Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
권호 표지
DOI QR코드

DOI QR Code

The Adjacent Vessel Sign on Breast MRI: New Data and a Subgroup Analysis for 1,084 Histologically Verified Cases

  • Dietzel, Matthias (Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena) ;
  • Baltzer, Pascal A.T. (Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena) ;
  • Vag, Tibor (Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena) ;
  • Herzog, Aimee (Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena) ;
  • Gajda, Mieczyslaw (Institute of Pathology, Friedrich-Schiller-University Jena) ;
  • Camara, Oumar (Clinic of Gynecology, Friedrich-Schiller-University Jena) ;
  • Kaiser, Werner A. (Institute of Diagnostic and Interventional Radiology, Friedrich-Schiller-University Jena)
  • Received : 2009.07.14
  • Accepted : 2009.11.02
  • Published : 2010.04.01
⟨ Previous Next ⟩

Abstract

Objective: The adjacent vessel sign (AVS) is a descriptor for differentiating malignant from benign breast lesions on breast MRI (bMRI). This investigation was designed to verify the previous reports on the diagnostic accuracy of AVS and to assess correlation between AVS, histopathological diagnosis, lesion size and lesion grade. Materials and Methods: This study was approved by the local ethical committee. Experienced radiologists evaluated 1,084 lesions. The exclusion criteria were no histological verification after bMRI and breast interventions that were done up to one year before bMRI (surgery, core biopsy, chemo- or radiation therapy). The native and dynamic contrast-enhanced T1-weighted series were acquired using standardized protocols. The AVS was rated positive if a vessel leading to a lesion could be visualized. Prevalence of an AVS was correlated with the lesions' size, grade and histology using Chi-square-tests. Results: The AVS was significantly associated with malignancy (p < 0.001; sensitivity: 47%, specificity: 88%, positive-predictive-value (PPV): 85%). Malignant lesions > 2 cm more often presented with an AVS than did those malignant lesions < 2 cm (p < 0.0001; sensitivity: 65%, PPV: 90%). There was no correlation of the AVS with the tumor grade. The prevalence of an AVS didn't significantly differ between invasive lobular carcinomas versus ductal carcinomas. In situ cancers were less frequently associated with an AVS (p < 0.001). Conclusion: The adjacent vessel sign was significantly associated with malignancy. Thus, it can be used to accurately assess breast lesions on bMRI. In this study, the AVS was particularly associated with advanced and invasive carcinomas.

