Anatomical structure modeling from medical images

Virtual and augmented reality systems and three-dimensional printing of the renal model-novel trends to guide preoperative planning for renal cancer

Objective

This study aimed to explore the applications of three-dimensional (3D) technology, including virtual reality, augmented reality (AR), and 3D printing system, in the field of medicine, particularly in renal interventions for cancer treatment.

Methods

A specialized software transforms 2D medical images into precise 3D digital models, facilitating improved anatomical understanding and surgical planning. Patient-specific 3D printed anatomical models are utilized for preoperative planning, intraoperative guidance, and surgical education. AR technology enables the overlay of digital perceptions onto real-world surgical environments.

Results

Patient-specific 3D printed anatomical models have multiple applications, such as preoperative planning, intraoperative guidance, trainee education, and patient counseling. Virtual reality involves substituting the real world with a computer-generated 3D environment, while AR overlays digitally created perceptions onto the existing reality. The advances in 3D modeling technology have sparked considerable interest in their application to partial nephrectomy in the realm of renal cancer. 3D printing, also known as additive manufacturing, constructs 3D objects based on computer-aided design or digital 3D models. Utilizing 3D-printed preoperative renal models provides benefits for surgical planning, offering a more reliable assessment of the tumor's relationship with vital anatomical structures and enabling better preparation for procedures. AR technology allows surgeons to visualize patient-specific renal anatomical structures and their spatial relationships with surrounding organs by projecting CT/MRI images onto a live laparoscopic video. Incorporating patient-specific 3D digital models into healthcare enhances best practice, resulting in improved patient care, increased patient satisfaction, and cost saving for the healthcare system.

Supervised recursive segmentation of volumetric CT images for 3D reconstruction of lung and vessel tree

Three dimensional reconstruction of lung and vessel tree has great significance to 3D observation and quantitative analysis for lung diseases. This paper presents non-sheltered 3D models of lung and vessel tree based on a supervised semi-3D lung tissues segmentation method. A recursive strategy based on geometric active contour is proposed instead of the "coarse-to-fine" framework in existing literature to extract lung tissues from the volumetric CT slices. In this model, the segmentation of the current slice is supervised by the result of the previous one slice due to the slight changes between adjacent slice of lung tissues. Through this mechanism, lung tissues in all the slices are segmented fast and accurately. The serious problems of left and right lungs fusion, caused by partial volume effects, and segmentation of pleural nodules can be settled meanwhile during the semi-3D process. The proposed scheme is evaluated by fifteen scans, from eight healthy participants and seven participants suffering from early-stage lung tumors. The results validate the good performance of the proposed method compared with the "coarse-to-fine" framework. The segmented datasets are utilized to reconstruct the non-sheltered 3D models of lung and vessel tree.

Patient-specific anisotropic model of human trunk based on MR data

There are many ways to generate geometrical models for numerical simulation, and most of them start with a segmentation step to extract the boundaries of the regions of interest. This paper presents an algorithm to generate a patient-specific three-dimensional geometric model, based on a tetrahedral mesh, without an initial extraction of contours from the volumetric data. Using the information directly available in the data, such as gray levels, we built a metric to drive a mesh adaptation process. The metric is used to specify the size and orientation of the tetrahedral elements everywhere in the mesh. Our method, which produces anisotropic meshes, gives good results with synthetic and real MRI data. The resulting model quality has been evaluated qualitatively and quantitatively by comparing it with an analytical solution and with a segmentation made by an expert. Results show that our method gives, in 90% of the cases, as good or better meshes as a similar isotropic method, based on the accuracy of the volume reconstruction for a given mesh size. Moreover, a comparison of the Hausdorff distances between adapted meshes of both methods and ground-truth volumes shows that our method decreases reconstruction errors faster.

The Parametric Model of the Human Mandible Coronoid Process Created by Method of Anatomical Features

Geometrically accurate and anatomically correct 3D models of the human bones are of great importance for medical research and practice in orthopedics and surgery. These geometrical models can be created by the use of techniques which can be based on input geometrical data acquired from volumetric methods of scanning (e.g., Computed Tomography (CT)) or on the 2D images (e.g., X-ray). Geometrical models of human bones created in such way can be applied for education of medical practitioners, preoperative planning, etc. In cases when geometrical data about the human bone is incomplete (e.g., fractures), it may be necessary to create its complete geometrical model. The possible solution for this problem is the application of parametric models. The geometry of these models can be changed and adapted to the specific patient based on the values of parameters acquired from medical images (e.g., X-ray). In this paper, Method of Anatomical Features (MAF) which enables creation of geometrically precise and anatomically accurate geometrical models of the human bones is implemented for the creation of the parametric model of the Human Mandible Coronoid Process (HMCP). The obtained results about geometrical accuracy of the model are quite satisfactory, as it is stated by the medical practitioners and confirmed in the literature.

