RESUMO
Mammographic percent density, the proportion of fibroglandular tissue in the breast, is a strong risk factor for breast cancer, but its determinants in young women are unknown. We examined associations of magnetic resonance imaging (MRI) breast-tissue composition at age 21 years with prospectively collected measurements of body size and composition from birth to early adulthood and markers of puberty (all standardized) in a sample of 500 nulliparous women from a prebirth cohort of children born in Avon, United Kingdom, in 1991-1992 and followed up to 2011-2014. Linear models were fitted to estimate relative change in MRI percent water, which is equivalent to mammographic percent density, associated with a 1-standard-deviation increase in the exposure of interest. In mutually adjusted analyses, MRI percent water was positively associated with birth weight (relative change (RC) = 1.03, 95% confidence interval (CI): 1.00, 1.06) and pubertal height growth (RC = 1.07, 95% CI: 1.02, 1.13) but inversely associated with pubertal weight growth (RC = 0.86, 95% CI: 0.84, 0.89) and changes in dual-energy x-ray absorptiometry percent body fat mass (e.g., for change between ages 11 years and 13.5 years, RC = 0.96, 95% CI: 0.93, 0.99). Ages at thelarche and menarche were positively associated with MRI percent water, but these associations did not persist upon adjustment for height and weight growth. These findings support the hypothesis that growth trajectories influence breast-tissue composition in young women, whereas puberty plays no independent role.
Assuntos
Composição Corporal , Mama/crescimento & desenvolvimento , Maturidade Sexual , Adolescente , Mama/diagnóstico por imagem , Criança , Pré-Escolar , Humanos , Lactente , Recém-Nascido , Imageamento por Ressonância Magnética , Estudos Prospectivos , Puberdade , Adulto JovemRESUMO
The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologia , Tecido Conjuntivo/diagnóstico por imagem , Tecido Conjuntivo/patologia , Imagem de Tensor de Difusão/métodos , Imageamento por Ressonância Magnética/métodos , Modelos Biológicos , Simulação por Computador , Feminino , Humanos , Interpretação de Imagem Assistida por Computador/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Células Tumorais CultivadasRESUMO
BACKGROUND: Breast density, the amount of fibroglandular tissue in the adult breast for a women's age and body mass index, is a strong biomarker of susceptibility to breast cancer, which may, like breast cancer risk itself, be influenced by events early in life. In the present study, we investigated the association between pre-natal exposures and breast tissue composition. METHODS: A sample of 500 young, nulliparous women (aged approximately 21 years) from a U.K. pre-birth cohort underwent a magnetic resonance imaging examination of their breasts to estimate percent water, a measure of the relative amount of fibroglandular tissue equivalent to mammographic percent density. Information on pre-natal exposures was collected throughout the mothers' pregnancy and shortly after delivery. Regression models were used to investigate associations between percent water and pre-natal exposures. Mediation analysis, and a systematic review and meta-analysis of the published literature, were also conducted. RESULTS: Adjusted percent water in young women was positively associated with maternal height (p for linear trend [p t] = 0.005), maternal mammographic density in middle age (p t = 0.018) and the participant's birth size (p t < 0.001 for birthweight). A 1-SD increment in weight (473 g), length (2.3 cm), head circumference (1.2 cm) and Ponderal Index (4.1 g/cm3) at birth were associated with 3 % (95 % CI 2-5 %), 2 % (95 % CI 0-3 %), 3 % (95 % CI 1-4 %) and 1 % (95 % CI 0-3 %), respectively, increases in mean adjusted percent water. The effect of maternal height on the participants' percent water was partly mediated through birth size, but there was little evidence that the effect of birthweight was primarily mediated via adult body size. The meta-analysis supported the study findings, with breast density being positively associated with birth size. CONCLUSIONS: These findings provide strong evidence of pre-natal influences on breast tissue composition. The positive association between birth size and relative amount of fibroglandular tissue indicates that breast density and breast cancer risk may share a common pre-natal origin.
