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Year 2020, Volume: 1 Issue: 1, 6 - 13, 15.06.2020

İrmak Durur-subasi Fatih Alper Pınar Tuncel Adem Karaman Veysel Esdur Elif Demirci Baki Hekimoğlu

Abstract

References

  • Reference1. Fornasa F, Nesoti MV, Bovo C, et al. Diffusion-weighted magnetic resonance imaging in the characterization of axillary lymph nodes in patients with breast cancer. J Magn Reson Imaging 2012; 36:858–64.
  • Reference2. Silverstein MJ, Skinner KA, Lomis TJ. Predicting axillary nodal positivity in 2282 patients with breast carcinoma. World J Surg 2001; 25:767–72.
  • Reference3. Mansel RE, Fallowfield L, Kissin M et al. Randomized multicenter trial of sentinel node biopsy versus standard axillary treatment in operable breast cancer: the ALMANAC trial. J Natl Cancer Inst 2006; 98:599–609.
  • Reference4. Durur-Subasi I, Durur-Karakaya A, Alper F et al (2013) Breast lesions with high signal intensity on T1-weighted MR images. Jpn J Radiol 31:653–61.
  • Reference5. Durur-Subasi I, Alper F, Akcay MN, et al. Magnetic resonance imaging findings of breast juvenile papillomatosis. Jpn J Radiol 2013; 31:419–23.
  • Reference6. Durur-Subasi I, Durur-Karakaya A, Karaman A, et al. Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions? Br J Radiol 2017; 90:20160803.
  • Reference7. Durur-Subasi I, Durur-Karakaya A, Karaman A et al. Value of MRI sequences for prediction of invasive breast carcinoma size. J Med Imaging Radiat Oncol 2014; 58:565–8.
  • Reference8. Durur-Karakaya A, Seker M, Durur-Subasi I. Diffusion-Weighted Imaging in Ectopic Pregnancy: Ring of Restriction Sign. Br J Radiol 2017; 90: 20170528.
  • Reference9. Pinker K, Helbich TH, Morris EA. The potential of multiparametric MRI of the breast. Br J Radiol 2017; 90:20160715.
  • Reference10. Guvenc I, Akay S, Ince S et al. Apparent diffusion coefficient value in invasive ductal carcinoma at 3.0 Tesla: is it correlated with prognostic factors? Br J Radiol 2016; 89:20150614.
  • Reference11. Cakir O, Arslan A, Inan N et al. Comparison of the diagnostic performances of diffusion parameters in diffusion weighted imaging and diffusion tensor imaging of breast lesions. Eur J Radiol 2013; 82:e801–6.
  • Reference12. Eyal E, Shapiro-Feinberg M, Furman-Haran E et al. Parametric diffusion tensor imaging of the breast. Invest Radiol 2012; 47:284–91.
  • Reference13. Partridge SC, Ziadloo A, Murthy R et al. Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging 2010; 31:339–47.
  • Reference14. Baltzer PA, Schäfer A, Dietzel M et al. Diffusion tensor magnetic resonance imaging of the breast: a pilot study. Eur Radiol 2011; 21:1–10.
  • Reference15. Tagliafico A, Rescinito G, Monetti F et al. Diffusion tensor magnetic resonance imaging of the normal breast: reproducibility of DTI-derived fractional anisotropy and apparent diffusion coefficient at 3.0 T. Radiol Med 2012; 117:992–1003.
  • Reference16. Kim JY, Kim JJ, Kim S, Choo KS, Kim A, Kang T, Park H. Diffusion tensor magnetic resonance imaging of breast cancer: associations between diffusion metrics and histological prognostic factors. Eur Radiol 2018; 28:3185-3193.
  • Reference17. Jaimes C, Darge K, Khrichenko D, et al. Diffusion tensor imaging and tractography of the kidney in children: feasibility and preliminary experience. Pediatr Radiol 2014; 44:30–41.
  • Reference18. Partridge SC, Nissan N, Rahbar H, et al. Diffusion-weighted breast MRI: Clinical applications and emerging techniques. J Magn Reson Imaging 2017; 45:337–55.
  • Reference19. Kim SH, Shin HJ, Shin KC et al. Diagnostic Performance of Fused Diffusion-Weighted Imaging Using T1-Weighted Imaging for Axillary Nodal Staging in Patients With Early Breast Cancer. Clin Breast Cancer 2017; 17:154–63.
  • Reference20. Xing H, Song CL, Li WJ. Meta analysis of lymph node metastasis of breast cancer patients: clinical value of DWI and ADC value. Eur J Radiol 2016; 85:1132–7.
  • Reference21. Rautiainen S, Könönen M, Sironen R et al. Preoperative axillary staging with 3.0-T breast MRI: clinical value of diffusion imaging and apparent diffusion coefficient. PLoS One 2015; 10:e0122516.
  • Reference22. Rahbar H, Conlin JL, Parsian S, et al. Suspicious axillary lymph nodes identified on clinical breast MRI in patients newly diagnosed with breast cancer: can quantitative features improve discrimination of malignant from benign? Acad Radiol 2015; 22:430–8.
  • Reference23. Yamaguchi K, Schacht D, Nakazono T, et al. Diffusion weighted images of metastatic as compared with nonmetastatic axillary lymph nodes in patients with newly diagnosed breast cancer. J Magn Reson Imaging 2015; 42:771–8.
  • Reference24. Kamitani T, Hatakenaka M, Yabuuchi H et al. Detection of axillary node metastasis using diffusion-weighted MRI in breast cancer. Clin Imaging 2013; 37:56–61.
  • Reference25. Karaman A, Durur-Subasi I, Alper F, et al. Is it better to include necrosis in apparent diffusion coefficient (ADC) measurements? The necrosis/wall ADC ratio to differentiate malignant and benign necrotic lung lesions: Preliminary results. J Magn Reson Imaging 2017; 46:1001–6.
  • Reference26. Iannicelli E, Di Pietropaolo M, Pilozzi E et al. Value of diffusion-weighted MRI and apparent diffusion coefficient measurements for predicting the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy. Abdom Radiol (NY) 2016; 41:1906–17.
  • Reference27. Nesbakken A, Nygaard K, Westerheim O, et al, Local recurrence after mesorectal excision for rectal cancer. Eur J Surg Oncol 2002; 28:126–34.
  • Reference28. Kapiteijn E, Marijnen CA, Nagtegaal ID et al. Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer. N Engl J Med 2001; 345:638–46.
  • Reference29. Henzler T, Schmid-Bindert G, Schoenberg SO, et al. Diffusion and perfusion MRI of the lung and mediastinum. Eur J Radiol 2010; 76:329–36.
  • Reference30. Durur-Subasi I. DW-MRI of the breast: a pictorial review. Insights Imaging. 2019;10(1):61.
  • Reference31. Durur-Subasi I. Diagnostic and Interventional Radiology in Idiopathic Granulomatous Mastitis. Eurasian J Med. 2019;51(3):293–297.
  • Reference32. Jiang R, Ma Z, Dong H, et al. Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity. Br J Radiol 2016; 89:20160076.

