Miguel A. Lago

Estimation of the elastic parameters of human liver biomechanical models by means of medical images and evolutionary computation

This paper presents a method to computationally estimate the elastic parameters of two biomechanical models proposed for the human liver. The method is aimed at avoiding the invasive measurement of its mechanical response. The chosen models are a second order Mooney-Rivlin model and an Ogden model. A novel error function, the geometric similarity function (GSF), is formulated using similarity coefficients widely applied in the field of medical imaging (Jaccard coefficient and Hausdorff coefficient). This function is used to compare two 3D images. One of them corresponds to a reference deformation carried out over a finite element (FE) mesh of a human liver from a computer tomography image, whilst the other one corresponds to the FE simulation of that deformation in which variations in the values of the model parameters are introduced. Several search strategies, based on GSF as cost function, are developed to accurately find the elastics parameters of the models, namely: two evolutionary algorithms (scatter search and genetic algorithm) and an iterative local optimization. The results show that GSF is a very appropriate function to estimate the elastic parameters of the biomechanical models since the mean of the relative mean absolute errors committed by the three algorithms is lower than 4%.

A new methodology for the in vivo estimation of the elastic constants that characterize the patient-specific biomechanical behavior of the human cornea

This work presents a methodology for the in vivo characterization of the complete biomechanical behavior of the human cornea of each patient. Specifically, the elastic constants of a hyperelastic, second-order Ogden model were estimated for 24 corneas corresponding to 12 patients. The finite element method was applied to simulate the deformation of human corneas due to non-contact tonometry, and an iterative search controlled by a genetic heuristic was used to estimate the elastic parameters that most closely approximates the simulated deformation to the real one. The results from a synthetic experiment showed that these parameters can be estimated with an error of about 5%. The results of 24 in vivo corneas showed an overlap of about 90% between simulation and real deformed cornea and a modified Hausdorff distance of 25 μm, which indicates the great accuracy of the proposed methodology.

Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image.

In this study, six biomechanical models for simulating lamb liver behaviour are presented. They are validated using similarity coefficients from Medical Image on reconstructed volumes from computerised tomography images. In particular, the Jaccard and Hausdorff coefficients are used. Loads of 20 and 40 g are applied to the livers and their deformation is simulated by means of the finite element method. The models used are a linear elastic model, a neo-Hookean model, a Mooney–Rivlin model, an Ogden model, a linear viscoelastic model and a viscohyperelastic model. The model that provided a behaviour that is closest to reality was the viscohyperelastic model, where the hyperelastic part was modelled with an Ogden model.

Patient-specific simulation of the intrastromal ring segment implantation in corneas with keratoconus

PURPOSEnThe purpose of this study was the simulation of the implantation of intrastromal corneal-ring segments for patients with keratoconus. The aim of the study was the prediction of the corneal curvature recovery after this intervention.nnnMETHODSnSeven patients with keratoconus diagnosed and treated by implantation of intrastromal corneal-ring segments were enrolled in the study. The 3D geometry of the cornea of each patient was obtained from its specific topography and a hyperelastic model was assumed to characterize its mechanical behavior. To simulate the intervention, the intrastromal corneal-ring segments were modeled and placed at the same location at which they were placed in the surgery. The finite element method was then used to obtain a simulation of the deformation of the cornea after the ring segment insertion. Finally, the predicted curvature was compared with the real curvature after the intervention.nnnRESULTSnThe simulation of the ring segment insertion was validated comparing the curvature change with the data after the surgery. Results showed a flattening of the cornea which was in consonance with the real improvement of the corneal curvature. The mean difference obtained was of 0.74 mm using properties of healthy corneas.nnnCONCLUSIONSnFor the first time, a patient-specific model of the cornea has been used to predict the outcomes of the surgery after the intrastromal corneal-ring segments implantation in real patients.

Genetic algorithms for estimating the biomechanical behavior of breast tissues

The accuracy of the patient-specific biomechanical models of the breast is a major concern for applications related with simulation, surgical guidance or cancer diagnosis. Being able to predict the localization of a lesion depends on the realism of the selected model. However, obtaining a realistic model of the breast tissues is not straightforward since the biomechanical parameters of the breast internal tissues vary significantly from one patient to another. This paper presents an iterative search algorithm which is able to obtain the parameters of a proposed biomechanical model. A methodology based on genetic algorithms was used in order to estimate the biomechanical model of the breast tissues. The similarity between the estimated model and the real model presents an overlap of about 94% and a maximum average distance below 1mm. This algorithm can be easily translated to real cases.

Interactions of lesion detectability and size across single-slice DBT and 3D DBT.

Three dimensional image modalities introduce a new paradigm for visual search requiring visual exploration of a larger search space than 2D imaging modalities. The large number of slices in the 3D volumes and the limited reading times make it difficult for radiologists to explore thoroughly by fixating with their high resolution fovea on all regions of each slice. Thus, for 3D images, observers must rely much more on their visual periphery (points away from fixation) to process image information. We previously found a dissociation in signal detectability between 2D and 3D search tasks for small signals in synthetic textures evaluated with non-radiologist trained observers. Here, we extend our evaluation to more clinically realistic backgrounds and radiologist observers. We studied the detectability of simulated microcalcifications (MCALC) and masses (MASS) in Digital Breast Tomosynthesis (DBT) utilizing virtual breast phantoms. We compared the lesion detectability of 8 radiologists during free search in 3D DBT and a 2D single-slice DBT (center slice of the 3D DBT). Our results show that the detectability of the microcalcification degrades significantly in 3D DBT with respect to the 2D single-slice DBT. On the other hand, the detectability for masses does not show this behavior and its detectability is not significantly different. The large deterioration of the 3D detectability of microcalcifications relative to masses may be related to the peripheral processing given the high number of cases in which the microcalcification was missed and the high number of search errors. Together, the results extend previous findings with synthetic textures and highlight how search in 3D images is distinct from 2D search as a consequence of the interaction between search strategies and the visibility of signals in the visual periphery.