Assuntos
Glândulas Mamárias Humanas/diagnóstico por imagem , Exposição Materna , Efeitos Tardios da Exposição Pré-Natal , Adulto , Densidade da Mama , Feminino , Seguimentos , Humanos , Imageamento por Ressonância Magnética , Glândulas Mamárias Humanas/patologia , Exposição Materna/efeitos adversos , Vigilância da População , Gravidez , Fatores de Risco , Reino Unido/epidemiologia , Adulto JovemRESUMO
BACKGROUND: Inter-women and intra-women comparisons of mammographic density (MD) are needed in research, clinical and screening applications; however, MD measurements are influenced by mammography modality (screen film/digital) and digital image format (raw/processed). We aimed to examine differences in MD assessed on these image types. METHODS: We obtained 1294 pairs of images saved in both raw and processed formats from Hologic and General Electric (GE) direct digital systems and a Fuji computed radiography (CR) system, and 128 screen-film and processed CR-digital pairs from consecutive screening rounds. Four readers performed Cumulus-based MD measurements (n = 3441), with each image pair read by the same reader. Multi-level models of square-root percent MD were fitted, with a random intercept for woman, to estimate processed-raw MD differences. RESULTS: Breast area did not differ in processed images compared with that in raw images, but the percent MD was higher, due to a larger dense area (median 28.5 and 25.4 cm2 respectively, mean âdense area difference 0.44 cm (95% CI: 0.36, 0.52)). This difference in âdense area was significant for direct digital systems (Hologic 0.50 cm (95% CI: 0.39, 0.61), GE 0.56 cm (95% CI: 0.42, 0.69)) but not for Fuji CR (0.06 cm (95% CI: -0.10, 0.23)). Additionally, within each system, reader-specific differences varied in magnitude and direction (p < 0.001). Conversion equations revealed differences converged to zero with increasing dense area. MD differences between screen-film and processed digital on the subsequent screening round were consistent with expected time-related MD declines. CONCLUSIONS: MD was slightly higher when measured on processed than on raw direct digital mammograms. Comparisons of MD on these image formats should ideally control for this non-constant and reader-specific difference.
Assuntos
Densidade da Mama , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/patologia , Processamento de Imagem Assistida por Computador , Mamografia/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Humanos , Pessoa de Meia-IdadeRESUMO
PURPOSE: To compare and evaluate intensity-based registration methods for computation of serial x-ray mammogram correspondence. METHODS: X-ray mammograms were simulated from MRIs of 20 women using finite element methods for modeling breast compressions and employing a MRI/x-ray appearance change model. The parameter configurations of three registration methods, affine, fluid, and free-form deformation (FFD), were optimized for registering x-ray mammograms on these simulated images. Five mammography film readers independently identified landmarks (tumor, nipple, and usually two other normal features) on pairs of diagnostic and corresponding prediagnostic digitized images from 52 breast cancer cases. Landmarks were independently reidentified by each reader. Target registration errors were calculated to compare the three registration methods using the reader landmarks as a gold standard. Data were analyzed using multilevel methods. RESULTS: Between-reader variability varied with landmark (p < 0.01) and screen (p = 0.03), with between-reader mean distance (mm) in point location on the diagnostic/prediagnostic images of 2.50 (95% CI 1.95, 3.15)/2.84 (2.24, 3.55) for nipples and 4.26 (3.43, 5.24)/4.76 (3.85, 5.84) for tumors. Registration accuracy was sensitive to the type of landmark and the amount of breast density. For dense breasts (> or = 40%), the affine and fluid methods outperformed FFD. For breasts with lower density, the affine registration surpassed both fluid and FFD. Mean accuracy (mm) of the affine registration varied between 3.16 (95% CI 2.56, 3.90) for nipple points in breasts with density 20%-39% and 5.73 (4.80, 6.84) for tumor points in breasts with density < 20%. CONCLUSIONS: Affine registration accuracy was comparable to that between independent film readers. More advanced two-dimensional nonrigid registration algorithms were incapable of increasing the accuracy of image alignment when compared to affine registration.