Constructing complex 3D biological environments from medical imaging using high performance computing

Extracting information about the structure of biological tissue from static image data is a complex task requiring computationally intensive operations. Here, we present how multicore CPUs and GPUs have been utilized to extract information about the shape, size, and path followed by the mammalian oviduct, called the fallopian tube in humans, from histology images, to create a unique but realistic 3D virtual organ. Histology images were processed to identify the individual cross sections and determine the 3D path that the tube follows through the tissue. This information was then related back to the histology images, linking the 2D cross sections with their corresponding 3D position along the oviduct. A series of linear 2D spline cross sections, which were computationally generated for the length of the oviduct, were bound to the 3D path of the tube using a novel particle system technique that provides smooth resolution of self-intersections. This results in a unique 3D model of the oviduct, which is grounded in reality. The GPU is used for the processor intensive operations of image processing and particle physics based simulations, significantly reducing the time required to generate a complete model.

Image-based variational meshing

In medical simulations involving tissue deformation, the finite element method (FEM) is a widely used technique, where the size, shape, and placement of the elements in a model are important factors that affect the interpolation and numerical errors of a solution. Conventional model generation schemes for FEM consist of a segmentation step delineating the anatomy followed by a meshing step generating elements conforming to this segmentation. In this paper, a single-step model generation technique is proposed based on optimization. Starting from an initial mesh covering the domain of interest, the mesh nodes are adjusted to minimize an objective function which penalizes intra-element intensity variations and poor element geometry for the entire mesh. Trade-offs between mesh geometry quality and intra-element variance are achieved by adjusting the relative weights of the geometric and intensity variation components of the cost function. This meshing approach enables a more accurate rendering of shapes with fewer elements and provides more accurate models for deformation simulation, especially when the image intensities represent a mechanical feature of the tissue such as the elastic modulus. The use of the proposed mesh optimization is demonstrated in 2-D and 3-D on synthetic phantoms, MR images of the brain, and CT images of the kidney. A comparison with previous meshing techniques that do not account for image intensity is also provided demonstrating the benefits of our approach.

Finite element analysis of the human mandible at 3 different stages of life

OBJECTIVE

This study analyzed detailed models of human mandibles at 3 different stages of life with simulation of supra normal chewing forces at static conditions.

METHODS AND MATERIALS

Finite element analysis (FEA) was used to generate models from cone-beam computerized tomograms (CBCT) of 3 patients aged 12, 20, and 67 years, using numerically calculated material parameters. Estimated chewing forces were then applied to the simulations.

RESULTS

The results reflect higher elasticity in younger models in all regions of the mandible. The experimental models show that physiologic load stress and strain distributional changes of the mandible vary according to age.

CONCLUSION

The CBCT-based model generation used in this study provided high-quality model definition of the 3 individual patients of different ages. FEA has great potential to predict bone responses to paradigms of mechanical activity. Future applications of FEA will include surgical planning, surgical hardware testing, and the design of scaffolds and tissue-engineered constructs.

Analysis of existing methods for 3D modelling of femurs starting from two orthogonal images and development of a script for a commercial software package

BACKGROUND

At present the interest in medical field about the generation of three-dimensional digital models of anatomical structures increases due to the widespread diffusion of CAS--computer assisted surgery--systems. Most of them are based on CT--computer tomography--or MR--magnetic resonance--data volumes but sometimes this information is not available; there are only few X-ray, ultrasound or fluoroscopic images.

METHODS

This paper describes the study and the development of a script for a commercial software package (3ds Max) able to reconfigure the template model of a femur starting from two orthogonal images representing the specific patient's anatomy.

RESULTS

The script was used in several tests as summarized in this paper and the results appear to be interesting and acceptable, even for the medical experts that evaluated them.

CONCLUSIONS

The script developed in this work allows the generation of the 3D model of a femur in a very simple way (the user interface has been developed obeying to the main usability guidelines) and using a widespread commercial package. The quality of the results can be compared to the quality of more expensive and specialized systems.

Anisotropic finite element modeling for patient-specific mandible

This paper presents an ad hoc modular software tool to quasi-automatically generate patient-specific three-dimensional (3D) finite element (FE) model of the human mandible. The main task is taking into account the complex geometry of the individual mandible, as well as the inherent highly anisotropic material law. At first, by computed tomography data (CT), the individual geometry of the complete range of mandible was well reproduced, also the separation between cortical and cancellous bone. Then, taking advantage of the inherent shape nature as 'curve' long bone, the algorithm employed a pair of B-spline curves running along the entire upper and lower mandible borders as auxiliary baselines, whose directions are also compatible with that of the trajectory of maximum material stiffness throughout the cortical bone of the mandible. And under the guidance of this pair of auxiliary baselines, a sequence of B-spline surfaces were interpolated adaptively as curve cross-sections to cut the original geometry. Following, based on the produced curve contours and the corresponding curve cross-section surfaces, quite well structured FE volume meshes were constructed, as well as the inherent trajectory vector fields of the anisotropic material (orthotropic for cortical bone and transversely isotropic for cancellous bone). Finally, a sensitivity analysis comprising various 3D FE simulations was carried out to reveal the relevance of elastic anisotropy for the load carrying behavior of the mandible.