Keywords

References

  1. Fischer DR, Malich A, Wurdinger S, Boettcher J, Dietzel M, Kaiser WA. The adjacent vessel on dynamic contrast-enhanced breast MRI. AJR Am J Roentgenol 2006;187:W147-W151 https://doi.org/10.2214/AJR.05.0377
  2. Fischer DR, Wurdinger S, Boettcher J, Malich A, Kaiser WA. Further signs in the evaluation of magnetic resonance mammography: a retrospective study. Invest Radiol 2005;40:430-435 https://doi.org/10.1097/01.rli.0000167138.52283.aa
  3. Malich A, Fischer DR, Wurdinger S, Boettcher J, Marx C, Facius M, et al. Potential MRI interpretation model: differentiation of benign from malignant breast masses. AJR Am J Roentgenol 2005;185:964-970 https://doi.org/10.2214/AJR.04.1073
  4. Peters NH, Borel Rinkes IH, Zuithoff NP, Mali WP, Moons KG, Peeters PH. Meta-analysis of MR imaging in the diagnosis of breast lesions. Radiology 2008;246:116-124 https://doi.org/10.1148/radiol.2461061298
  5. Lee SH, Cho N, Kim SJ, Cha JH, Cho KS, Ko ES, et al. Correlation between high resolution dynamic MR features and prognostic factors in breast cancer. Korean J Radiol 2008;9:10-18 https://doi.org/10.3348/kjr.2008.9.1.10
  6. Ko EY, Han BK, Shin JH, Kang SS. Breast MRI for evaluating patients with metastatic axillary lymph node and initially negative mammography and sonography. Korean J Radiol 2007;8:382-389 https://doi.org/10.3348/kjr.2007.8.5.382
  7. Kim do Y, Moon WK, Cho N, Ko ES, Yang SK, Park JS, et al. MRI of the breast for the detection and assessment of the size of ductal carcinoma in situ. Korean J Radiol 2007;8:32-39 https://doi.org/10.3348/kjr.2007.8.1.32
  8. Renz DM, Baltzer PA, Kullnig PE, Bottcher J, Vag T, Gajda M, et al. Clinical value of computer-assisted analysis in MR mammography. A comparison between two systems and three observers with different levels of experience. Rofo 2008;180:968-976 https://doi.org/10.1055/s-2008-1027772
  9. Williams TC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. Breast MR imaging: computer-aided evaluation program for discriminating benign from malignant lesions. Radiology 2007;244:94-103 https://doi.org/10.1148/radiol.2441060634
  10. Thomas MA, Lipnick S, Velan SS, Liu X, Banakar S, Binesh N, et al. Investigation of breast cancer using two-dimensional MRS. NMR Biomed 2009;22:77-91 https://doi.org/10.1002/nbm.1310
  11. Mountford C, Ramadan S, Stanwell P, Malycha P. Proton MRS of the breast in the clinical setting. NMR Biomed 2009;22:54-64 https://doi.org/10.1002/nbm.1301
  12. Sardanelli F, Fausto A, Esseridou A, Di Leo G, Kirchin MA. Gadobenate dimeglumine as a contrast agent for dynamic breast magnetic resonance imaging: effect of higher initial enhancement thresholds on diagnostic performance. Invest Radiol 2008;43:236-242 https://doi.org/10.1097/RLI.0b013e318160678d
  13. Yabuuchi H, Matsuo Y, Okafuji T, Kamitani T, Soeda H, Setoguchi T, et al. Enhanced mass on contrast-enhanced breast MR imaging: lesion characterization using combination of dynamic contrast-enhanced and diffusion-weighted MR images. J Magn Reson Imaging 2008;28:1157-1165 https://doi.org/10.1002/jmri.21570
  14. Park JM, Park JH. Human in-vivo 31P MR spectroscopy of benign and malignant breast tumors. Korean J Radiol 2001;2:80-86 https://doi.org/10.3348/kjr.2001.2.2.80
  15. Vassiou K, Kanavou T, Vlychou M, Poultsidi A, Athanasiou E, Arvanitis DL, et al. Characterization of breast lesions with CEMR multimodal morphological and kinetic analysis: comparison with conventional mammography and high-resolution ultrasound. Eur J Radiol 2009;70:69-76 https://doi.org/10.1016/j.ejrad.2008.01.012
  16. Tardivon AA, Athanasiou A, Thibault F, El Khoury C. Breast imaging and reporting data system (BIRADS): magnetic resonance imaging. Eur J Radiol 2007;61:212-215 https://doi.org/10.1016/j.ejrad.2006.08.036