Assuntos
Neoplasias da Mama/diagnóstico por imagem , Processamento de Imagem Assistida por Computador/métodos , Mamografia/métodos , Radiologia/métodos , Adulto , Algoritmos , Automação , Feminino , Humanos , Imageamento por Ressonância Magnética , Pessoa de Meia-Idade , Modelos Teóricos , Variações Dependentes do ObservadorRESUMO
BACKGROUND: Endogenous hormones are associated with breast cancer risk, but little is known about their role on breast tissue composition, a strong risk predictor. This study aims to investigate the relationship between growth and sex hormone levels and breast tissue composition in young nulliparous women. METHODS: A cross-sectional study of 415 young (age â¼21.5 years) nulliparous women from an English prebirth cohort underwent a MRI examination of their breasts to estimate percent-water (a proxy for mammographic percent density) and provided a blood sample to measure plasma levels of growth factors (insulin-like growth factor-I, insulin-like growth factor-II, insulin growth factor-binding protein-3, growth hormone) and, if not on hormonal contraception (n = 117) sex hormones (dehydroepiandrosterone, androstenedione, testosterone, estrone, estadiol, sex hormone-binding globulin, prolactin). Testosterone (n = 330) and sex hormone-binding globulin (n = 318) were also measured at age 15.5 years. Regression models were used to estimate the relative difference (RD) in percent-water associated with one SD increment in hormone levels. RESULTS: Estradiol at age 21.5 and sex hormone-binding globulin at age 21.5 were positively associated with body mass index (BMI)-adjusted percent-water [RD (95% confidence interval (CI)): 3% (0%-7%) and 3% (1%-5%), respectively]. There was a positive nonlinear association between androstenedione at age 21.5 and percent-water. Insulin-like growth factor-I and growth hormone at age 21.5 were also positively associated with BMI-adjusted percent-water [RD (95% CI): 2% (0%-4%) and 4% (1%-7%), respectively]. CONCLUSIONS: The findings suggest that endogenous hormones affect breast tissue composition in young nulliparous women. IMPACT: The well-established associations of childhood growth and development with breast cancer risk may be partly mediated by the role of endogenous hormones on breast tissue composition.
Assuntos
Mama/metabolismo , Hormônio do Crescimento/metabolismo , Globulina de Ligação a Hormônio Sexual/metabolismo , Adolescente , Adulto , Estudos Transversais , Feminino , Humanos , Paridade , Adulto JovemRESUMO
Establishing spatial correspondence between features visible in X-ray mammograms obtained at different times has great potential to aid assessment and quantitation of change in the breast indicative of malignancy. The literature contains numerous nonrigid registration algorithms developed for this purpose, but existing approaches are flawed by the assumption of inappropriate 2-D transformation models and quantitative estimation of registration accuracy is limited. In this paper, we describe a novel validation method which simulates plausible mammographic compressions of the breast using a magnetic resonance imaging (MRI) derived finite element model. By projecting the resulting known 3-D displacements into 2-D and generating pseudo-mammograms from these same compressed magnetic resonance (MR) volumes, we can generate convincing images with known 2-D displacements with which to validate a registration algorithm. We illustrate this approach by computing the accuracy for two conventional nonrigid 2-D registration algorithms applied to mammographic test images generated from three patient MR datasets. We show that the accuracy of these algorithms is close to the best achievable using a 2-D one-to-one correspondence model but that new algorithms incorporating more representative transformation models are required to achieve sufficiently accurate registrations for this application.
Assuntos
Algoritmos , Neoplasias da Mama/diagnóstico por imagem , Mamografia/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Software , Técnica de Subtração , Simulação por Computador , Humanos , Modelos Biológicos , Intensificação de Imagem Radiográfica/métodos , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Validação de Programas de ComputadorRESUMO
A method to accurately measure the position and orientation of an acetabular cup implant from postoperative X-rays has been designed and validated. The method uses 2-D-3-D registration to align both the prosthesis and the preoperative computed tomography (CT) volume to the X-ray image. This allows the position of the implant to be calculated with respect to a CT-based surgical plan. Experiments have been carried out using ten sets of patient data. A conventional plain-film measurement technique was also investigated. A gold standard implant position and orientation was calculated using postoperative CT. Results show our method to be significantly more accurate than the plain-film method for calculating cup anteversion. Cup orientation and position could be measured to within a mean absolute error of 1.4 mm or degrees.
