2D/3D image fusion of x-ray mammograms with speed of sound images: evaluation and visualization

Breast cancer is the most common cancer among women. The established screening method to detect breast cancer is X-ray mammography. However, X-ray frequently provides poor contrast of tumors located within glandular tissue. In this case, additional modalities like MRI are used for diagnosis in clinical routine. A new imaging approach is Ultrasound Computer Tomography, generating three-dimensional speed of sound images. High speed of sound values are expected to be an indicator of cancerous structures. Therefore, the combination of speed of sound images and X-ray mammograms may benefit early breast cancer diagnosis. In previous work, we proposed a method based on Finite Elements to automatically register speed of sound images with the according mammograms. The FEM simulation overcomes the challenge that X-ray mammograms show two-dimensional projections of a deformed breast whereas speed of sound images render a three-dimensional undeformed breast in prone position. In this work, 15 datasets from a clinical study were used for further evaluation of the registration quality. The quality of the registration was measured by the displacement of the center of a lesion marked in both modalities. We found a mean displacement of 7.1 mm. For visualization, an overlay technique was developed, which displays speed of sound information directly on the mammogram. Hence, the methodology provides a good basis for multimodal diagnosis using mammograms and speed of sound images. It proposes a guidance tool for radiologists who may benefit from the combined information.

[1]  Nicole V. Ruiter,et al.  Registration of x-ray mammograms and three-dimensional speed of sound images of the female breast , 2010, Medical Imaging.

[2]  David A. Boas,et al.  Tetrahedral mesh generation from volumetric binary and grayscale images , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[3]  James F. Greenleaf,et al.  CLINICAL IMAGING WITH TRANSMISSIVE ULTRASONIC COMPUTERIZED TOMOGRAPHY , 1981 .

[4]  R. Sivaramakrishna,et al.  Detection of breast cancer at a smaller size can reduce the likelihood of metastatic spread: a quantitative analysis. , 1997, Academic radiology.

[5]  W. Kaiser,et al.  Robotic system for biopsy and therapy of breast lesions in a high-field whole-body magnetic resonance tomography unit. , 2000, Investigative radiology.

[6]  U. Bick Mammographie-Screening in Deutschland : Wie, wann und warum? , 2006 .

[7]  Cuiping Li,et al.  In-vivo imaging results with ultrasound tomography: report on an ongoing study at the Karmanos Cancer Institute , 2010, Medical Imaging.

[8]  Wendy B DeMartini,et al.  A Review of Current Evidence-Based Clinical Applications for Breast Magnetic Resonance Imaging , 2008, Topics in magnetic resonance imaging : TMRI.

[9]  H. Gemmeke,et al.  3D ultrasound computer tomography for medical imaging , 2007 .

[10]  Patrick M. Knupp,et al.  Fundamentals of Grid Generation , 2020 .

[11]  W. Kaiser,et al.  Model-based registration of X-ray mammograms and MR images of the female breast , 2006, IEEE Transactions on Nuclear Science.

[12]  S. Diekmann,et al.  Mammographiescreening in Deutschland , 2007, Der Radiologe.

[13]  N. Duric,et al.  Detection of breast cancer with ultrasound tomography: first results with the Computed Ultrasound Risk Evaluation (CURE) prototype. , 2007, Medical physics.