Purpose: Patient-specific biomedical modeling of the breast is of interest for medical applications such as image registration, image guided procedures and the alignment for biopsy or surgery purposes. The computation of elastic properties is essential to simulate deformations in a realistic way. This study presents an innovative analytical method to compute the elastic modulus and evaluate the elasticity of a breast using magnetic resonance (MRI) images of breast phantoms.
Methods: An analytical method for elasticity computation was developed and subsequently validated on a series of geometric shapes, and on four physical breast phantoms that are supported by a planar frame. This method can compute the elasticity of a shape directly from a set of MRI scans. For comparison, elasticity values were also computed numerically using two different simulation software packages.
Results: Application of the different methods on the geometric shapes shows that the analytically derived elongation differs from simulated elongation by less than 9% for cylindrical shapes, and up to 18% for other shapes that are also substantially vertically supported by a planar base. For the four physical breast phantoms, the analytically derived elasticity differs from numeric elasticity by 18% on average, which is in accordance with the difference in elongation estimation for the geometric shapes. The analytic method has shown to be multiple orders of magnitude faster than the numerical methods.
Conclusion: It can be concluded that the analytical elasticity computation method has good potential to supplement or replace numerical elasticity simulations in gravity-induced deformations, for shapes that are substantially supported by a planar base perpendicular to the gravitational field. The error is manageable, while the calculation procedure takes less than one second as opposed to multiple minutes with numerical methods. The results will be used in the MRI and Ultrasound Robotic Assisted Biopsy (MURAB) project.
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http://dx.doi.org/10.1007/s11548-018-1803-x | DOI Listing |
Cancer Manag Res
January 2025
School of Physics, Universiti Sains Malaysia, Penang, 11800 Gelugor, Malaysia.
Introduction: Breast cancer is a significant worldwide health issue, particularly in Jordan, where early detection via mammography is essential for effective disease management. Despite the little radiation risk associated with mammography, it is crucial to monitor radiation exposure to guarantee patient safety. This study intends to assess skin entrance exposure and compute the Mean Glandular Dose (MGD) in mammography units to determine adherence to established criteria and pinpoint areas for enhancement.
View Article and Find Full Text PDFPediatr Radiol
January 2025
Boston Children's Hospital, 300 Longwood Avenue, Boston, MA, 02115, USA.
Background: Radiographic skeletal survey plays an important role in the diagnosis of infant abuse. Some practitioners have expressed concerns about the radiation exposure from this examination.
Objective: To utilize state-of-the-art hybrid computational phantoms to more accurately estimate radiation doses of skeletal surveys performed for suspected infant abuse.
MethodsX
June 2025
Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Rabigh 21911, Saudi Arabia.
Breast cancer is the most commonly diagnosed neoplasm and one of the most widespread cancers among women. The research advanced the Mf-EIT hardware through analogue discovery, component assessment, hardware integration, software creation, and data reconstruction utilizing Gauss-Newton and GREIT approaches. The breast cancer phantom consisted of a gelatin and sodium chloride solution.
View Article and Find Full Text PDFJ Med Imaging (Bellingham)
January 2025
University of Houston, Department of Biomedical Engineering, Houston, Texas, United States.
Purpose: Digital phantoms are one of the key components of virtual imaging trials (VITs) that aim to assess and optimize new medical imaging systems and algorithms. However, these phantoms vary in their voxel resolution, appearance, and structural details. We investigate whether and how variations between digital phantoms influence system optimization with digital breast tomosynthesis (DBT) as a chosen modality.
View Article and Find Full Text PDFAsia Ocean J Nucl Med Biol
January 2025
Department of Radiology, Faculty of Medicine, Shimane University, Izumo, Japan.
Objectives: We investigated image quality and standardized uptake values (SUVs) for different lesion sizes using clinical data generated by F-FDG-prone breast silicon photomultiplier (SiPM)-based positron emission tomography/computed tomography (PET/CT).
Methods: We evaluated the effect of point-spread function (PSF) modeling and Gaussian filtering (Gau) and determined the optimal reconstruction conditions. We compared the signal-to-noise ratio (SNR), contrast, %coefficient of variation (%CV), SUV, and Likert scale score between ordered-subset expectation maximization (OSEM) time-of-flight (TOF) and OSEM+TOF+PSF in phantom and clinical studies.
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