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Solitary bone tumor imaging reporting and data system (BTI-RADS): initial assessment of a systematic imaging evaluation and comprehensive reporting method

  • Musculoskeletal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

Identify the most pertinent imaging features for solitary bone tumor characterization using a multimodality approach and propose a systematic evaluation system.

Methods

Data from a prospective trial, including 230 participants with histologically confirmed bone tumors, typical “do not touch” lesions, and stable chondral lesions, were retrospectively evaluated. Clinical data, CT, and MR imaging features were analyzed by a musculoskeletal radiologist blinded to the diagnosis using a structured report. The benign-malignant distribution of lesions bearing each image feature evaluated was compared to the benign-malignant distribution in the study sample. Benign and malignant indicators were identified. Two additional readers with different expertise levels independently evaluated the study sample.

Results

The sample included 140 men and 90 women (mean age 40.7 ± 18.3 years). The global benign-malignant distribution was 67–33%. Seven imaging features reached the criteria for benign indicators with a mean frequency of benignancy of 94%. Six minor malignant indicators were identified with a mean frequency of malignancy of 60.5%. Finally, three major malignant indicators were identified (Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease) with a mean frequency of malignancy of 82.4%. A bone tumor imaging reporting and data system (BTI-RADS) was proposed. The reproducibility of the BTI-RADS was considered fair (kappa = 0.67) with a mean frequency of malignancy in classes I, II, III, and IV of 0%, 2.2%, 20.1%, and 71%, respectively.

Conclusion

BTI-RADS is an evidence-based systematic approach to solitary bone tumor characterization with a fair reproducibility, allowing lesion stratification in classes of increasing malignancy frequency.

Trial registration

Clinical trial number NCT02895633.

Key Points

• The most pertinent CT and MRI criteria allowing bone tumor characterization were defined and presented.

• Lodwick-Madewell grade III, aggressive periosteal reaction, and suspected metastatic disease should be considered major malignant indicators associated with a frequency of malignancy over 75%.

• The proposed evidence-based multimodality reporting system stratifies solitary bone tumors in classes with increasing frequencies of malignancy.

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Abbreviations

BTI-RADS:

Bone tumor imaging reporting and data system

ETL:

Echo train length

FOV:

Field of view

NEX:

Number of excitations

ResOs:

Reference Network for Bone Sarcomas and rare tumors

TE:

Echo time

TR:

Repetition time

References

  1. Rajiah P, Ilaslan H, Sundaram M (2011) Imaging of primary malignant bone tumors (nonhematological). Radiol Clin North Am 49:1135–1161

    Article  PubMed  Google Scholar 

  2. Casali PG, Bielack S, Abecassis N et al (2018) Bone sarcomas: ESMO-PaedCan-EURACAN Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol 29:iv79–iv95

    Article  CAS  PubMed  Google Scholar 

  3. Pfister DG, Rubin DM, Elkin EB et al (2015) Risk adjusting survival outcomes in hospitals that treat patients with cancer without information on cancer stage. JAMA Oncol 1:1303–1310

    Article  PubMed  PubMed Central  Google Scholar 

  4. Do BH, Langlotz C, Beaulieu CF (2017) Bone tumor diagnosis using a naïve Bayesian model of demographic and radiographic features. J Digit Imaging 30:640–647

    Article  PubMed  PubMed Central  Google Scholar 

  5. Madewell JE, Ragsdale BD, Sweet DE (1981) Radiologic and pathologic analysis of solitary bone lesions. Part I: internal margins. Radiol Clin North Am 19:715–748

    CAS  PubMed  Google Scholar 

  6. Ragsdale BD, Madewell JE, Sweet DE (1981) Radiologic and pathologic analysis of solitary bone lesions. Part II: periosteal reactions. Radiol Clin North Am 19:749–783

    CAS  PubMed  Google Scholar 

  7. Sweet DE, Madewell JE, Ragsdale BD (1981) Radiologic and pathologic analysis of solitary bone lesions. Part III: matrix patterns. Radiol Clin North Am 19:785–814

    CAS  PubMed  Google Scholar 

  8. Miller TT (2008) Bone tumors and tumor-like conditions: analysis with conventional radiography. Radiology 246:662–674

    Article  PubMed  Google Scholar 

  9. Mehta K, McBee MP, Mihal DC, England EB (2017) Radiographic analysis of bone tumors: a systematic approach. Semin Roentgenol 52:194–208

    Article  PubMed  Google Scholar 

  10. Parlier-Cuau C, Bousson V, Ogilvie CM, Lackman RD, Laredo J-D (2011) When should we biopsy a solitary central cartilaginous tumor of long bones? Literature review and management proposal. Eur J Radiol 77:6–12

    Article  PubMed  Google Scholar 

  11. Sampath Kumar V, Tyrrell PNM, Singh J, Gregory J, Cribb GL, Cool P (2016) Surveillance of intramedullary cartilage tumours in long bones. Bone Joint J 98:1542–1547

