Skip to main content
SpringerLink
Log in

Conventional MR and diffusion-weighted imaging of musculoskeletal soft tissue malignancy: correlation with histologic grading

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

Abstract

Aim

To evaluate proven soft tissue musculoskeletal malignancies blinded to their Fédération Nationale des Centres de Lutte Contre le Cancer histologic grades to identify the predictive values of conventional MR findings and best fit region of interest (ROI) apparent diffusion coefficient (ADC) measurements.

Materials and methods

Fifty-one consecutive patients with different histologic grades were evaluated by four readers (R1–4) of different experience levels. Quantitatively, the maximum longitudinal size, tumor to muscle signal intensity ratios, and ADC measurements and, qualitatively, the spatial location of the tumor, its signal alterations, heterogeneity, intralesional hemorrhage or fat, and types of enhancement were assessed. Intraclass correlation, weighted kappa, ANOVA, and Fisher exact tests were used.

Results

There were 22/51 (43%) men (mean age ± SD = 52 ± 16 years) and 29/51 (57%) women (mean age ± SD = 54± 17 years), with the majority of tumors 38/51 (75%) in the lower extremities. Histologic grades were I in 8/51 (16%), II in 17/51 (33%), and III in 26/51 (51%), respectively. The longitudinal dimensions were different among three grades (p = 0.0015), largest with grade I. More central enhancements and deep locations were seen in grade III tumors (p = 0.0191, 0.0246). The ADC mean was significantly lower in grade III than in grade I or II (p < 0.0001 and p = 0.04). The ADC min was significantly lower in grade III than in grade I (p = 0.02). Good to excellent agreements were seen for T1/T2 tumor/muscle ratios, longitudinal dimension, and ADC (ICC = 0.60–0.98).

Conclusion

Longitudinal tumor dimension, central enhancement, and ADC values differentiate histology grades in musculoskeletal soft tissue malignancy with good to excellent inter-reader reliability.

Key Points

• The longitudinal tumor dimension of grade III malignancy is smaller than that of grade I (p < 0.0001), and higher-grade tumors are located deeper (p = 0.0246).

• The ADC mean is significantly lower in grade III than in grade I or grade II (p < 0.0001 and p = 0.04).

• The ADC minimum is significantly lower in grade III than in grade I (p = 0.02).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

DWI:

Diffusion-weighted imaging

FNCLCC:

Fédération Nationale des Centres de Lutte Contre le Cancer

ROI:

Region of interest

References

  1. Murphey MD, Kransdorf MJ, Smith SE (1999) Imaging of soft tissue neoplasms in the adult: malignant tumors. Semin Musculoskelet Radiol 3:39–58. https://doi.org/10.1055/s-2008-1080050

    Article  PubMed  Google Scholar 

  2. Kransdorf MJ, Bancroft LW, Peterson JJ, Murphey MD, Foster WC, Temple HT (2002) Imaging of fatty tumors: distinction of lipoma and well-differentiated liposarcoma. Radiology 224:99–104. https://doi.org/10.1148/radiol.2241011113

  3. Murphey MD, Gibson MS, Jennings BT, Crespo-Rodríguez AM, Fanburg-Smith J, Gajewski DA (2006) From the archives of the AFIP: imaging of synovial sarcoma with radiologic-pathologic correlation. Radiographics 26:1543–1565. https://doi.org/10.1148/rg.265065084

  4. Walker L, Thompson D, Easton D et al (2006) A prospective study of neurofibromatosis type 1 cancer incidence in the UK. Br J Cancer 95:233–238. https://doi.org/10.1038/sj.bjc.6603227

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Coran A, Ortolan P, Attar S et al (2017) Magnetic resonance imaging assessment of lipomatous soft-tissue tumors. In Vivo 31:387–395

  6. Guillou L, Coindre JM, Bonichon F et al (1997) 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 15:350–362. https://doi.org/10.1200/JCO.1997.15.1.350

    Article  CAS  PubMed  Google Scholar 

  7. Oliveira AM, Nascimento AG (2001) Grading in soft tissue tumors: principles and problems. Skeletal Radiol 30:543–559. https://doi.org/10.1007/s002560100408

    Article  CAS  PubMed  Google Scholar 

  8. Gielen JL, De Schepper AM, Vanhoenacker F et al (2004) Accuracy of MRI in characterization of soft tissue tumors and tumor-like lesions. A prospective study in 548 patients. Eur Radiol 14:2320–2330. https://doi.org/10.1007/s00330-004-2431-0

