J Korean Soc Magn Reson Med.  2013 Jun;17(2):101-109. 10.13104/jksmrm.2013.17.2.101.

Preoperative Prediction of Ductal Carcinoma in situ Underestimation of the Breast using Dynamic Contrast Enhanced and Diffusion-weighted Imaging

• Park M
• Kim EK
• Kim MJ
• Moon HJ

• KMID: 2099869
• DOI: http://doi.org/10.13104/jksmrm.2013.17.2.101

Abstract

OBJECTIVE
To investigate roles of dynamic contrast enhanced magnetic resonance (DCE MR) and diffusion-weighted (DW) imaging in preoperative prediction of underestimation of ductal carcinoma in situ (DCIS)> or =2cm on US guided core needle biopsy.
MATERIALS AND METHODS
Twenty two patients with DCIS on US-guided 14 gauge core needle biopsy were included. Patients were divided into a group with and without DCIS underestimation based on histopathology. MR images including DCE and DW imaging were obtained with a 3.0-T MR. The lesion type (mass or non-mass), enhancement pattern, peak enhancement, and apparent diffusion coefficient (ADC) values of proven malignant masses were generated using software of CADstream and compared between two groups using Fisher's exact test and Mann Whitney test.
RESULTS
Eight patients were in the group with underestimation and 14 patients were in the group without underestimation. The lesion type and enhancement pattern were not different between two groups (P values = 1.000 and 0.613, respectively). The median peak enhancement of lesions with underestimation was 159.5%, higher than 133.5% of those without underestimation, but not significant (P value = 0.413). The median ADC value of lesions with underestimation was 1.26x10(-3) mm2/sec, substantially lower than 1.35x10(-3) mm2/sec of those without underestimation (P value = 0.094).
CONCLUSION
ADC values had the potential to preoperatively predict DCIS underestimation on US-guided core needle biopsy, although a large prospective series study should be conducted to confirm these results.

Keyword

Breast malignancy; Underestimation; Breast core needle biopsy; Dynamic contrast enhanced magnetic resonance imaging; Diffusion-weighted magnetic resonance imaging

MeSH Terms

Biopsy, Large-Core Needle
Breast
Carcinoma, Ductal
Carcinoma, Intraductal, Noninfiltrating
Diffusion
Humans
Magnetic Resonance Spectroscopy
Needles

Figure

• 

  Fig. 1 Depiction of peak enhancement and drawing region of interest to measure apparent diffusion coefficient on apparent diffusion coefficient map using CADstream. a. A 73-year-old woman had a 23 mm enhancing lesion in her left breast on a T1-weighted non-fat-suppressed dynamic contrast-enhanced image (arrow). The lesion was diagnosed as ductal carcinoma in situ on ultrasound guided core needle biopsy. b. The peak enhancement within the enhancing lesion was 181%. c. The lesion demonstrated low signal intensity on the apparent diffusion coefficient mapping image. d. The apparent diffusion coefficient value of the lesion on the apparent diffusion coefficient map was 1.13×10-3 mm2/sec and the mean apparent diffusion coefficient of three measurements was 1.17×10-3 mm2/sec. She was diagnosed as an invasive ductal carcinoma with 19 mm of the invasive component, not otherwise specified in her left breast at surgery, and was placed in the group with underestimation.

• 

  Fig. 2 A 49-year-old woman with ductal carcinoma in situ without underestimation. a. A 49 mm lesion showed enhancement in the right breast on T1-weighted dynamic contrast-enhanced image (arrow) and the lesion was diagnosed as ductal carcinoma in situ on ultrasound guided 14-gauge core needle biopsy. b. The peak enhancement within the lesion was 164%. c. The lesion showed low signal intensity on the apparent diffusion coefficient mapping image. d. The apparent diffusion coefficient value of the lesions was 1.62×10-3 mm2/sec and mean of three measurements was 1.66×10-3 mm2/sec.

Reference

1. Schueller G, Jaromi S, Ponhold L, et al. US-guided 14-gauge core-needle breast biopsy: results of a validation study in 1352 cases. Radiology. 2008; 248:406.