Diffusion tensor imaging of metastatic axillary lymph nodes

Year 2020, Volume: 1 Issue: 1, 6 - 13, 15.06.2020

İrmak Durur-subasi Fatih Alper Pınar Tuncel Adem Karaman Veysel Esdur Elif Demirci Baki Hekimoğlu

Abstract

Objective: It was aimed to investigate whether the fractional anisotropy (FA) differs for the benign and metastatic axillary lymph nodes (LNs).
Material and Methods: 58 women with benign (n=33) and metastatic (n=25) axillary LNs who underwent diffusion weighted and tensor imaging with a 3T scanner were enrolled. Apparent diffusion coefficient (ADC) and FA, cortex thickness, long and short axes were measured retrospectively and compared statistically. Observer reliabilities were also assessed in terms of intra and inter-reviewer variability.
Results: Metastatic LNs showed significantly lower ADC and FA values and greater cortex thickness, long and short axes. ROC test showed the area under the curve values of 0.876 for ADC, 0.661 for FA and 0.960 for cortex thickness. Cortex thickness had excellent sensitivity, specificity, and accuracy. A cutoff value of 3.5 mm for cortex thickness had 92% sensitivity, 94% specificity, 92% positive predictive value (PV), 93% negative PV, and 93% accuracy. A cutoff value of 0.774x10-3 mm2/s for ADC had 84% sensitivity, 82% specificity, 79% positive PV, 90% negative PV, and 84% accuracy. A cutoff value of 0.423 x10-3 mm2/s for FA had 64% sensitivity, 76% specificity, 67% positive PV, 71% negative PV, and 71% accuracy. High intra- and inter-observer reliabilities were seen.
Conclusion: Among the parameters assessed by our study, cortex thickness had superior accuracy. ADC and FA showed a respectable diagnostic performance, especially the first one having a high negative PV and the second one relatively high specificity.