    Article  PubMed  Google Scholar 

  9. Berquist TH, Ehman RL, King BF, Hodgman CG, Ilstrup DM (1990) Value of MR imaging in differentiating benign from malignant soft-tissue masses: study of 95 lesions. AJR Am J Roentgenol 155:1251–1255. https://doi.org/10.2214/ajr.155.6.2122675

  10. Vanhoenacker FM, Van Looveren K, Trap K et al (2012) Grading and characterization of soft tissue tumors on magnetic resonance imaging: the value of an expert second opinion report. Insights Imaging 3:131–138. https://doi.org/10.1007/s13244-012-0151-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Mesko NW, Wilson RJ, Lawrenz JM et al (2018) Pre-operative evaluation prior to soft tissue sarcoma excision—why can’t we get it right? Eur J Surg Oncol 44:243–250. https://doi.org/10.1016/j.ejso.2017.11.001

    Article  CAS  PubMed  Google Scholar 

  12. Dyrop HB, Vedsted P, Rædkjær M, Safwat A, Keller J (2017) Imaging investigations before referral to a sarcoma center delay the final diagnosis of musculoskeletal sarcoma. Acta Orthop 88:211–216. https://doi.org/10.1080/17453674.2016.1278113

  13. Gruber L, Gruber H, Luger AK, Glodny B, Henninger B, Loizides A (2017) Diagnostic hierarchy of radiological features in soft tissue tumours and proposition of a simple diagnostic algorithm to estimate malignant potential of an unknown mass. Eur J Radiol 95:102–110. https://doi.org/10.1016/j.ejrad.2017.07.020

  14. Zhao F, Ahlawat S, Farahani SJ et al (2014) Can MR imaging be used to predict tumor grade in soft-tissue sarcoma? Radiology 272:192–201. https://doi.org/10.1148/radiol.14131871

    Article  PubMed  Google Scholar 

  15. Jahed K, Khazai B, Umpierrez M, Subhawong TK, Singer AD (2018) Pitfalls in soft tissue sarcoma imaging: chronic expanding hematomas. Skeletal Radiol 47:119–124. https://doi.org/10.1007/s00256-017-2770-y

  16. Ahlawat S, Khandheria P, Subhawong TK, Fayad LM (2015) Differentiation of benign and malignant skeletal lesions with quantitative diffusion weighted MRI at 3T. Eur J Radiol 84:1091–1097. https://doi.org/10.1016/j.ejrad.2015.02.019

    Article  PubMed  Google Scholar 

  17. Singer AD, Pattany PM, Fayad LM, Tresley J, Subhawong TK (2016) Volumetric segmentation of ADC maps and utility of standard deviation as measure of tumor heterogeneity in soft tissue tumors. Clin Imaging 40:386–391. https://doi.org/10.1016/j.clinimag.2015.11.017

  18. Sagiyama K, Watanabe Y, Kamei R et al (2017) Multiparametric voxel-based analyses of standardized uptake values and apparent diffusion coefficients of soft-tissue tumours with a positron emission tomography/magnetic resonance system: preliminary results. Eur Radiol 27:5024–5033. https://doi.org/10.1007/s00330-017-4912-y

    Article  PubMed  Google Scholar 

  19. Ahlawat S, Khandheria P, Del Grande F et al (2016) Interobserver variability of selective region-of-interest measurement protocols for quantitative diffusion weighted imaging in soft tissue masses: comparison with whole tumor volume measurements. J Magn Reson Imaging 43:446–454. https://doi.org/10.1002/jmri.24994

    Article  PubMed  Google Scholar 

  20. Fisher S, Wadhwa V, Manthuruthil C, Cheng J, Chhabra A (2016) Clinical impact of magnetic resonance neurography in patients with brachial plexus neuropathies. Br J Radiol 89:20160503. https://doi.org/10.1259/bjr.20160503

  21. Barbieri S, Brönnimann M, Boxler S, Vermathen P, Thoeny HC (2017) Differentiation of prostate cancer lesions with high and with low Gleason score by diffusion-weighted MRI. Eur Radiol 27:1547–1555. https://doi.org/10.1007/s00330-016-4449-5

  22. Li X, Zhang K, Shi Y, Wang F, Meng X (2016) Correlations between the minimum and mean apparent diffusion coefficient values of hepatocellular carcinoma and tumor grade. J Magn Reson Imaging 44:1442–1447. https://doi.org/10.1002/jmri.25323

  23. Kang Y, Choi SH, Kim YJ et al (2011) Gliomas: histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging—correlation with tumor grade. Radiology 261:882–890. https://doi.org/10.1148/radiol.11110686