  17. Dietzel M, Baltzer PAT, Vag T, Gajda M, Camara O, Kaiser WA. The hook sign for differential diagnosis of malignant from benign lesions in magnetic resonance mammography - Experience in a study of 1084 histologically verified cases. Acta Radiol 2010;51:137-143 https://doi.org/10.3109/02841850903463638
  18. Elston CW, Ellis IO. Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up. Histopathology 1991;19:403-410 https://doi.org/10.1111/j.1365-2559.1991.tb00229.x
  19. Armitage P, Berry G. Statistical methods in medical research, 3rd ed. London: Blackwell Scientific, 1994:131
  20. Newcombe RG. Two-sided confidence intervals for the single proportion: comparison of seven methods. Stat Med 1998;17:857-872 https://doi.org/10.1002/(SICI)1097-0258(19980430)17:8<857::AID-SIM777>3.0.CO;2-E
  21. Bland M. An introduction to medical statistics. Oxford: Oxford University Press, 2000
  22. Langer SA, Horst KC, Ikeda DM, Daniel BL, Kong CS, Dirbas FM. Pathologic correlates of false positive breast magnetic resonance imaging findings: which lesions warrant biopsy? Am J Surg 2005;190:633-640 https://doi.org/10.1016/j.amjsurg.2005.06.030
  23. Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesis and metastasis--correlation in invasive breast carcinoma. N Engl J Med 1991;324:1-8 https://doi.org/10.1056/NEJM199101033240101
  24. Bassler R. Mamma. In: Remmele W, ed. Pathologie. Berlin: Springer, 1997:135-365
  25. Fridman V, Humblet C, Bonjean K, Boniver J. Assessment of tumor angiogenesis in invasive breast carcinomas: absence of correlation with prognosis and pathological factors. Virchows Arch 2000;437:611-617 https://doi.org/10.1007/s004280000292
  26. Weidner N, Folkman J, Pozza F, Bevilacqua P, Allred EN, Moore DH, et al. Tumor angiogenesis: a new significant and independent prognostic indicator in early-stage breast carcinoma. J Natl Cancer Inst 1992;84:1875-1887 https://doi.org/10.1093/jnci/84.24.1875
  27. Westerhof JP, Fischer U, Moritz JD, Oestmann JW. MR imaging of mammographically detected clustered microcalcifications: is there any value? Radiology 1998;207:675-681 https://doi.org/10.1148/radiology.207.3.9609890
  28. Gilles R, Meunier M, Lucidarme O, Zafrani B, Guinebretiere JM, Tardivon AA, et al. Clustered breast microcalcifications: evaluation by dynamic contrast-enhanced subtraction MRI. J Comput Assist Tomogr 1996;20:9-14 https://doi.org/10.1097/00004728-199601000-00003
  29. Brinck U, Fischer U, Korabiowska M, Jutrowski M, Schauer A, Grabbe E. The variability of fibroadenoma in contrast-enhanced dynamic MR mammography. AJR Am J Roentgenol 1997;168:1331-1334 https://doi.org/10.2214/ajr.168.5.9129437
  30. Folkman J, Shing Y. Angiogenesis. J Biol Chem 1992;267:10931-10934
  31. Kaiser WA. MR mammography--a critical stocktaking. Rofo 1996;165:425-427 https://doi.org/10.1055/s-2007-1015784
  32. Fischer U, Kopka L, Grabbe E. Breast carcinoma: effect of preoperative contrast-enhanced MR imaging on the therapeutic approach. Radiology 1999;213:881-888 https://doi.org/10.1148/radiology.213.3.r99dc01881
  33. Nunes LW, Schnall MD, Orel SG, Hochman MG, Langlotz CP, Reynolds CA, et al. Breast MR imaging: interpretation model. Radiology 1997;202:833-841 https://doi.org/10.1148/radiology.202.3.9051042
  34. Kuhl CK. Current status of breast MR imaging. Part 2. Clinical applications. Radiology 2007;244:672-691 https://doi.org/10.1148/radiol.2443051661
  35. Liberman L, Mason G, Morris EA, Dershaw DD. Does size matter? Positive predictive value of MRI-detected breast lesions as a function of lesion size. AJR Am J Roentgenol 2006;186:426-430 https://doi.org/10.2214/AJR.04.1707

