Abstract
Purpose
Breast cancer is the most common cancer among women. The established screening method to detect breast cancer is X-ray mammography. Additionally, MRI is used for diagnosis in clinical routine. Due to complementary diagnostic information, both modalities are often read in combination. Yet, the correlation is challenging due to different dimensionality of images and different patient positioning. In this paper, we describe a method to fuse X-ray mammograms with DCE-MRI. The present study was conducted to evaluate the feasibility of the approach.
Methods
For the combination of information from both modalities, the images have to be registered using a compression simulation based on a patient-specific biomechanical model. The registered images can be compared directly. The contrast enhancement in the DCE-MRI volume is evaluated using parametric enhancement maps. A projection image of the contrast enhancement is created. The image fusion combines it with X-ray mammograms for intuitive multimodal diagnosis.
Results
The image fusion was evaluated using 11 clinical datasets. For 10 of 11 datasets, a good accuracy of the image registration was achieved. The overlap of contrast-enhanced regions with marked lesions in the mammogram is 61%. Lesions are clearly differentiable from surrounding tissue by the DCE-MRI projection in 10 of 11 cases.
Conclusion
The described preliminary results are promising, thus we expect the visualization of quantitative information from dynamic MRI together with mammograms to be beneficial for multimodal diagnosis. Because of the use of clinical standard modalities, no additional image acquisition is needed.
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References
Fischer T, Bick U, Thomas A (2007) Mammographie-screening in Deutschland. Vis J 15: 62–67
American Cancer Society: (2009) Breast cancer facts and figures 2009–2010. American Cancer Society, Inc, Atlanta
Sivaramakrishna R, Gordon R (1997) Detection of breast cancer at a smaller size can reduce the likelihood of metastatic spread: a quantitative analysis. Acad Radiol 4(1): 8–12
Schulz-Wendtland R, Fuchsjager M, Wacker T, Hermann KP (2009) Digital mammography: an update. Eur J Radiol 72: 258–265
Pisano ED, Hendrick E, Yaffe MJ, Baum JK, Suddhasatta A, Cormack JB, Hanna LA, Conant EF, Fajardo LL, Bassett LW, D’Orsi CJ, Jong RA, Rebner M, Tosteson ANA, Gatsonis CA (2008) Diagnostic accuracy of digital versus film mammography: exploratory analysis of selected population subgroups in DMIST. Radiol 246(2): 376–383
DeMartini W, Lehmann C (2008) A review of current evidence-based clinical applications for breast magnetic resonance imaging. Top Magn Reson Imaging 19: 143–150
Kaiser WA, Zeitler E (1989) MR-imaging of the breast: fast imaging sequences with and without Gd-DTPA. Radiol 170: 681–686
Baltzer PA, Dietzel M, Vag T, Beger S, Freiberg C, Herzog AB, Gajda M, Camara O, Kaiser WA (2009) Can color-coded parametric maps improve dynamic enhancement pattern analysis in MR mammography? RoFo: Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin (Epub ahead of print)
Houssami N, Ciatto S, Macaskill P, Lord SJ, Warren RM, Dixon JM, Irwig L (2008) 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 26(19): 3248–3258
Warner E, Messersmith H, Causer P, Eisen A, Shumak R, Plewes D (2008) Systematic review: using magnetic resonance imaging to screen women at high risk for breast cancer. Ann Intern Med 148(9): 671–679
Kaiser WA, Fischer H, Vagner J, Selig M (2000) Robotic system for biopsy and therapy of breast lesions in a high-field whole-body magnetic resonance tomography unit. Invest Radiol 35(8): 513–519
