Towards an in-plane methodology to track breast lesions using mammograms and patient-specific finite-element simulations
Resumen: 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 patient''s 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.
Idioma: Inglés
DOI: 10.1088/1361-6560/aa8d62
Año: 2017
Publicado en: Physics in Medicine and Biology 62, 22 (2017), 8720-8738
ISSN: 0031-9155

Factor impacto JCR: 2.665 (2017)
Categ. JCR: RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING rank: 42 / 127 = 0.331 (2017) - Q2 - T2
Categ. JCR: ENGINEERING, BIOMEDICAL rank: 27 / 78 = 0.346 (2017) - Q2 - T2

Factor impacto SCIMAGO: 1.263 - Radiology, Nuclear Medicine and Imaging (Q1) - Radiological and Ultrasound Technology (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2016-79302-R
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)

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