    Article  PubMed  Google Scholar 

  24. Teixeira PA, Gay F, Chen B et al (2016) Diffusion-weighted magnetic resonance imaging for the initial characterization of non-fatty soft tissue tumors: correlation between T2 signal intensity and ADC values. Skeletal Radiol 45:263–271. https://doi.org/10.1007/s00256-015-2302-6

    Article  PubMed  Google Scholar 

  25. Pekcevik Y, Kahya MO, Kaya A (2015) Characterization of soft tissue tumors by diffusion-weighted imaging. Iran J Radiol 12:e15478. https://doi.org/10.5812/iranjradiol.15478v2

    Article  PubMed  PubMed Central  Google Scholar 

  26. van Rijswijk CS, Kunz P, Hogendoorn PC, Taminiau AH, Doornbos J, Bloem JL (2002) Diffusion-weighted MRI in the characterization of soft-tissue tumors. J Magn Reson Imaging 15:302–307

  27. Degnan AJ, Chung CY, Shah AJ (2018) Quantitative diffusion-weighted magnetic resonance imaging assessment of chemotherapy treatment response of pediatric osteosarcoma and Ewing sarcoma malignant bone tumors. Clin Imaging 47:9–13. https://doi.org/10.1016/j.clinimag.2017.08.003

    Article  PubMed  Google Scholar 

  28. Oka K, Yakushiji T, Sato H, Hirai T, Yamashita Y, Mizuta H (2010) The value of diffusion-weighted imaging for monitoring the chemotherapeutic response of osteosarcoma: a comparison between average apparent diffusion coefficient and minimum apparent diffusion coefficient. Skeletal Radiol 39:141–146. https://doi.org/10.1007/s00256-009-0830-7

  29. Maeda M, Matsumine A, Kato H et al (2007) Soft-tissue tumors evaluated by line-scan diffusion-weighted imaging: influence of myxoid matrix on the apparent diffusion coefficient. J Magn Reson Imaging 25:1199–1204. https://doi.org/10.1002/jmri.20931

    Article  PubMed  Google Scholar 

  30. Subhawong TK, Durand DJ, Thawait GK, Jacobs MA, Fayad LM (2013) Characterization of soft tissue masses: can quantitative diffusion weighted imaging reliably distinguish cysts from solid masses? Skeletal Radiol 42:1583–1592. https://doi.org/10.1007/s00256-013-1703-7

  31. Del Grande F, Ahlawat S, Subhawong T, Fayad LM (2017) Characterization of indeterminate soft tissue masses referred for biopsy: what is the added value of contrast imaging at 3.0 tesla? J Magn Reson Imaging 45:390–400

  32. Corino VDA, Montin E, Messina A et al (2018) Radiomic analysis of soft tissues sarcomas can distinguish intermediate from high-grade lesions. J Magn Reson Imaging 47:829–840. https://doi.org/10.1002/jmri.25791

    Article  PubMed  Google Scholar 

Download references

Funding

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

Author information

Authors and Affiliations

  1. Radiology, UT Southwestern Medical Center, Dallas, TX, 75022, USA

    Avneesh Chhabra, Oganes Ashikyan, Chenelle Slepicka, Nathan Dettori & Yin Xi

  2. Orthopedics, UT Southwestern Medical Center, Dallas, TX, USA

    Avneesh Chhabra & Alexandra Callan

  3. Pathology, UT Southwestern Medical Center, Dallas, TX, USA

    Helena Hwang

  4. Surgical Oncology, UT Southwestern Medical Center, Dallas, TX, USA

    Rohit R. Sharma

Authors
  1. Avneesh Chhabra
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oganes Ashikyan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chenelle Slepicka
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nathan Dettori
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Helena Hwang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Alexandra Callan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Rohit R. Sharma
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yin Xi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Avneesh Chhabra.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Avneesh Chhabra, MD.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: AC: consultant, ICON Medical; royalties: Jaypee, Wolters. OA, CS, ND, HW, AC, RS, and YX: no disclosures.

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (YX) has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Cross sectional

• Performed at one institution

Electronic supplementary material

ESM 1

(DOCX 42 kb)

ESM 2

(DOCX 50 kb)

ESM 3

(DOCX 67 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chhabra, A., Ashikyan, O., Slepicka, C. et al. Conventional MR and diffusion-weighted imaging of musculoskeletal soft tissue malignancy: correlation with histologic grading. Eur Radiol 29, 4485–4494 (2019). https://doi.org/10.1007/s00330-018-5845-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-018-5845-9

Keywords

Search

Navigation