A step‐by‐step review on patient‐specific biomechanical finite element models for breast MRI to x‐ray mammography registration

Abstract

Breast magnetic resonance imaging (MRI) and x-ray mammography are two image modalities widely used for the early detection and diagnosis of breast diseases in women. The combination of these modalities leads to a more accurate diagnosis and treatment of breast diseases. The aim of this paper is to review the registration between breast MRI and x-ray mammographic images using patient-specific finite element-based biomechanical models. Specifically, a biomechanical model is obtained from the patient's MRI volume and is subsequently used to mimic the mammographic acquisition. Due to the different patient positioning and movement restrictions applied in each image modality, the finite element analysis provides a realistic physics-based approach to perform the breast deformation. In contrast with other reviews, we do not only expose the overall process of compression and registration but we also include main ideas, describe challenges, and provide an overview of the used software in each step of the process. Extracting an accurate description from the MR images and preserving the stability during the finite element analysis require an accurate knowledge about the algorithms used, as well as the software and underlying physics. The wide perspective offered makes the paper suitable not only for expert researchers but also for graduate students and clinicians. We also include several medical applications in the paper, with the aim to fill the gap between the engineering and clinical performance.

Ultrasound waves in tumors via needle irradiation for precise medicine

“…In particular, the elastic modulus of breast tumor masses with volumes ranging from approximately 500 to 1250 mm 3 resulted in an increase from approximately 10 kPa to 16 kPa, compared in Fig. 1 with a normal tissue modulus of 2 kPa, coherently with the interval of 0.25–4 kPa reported in the literature 58 , 59 for breast tissue samples under vanishing precompression. An almost incompressible Poisson ratio is additionally assumed 41 , 60 , implying that the density of the tissue does not significantly change during volumetric growth.…”

A review of bioengineering techniques applied to breast tissue: Mechanical properties, tissue engineering and finite element analysis

“…Each breast is organized in lobes of glands, called lobules, and contains the excretory ducts, which drain into the lactiferous sinus, radiating from the central nipple-areolar complex. Those lobes are embedded in fibrous and adipose tissues ( Ramião et al, 2016 ), along with the nerves and blood and lymphatic vessels ( Babarenda Gamage et al, 2017 ; García et al, 2018 ). To keep the shape and contour of the breast and hold it in place, there are the fibrous suspensory ligaments, named Cooper’s ligaments ( Ramião et al, 2016 ; Babarenda Gamage et al, 2017 ).…”

“…Regarding breast tissues, besides morphology and structure, also the mechanical properties change along a woman’s life, due to factors such as age, menstrual cycle, pregnancy, menopause, lactation, etc. ( Babarenda Gamage et al, 2017 ; García et al, 2018 ; Ng and Lin, 2019 ). An example is the stretching and weakening of the Cooper’s ligaments that are observed with aging ( Ramião et al, 2016 ).…”

Using Breast Tissue Information and Subject-Specific Finite-Element Models to Optimize Breast Compression Parameters for Digital Mammography

“…The Mooney-Rivlin model is a kind of hyperelastic model. Although the hyperelastic model has been proven to have more accurate results in breast deformation than the linear model [7], the reliability of the Mooney-Rivlin model in breast compression simulation has not been clinically validated. In this study, the Mooney-Rivlin model was used to perform CBT simulation for different compression forces.…”

“…To bridge the gap between breast MRI and mammography, simulation of breast compression using the finite element method (FEM) has been performed for breast tumor excision [6] and breast imaging [7]. Shih et al [8] used MR images and the hyperelastic model to simulate four cases of breast compression in craniocaudal (CC) and mediolateral oblique (MLO) views.…”