Conventional MR and Diffusion-weighted Imaging of Musculoskeletal Soft Tissue Malignancy: Correlation with Histologic Grading

Overview

Journal Eur Radiol

Specialty Radiology

Date 2018 Dec 5

PMID 30511176

Citations 28

Authors

Avneesh Chhabra

Oganes Ashikyan

Chenelle Slepicka

Nathan Dettori

Helena Hwang

Alexandra Callan

Rohit R Sharma

Yin Xi

Affiliations

Soon will be listed here.

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).

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References

Murphey M, Kransdorf M, Smith S . Imaging of Soft Tissue Neoplasms in the Adult: Malignant Tumors. Semin Musculoskelet Radiol. 2001; 3(1):39-58. DOI: 10.1055/s-2008-1080050. View

Oliveira A, Nascimento A . Grading in soft tissue tumors: principles and problems. Skeletal Radiol. 2001; 30(10):543-59. DOI: 10.1007/s002560100408. View

van Rijswijk C, Kunz P, Hogendoorn P, Taminiau A, Doornbos J, Bloem J . Diffusion-weighted MRI in the characterization of soft-tissue tumors. J Magn Reson Imaging. 2002; 15(3):302-7. DOI: 10.1002/jmri.10061. View

Kransdorf M, Bancroft L, Peterson J, Murphey M, Foster W, Temple H . Imaging of fatty tumors: distinction of lipoma and well-differentiated liposarcoma. Radiology. 2002; 224(1):99-104. DOI: 10.1148/radiol.2241011113. View

Gielen J, De Schepper A, Vanhoenacker F, Parizel P, Wang X, Sciot R . Accuracy of MRI in characterization of soft tissue tumors and tumor-like lesions. A prospective study in 548 patients. Eur Radiol. 2004; 14(12):2320-30. DOI: 10.1007/s00330-004-2431-0. View

Walker L, Thompson D, Easton D, Ponder B, Ponder M, Frayling I . A prospective study of neurofibromatosis type 1 cancer incidence in the UK. Br J Cancer. 2006; 95(2):233-8. PMC: 2360616. DOI: 10.1038/sj.bjc.6603227. View

Murphey M, Gibson M, Jennings B, Crespo-Rodriguez A, Fanburg-Smith J, Gajewski D . From the archives of the AFIP: Imaging of synovial sarcoma with radiologic-pathologic correlation. Radiographics. 2006; 26(5):1543-65. DOI: 10.1148/rg.265065084. View

Maeda M, Matsumine A, Kato H, Kusuzaki K, Maier S, Uchida A . Soft-tissue tumors evaluated by line-scan diffusion-weighted imaging: influence of myxoid matrix on the apparent diffusion coefficient. J Magn Reson Imaging. 2007; 25(6):1199-204. DOI: 10.1002/jmri.20931. View

Oka K, Yakushiji T, Sato H, Hirai T, Yamashita Y, Mizuta H . 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. 2009; 39(2):141-6. DOI: 10.1007/s00256-009-0830-7. View

10.

Berquist T, Ehman R, King B, Hodgman C, Ilstrup D . Value of MR imaging in differentiating benign from malignant soft-tissue masses: study of 95 lesions. AJR Am J Roentgenol. 1990; 155(6):1251-5. DOI: 10.2214/ajr.155.6.2122675. View

11.

Kang Y, Choi S, Kim Y, Kim K, Sohn C, Kim J . Gliomas: Histogram analysis of apparent diffusion coefficient maps with standard- or high-b-value diffusion-weighted MR imaging--correlation with tumor grade. Radiology. 2011; 261(3):882-90. DOI: 10.1148/radiol.11110686. View

12.

Vanhoenacker F, Van Looveren K, Trap K, Desimpelaere J, Wouters K, Van Dyck P . Grading and characterization of soft tissue tumors on magnetic resonance imaging: the value of an expert second opinion report. Insights Imaging. 2012; 3(2):131-8. PMC: 3314736. DOI: 10.1007/s13244-012-0151-6. View

13.

Subhawong T, Durand D, Thawait G, Jacobs M, Fayad L . Characterization of soft tissue masses: can quantitative diffusion weighted imaging reliably distinguish cysts from solid masses?. Skeletal Radiol. 2013; 42(11):1583-92. PMC: 9372881. DOI: 10.1007/s00256-013-1703-7. View

14.

Zhao F, Ahlawat S, Farahani S, Weber K, Montgomery E, Carrino J . Can MR imaging be used to predict tumor grade in soft-tissue sarcoma?. Radiology. 2014; 272(1):192-201. DOI: 10.1148/radiol.14131871. View

15.

Ahlawat S, Khandheria P, Subhawong T, Fayad L . Differentiation of benign and malignant skeletal lesions with quantitative diffusion weighted MRI at 3T. Eur J Radiol. 2015; 84(6):1091-7. DOI: 10.1016/j.ejrad.2015.02.019. View

16.

Ahlawat S, Khandheria P, Del Grande F, Morelli J, Subhawong T, Demehri S . 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. 2015; 43(2):446-54. DOI: 10.1002/jmri.24994. View

17.

Pekcevik Y, Kahya M, Kaya A . Characterization of Soft Tissue Tumors by Diffusion-Weighted Imaging. Iran J Radiol. 2015; 12(3):e15478. PMC: 4632135. DOI: 10.5812/iranjradiol.15478v2. View

18.

Gondim Teixeira P, Gay F, Chen B, Zins M, Sirveaux F, Felblinger J . 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. 2015; 45(2):263-71. DOI: 10.1007/s00256-015-2302-6. View

19.

Singer A, Pattany P, Fayad L, Tresley J, Subhawong T . Volumetric segmentation of ADC maps and utility of standard deviation as measure of tumor heterogeneity in soft tissue tumors. Clin Imaging. 2016; 40(3):386-91. DOI: 10.1016/j.clinimag.2015.11.017. View

20.

Li X, Zhang K, Shi Y, Wang F, Meng X . Correlations between the minimum and mean apparent diffusion coefficient values of hepatocellular carcinoma and tumor grade. J Magn Reson Imaging. 2016; 44(6):1442-1447. DOI: 10.1002/jmri.25323. View