Ruiter NV, Stotzka R, Müller TO, Gemmeke H, Reichenbach JR, Kaiser WA (2006) Model-based registration of X-ray mammograms and MR images of the female breast. IEEE Trans on Nucl Sci 53: 204–211
Baum KG, Helguera M, Krol A (2008) Fusion viewer: a new tool for fusion and visualization of multimodal medical data sets. J Digit Imaging 21(Suppl 1): 59–68
Behrenbruch CP, Marias K, Armitage PA, Yam M, Moore N, English RE, Clarke J, Brady M (2003) Fusion of contrast-enhanced breast MR and mammographic imaging data. Med Image Anal 7: 311–340
Behrenbruch C, Marias K, Armitage PA, Yam M, Moore N, English RE, Clarke PJ, Leong FJ, Brady JM (2004) Fusion of contrast-enhanced breast MR and mammographic imaging data. The Br J Radiol 77: 201–208
Marti R, Rubin C, Denton E, Zwiggelaar R (2002) Mammographic X-Ray and MR Correspondence. In: Proceedings of International Workshop on Digit Mammogr 2002, pp 527–529
Marti R, Zwiggelaar R, Rubin C, Denton E (2004) Two-dimensional-three-dimensional correspondence in mammography. Cybern and Syst: An Int J 35(1): 85–105
Mertzanidou T, Hipwell JH, Tanner C, Hawkes DJ (2010) An intensity-based approach to x-ray mammography - MRI registration. Med Imaging 2010: Image Processing, SPIE 7623:76232Z
Rajagopal V, Chung JH, Highnam RP, Warren R, Nielsen PM, Nash MP (2010) Mapping microcalcifications between 2D mammograms and 3D MRI using a biomechanical model of the breast. In: Comp Biomech for Med, pp 17–28. Springer, New York
Chan T, Vese L (2001) Active contours without edges. IEEE Trans Image Process 10: 266–277
Zienkiewicz OC, Taylor RL (2000) The Finite Element Method, vol 1, 5th edn. Butterworth Heinemann, Oxford
Zienkiewidz OC, Taylor RL (2000) The Finite Element Method, vol 2, 5th edn. Butterworth Heinemann, Oxford
Dassault Systèmes Simulia Corp. (SIMULIA): Abaqus FEA (2010), http://www.simulia.com/products/abaqus_fea.html. Accessed 17 March 2011
Dassault Systèmes (2009) Abaqus Theory Manual
Fang Q, Boas D (2009) Tetrahedral mesh generation from volumetric binary and gray-scale images. In: Proceedings of IEEE International Symp Biomed Imaging 2009, pp 1142–1145
Wellman PS, Howe RD, Dalton E, Kern KA (1999) Breast tissue stiffness in compression is correlated to histological diagnosis. Technical Report, Harvard BioRobotics Laboratory
Ruiter N (2003) Registration of X-ray mammograms and MR-volumes. Dissertation, University of Mannheim, Germany
Ikeda DM, Hylton NM, Kuhl CK et al (2003) MRI Breast Imaging Reporting and Data System Atlas, 1st edn. American College of Radiology, Reston
Baltzer PA, Freiberg C, Berger S et al (2009) Clinical MR-mammography: are computer-assisted methods superior to visual or manual measurements for curve type analysis? A systematic approach. Acad Radiol 16(9): 1070–1076
Degani H, Gusis V, Weinstein D, Fields S, Strano S (1997) Mapping pathophysiological features of breast tumors by MRI at high spatial resolution. Nat Med 2: 780–782
Hauth EA, Stockamp C, Maderwald S, Mühler A, Kimmig R, Jaeger H, Barkhausen J, Forsting M (2006) Evaluation of the three-time-point method for diagnosis of breast lesions in contrast-enhanced MR mammography. Clin Imaging 30(3): 160–165
Kaiser WA (2007) Signs in MR-Mammography. Springer, Berlin
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Hopp, T., Baltzer, P., Dietzel, M. et al. 2D/3D image fusion of X-ray mammograms with breast MRI: visualizing dynamic contrast enhancement in mammograms. Int J CARS 7, 339–348 (2012). https://doi.org/10.1007/s11548-011-0623-z
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DOI: https://doi.org/10.1007/s11548-011-0623-z