Andrés Lapuebla-Ferri

A patient-specific FE-based methodology to simulate prosthesis insertion during an augmentation mammoplasty.

Breast augmentation surgery is a widespread practice for aesthetic purposes. Current techniques, however, are not able to reliably predict the desired final aspect of the breast after the intervention, whose success relies almost completely on the surgeons skill. In this way, patient-specific methodologies capable of predicting the outcomes of such interventions are of particular interest. In this paper, a finite element biomechanical model of the breast of a female patient before an augmentation mammoplasty was generated using computer tomography images. Prosthesis insertion during surgery was simulated using the theory of finite elasticity. Hyperelastic constitutive models were considered for breast tissues and silicone implants. The deformed geometry obtained from finite element analysis was compared qualitatively and quantitatively with the real breast shape of the patient lying in supine position, with root-mean-squared errors less than 3mm. The results indicate that the presented methodology is able to reasonably predict the aspect of the breast in an intermediate step of augmentation mammoplasty, and reveal the potential capabilities of finite element simulations for visualization and prediction purposes. However, further work is required before this methodology can be helpful in aesthetic surgery planning.

Towards an in-plane methodology to track breast lesions using mammograms and patient-specific finite-element simulations

In breast cancer screening or diagnosis, it is usual to combine different images in order to locate a lesion as accurately as possible. These images are generated by using a single or several imaging techniques. As X-ray based mammography is used widespread, a breast lesion is located in the same plane of the image (mammogram), but tracking of a breast lesion across mammograms corresponding to different views is a daring task for medical physicians. According to this, simulation tools and methodologies that use patient-specific numerical models can facilitate the task of fusing information from different images. Additionally, these tools need to be as straightforward as possible to facilitate its translation to the clinical area. This paper presents a patient-specific, finite element (FE) based and semi-automated simulation methodology to track breast lesions across mammograms. A realistic, three-dimensional, computer model of a patients breast was generated from magnetic resonance imaging (MRI) to simulate mammographic compressions in cranio-caudal (CC, head-to-toe) and medio-lateral oblique (MLO, shoulder-to-opposite hip) directions. For each compression being simulated, a virtual mammogram was obtained and posteriorly superimposed to the corresponding real mammogram, by sharing the nipple as a common feature. Two-dimensional rigid-body transformations were applied, and the error distance measured between the centroids of the tumor previously located on each image was 3.84 mm and 2.41 mm for CC and MLO compression, respectively. Considering that the scope of this work is to conceive a methodology translatable to the clinical practice, the results indicate that it could be helpful to support tracking of breast lesions. .In breast cancer screening or diagnosis, it is usual to combine different images in order to locate a lesion as accurately as possible. These images are generated using a single or several imaging techniques. As x-ray-based mammography is widely used, a breast lesion is located in the same plane of the image (mammogram), but tracking it across mammograms corresponding to different views is a challenging task for medical physicians. Accordingly, simulation tools and methodologies that use patient-specific numerical models can facilitate the task of fusing information from different images. Additionally, these tools need to be as straightforward as possible to facilitate their translation to the clinical area. This paper presents a patient-specific, finite-element-based and semi-automated simulation methodology to track breast lesions across mammograms. A realistic three-dimensional computer model of a patients breast was generated from magnetic resonance imaging to simulate mammographic compressions in cranio-caudal (CC, head-to-toe) and medio-lateral oblique (MLO, shoulder-to-opposite hip) directions. For each compression being simulated, a virtual mammogram was obtained and posteriorly superimposed to the corresponding real mammogram, by sharing the nipple as a common feature. Two-dimensional rigid-body transformations were applied, and the error distance measured between the centroids of the tumors previously located on each image was 3.84 mm and 2.41 mm for CC and MLO compression, respectively. Considering that the scope of this work is to conceive a methodology translatable to clinical practice, the results indicate that it could be helpful in supporting the tracking of breast lesions.

Numerical Modelling of Human Breast Deformation

Most surgical procedures in breast plastic surgery are either reconstructive procedures following oncologic interventions (tumorectomy, quadrantectomy, mastectomy…) or aesthetic ones, including both augmentation and reduction. With current techniques, the results of such procedures cannot be fully guaranteed. Usually, surgical planning is based on a photographic and anthropometric study of only the breast. Among others, one of the difficulties that plastic surgeons have is the noticeable change of the breast shape with the position of the patient. Thus, it is more and more necessary to plan a presurgical methodology to help the plastic surgeon and guarantee the patient a successful result of the intervention. Numerical methods such as finite element simulations can help in predicting the deformations of a specific tissue if a suitable definition of the tissue is introduced. These models take into account the constitutive behaviour of the involved materials, the boundary conditions and the externally applied loads. Thus, numerical modelling can be used as a powerful tool to provide accurate and useful information to the surgeon planning such surgical procedures.