarcomas (STS). The goal of this study is to determine magnetic resonance imaging features related to histopathological grade and aggressiveness of STS.
Material and Method: This retrospective single-center study involved preoperative contrast-enhanced MRI examinations of 64 patients with STS. MRI findings evaluated were; heterogeneity, necrosis, hemorrhage, and relationship with surrounding tissue in T1-weighted (T1W), T2-weighted (T2W), and T1W post-contrast sequences of the lesion. Histological grade was determined with the Fédération Nationale des Centres de Lutte Contre Le Cancer (FNCLCC) grading system, and the aggressiveness of the lesion was measured with the Ki-67 index.
Results: Sixty-four patients (mean age 45.5±21.6, M/F ratio 34/30) with STS were included. 33 (51.6%) patients graded as FNCLCC grade 3. On MRI examinations, the absence of necrosis was significantly associated with FNCLCC grade 1 and a low Ki-67 index (p<0.001). The presence of hemorrhage signal distinguished as a hyperintense signal on T1W, tail sign, and post-contrast peritumoral enhancement was significantly higher in FNCLCC grade 3 soft tissue sarcomas (p:0.008, p:0.001, p:0.004, respectively). The presence of peritumoral edema on T2W imaging in all high-grade patients also showed a strong relationship between these two (p:0.001).
Conclusion: Our study found that the presence of hemorrhage signal, tail sign, peritumoral enhancement, clear borders of 50% and less obtained from conventional MRI features of soft tissue sarcomas are associated with high grade tumors. The absence of necrosis signal, clear borders of 90% and above in MRI were significantly associated with FNCLCC grade 1.