Evaluation of search strategies for microcalcifications and masses in 3D images.

Medical imaging is quickly evolving towards 3D image modalities such as computed tomography (CT), magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT). These 3D image modalities add volumetric information but further increase the need for radiologists to search through the image data set. Although much is known about search strategies in 2D images less is known about the functional consequences of different 3D search strategies. We instructed readers to use two different search strategies: drillers had their eye movements restricted to a few regions while they quickly scrolled through the image stack, scanners explored through eye movements the 2D slices. We used real-time eye position monitoring to ensure observers followed the drilling or the scanning strategy while approximately preserving the percentage of the volumetric data covered by the useful field of view. We investigated search for two signals: a simulated microcalcification and a larger simulated mass. Results show an interaction between the search strategy and lesion type. In particular, scanning provided significantly better detectability for microcalcifications at the cost of 5 times more time to search while there was little change in the detectability for the larger simulated masses. Analyses of eye movements support the hypothesis that the effectiveness of a search strategy in 3D imaging arises from the interaction of the fixational sampling of visual information and the signals’ visibility in the visual periphery.

Observer templates in 2D and 3D localization tasks.

In this study we examine search performance for 3D forced-localization tasks in Gaussian random textures in which subjects are able to freely scroll through the image as part of their search for the target. We also evaluate a 2D single-slice version of the same task for comparison. We analyze these experiments using both efficiency with respect to the Ideal Observer and the classification image technique, which directly estimates the weighting function used by observers for a task. We are particularly interested in whether subjects can efficiently integrate across multiple slices in depth as part of performing the localization task. In the 3D tasks, the image display we use allows subjects to freely scroll through a volumetric image, and a localization response is made through a mouse-click on the image. The search region has a relatively modest size (approx. 8.8° visual angle). Localization responses are considered correct if they are close to the target center (within 6 voxels). The classification image methodology uses noise fields from the incorrect localizations to build an estimate of the weights used by the observer to perform the task. The basic idea is that incorrect localizations occur in regions of the image where the noise field matches the weighting profile, thereby eliciting a strong internal response. The efficiency results indicate differences between 2D and 3D search tasks, with lower efficiency for large target in the 3D task. The classification images suggest that this finding can be explained by the lack of spatial integration across slices.

Developing populations of software breast phantoms for virtual clinical trials.

Virtual Clinical Trials (VCTs) of breast imaging have been used as a tool for the evaluation and optimization of novel imaging systems through computer simulations of breast anatomy, image acquisition, and interpretation. VCTs offer significant advantages over clinical trials in terms of cost, duration, and radiation risk. The performance of VCTs depends on the selection of simulated breasts to represent the population of interest. We have developed a method for selecting populations of software breast phantoms to match the clinical distribution of compressed breast thickness and breast percent density. We extracted the compressed thickness information from anonymized DICOM headers of mammography images from 10,705 women who had their breast screening exams within a year (09/2010-08/2011). Percent density was estimated using an open source software tool. Characteristic clinical sub-populations were identified by performing k-means clustering, and represented by separate sets of phantoms. The corresponding thickness of uncompressed phantoms was selected assuming 50% thickness reduction during mammographic compression. The phantom volumetric density was selected based upon a relationship between mammographic (2D) percent density and volumetric (3D) density, estimated from clinical images. Using a set of 24 representative phantoms, we were able to match the analyzed clinical population completely for the compressed breast thickness, and within two percentage points of the volumetric breast density. Representative phantoms can be used to generate the full population of virtual patients, of a size determined by the power-analysis of the specific VCT, by random variations of the internal phantom composition.

Foveated model observers to predict human performance in 3D images

We evaluate 3D search requires model observers that take into account the peripheral human visual processing (foveated models) to predict human observer performance. We show that two different 3D tasks, free search and location-known detection, influence the relative human visual detectability of two signals of different sizes in synthetic backgrounds mimicking the noise found in 3D digital breast tomosynthesis. One of the signals resembled a microcalcification (a small and bright sphere), while the other one was designed to look like a mass (a larger Gaussian blob). We evaluated current standard models observers (Hotelling; Channelized Hotelling; non-prewhitening matched filter with eye filter, NPWE; and non-prewhitening matched filter model, NPW) and showed that they incorrectly predict the relative detectability of the two signals in 3D search. We propose a new model observer (3D Foveated Channelized Hotelling Observer) that incorporates the properties of the visual system over a large visual field (fovea and periphery). We show that the foveated model observer can accurately predict the rank order of detectability of the signals in 3D images for each task. Together, these results motivate the use of a new generation of foveated model observers for predicting image quality for search tasks in 3D imaging modalities such as digital breast tomosynthesis or computed tomography.