2. Liberman L. Clinical management issues in percutaneous core breast biopsy. Radiol Clin North Am. 2000; 38:791–807.

3. Youk JH, Kim EK, Kwak JY, Son EJ, Park BW, Kim SI. Benign papilloma without atypia diagnosed at US-guided 14-gauge core-needle biopsy: clinical and US features predictive of upgrade to malignancy. Radiology. 2011; 258:81–88.

4. O'Flynn EA, Wilson AR, Michell MJ. Image-guided breast biopsy: state-of-the-art. Clin Radiol. 2010; 65:259–270.

5. Helbich TH, Matzek W, Fuchsjäger MH. Stereotactic and ultrasound-guided breast biopsy. Eur Radiol. 2004; 14:383–393.

6. Sauer G, Deissler H, Strunz K, et al. Ultrasound-guided large-core needle biopsies of breast lesions: analysis of 962 cases to determine the number of samples for reliable tumour classification. Br J Cancer. 2005; 92:231–235.

7. Schoonjans JM, Brem RF. Fourteen-gauge ultrasonographically guided large-core needle biopsy of breast masses. J Ultrasound Med. 2001; 20:967–972.

8. Smith DN, Rosenfield Darling ML, Meyer JE, et al. The utility of ultrasonographically guided large-core needle biopsy: results from 500 consecutive breast biopsies. J Ultrasound Med. 2001; 20:43–49.

9. Suh Y, Kim M, Kim E, et al. Comparison of the underestimation rate in cases with ductal carcinoma in situ at ultrasound-guided core biopsy: 14-gauge automated core-needle biopsy vs 8-or 11-gauge vacuum-assisted biopsy. Br J Radiol. 2012; 85:e349–e356.

10. Verkooijen HM, Peeters PH, Buskens E, et al. Diagnostic accuracy of large-core needle biopsy for nonpalpable breast disease: a meta-analysis. Br J Cancer. 2000; 82:1017–1021.

11. Bhooshan N, Giger ML, Jansen SA, Li H, Lan L, Newstead GM. Cancerous breast lesions on dynamic contrast-enhanced MR images: computerized characterization for image-based prognostic markers. Radiology. 2010; 254:680–690.

12. Edge SB, Byrd DR, Compton CC, Fritz AG, Greene FL, Trotti A. AJCC Cancer Staging Manual. 7th ed. Chicago, IL: Springer;2009.

13. Kuhl CK, Schild HH. Dynamic image interpretation of MRI of the breast. J Magn Reson Imaging. 2000; 12:965–974.

14. Van Goethem M, Schelfout K, Kersschot E, et al. Comparison of MRI features of different grades of DCIS and invasive carcinoma of the breast. JBR BTR. 2005; 88:225–232.

15. Chen W, Giger ML, Li H, Bick U, Newstead GM. Volumetric texture analysis of breast lesions on contrast-enhanced magnetic resonance images. Magn Reson Med. 2007; 58:562–571.

16. Peters NH, Vincken KL, van den Bosch MA, Luijten PR, Mali WP, Bartels LW. Quantitative diffusion weighted imaging for differentiation of benign and malignant breast lesions: the influence of the choice of b-values. J Magn Reson Imaging. 2010; 31:1100–1105.

17. Rubesova E, Grell AS, De Maertelaer V, Metens T, Chao SL, Lemort M. Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging. 2006; 24:319–324.

18. Woodhams R, Matsunaga K, Kan S, et al. ADC mapping of benign and malignant breast tumors. Magn Reson Med Sci. 2005; 4:35–42.

19. Iima M, Le Bihan D, Okumura R, et al. Apparent diffusion coefficient as an MR imaging biomarker of low-risk ductal carcinoma in situ: a pilot study. Radiology. 2011; 260:364–372.

20. Rahbar H, Partridge SC, Eby PR, et al. Characterization of ductal carcinoma in situ on diffusion-weighted breast MRI. Eur Radiol. 2011; 21:2011–2019.

21. Partridge SC, Demartini WB, Kurland BF, Eby PR, White SW, Lehman CD. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010; 31:562–570.

