DIFFUSION WEIGHTED IMAGING OF SOFT TISSUE MASSES: CAN APPARENT DIFFUSION COEFFICIENT MEASUREMENT DIFFERENTIATE BETWEEN MALIGNANT AND BENIGN LESIONS ?

Year 2023, Volume: 24 Issue: 4, 481 - 487, 09.10.2023

Mehmet Oğuzman , Cüneyt Çalışır , Ulukan İnan

https://doi.org/10.18229/kocatepetip.1122866

Abstract

OBJECTIVE: To investigate the efficacy of apparent diffusion coefficient (ADC) mapping obtained using the diffusion-weighted imaging (DWI) method in the differentiation of benign and malignant lesions of soft tissue tumors and to establish a quantitative cut-off value for ADC to be used in the differentiation of these lesions.
MATERIAL AND METHODS: This retrospective study included a total of 34 patients who underwent DWI due to soft tissue masses and had available histopathological results. According to the pathological results; patients were categorized as having benign and malignant lesions. Measurements were performed using the free hand-drawn region of interest technique. It was investigated whether there was any difference in the evaluated parameters (size, age, gender, and minimum, mean and maximum ADC values). The cut-off value for the parameters evaluated in DWI was determined by the Receiver Operating Characteristic (ROC) analysis.
RESULTS: The mean minimum ADC value was 1,28×10-³mm²/s in benign soft tissue masses and 1,00×10-³mm²/s in malignant soft tissue masses. Minimum ADC values differ statistically between the two groups. (p=0,007). A cut-off value of ≤1,01×10-³mm²/s for the minimum ADC allowed for the characterization of soft tissue masses at 78,95% sensitivity and 73,33% specificity. However, the mean and maximum ADC values were not statistically significantly different between the two groups. (p=0,319 and 0,960, respectively).
CONCLUSIONS: DWI is an effective method in the evaluation of soft tissue masses in the differentiation of benign and malignant, and taking the cut-off value as ≤1,01×10-³mm²/s in the calculation of minimum ADC will increase the clinical usefulness.

Keywords

Diffusion-weighted MRI, Magnetic resonance Imaging, Soft tissue neoplasms.

YUMUŞAK DOKU KİTLELERİNDE DİFÜZYON AĞIRLIKLI GÖRÜNTÜLEME: GÖRÜNÜR DİFÜZYON KATSAYISI ÖLÇÜMÜ MALİGN LEZYONLARI BENİGNLERDEN AYIRABİLİR Mİ ?

Abstract

AMAÇ: Yumuşak doku tümörlerinin değerlendirilmesinde di-füzyon ağırlıklı görüntüleme (DAG) yöntemi ile elde olunan gö-rünür difüzyon katsayısı (apparent diffusion coefficient, ADC) haritalamasının benign ve malign lezyonların ayrımında etkinli-ğini değerlendirmek ve bu lezyonların ayrımında kullanılabile-cek niceliksel ADC eşik değeri oluşturmak.GEREÇ VE YÖNTEM: Bu retrospektif çalışmaya yumuşak doku kitleleri nedeniyle DAG yapılan ve histopatolojik sonuçları mevcut olan toplam 34 hasta dahil edildi. Patolojik sonuçlarına göre hastalar benign ve malign lezyonlara sahip olarak katego-rize edildi. Ölçümler serbest el ilgi bölgesi tekniği kullanılarak yapıldı. Değerlendirilen parametrelerde herhangi bir fark olup olmadığı araştırıldı (boyut, yaş, cinsiyet, minimum, ortalama ve maksimum ADC değerleri). DAG’de değerlendirilen parametre-ler için kesim değeri Alıcı işlem karakteristikleri (ROC), Receiver Operating Characteristic) analizi ile belirlendi. BULGULAR: Minimum ADC değeri ortalaması benign yumuşak doku kitlelerinde 1,28x10-³mm²/s, malign yumuşak doku kit-lelerinde 1,00x10-³mm²/s ölçüldü. Minimum ADC değerleri iki grup arasında istatistiksel olarak anlamlı farklılık göstermekte-dir (p=0,007). Minimum ADC için ≤1,01x10-³mm²/s eşik değerini kullanarak %78,95 duyarlılık ve %73,33 özgüllük ile yumuşak doku kitlelerini karakterize edilmesini sağladık. Ortalama ve maksimum ADC değerleri iki grup arasında istatistiksel olarak anlamlı farklılığa sahip değildir (sırasıyla p=0,319; 0,960). SONUÇ: DAG yumuşak doku kitlelerin değerlendirilmesinde benign ve malign ayrımında etkili bir yöntemdir ve minimum ADC hesaplamasında ≤1,01x10-³mm²/s eşik değerinin kullanımı klinik yararlılığı artıracaktır.