Assuntos
Acetábulo/diagnóstico por imagem , Acetábulo/cirurgia , Artroplastia de Quadril/métodos , Imageamento Tridimensional/métodos , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Técnica de Subtração , Tomografia Computadorizada por Raios X/métodos , Artroplastia de Quadril/instrumentação , Prótese de Quadril , Humanos , Cuidados Pós-Operatórios/métodos , Intensificação de Imagem Radiográfica/métodosRESUMO
OBJECTIVE: The tumor microenvironment plays a crucial role in regulating tumor progression by a number of different mechanisms, in particular, the remodeling of collagen fibers in tumor-associated stroma, which has been reported to be related to patient survival. The underlying motivation of this work is that remodeling of collagen fibers gives rise to observable patterns in hematoxylin and eosin (H&E) stained slides from clinical cases of invasive breast carcinoma that the pathologist can label as mature or immature stroma. The aim of this paper is to categorise and automatically classify stromal regions according to their maturity and show that this classification agrees with that of skilled observers, hence providing a repeatable and quantitative measure for prognostic studies. METHODS: We use multiscale basic image features and local binary patterns, in combination with a random decision trees classifier for classification of breast cancer stroma regions-of-interest (ROI). RESULTS: We present results from a cohort of 55 patients with analysis of 169 ROI. Our multiscale approach achieved a classification accuracy of 84%. CONCLUSION: This work demonstrates the ability of texture-based image analysis to differentiate breast cancer stroma maturity in clinically acquired H&E-stained slides at least as well as skilled observers.
Assuntos
Algoritmos , Neoplasias da Mama/patologia , Interpretação de Imagem Assistida por Computador/métodos , Microscopia/métodos , Reconhecimento Automatizado de Padrão/métodos , Células Estromais/patologia , Biópsia/métodos , Feminino , Humanos , Gradação de Tumores , Reprodutibilidade dos Testes , Sensibilidade e Especificidade , Células Tumorais CultivadasRESUMO
We present an in-silico model of avascular poroelastic tumour growth coupled with a multiscale biphasic description of the tumour-host environment. The model is specified to in-vitro data, facilitating biophysically realistic simulations of tumour spheroid growth into a dense collagen hydrogel. We use the model to first confirm that passive mechanical remodelling of collagen fibres at the tumour boundary is driven by solid stress, and not fluid pressure. The model is then used to demonstrate the influence of collagen microstructure on peritumoural permeability and interstitial fluid flow. Our model suggests that at the tumour periphery, remodelling causes the peritumoural stroma to become more permeable in the circumferential than radial direction, and the interstitial fluid velocity is found to be dependent on initial collagen alignment. Finally we show that solid stresses are negatively correlated with peritumoural permeability, and positively correlated with interstitial fluid velocity. These results point to a heterogeneous, microstructure-dependent force environment at the tumour-peritumoural stroma interface.
Assuntos
Proliferação de Células , Simulação por Computador , Modelos Biológicos , Neoplasias/patologia , Progressão da Doença , Humanos , Microambiente TumoralRESUMO
PURPOSE: To compare two methods of automatic breast segmentation with each other and with manual segmentation in a large subject cohort. To discuss the factors involved in selecting the most appropriate algorithm for automatic segmentation and, in particular, to investigate the appropriateness of overlap measures (e.g., Dice and Jaccard coefficients) as the primary determinant in algorithm selection. METHODS: Two methods of breast segmentation were applied to the task of calculating MRI breast density in 200 subjects drawn from the Avon Longitudinal Study of Parents and Children, a large cohort study with an MRI component. A semiautomated, bias-corrected, fuzzy C-means (BC-FCM) method was combined with morphological operations to segment the overall breast volume from in-phase Dixon images. The method makes use of novel, problem-specific insights. The resulting segmentation mask was then applied to the corresponding Dixon water and fat images, which were combined to give Dixon MRI density values. Contemporaneously acquired T1 - and T2 -weighted image datasets were analyzed using a novel and fully automated algorithm involving image filtering, landmark identification, and explicit location of the pectoral muscle boundary. Within the region found, fat-water discrimination was performed using an Expectation Maximization-Markov Random Field technique, yielding a second independent estimate of MRI density. RESULTS: Images are presented for two individual women, demonstrating how the difficulty of the problem is highly subject-specific. Dice and Jaccard coefficients comparing the semiautomated BC-FCM method, operating on Dixon source data, with expert manual segmentation are presented. The corresponding results for the method based on T1 - and T2 -weighted data are slightly lower in the individual cases shown, but scatter plots and interclass correlations for the cohort as a whole show that both methods do an excellent job in segmenting and classifying breast tissue. CONCLUSIONS: Epidemiological results demonstrate that both methods of automated segmentation are suitable for the chosen application and that it is important to consider a range of factors when choosing a segmentation algorithm, rather than focus narrowly on a single metric such as the Dice coefficient.