Keywords

Axilla Apparent Diffusion Coefficient Diffusion Tensor Imaging Fractional Anisotropy Lymph Nodes Magnetic Resonance Imaging

References

  • Reference1. Fornasa F, Nesoti MV, Bovo C, et al. Diffusion-weighted magnetic resonance imaging in the characterization of axillary lymph nodes in patients with breast cancer. J Magn Reson Imaging 2012; 36:858–64.
  • Reference2. Silverstein MJ, Skinner KA, Lomis TJ. Predicting axillary nodal positivity in 2282 patients with breast carcinoma. World J Surg 2001; 25:767–72.
  • Reference3. Mansel RE, Fallowfield L, Kissin M et al. Randomized multicenter trial of sentinel node biopsy versus standard axillary treatment in operable breast cancer: the ALMANAC trial. J Natl Cancer Inst 2006; 98:599–609.
  • Reference4. Durur-Subasi I, Durur-Karakaya A, Alper F et al (2013) Breast lesions with high signal intensity on T1-weighted MR images. Jpn J Radiol 31:653–61.
  • Reference5. Durur-Subasi I, Alper F, Akcay MN, et al. Magnetic resonance imaging findings of breast juvenile papillomatosis. Jpn J Radiol 2013; 31:419–23.
  • Reference6. Durur-Subasi I, Durur-Karakaya A, Karaman A, et al. Is the necrosis/wall ADC ratio useful for the differentiation of benign and malignant breast lesions? Br J Radiol 2017; 90:20160803.
  • Reference7. Durur-Subasi I, Durur-Karakaya A, Karaman A et al. Value of MRI sequences for prediction of invasive breast carcinoma size. J Med Imaging Radiat Oncol 2014; 58:565–8.
  • Reference8. Durur-Karakaya A, Seker M, Durur-Subasi I. Diffusion-Weighted Imaging in Ectopic Pregnancy: Ring of Restriction Sign. Br J Radiol 2017; 90: 20170528.
  • Reference9. Pinker K, Helbich TH, Morris EA. The potential of multiparametric MRI of the breast. Br J Radiol 2017; 90:20160715.
  • Reference10. Guvenc I, Akay S, Ince S et al. Apparent diffusion coefficient value in invasive ductal carcinoma at 3.0 Tesla: is it correlated with prognostic factors? Br J Radiol 2016; 89:20150614.
  • Reference11. Cakir O, Arslan A, Inan N et al. Comparison of the diagnostic performances of diffusion parameters in diffusion weighted imaging and diffusion tensor imaging of breast lesions. Eur J Radiol 2013; 82:e801–6.
  • Reference12. Eyal E, Shapiro-Feinberg M, Furman-Haran E et al. Parametric diffusion tensor imaging of the breast. Invest Radiol 2012; 47:284–91.
  • Reference13. Partridge SC, Ziadloo A, Murthy R et al. Diffusion tensor MRI: preliminary anisotropy measures and mapping of breast tumors. J Magn Reson Imaging 2010; 31:339–47.
  • Reference14. Baltzer PA, Schäfer A, Dietzel M et al. Diffusion tensor magnetic resonance imaging of the breast: a pilot study. Eur Radiol 2011; 21:1–10.
  • Reference15. Tagliafico A, Rescinito G, Monetti F et al. Diffusion tensor magnetic resonance imaging of the normal breast: reproducibility of DTI-derived fractional anisotropy and apparent diffusion coefficient at 3.0 T. Radiol Med 2012; 117:992–1003.
  • Reference16. Kim JY, Kim JJ, Kim S, Choo KS, Kim A, Kang T, Park H. Diffusion tensor magnetic resonance imaging of breast cancer: associations between diffusion metrics and histological prognostic factors. Eur Radiol 2018; 28:3185-3193.
  • Reference17. Jaimes C, Darge K, Khrichenko D, et al. Diffusion tensor imaging and tractography of the kidney in children: feasibility and preliminary experience. Pediatr Radiol 2014; 44:30–41.
  • Reference18. Partridge SC, Nissan N, Rahbar H, et al. Diffusion-weighted breast MRI: Clinical applications and emerging techniques. J Magn Reson Imaging 2017; 45:337–55.