Keywords

Magnetic resonance imaging, FNCLCC grading, soft-tissue sarcoma

References

• Kolovich GG, Wooldridge AN, Christy JM, Crist MK, MayersonJL, Scharschmidt TJ. A retrospective statistical analysis of high-grade soft tissue sarcomas. Med Oncol 2012; 29: 1335-44.
• Jo VY, Fletcher CD. WHO classification of soft tissue tumours: an update based on the 2013 edition. Pathology 2014; 46: 95-104.
• ESMO/European Sarcoma Network Working Group. Soft tissue and visceral sarcomas: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 2014; 25: iii102-12.
• Noebauer-Huhmann IM, Weber MA, Lalam RK et al. Soft tissue tumors in adults: ESSR-approved guidelines for diagnostic imaging. Semin Musculoskelet Radiol 2015; 19: 475-82.
• Stefanovski PD, Bidoli E, De Paoli A, et al. Prognostic factors in soft tissue sarcomas: a study of 395 patients. Eur J Surg Oncol 2002; 28: 153-64.
• Schneider N, Strauss DC, Smith MJ et al. The adequacy of core biopsy in the assessment of smooth muscle neoplasms of soft tissues. Am J Surg Pathol 2017; 41: 923-31.
• Kim BR, Kang Y, LeeJ, et al. Tumor grading of soft tissue sarcomas: assessment with whole-tumor histogram analysis of apparent diffusion coefficient. Eur J Radiol 2022; 151: 110319.
• Mitsuyoshi G, Naito N, Kawai A et al. Accurate diagnosis of musculoskeletal lesions by core needle biopsy. J Surg Oncol 2006; 94: 21-7.
• Trojani M, Contesso G, Coindre JM et al. Soft‐tissue sarcomas of adults; study of pathological prognostic variables and definition of a histopathological grading system. Int J Cancer 1984; 33: 37-42.
• Meara RS, Cangiarella J, Simsir A, Horton D, Eltoum I, Chhieng DC. Prediction of aggressiveness of gastrointestinal stromal tumours based on immunostaining with bcl‐2, Ki‐67 and p53. Cytopathology 2007; 18: 283-9.
• Scotlandi K, Serra M, Manara MC et al. Clinical relevance of Ki‐67 expression in bone tumors. Cancer 1995; 75: 806-14.
• Zhao F, Ahlawat S, Farahani SJ, et al. Can MR imaging be used to predict tumor grade in soft-tissue sarcoma? Radiology 2014; 272: 192-201.
• Crombé A, Marcellin PJ, Buy X et al. Soft-tissue sarcomas: assessment of MRI features correlating with histologic grade and patient outcome. Radiology 2019; 291: 710-21.
• Yan R, Hao D, Li J et al. Magnetic Resonance Imaging‐Based Radiomics Nomogram for Prediction of the Histopathological Grade of Soft Tissue Sarcomas: A Two‐Center Study. J Magn Reson Imaging 2021; 53: 1683-96.
• Jones C, Liu K, Hirschowitz S, Klipfel N, Layfield LJ. Concordance of histopathologic and cytologic grading in musculoskeletal sarcomas: can grades obtained from analysis of the fine‐needle aspirates serve as the basis for therapeutic decisions? Cancer 2002; 96: 83-91.
• Adams SC, Potter BK, Pitcher DJ, Temple HT. Office-based core needle biopsy of bone and soft tissue malignancies: an accurate alternative to open biopsy with infrequent complications. Clin Orthop Relat Res 2010; 468: 2774-80.
• Traina F, Errani C, Toscano A et al. Current concepts in the biopsy of musculoskeletal tumors: AAOS exhibit selection. J Bone Joint Surg Am 2015; 97: e7.
• Kasraeian S, Allison DC, Ahlmann ER, Fedenko AN, Menendez LR. A comparison of fine-needle aspiration, core biopsy, and surgical biopsy in the diagnosis of extremity soft tissue masses. Clin Orthop Relat Res 2010; 468: 2992-3002.
• Hoeber I, Spillane AJ, Fisher C, Thomas JM. Accuracy of biopsy techniques for limb and limb girdle soft tissue tumors. Ann Surg Oncol 2001; 8: 80-7.
• Strauss DC, Qureshi YA, Hayes AJ, Thway K, Fisher C, Thomas JM. The role of core needle biopsy in the diagnosis of suspected soft tissue tumours. J Surg Oncol 2010; 102: 523-9.
• De Marchi A, Brach del Prever EM, Linari A et al. Accuracy of core-needle biopsy after contrast-enhanced ultrasound in soft-tissue tumours. Eur Radiol 2010; 20: 2740-8.
• Guillou L, Coindre JM, Bonichon F et al. Comparative study of the National Cancer Institute and French Federation of Cancer Centers Sarcoma Group grading systems in a population of 410 adult patients with soft tissue sarcoma. J Clin Oncol 1997; 15: 350-62.
• Koh TS, Thng CH, Hartono S et al. Assessment of tumor necrotic fraction by dynamic contrast‐enhanced MRI: a preclinical study of human tumor xenografts with histopathologic correlation. NMR Biomed 2014; 27: 486-94.
• Zhang Y, Zhu Y, Shi X et al. Soft tissue sarcomas: preoperative predictive histopathological grading based on radiomics of MRI. Acad Radiol 2019; 26: 1262-8.
• Peeken JC, Spraker MB, Knebel C et al. Tumor grading of soft tissue sarcomas using MRI-based radiomics. EBioMedicine 2019; 48: 332-40.
• Crombé A, Fadli D, Italiano A, Saut O, Buy X, Kind M. Systematic review of sarcomas radiomics studies: Bridging the gap between concepts and clinical applications?. Eur J Radiol 2020; 132: 109283.
• Wang H, Chen H, Duan S, Hao D, Liu J. Radiomics and machine learning with multiparametric preoperative MRI may accurately predict the histopathological grades of soft tissue sarcomas. J Magn Reson Imaging 2020; 51: 791-7.
• Xu W, Hao D, Hou F, Zhang D, Wang H. Soft tissue sarcoma: preoperative MRI-based radiomics and machine learning may be accurate predictors of histopathologic grade. AJR Am J Roentgenol 2020; 215: 963-9.
• Gitto S, Cuocolo R, Albano D et al. CT and MRI radiomics of bone and soft-tissue sarcomas: a systematic review of reproducibility and validation strategies. Insights Imaging 2021; 12: 1-14.