    Article  PubMed  Google Scholar 

  12. Greenspan A (2004) Orthopedic Imaging: a practical approach, 4th edn. Lippincott Williams & Wilkins, Philadelphia

    Google Scholar 

  13. Jacobson JA, Girish G, Jiang Y, Sabb BJ (2008) Radiographic evaluation of arthritis: degenerative joint disease and variations. Radiology 248:737–747

    Article  PubMed  Google Scholar 

  14. Pitt MJ, Graham AR, Shipman JH, Birkby W (1982) Herniation pit of the femoral neck. AJR Am J Roentgenol 138:1115–1121

    Article  CAS  PubMed  Google Scholar 

  15. Yumoto T, Joko R, Yamakawa Y, Yamada T, Naito H, Nakao A (2018) Subperiosteal hematoma of the iliac bone: an unusual cause of acute hip pain after a fall. Am J Case Rep 19:1083–1086

    Article  PubMed  PubMed Central  Google Scholar 

  16. Ben Zakoun J, Dallaudière B, Palazzo E, Lefere M, Monteil J, Dieudé P (2014) Chronic ossified subperiosteal hematoma of the iliac bone. Diagn Interv Imaging 95:889–891

    Article  CAS  PubMed  Google Scholar 

  17. Guillin R, Moser T, Koob M et al (2012) Subperiosteal hematoma of the iliac bone: imaging features of acute and chronic stages with emphasis on pathophysiology. Skeletal Radiol 41:667–675

    Article  PubMed  Google Scholar 

  18. Goodin GS, Shulkin BL, Kaufman RA, McCarville MB (2006) PET/CT characterization of fibroosseous defects in children: 18F-FDG uptake can mimic metastatic disease. AJR Am J Roentgenol 187:1124–1128

    Article  PubMed  Google Scholar 

  19. Onitsuka H (1977) Roentgenologic aspects of bone islands. Radiology 123:607–612

    Article  CAS  PubMed  Google Scholar 

  20. Ulano A, Bredella MA, Burke P et al (2016) Distinguishing untreated osteoblastic metastases from enostoses using CT attenuation measurements. AJR Am J Roentgenol 207:362–368

    Article  PubMed  Google Scholar 

  21. Rosenblatt J, Koder A (2019) Understanding unicameral and aneurysmal bone cysts. Pediatr Rev 40:51–59

    Article  PubMed  Google Scholar 

  22. Saito N, Nadgir RN, Flower EN, Sakai O (2010) Clinical and radiologic manifestations of sickle cell disease in the head and neck. Radiographics 30:1021–1034

    Article  PubMed  Google Scholar 

  23. Costelloe CM, Madewell JE (2013) Radiography in the initial diagnosis of primary bone tumors. AJR Am J Roentgenol 200:3–7

    Article  PubMed  Google Scholar 

  24. Priolo F, Cerase A (1998) The current role of radiography in the assessment of skeletal tumors and tumor-like lesions. Eur J Radiol 27:S77–S85

    Article  PubMed  Google Scholar 

  25. Campanacci M, Mercuri M, Gasbarrini A, Campanacci L (1998) The value of imaging in the diagnosis and treatment of bone tumors. Eur J Radiol 27:S116–S122

    Article  PubMed  Google Scholar 

  26. Nichols RE, Dixon LB (2011) Radiographic analysis of solitary bone lesions. Radiol Clin North Am 49:1095–1114

    Article  PubMed  Google Scholar 

  27. Caracciolo JT, Temple HT, Letson GD, Kransdorf MJ (2016) A modified Lodwick-Madewell grading system for the evaluation of lytic bone lesions. AJR Am J Roentgenol 207:150–156

    Article  PubMed  Google Scholar 

  28. Fleiss L, Levin B, Paik MC (1981) Statistical methods for rates and proportions, 2nd edn. John Wiley, New York

    Google Scholar 

  29. Rosenkrantz AB, Kim S, Lim RP et al (2013) Prostate cancer localization using multiparametric MR imaging: comparison of Prostate Imaging Reporting and Data System (PI-RADS) and Likert scales. Radiology 269:482–492

    Article  PubMed  Google Scholar 

  30. Tessler FN, Middleton WD, Grant EG et al (2017) ACR Thyroid Imaging, Reporting and Data System (TI-RADS): white paper of the ACR TI-RADS Committee. J Am Coll Radiol 14:587–595

    Article  PubMed  Google Scholar 

  31. Gholamrezanezhad A, Kessler M, Hayeri SM (2017) The need for standardization of musculoskeletal practice reporting: learning from ACR BI-RADS, Liver Imaging-Reporting and Data System, and Prostate Imaging-Reporting and Data System. J Am Coll Radiol 14:1585–1587