  • Reference19. Kim SH, Shin HJ, Shin KC et al. Diagnostic Performance of Fused Diffusion-Weighted Imaging Using T1-Weighted Imaging for Axillary Nodal Staging in Patients With Early Breast Cancer. Clin Breast Cancer 2017; 17:154–63.
  • Reference20. Xing H, Song CL, Li WJ. Meta analysis of lymph node metastasis of breast cancer patients: clinical value of DWI and ADC value. Eur J Radiol 2016; 85:1132–7.
  • Reference21. Rautiainen S, Könönen M, Sironen R et al. Preoperative axillary staging with 3.0-T breast MRI: clinical value of diffusion imaging and apparent diffusion coefficient. PLoS One 2015; 10:e0122516.
  • Reference22. Rahbar H, Conlin JL, Parsian S, et al. Suspicious axillary lymph nodes identified on clinical breast MRI in patients newly diagnosed with breast cancer: can quantitative features improve discrimination of malignant from benign? Acad Radiol 2015; 22:430–8.
  • Reference23. Yamaguchi K, Schacht D, Nakazono T, et al. Diffusion weighted images of metastatic as compared with nonmetastatic axillary lymph nodes in patients with newly diagnosed breast cancer. J Magn Reson Imaging 2015; 42:771–8.
  • Reference24. Kamitani T, Hatakenaka M, Yabuuchi H et al. Detection of axillary node metastasis using diffusion-weighted MRI in breast cancer. Clin Imaging 2013; 37:56–61.
  • Reference25. Karaman A, Durur-Subasi I, Alper F, et al. Is it better to include necrosis in apparent diffusion coefficient (ADC) measurements? The necrosis/wall ADC ratio to differentiate malignant and benign necrotic lung lesions: Preliminary results. J Magn Reson Imaging 2017; 46:1001–6.
  • Reference26. Iannicelli E, Di Pietropaolo M, Pilozzi E et al. Value of diffusion-weighted MRI and apparent diffusion coefficient measurements for predicting the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy. Abdom Radiol (NY) 2016; 41:1906–17.
  • Reference27. Nesbakken A, Nygaard K, Westerheim O, et al, Local recurrence after mesorectal excision for rectal cancer. Eur J Surg Oncol 2002; 28:126–34.
  • Reference28. Kapiteijn E, Marijnen CA, Nagtegaal ID et al. Preoperative radiotherapy combined with total mesorectal excision for resectable rectal cancer. N Engl J Med 2001; 345:638–46.
  • Reference29. Henzler T, Schmid-Bindert G, Schoenberg SO, et al. Diffusion and perfusion MRI of the lung and mediastinum. Eur J Radiol 2010; 76:329–36.
  • Reference30. Durur-Subasi I. DW-MRI of the breast: a pictorial review. Insights Imaging. 2019;10(1):61.
  • Reference31. Durur-Subasi I. Diagnostic and Interventional Radiology in Idiopathic Granulomatous Mastitis. Eurasian J Med. 2019;51(3):293–297.
  • Reference32. Jiang R, Ma Z, Dong H, et al. Diffusion tensor imaging of breast lesions: evaluation of apparent diffusion coefficient and fractional anisotropy and tissue cellularity. Br J Radiol 2016; 89:20160076.
There are 32 citations in total.

Details

Primary Language English
Subjects ​Internal Diseases
Journal Section Research Articles
Authors

İrmak Durur-subasi 0000-0003-3122-4499

Fatih Alper 0000-0002-9483-8861

Pınar Tuncel 0000-0002-2417-8546

Adem Karaman 0000-0002-3091-0609

Veysel Esdur This is me 0000-0001-6729-3600

Elif Demirci

Baki Hekimoğlu 0000-0002-1824-5853

Publication Date June 15, 2020
Submission Date May 24, 2020
Published in Issue Year 2020 Volume: 1 Issue: 1

Cite

EndNote Durur-subasi İ, Alper F, Tuncel P, Karaman A, Esdur V, Demirci E, Hekimoğlu B (June 1, 2020) Diffusion tensor imaging of metastatic axillary lymph nodes. New Trends in Medicine Sciences 1 1 6–13.
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