Assuntos
Algoritmos , Mama/diagnóstico por imagem , Imageamento por Ressonância Magnética , Feminino , Humanos , Estudos Longitudinais , RadiografiaRESUMO
PURPOSE: In breast imaging, radiological in vivo images, such as x-ray mammography and magnetic resonance imaging (MRI), are used for tumor detection, diagnosis, and size determination. After excision, the specimen is typically sliced into slabs and a small subset is sampled. Histopathological imaging of the stained samples is used as the gold standard for characterization of the tumor microenvironment. A 3D volume reconstruction of the whole specimen from the 2D slabs could facilitate bridging the gap between histology and in vivo radiological imaging. This task is challenging, however, due to the large deformation that the breast tissue undergoes after surgery and the significant undersampling of the specimen obtained in histology. In this work, we present a method to reconstruct a coherent 3D volume from 2D digital radiographs of the specimen slabs. METHODS: To reconstruct a 3D breast specimen volume, we propose the use of multiple target neighboring slices, when deforming each 2D slab radiograph in the volume, rather than performing pairwise registrations. The algorithm combines neighborhood slice information with free-form deformations, which enables a flexible, nonlinear deformation to be computed subject to the constraint that a coherent 3D volume is obtained. The neighborhood information provides adequate constraints, without the need for any additional regularization terms. RESULTS: The volume reconstruction algorithm is validated on clinical mastectomy samples using a quantitative assessment of the volume reconstruction smoothness and a comparison with a whole specimen 3D image acquired for validation before slicing. Additionally, a target registration error of 5 mm (comparable to the specimen slab thickness of 4 mm) was obtained for five cases. The error was computed using manual annotations from four observers as gold standard, with interobserver variability of 3.4 mm. Finally, we illustrate how the reconstructed volumes can be used to map histology images to a 3D specimen image of the whole sample (either MRI or CT). CONCLUSIONS: Qualitative and quantitative assessment has illustrated the benefit of using our proposed methodology to reconstruct a coherent specimen volume from serial slab radiographs. To our knowledge, this is the first method that has been applied to clinical breast cases, with the goal of reconstructing a whole specimen sample. The algorithm can be used as part of the pipeline of mapping histology images to ex vivo and ultimately in vivo radiological images of the breast.
Assuntos
Algoritmos , Mama/diagnóstico por imagem , Mama/patologia , Técnicas Histológicas/métodos , Imageamento Tridimensional/métodos , Mamografia/métodos , Artefatos , Mama/cirurgia , Humanos , Imageamento por Ressonância Magnética/métodos , Dinâmica não Linear , Variações Dependentes do Observador , Tomografia Computadorizada por Raios X/métodosRESUMO
Physically realistic patient-specific biomechanical modelling is of paramount importance for many medical applications, where the geometry of tissues or organs is usually constructed from in vivo images. However, it is common for such biological structures to correspond to a deformed state due to being under external loadings. This necessitates the determination of the stress distribution of the known deformed state through an inverse analysis approach. To achieve this, we propose here a generalised finite element displacement/pressure (u/p)-formulation for evaluating the unloaded configuration of in vivo biological soft tissues that exhibit quasi-incompressible behaviour under finite deformations. Validity and applicability of the proposed numerical framework to practical inverse analysis problems in biomechanics is demonstrated through various numerical examples. The corresponding simulations utilise in vivo measurements of patient-specific geometries derived from different medical imaging modalities, and include recovery of the pressure-free configuration of human aortas and the gravity-free shape of the female breast.