Keywords

Difüzyon ağırlıklı MRG, Manyetik rezo-nans görüntüleme, Yumuşak doku neoplazileri

References

• 1. Frassica FJ, Khanna JA, McCarthy EF. The role of MR imaging in soft tissue tumor evaluation: perspective of the orthopedic oncologist and musculoskeletal pathologist. Magn Reson Imaging Clin N Am. 2000;8:915-27.
• 2. Jackson A, Buckley DL, Parker GJ. Dynamic contrast-enhanced magnetic resonance imaging in oncology. Taylor JS, Reddick WE, editors: Springer. 2005;2:23-37.
• 3. Perez-Rodriguez J, Lai S, Ehst BD, et al. Nephrogenic systemic fibrosis: incidence, associations, and effect of risk factor assessment--report of 33 cases. Radiology. 2009;250:371-7.
• 4. Petscavage-Thomas JM, Walker EA, Logie CI, et al. Soft-tissue myxomatous lesions: review of salient imaging features with pathologic comparison. Radiographics. 2014;34:964-80.
• 5. Lisson CS, Lisson CG, Beer M, et al. Radiological Diagnosis of Soft Tissue Tumors in Adults: MRI Imaging of Selected Entities Delineating Benign and Malignant Tumors. Rofo. 2019;191:323-32.
• 6. Subhawong TK, Jacobs MA, Fayad LM. Insights into quantitative diffusion-weighted MRI for musculoskeletal tumor imaging. AJR Am J Roentgenol. 2014;203:560-72.
• 7. Subhawong TK, Durand DJ, Thawait GK, et al. Characterization of soft tissue masses: can quantitative diffusion weighted imaging reliably distinguish cysts from solid masses? Skeletal Radiol. 2013;42:1583-92.
• 8. Einarsdóttir H, Karlsson M, Wejde J, et al. Diffusion-weighted MRI of soft tissue tumours. Eur Radiol. 2004;14:959-63.
• 9. Nagata S, Nishimura H, Uchida M, et al. Diffusion-weighted imaging of soft tissue tumors: usefulness of the apparent diffusion coefficient for differential diagnosis. Radiat Med. 2008;26:287-95.
• 10. Razek A, Nada N, Ghaniem M, et al. Assessment of soft tissue tumours of the extremities with diffusion echoplanar MR imaging. Radiol Med. 2012;117:96-101.
• 11. Surov A, Nagata S, Razek AA, et al. Comparison of ADC values in different malignancies of the skeletal musculature: a multicentric analysis. Skeletal Radiol. 2015;44:995-1000.
• 12. Subhawong TK, Jacobs MA, Fayad LM. Diffusion-weighted MR imaging for characterizing musculoskeletal lesions. Radiographics. 2014;34:1163-77.
• 13. Del Grande F, Ahlawat S, Subhawong T, et al. 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. 2017;45:390-400.
• 14. Jeon JY, Chung HW, Lee MH, et al. Usefulness of diffusion-weighted MR imaging for differentiating between benign and malignant superficial soft tissue tumours and tumour-like lesions. Br J Radiol. 2016;89:20150929.
• 15. Genovese E, Cani A, Rizzo S, et al. Comparison between MRI with spin-echo echo-planar diffusion-weighted sequence (DWI) and histology in the diagnosis of soft-tissue tumours. La radiologia medica. 2011;116:644-56.
• 16. Maeda M, Matsumine A, Kato H, et al. Soft‐tissue tumors evaluated by line‐scan diffusion‐weighted imaging: Influence of myxoid matrix on the apparent diffusion coefficient. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine. 2007;25:1199-204.
• 17. Baur A, Reiser MF. Diffusion-weighted imaging of the musculoskeletal system in humans. Skeletal Radiol. 2000;29:555-62.
• 18. Yamasaki F, Kurisu K, Satoh K, et al. Apparent diffusion coefficient of human brain tumors at MR imaging. Radiology. 2005;235:985-91.