Methods for modeling and predicting mechanical deformations of the breast under external perturbations

Azar, Fred S.; Metaxas, Dimitris N.; Schnall, Mitchell D.

doi:10.1016/s1361-8415(01)00053-6

Cited by 132 publications

(54 citation statements)

References 32 publications

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“…The average numbers are in rough agreement with the previously published ex vivo work on biopsy samples, despite the many complicating factors (geometry, boundary conditions, tissue heterogeneity) in our measurement. We note that Azar et al (11) suggested that fibroglandular and fatty tissues in the breast become compartmentalized and therefore differ in mechanical properties from isolated excised samples; additionally, work by Lorenzen et al (88) with magnetic resonance elastography suggests large (~±30%) changes in fibroglandular elasticity occur during the course of a woman’s menstrual cycle. Despite limitations, we are encouraged by the initial mechanical response data.…”

Section: Discussionmentioning

confidence: 67%

Blood Flow Reduction in Breast Tissue due to Mammographic Compression

et al. 2014

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Rationale and objectives This study measures hemodynamic properties such as blood flow and hemoglobin concentration and oxygenation in the healthy human breast under a wide range of compressive loads. Because many breast-imaging technologies derive contrast from the deformed breast, these load-dependent vascular responses affect contrast agent–enhanced and hemoglobin-based breast imaging. Methods Diffuse optical and diffuse correlation spectroscopies were used to measure the concentrations of oxygenated and deoxygenated hemoglobin, lipid, water, and microvascular blood flow during axial breast compression in the parallel-plate transmission geometry. Results Significant reductions (P < .01) in total hemoglobin concentration (~30%), blood oxygenation (~20%), and blood flow (~87%) were observed under applied pressures (forces) of up to 30 kPa (120 N) in 15 subjects. Lipid and water concentrations changed <10%. Conclusions Imaging protocols based on injected contrast agents should account for variation in tissue blood flow due to mammographic compression. Similarly, imaging techniques that depend on endogenous blood contrasts will be affected by breast compression during imaging.

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Section: Discussionmentioning

confidence: 67%

Blood Flow Reduction in Breast Tissue due to Mammographic Compression

et al. 2014

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“…This paper shows that blood volume variations convey information about the viscoelastic properties of breast tissue, and that this information can be used to increase the accuracy of metabolic modeling. Future work will include developing a Windkessel model [44] to more accurately describe the response of different vascular compartments to pressure variations and its linkage to the observed optical properties, using the foundation offered by previous work on non-linear elastic [45] or poroelastic [46] representations of biological tissue. Clinically, tomographic optical imaging may permit within-patient region of interest comparisons of these new biomarkers to obtain diagnostic information, without the need for absolute quantification.…”

Section: Discussionmentioning

confidence: 99%

Dynamic functional and mechanical response of breast tissue to compression

Carp¹,

Selb²,

Fang³

et al. 2008

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Physiological tissue dynamics following breast compression offer new contrast mechanisms for evaluating breast health and disease with near infrared spectroscopy. We monitored the total hemoglobin concentration and hemoglobin oxygen saturation in 28 healthy female volunteers subject to repeated fractional mammographic compression. The compression induces a reduction in blood flow, in turn causing a reduction in hemoglobin oxygen saturation. At the same time, a two phase tissue viscoelastic relaxation results in a reduction and redistribution of pressure within the tissue and correspondingly modulates the tissue total hemoglobin concentration and oxygen saturation. We observed a strong correlation between the relaxing pressure and changes in the total hemoglobin concentration bearing evidence of the involvement of different vascular compartments. Consequently, we have developed a model that enables us to disentangle these effects and obtain robust estimates of the tissue oxygen consumption and blood flow. We obtain estimates of 1.9±1.3 µmol/100mL/min for OC and 2.8±1.7 mL/100mL/min for blood flow, consistent with other published values.

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“…First of all, in the field of bio-mechanics it is a common approach to apply FEM analysis with CT or MR images [18], [19]. In the most cases they use scanned images for creating mesh models for applying 3D FEM analysis and the image segmentation was done with some conventional methods.…”

Section: Introductionmentioning

confidence: 99%

CT Image Segmentation Using FEM with Optimized Boundary Condition

et al. 2012

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The authors propose a CT image segmentation method using structural analysis that is useful for objects with structural dynamic characteristics. Motivation of our research is from the area of genetic activity. In order to reveal the roles of genes, it is necessary to create mutant mice and measure differences among them by scanning their skeletons with an X-ray CT scanner. The CT image needs to be manually segmented into pieces of the bones. It is a very time consuming to manually segment many mutant mouse models in order to reveal the roles of genes. It is desirable to make this segmentation procedure automatic. Although numerous papers in the past have proposed segmentation techniques, no general segmentation method for skeletons of living creatures has been established. Against this background, the authors propose a segmentation method based on the concept of destruction analogy. To realize this concept, structural analysis is performed using the finite element method (FEM), as structurally weak areas can be expected to break under conditions of stress. The contribution of the method is its novelty, as no studies have so far used structural analysis for image segmentation. The method's implementation involves three steps. First, finite elements are created directly from the pixels of a CT image, and then candidates are also selected in areas where segmentation is thought to be appropriate. The second step involves destruction analogy to find a single candidate with high strain chosen as the segmentation target. The boundary conditions for FEM are also set automatically. Then, destruction analogy is implemented by replacing pixels with high strain as background ones, and this process is iterated until object is decomposed into two parts. Here, CT image segmentation is demonstrated using various types of CT imagery.

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Methods for modeling and predicting mechanical deformations of the breast under external perturbations

Cited by 132 publications

References 32 publications

Blood Flow Reduction in Breast Tissue due to Mammographic Compression

Blood Flow Reduction in Breast Tissue due to Mammographic Compression

Dynamic functional and mechanical response of breast tissue to compression

CT Image Segmentation Using FEM with Optimized Boundary Condition

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