Assuntos
Aorta , Mama , Análise de Elementos Finitos , Modelos Biológicos , Estresse Mecânico , Aorta/patologia , Aorta/fisiopatologia , Mama/patologia , Mama/fisiopatologia , Feminino , Humanos , MasculinoRESUMO
Breast radiology encompasses the full range of imaging modalities from routine imaging via x-ray mammography, magnetic resonance imaging and ultrasound (both two- and three-dimensional), to more recent technologies such as digital breast tomosynthesis, and dedicated breast imaging systems for positron emission mammography and ultrasound tomography. In addition new and experimental modalities, such as Photoacoustics, Near Infrared Spectroscopy and Electrical Impedance Tomography etc, are emerging. The breast is a highly deformable structure however, and this greatly complicates visual comparison of imaging modalities for the purposes of breast screening, cancer diagnosis (including image guided biopsy), tumour staging, treatment monitoring, surgical planning and simulation of the effects of surgery and wound healing etc. Due primarily to the challenges posed by these gross, non-rigid deformations, development of automated methods which enable registration, and hence fusion, of information within and across breast imaging modalities, and between the images and the physical space of the breast during interventions, remains an active research field which has yet to translate suitable methods into clinical practice. This review describes current research in the field of breast biomechanical modelling and identifies relevant publications where the resulting models have been incorporated into breast image registration and simulation algorithms. Despite these developments there remain a number of issues that limit clinical application of biomechanical modelling. These include the accuracy of constitutive modelling, implementation of representative boundary conditions, failure to meet clinically acceptable levels of computational cost, challenges associated with automating patient-specific model generation (i.e. robust image segmentation and mesh generation) and the complexity of applying biomechanical modelling methods in routine clinical practice.
Assuntos
Neoplasias da Mama/patologia , Interpretação de Imagem Assistida por Computador/métodos , Fenômenos Biomecânicos , Simulação por Computador , Feminino , Humanos , Mamografia/métodosRESUMO
Surgical treatment for early-stage breast carcinoma primarily necessitates breast conserving therapy (BCT), where the tumour is removed while preserving the breast shape. To date, there have been very few attempts to develop accurate and efficient computational tools that could be used in the clinical environment for pre-operative planning and oncoplastic breast surgery assessment. Moreover, from the breast cancer research perspective, there has been very little effort to model complex mechano-biological processes involved in wound healing. We address this by providing an integrated numerical framework that can simulate the therapeutic effects of BCT over the extended period of treatment and recovery. A validated, three-dimensional, multiscale finite element procedure that simulates breast tissue deformations and physiological wound healing is presented. In the proposed methodology, a partitioned, continuum-based mathematical model for tissue recovery and angiogenesis, and breast tissue deformation is considered. The effectiveness and accuracy of the proposed numerical scheme is illustrated through patient-specific representative examples. Wound repair and contraction numerical analyses of real MRI-derived breast geometries are investigated, and the final predictions of the breast shape are validated against post-operative follow-up optical surface scans from four patients. Mean (standard deviation) breast surface distance errors in millimetres of 3.1 (±3.1), 3.2 (±2.4), 2.8 (±2.7) and 4.1 (±3.3) were obtained, demonstrating the ability of the surgical simulation tool to predict, pre-operatively, the outcome of BCT to clinically useful accuracy.
Assuntos
Neoplasias da Mama/cirurgia , Mastectomia Segmentar/métodos , Planejamento de Assistência ao Paciente , Fenômenos Biomecânicos , Feminino , Análise de Elementos Finitos , Humanos , Imageamento por Ressonância Magnética , Neovascularização Patológica , Resultado do Tratamento , CicatrizaçãoRESUMO
Here we introduce a model of solid tumour growth coupled with a multiscale biomechanical description of the tumour microenvironment, which facilitates the explicit simulation of fibre-fibre and tumour-fibre interactions. We hypothesise that such a model, which provides a purely mechanical description of tumour-host interactions, can be used to explain experimental observations of the effect of collagen micromechanics on solid tumour growth. The model was specified to mouse tumour data, and numerical simulations were performed. The multiscale model produced lower stresses than an equivalent continuum-like approach, due to a more realistic remodelling of the collagen microstructure. Furthermore, solid tumour growth was found to cause a passive mechanical realignment of fibres at the tumour boundary from a random to a circumferential orientation. This is in accordance with experimental observations, thus demonstrating that such a response can be explained as purely mechanical. Finally, peritumoural fibre network anisotropy was found to produce anisotropic tumour morphology. The dependency of tumour morphology on the peritumoural microstructure was reduced by adding a load-bearing non-collagenous component to the fibre network constitutive equation.
