Abstract
The purpose of this study was to investigate prospectively whether the apparent diffusion coefficients (ADCs) of both breast cancer and normal fibroglandular tissue vary with the menstrual cycle and menopausal status. Institutional review board approval was obtained, and informed consent was obtained from each participant. Fifty-seven women (29 premenopausal, 28 postmenopausal) with newly diagnosed breast cancer underwent diffusion-weighted imaging twice (interval 12–20 days) before surgery. Two radiologists independently measured ADC of breast cancer and normal contralateral breast tissue, and we quantified the differences according to the phases of menstrual cycle and menopausal status. With normal fibroglandular tissue, ADC was significantly lower in postmenopausal than in premenopausal women (P = 0.035). In premenopausal women, ADC did not differ significantly between proliferative and secretory phases in either breast cancer or normal fibroglandular tissue (P = 0.969 and P = 0.519, respectively). In postmenopausal women, no significant differences were found between ADCs measured at different time intervals in either breast cancer or normal fibroglandular tissue (P = 0.948 and P = 0.961, respectively). The within-subject variability of the ADC measurements was quantified using the coefficient of variation (CV) and was small: the mean CVs of tumor ADC were 2.90 % (premenopausal) and 3.43 % (postmenopausal), and those of fibroglandular tissue ADC were 4.37 % (premenopausal) and 2.55 % (postmenopausal). Both intra- and interobserver agreements were excellent for ADC measurements, with intraclass correlation coefficients in the range of 0.834–0.974. In conclusion, the measured ADCs of breast cancer and normal fibroglandular tissue were not affected significantly by menstrual cycle, and the measurements were highly reproducible both within and between observers.
Similar content being viewed by others
References
Ramakrishnan R, Khan SA, Badve S (2002) Morphological changes in breast tissue with menstrual cycle. Mod Pathol 15:1348–1356
Longacre TA, Bartow SA (1986) A correlative morphologic study of human breast and endometrium in the menstrual cycle. Am J Surg Pathol 10:382–393
Vogel PM, Georgiade NG, Fetter BF, Vogel FS, McCarty KS Jr (1981) The correlation of histologic changes in the human breast with the menstrual cycle. Am J Pathol 104:23–34
Kuhl CK, Bieling HB, Gieseke J, Kreft BP, Sommer T, Lutterbey G, Schild HH (1997) Healthy premenopausal breast parenchyma in dynamic contrast-enhanced MR imaging of the breast: normal contrast medium enhancement and cyclical-phase dependency. Radiology 203:137–144
Muller-Schimpfle M, Ohmenhauser K, Stoll P, Dietz K, Claussen CD (1997) Menstrual cycle and age: influence on parenchymal contrast medium enhancement in MR imaging of the breast. Radiology 203:145–149
Sardanelli F, Boetes C, Borisch B et al (2010) Magnetic resonance imaging of the breast: recommendations from the EUSOMA working group. Eur J Cancer 46:1296–1316
Partridge SC (2008) Future applications and innovations of clinical breast magnetic resonance imaging. Top Magn Reson Imaging 19:171–176
Partridge SC, Mullins CD, Kurland BF, Allain MD, DeMartini WB, Eby PR, Lehman CD (2010) Apparent diffusion coefficient values for discriminating benign and malignant breast MRI lesions: effects of lesion type and size. Am J Roentgenol 194:1664–1673
Marini C, Iacconi C, Giannelli M, Cilotti A, Moretti M, Bartolozzi C (2007) Quantitative diffusion-weighted MR imaging in the differential diagnosis of breast lesion. Eur Radiol 17:2646–2655
Rubesova E, Grell A, De Maertelaer V, Metens T, Chao SL, Lemort M (2006) Quantitative diffusion imaging in breast cancer: a clinical prospective study. J Magn Reson Imaging 24:319–324
Kim JY, Seo HB, Park S, Moon JI, Lee JW, Lee NK, Lee SW, Bae YT (2015) Early-stage invasive ductal carcinoma: association of tumor apparent diffusion coefficient values with axillary lymph node metastasis. Eur J Radiol 84:2137–2143