    Article  PubMed  Google Scholar 

  32. Redondo A, Bagué S, Bernabeu D et al (2017) Malignant bone tumors (other than Ewing’s): clinical practice guidelines for diagnosis, treatment and follow-up by Spanish Group for Research on Sarcomas (GEIS). Cancer Chemother Pharmacol 80:1113–1131

    Article  PubMed  PubMed Central  Google Scholar 

  33. George A, Grimer R (2012) Early symptoms of bone and soft tissue sarcomas: could they be diagnosed earlier? Ann R Coll Surg Engl 94:261–266

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Bae JH, Lee IS, Song YS et al (2015) Bone tumors with an associated pathologic fracture: differentiation between benign and malignant status using radiologic findings. J Korean Soc Radiol 73:240–248

    Article  Google Scholar 

  35. Douis H, Parry M, Vaiyapuri S, Davies AM (2018) What are the differentiating clinical and MRI-features of enchondromas from low-grade chondrosarcomas? Eur Radiol 28:398–409

    Article  PubMed  Google Scholar 

  36. Murphey MD, Flemming DJ, Boyea SR, Bojescul JA, Sweet DE, Temple HT (1998) Enchondroma versus chondrosarcoma in the appendicular skeleton: differentiating features. Radiographics 18:1213–1237

    Article  CAS  PubMed  Google Scholar 

  37. Geirnaerdt MJ, Hermans J, Bloem JL et al (1997) Usefulness of radiography in differentiating enchondroma from central grade 1 chondrosarcoma. AJR Am J Roentgenol 169:1097–1104

    Article  CAS  PubMed  Google Scholar 

  38. Kalia V (2019) Advanced MRI features to help differentiate benign versus malignant cartilaginous lesions. Radiology: Imaging Cancer 1:e194010

    PubMed Central  Google Scholar 

  39. Sundaram M, McLeod RA (1990) MR imaging of tumor and tumor-like lesions of bone and soft tissue. AJR Am J Roentgenol 155:817–824

    Article  CAS  PubMed  Google Scholar 

  40. Verstraete KL, Lang P (2000) Bone and soft tissue tumors: the role of contrast agents for MR imaging. Eur J Radiol 34:229–246

    Article  CAS  PubMed  Google Scholar 

  41. Bisseret D, Kaci R, Lafage-Proust M-H et al (2015) Periosteum: characteristic imaging findings with emphasis on radiologic-pathologic comparisons. Skeletal Radiol 44:321–338

    Article  PubMed  Google Scholar 

  42. Panicek DM, Gatsonis C, Rosenthal DI et al (1997) CT and MR imaging in the local staging of primary malignant musculoskeletal neoplasms: report of the Radiology Diagnostic Oncology Group. Radiology 202:237–246

    Article  CAS  PubMed  Google Scholar 

  43. Ardran GM (1951) Bone destruction not demonstrable by radiography. Br J Radiol 24:107–109

    Article  CAS  PubMed  Google Scholar 

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Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

  1. Guilloz Imaging Department, Central Hospital, University Hospital Center of Nancy, 29 Avenue du Maréchal de Lattre de Tassigny, 54035, Nancy Cedex, France

    Guilherme Jaquet Ribeiro, Romain Gillet, Jean-Michel Trinh, Eve Euxibie, Alain Blum & Pedro Augusto Gondim Teixeira

  2. Université de Lorraine, Inserm, IADI, F-54000, Nancy, France

    Gabriela Hossu

  3. Emile Gallé Surgical Center, Regional University Hospital Center of Nancy, Nancy, France

    François Sirveaux

Authors
  1. Guilherme Jaquet Ribeiro
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  2. Romain Gillet
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  3. Gabriela Hossu
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  4. Jean-Michel Trinh
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  5. Eve Euxibie
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  8. Pedro Augusto Gondim Teixeira
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Corresponding author

Correspondence to Guilherme Jaquet Ribeiro.

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Guarantor

The scientific guarantor of this publication is Professor Pedro Augusto Gondim Teixeira.

Conflict of interest

Two authors involved in this work (Pedro Augusto Gondim Teixeira and Alain Blum) participate on a non-remunerated research contract with Canon Medical Systems for the development and clinical testing of post-processing tools for CT. The other authors have non-potential conflicts of interest to disclose.

Statistics and biometry

One of the authors, Gabriela Hossu, PhD, is a statistician.

Informed consent

Written informed consent was obtained from all participants in this study.

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Institutional Review Board approval was obtained.

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• prospective

• observational

• performed at one institution

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Ribeiro, G.J., Gillet, R., Hossu, G. et al. Solitary bone tumor imaging reporting and data system (BTI-RADS): initial assessment of a systematic imaging evaluation and comprehensive reporting method. Eur Radiol 31, 7637–7652 (2021). https://doi.org/10.1007/s00330-021-07745-9

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  • DOI: https://doi.org/10.1007/s00330-021-07745-9

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