Assuntos
Colágeno/metabolismo , Modelos Biológicos , Neoplasias/metabolismo , Neoplasias/patologia , Algoritmos , Animais , Fenômenos Biomecânicos , Linhagem Celular Tumoral , Proliferação de Células , Simulação por Computador , Análise de Elementos Finitos , Humanos , Camundongos , Estresse Mecânico , Carga TumoralRESUMO
Prone-to-supine breast image registration has potential application in the fields of surgical and radiotherapy planning, image guided interventions, and multi-modal cancer diagnosis, staging, and therapy response prediction. However, breast image registration of three dimensional images acquired in different patient positions is a challenging problem, due to large deformations induced to the soft breast tissue caused by the change in gravity loading. We present a symmetric, biomechanical simulation based registration framework which aligns the images in a central, virtually unloaded configuration. The breast tissue is modelled as a neo-Hookean material and gravity is considered as the main source of deformation in the original images. In addition to gravity, our framework successively applies image derived forces directly into the unloading simulation in place of a subsequent image registration step. This results in a biomechanically constrained deformation. Using a finite difference scheme avoids an explicit meshing step and enables simulations to be performed directly in the image space. The explicit time integration scheme allows the motion at the interface between chest and breast to be constrained along the chest wall. The feasibility and accuracy of the approach presented here was assessed by measuring the target registration error (TRE) using a numerical phantom with known ground truth deformations, nine clinical prone MRI and supine CT image pairs, one clinical prone-supine CT image pair and four prone-supine MRI image pairs. The registration reduced the mean TRE for the numerical phantom experiment from initially 19.3 to 0.9 mm and the combined mean TRE for all fourteen clinical data sets from 69.7 to 5.6 mm.
Assuntos
Mama , Processamento de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética , Mamografia , Tomografia Computadorizada por Raios X , Feminino , Humanos , Decúbito Ventral , Decúbito DorsalRESUMO
Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.
Assuntos
Neoplasias da Mama/epidemiologia , Mama/anormalidades , Glândulas Mamárias Humanas/anormalidades , Mamografia/métodos , Adulto , Idoso , Densidade da Mama , Neoplasias da Mama/patologia , Feminino , Humanos , Incidência , Agências Internacionais , Glândulas Mamárias Humanas/patologia , Pessoa de Meia-Idade , Fatores de RiscoRESUMO
The high incidence and low mortality of breast cancer surgery has led to an increasing emphasis on the cosmetic outcome of surgical treatment. Advances in aesthetic evaluation, as well as surgical planning and outcome prediction, have been investigated by using geometrically precise 3D modelling of the breast surface prior to surgery and after the procedure. However, existing solutions are based on expensive site specific setups and remain weakly validated. In this paper, we explore the possibility of using low-cost RGBD cameras as an affordable and mobile system for breast surface reconstruction. The methodology relies on sensor calibration, uncertainty-driven point filtering, dense reconstruction and subsequent multi-view joint optimization to diffuse residual pose errors. Results from a phantom study, with ground truth obtained through commercially available scanners, indicate that the approach is promising with RMS errors in order of 2 mm. A clinical study shows the practical applicability of our method and compares favourably to high-end scanning solutions.
Assuntos
Neoplasias da Mama , Mama , Calibragem , Estética , Humanos , Imagens de FantasmasRESUMO
We propose a new method for aligning three-dimensional (3-D) magnetic resonance angiography (MRA) with 2-D X-ray digital subtraction angiograms (DSA). Our method is developed from our algorithm to register computed tomography volumes to X-ray images based on intensity matching of digitally reconstructed radiographs (DRRs). To make the DSA and DRR more similar, we transform the MRA images to images of the vasculature and set to zero the contralateral side of the MRA to that imaged with DSA. We initialize the search for a match on a user defined circular region of interest. We have tested six similarity measures using both unsegmented MRA and three segmentation variants of the MRA. Registrations were carried out on images of a physical neuro-vascular phantom and images obtained during four neuro-vascular interventions. The most accurate and robust registrations were obtained using the pattern intensity, gradient difference, and gradient correlation similarity measures, when used in conjunction with the most sophisticated MRA segmentations. Using these measures, 95% of the phantom start positions and 82% of the clinical start positions were successfully registered. The lowest root mean square reprojection errors were 1.3 mm (standard deviation 0.6) for the phantom and 1.5 mm (standard deviation 0.9) for the clinical data sets. Finally, we present a novel method for the comparison of similarity measure performance using a technique borrowed from receiver operator characteristic analysis.