Razek AA, Gaballa G, Denewer NadaN (2010) Invasive ductal carcinoma: correlation of apparent diffusion coefficient value with pathological prognostic factors. NMR Biomed 23:619–623
Wu L, Hu J, Gu H, Hua J, Chen J, Xu JR (2012) Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer? Breast Cancer Res Treat 135:17–28
O’Flynn EA, Morgan VA, Giles SL (2012) Diffusion weighted imaging of the normal breast: reproducibility of apparent diffusion coefficient measurements and variation with menstrual cycle and menopausal status. Eur Radiol 22:1512–1518
Partridge SC, McKinnon GC, Henry RG, Hylton NM (2001) Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI. J Magn Reson Imaging 14:433–438
Shin S, Ko ES, Kim RB, Han BK, Nam SJ, Shin JH, Hahn SY (2015) Effect of menstrual cycle and menopausal status on apparent diffusion coefficient values and detectability of invasive ductal carcinoma on diffusion-weighted MRI. Breast Cancer Res Treat 149:751–759
Clendenen TV, Kim S, Moy L, Wan L, Rusinek H, Stanczyk FZ, Pike MC, Zeleniuch-Jacquotte A (2013) Magnetic resonance imaging (MRI) of hormone-induced breast changes in young premenopausal women. Magn Reson Imaging 31(1):1–9
El Khouli RH, Jacobs MA, Mezban SD, Huang P, Kamel IR, Macura KJ, Bluemke DA (2010) Diffusion-weighted imaging improves the diagnostic accuracy of conventional 3.0-T breast MR imaging. Radiology 256:64–73
Martincich L, Deantoni V, Bertotto I, Redana S, Kubatzki F, Sarotto I, Rossi V, Liotti M, Ponzone R, Aglietta M, Regge D, Montemurro F (2012) Correlations between diffusion-weighted imaging and breast cancer biomarkers. Eur Radiol 22:1519–1528
Nissan N, Furman-Haran E, Shapiro-Feinberg M, Grobgeld D, Degani H (2014) Diffusion-tensor MR imaging of the breast: hormonal regulation. Radiology 271:672–680
Hagmann P, Jonasson L, Maeder P, Thiran JP, Wedeen VJ, Meuli R (2006) Understanding diffusion MR Imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 26:S205–S223
Partridge SC, Singer L, Sun R, Wilmes LJ, Klifa CS, Lehman CD, Hylton NM (2011) Diffusion-weighted MRI: influence of intravoxel fat signal and breast density on breast tumor conspicuity and apparent diffusion coefficient measurements. Magn Reson Imaging 29:1215–1221
Wolfe JN (1976) Breast parenchymal patterns and their changes with age. Radiology 121:545–552
Pickles MD, Gibbs P, Lowry M (2006) Diffusion changes precede size reduction in neoadjuvant treatment of breast cancer. Magn Reson Imaging 24:843–847
Sharma U, Danishad KKA, Seenu V, Jagannathan NR (2009) Longitudinal study of the assessment by MRI and diffusion-weighted imaging of tumor response in patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy. NMR Biomed 22:104–113
Heijmen L, Verstappen MC, Ter Voert EE, Punt CJ, Oyen WJ, de Geus-Oei LF, Hermans JJ, Heerschap A, van Laarhoven HW (2012) Tumour response prediction by diffusion-weighted MR imaging: ready for clinical use? Crit Rev Oncol Hematol 83:194–207
Clauser P, Marcon M, Maieron M, Zuiani C, Bazzocchi M, Baltzer PA (2015) Is there a systematic bias of apparent diffusion coefficient (ADC) measurements of the breast if measured on different workstations? An inter- and intra-reader agreement study. Eur Radiol. doi:10.1007/s00330-015-4051-2
Giannotti E, Waugh S, Priba L, Davis Z, Crowe E, Vinnicombe S (2015) Assessment and quantification of sources of variability in breast apparent diffusion coefficient (ADC) measurements at diffusion weighted imaging. Eur J Radiol 84:1729–1736
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
Kim, J.Y., Suh, H.B., Kang, H.J. et al. Apparent diffusion coefficient of breast cancer and normal fibroglandular tissue in diffusion-weighted imaging: the effects of menstrual cycle and menopausal status. Breast Cancer Res Treat 157, 31–40 (2016). https://doi.org/10.1007/s10549-016-3793-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10549-016-3793-0