Cited by

  1. Magnetic Resonance Mammography of Invasive Lobular Versus Ductal Carcinoma: Systematic Comparison of 811 Patients Reveals High Diagnostic Accuracy Irrespective of Typing vol.34, pp.4, 2010, https://doi.org/10.1097/rct.0b013e3181db9f0e
  2. The Necrosis Sign in Magnetic Resonance-Mammography: Diagnostic Accuracy in 1,084 Histologically Verified Breast Lesions vol.16, pp.6, 2010, https://doi.org/10.1111/j.1524-4741.2010.00982.x
  3. Vessel Analysis on Contrast-Enhanced MRI of the Breast: Global or Local Vascularity? vol.195, pp.5, 2010, https://doi.org/10.2214/ajr.10.4984
  4. Resolving arterial phase and temporal enhancement characteristics in DCE MRM at high spatial resolution with TWIST acquisition vol.34, pp.4, 2010, https://doi.org/10.1002/jmri.22689
  5. The Great Mimicker: Zona Zoster at the Mastectomy Site Causing Contralateral Intramammary Lymph Node Enlargement vol.2012, pp.None, 2012, https://doi.org/10.1155/2012/468576
  6. Prognostic Role of MRI Enhancement Features in Patients With Breast Cancer: Value of Adjacent Vessel Sign and Increased Ipsilateral Whole-Breast Vascularity vol.199, pp.4, 2010, https://doi.org/10.2214/ajr.11.7895
  7. A Fully Automatic Multiscale 3-Dimensional Hessian-Based Algorithm for Vessel Detection in Breast DCE-MRI vol.47, pp.12, 2010, https://doi.org/10.1097/rli.0b013e31826dc3a4
  8. Bilateral analysis of the cross-sectional area of the internal mammary arteries and veins in patients with and without breast cancer on breast magnetic resonance imaging vol.4, pp.2, 2013, https://doi.org/10.1007/s13244-012-0214-8
  9. A simple and robust classification tree for differentiation between benign and malignant lesions in MR-mammography vol.23, pp.8, 2010, https://doi.org/10.1007/s00330-013-2804-3
  10. Adjacent vessel sign and breast imaging reporting and data system are valuable for diagnosis of benign and malignant breast lesions vol.28, pp.6, 2014, https://doi.org/10.1080/13102818.2014.974016
  11. A Rim-Enhanced Mass with Central Cystic Changes on MR Imaging: How to Distinguish Breast Cancer from Inflammatory Breast Diseases? vol.9, pp.3, 2010, https://doi.org/10.1371/journal.pone.0090355
  12. Effectiveness of Additional Diagnostic Parameters in Magnetic Resonance Mammography: A Comparative Study with the BI-RADS Classification and Scoring System vol.38, pp.6, 2014, https://doi.org/10.1097/rct.0000000000000132
  13. Magnetic Resonance Imaging of Intraductal Papillomas: Typical Findings and Differential Diagnosis vol.39, pp.2, 2010, https://doi.org/10.1097/rct.0000000000000188
  14. Dynamic contrast-enhanced breast magnetic resonance imaging for the prediction of early and late recurrences in breast cancer vol.95, pp.48, 2010, https://doi.org/10.1097/md.0000000000005330
  15. Breast Contrast Enhanced MR Imaging: Semi-Automatic Detection of Vascular Map and Predominant Feeding Vessel vol.11, pp.8, 2010, https://doi.org/10.1371/journal.pone.0161691
  16. Radiological imaging characteristics of intramammary hematological malignancies: results from a german multicenter study vol.7, pp.None, 2010, https://doi.org/10.1038/s41598-017-07409-z
  17. Quantitative analysis of vascular properties derived from ultrafast DCE‐MRI to discriminate malignant and benign breast tumors vol.81, pp.3, 2019, https://doi.org/10.1002/mrm.27529
  18. Prediction of Axillary Lymph Node Metastasis in Early Breast Cancer Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging and Diffusion-Weighted Imaging vol.23, pp.2, 2019, https://doi.org/10.13104/imri.2019.23.2.125
  19. Dynamic contrast‐enhanced and diffusion‐weighted MRI of invasive breast cancer for the prediction of sentinel lymph node status vol.51, pp.2, 2010, https://doi.org/10.1002/jmri.26865