22. Moon M, Cornfeld D, Weinreb J. Dynamic contrast-enhanced breast MR imaging. Magn Reson Imaging Clin N Am. 2009; 17:351–362.

23. Cho N, Moon WK, Chang JM, et al. Sonoelastographic lesion stiffness: preoperative predictor of the presence of an invasive focus in nonpalpable DCIS diagnosed at US-guided needle biopsy. Eur Radiol. 2011; 21:1618–1627.

24. Lyman GH, Giuliano AE, Somerfield MR, et al. American Society of Clinical Oncology guideline recommendations for sentinel lymph node biopsy in early-stage breast cancer. J Clin Oncol. 2005; 23:7703–7720.

25. American Cancer Society. Breast cancer survival rates by stage. 2012.

26. Gutierrez RL, DeMartini WB, Silbergeld JJ, et al. High cancer yield and positive predictive value: outcomes at a center routinely using preoperative breast MRI for staging. AJR Am J Roentgenol. 2011; 196:W93–W99.

27. Houssami N, Ciatto S, Macaskill P, et al. Accuracy and surgical impact of magnetic resonance imaging in breast cancer staging: systematic review and meta-analysis in detection of multifocal and multicentric cancer. J Clin Oncol. 2008; 26:3248–3258.

28. Pengel KE, Loo CE, Teertstra HJ, et al. The impact of preoperative MRI on breast-conserving surgery of invasive cancer: a comparative cohort study. Breast Cancer Res Treat. 2009; 116:161–169.

29. Rosen EL, Smith-Foley SA, DeMartini WB, Eby PR, Peacock S, Lehman CD. BI-RADS MRI Enhancement characteristics of ductal carcinoma in situ. Breast J. 2007; 13:545–550.

30. Jansen SA. Ductal carcinoma in situ: detection, diagnosis, and characterization with magnetic resonance imaging. Semin Ultrasound CT MR. 2011; 32:306–318.

31. Sakamoto N, Tozaki M, Higa K, et al. Categorization of non-mass-like breast lesions detected by MRI. Breast Cancer. 2008; 15:241–246.

32. Lehman CD, Peacock S, DeMartini WB, Chen X. A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity. AJR Am J Roentgenol. 2006; 187:51–56.

33. Meeuwis C, Van de Ven SM, Stapper G, et al. Computer-aided detection (CAD) for breast MRI: evaluation of efficacy at 3.0 T. Eur Radiol. 2010; 20:522–528.

34. Wang LC, DeMartini WB, Partridge SC, Peacock S, Lehman CD. MRI-detected suspicious breast lesions: predictive values of kinetic features measured by computer-aided evaluation. AJR Am J Roentgenol. 2009; 193:826–831.

35. Jansen SA, Newstead GM, Abe H, Shimauchi A, Schmidt RA, Karczmar GS. Pure ductal carcinoma in situ: kinetic and morphologic MR characteristics compared with mammographic appearance and nuclear grade. Radiology. 2007; 245:684–691.

36. Newell D, Nie K, Chen JH, et al. Selection of diagnostic features on breast MRI to differentiate between malignant and benign lesions using computer-aided diagnosis: differences in lesions presenting as mass and non-mass-like enhancement. Eur Radiol. 2010; 20:771–781.

37. Woodhams R, Ramadan S, Stanwell P, et al. Diffusion-weighted imaging of the breast: principles and clinical applications. Radiographics. 2011; 31:1059–1084.

38. Kuroki-Suzuki S, Kuroki Y, Nasu K, Nawano S, Moriyma N, Okazaki M. Detecting breast cancer with non-contrast MR imaging: combining diffusion-weighted and STIR imaging. Magn Reson Med Sci. 2007; 6:21–27.

39. Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C. Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol. 2007; 17:2646–2655.

40. Kuhl CK, Schrading S, Bieling HB, et al. MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study. Lancet. 2007; 370:485–492.

41. Liberman L, Morris EA, Dershaw DD, Abramson AF, Tan LK. MR imaging of the ipsilateral breast in women with percutaneously proven breast cancer. AJR Am J Roentgenol. 2003; 180:901–910.