Modelling and fabrication procedure for a 3D printed cardiac model - surgical planning of Left Ventricular Aneurysm.

The present paper describes a procedure for the development and production of a physical model for surgical planning of a Left Ventricular Aneurysm. The method is based on the general approach provided in Otton et al. (2017) and was customized to seek a reliable and fast procedure for the production of a specific type of cardiac model - i.e. chambers of the left side of the heart. The paper covers all the steps: processing of the data, segmentation, modelling and 3D printing; details are provided for all the phases, in order to allow the reproduction of the achieved results. The procedure relies on Computed Tomography - CT imaging as data source for the identification and modelling of the anatomy. Materialise Mimics was used as segmentation software to process the CT data. While its usefulness for the surgical needs was verified on a single clinical case (provided by the Careggi Hospital of Florence, Italy), the modelling procedure was tested twice, to produce a physical replica both ex-ante and ex-post surgical intervention.•The tools used for segmentation and generation of the printable model were customized to reduce modelling time for the specific type of desired model.•Detailed information on the use of modeling tools, not available in the literature, will be provided.•The procedure allows fabrication of a physical model representing the heart chambers in a short time.

Multimodal fusion of tomographic sequences of medical images: MRE spatially enhanced by MRI.

BACKGROUND AND OBJECTIVE: In biomedical fields, image analysis is often necessary for an accurate diagnosis. In order to obtain all the information needed to form an in-depth clinical picture, it may be useful to combine the contents of images taken under different diagnostic modes. Multimodal medical image fusion techniques enable complementary information acquired by different imaging devices to be automatically combined into a unique image. METHODS: In this paper, multimodal medical images fusion method based on multiresolution analysis (MRA) is proposed, with the aim to combine the high geometric content of magnetic resonance imaging (MRI) and the elasticity information of magnetic resonance elastography (MRE), simultaneously acquired on the same organs of a patient. First, the slices of MRE are volumetrically interpolated to exactly overlap, each with a slice of MRI. Then, the spatial details of MRI are extracted by means of MRA and injected into the corresponding slices of MRE. Due to the intrinsic dissimilarity between corresponding slices of MRE and MRI, the spatial details of MRI are modulated by local or global matching functions. RESULTS: The performance of the proposed method is quantitatively assessed considering radiometric and geometric consistency of the fused images with respect to their originals, in a comparison with two popular methods from the literature. For a qualitative evaluation, a visual inspection is carried out. CONCLUSIONS: The results show that the proposed method enables an effective MRI-MRE fusion that allows the elasticity information and geometric details of the examined organs to be evaluated in a single image.

Volumetric interpolation of tomographic sequences for accurate 3D reconstruction of anatomical parts.

BACKGROUND AND OBJECTIVE: Tomographic sequences of biomedical images are commonly used to achieve a three-dimensional visualization of the human anatomy. In some cases, the number of images contained in the sequence is limited, e.g., in low-dose computed tomography acquired on neonatal patients, resulting in a coarse and inaccurate 3D reconstruction. METHODS: In this paper, volumetric image interpolation methods, devised to increase the axial resolution of tomographic sequences and achieve a refined 3D reconstruction, are proposed and compared. The techniques taken into consideration are based on motion-compensated frame-interpolation concepts, which have been developed for video applications, mainly frame-rate conversion. RESULTS: The performance of the proposed methods is quantitatively assessed by using sequences with a simulated low axial resolution obtained from the decimation of standard high-resolution computed tomography sequences. Real data with an actual low axial resolution have been used as well for a qualitative evaluation of the proposed methods. CONCLUSIONS: The experimental results demonstrate that the proposed methods enable an effective slice interpolation and that the achievable 3D models clearly benefit from the increased axial resolution.

Current Practice in Preoperative Virtual and Physical Simulation in Neurosurgery.

In brain tumor surgery, an appropriate and careful surgical planning process is crucial for surgeons and can determine the success or failure of the surgery. A deep comprehension of spatial relationships between tumor borders and surrounding healthy tissues enables accurate surgical planning that leads to the identification of the optimal and patient-specific surgical strategy. A physical replica of the region of interest is a valuable aid for preoperative planning and simulation, allowing the physician to directly handle the patient's anatomy and easily study the volumes involved in the surgery. In the literature, different anatomical models, produced with 3D technologies, are reported and several methodologies were proposed. Many of them share the idea that the employment of 3D printing technologies to produce anatomical models can be introduced into standard clinical practice since 3D printing is now considered to be a mature technology. Therefore, the main aim of the paper is to take into account the literature best practices and to describe the current workflow and methodology used to standardize the pre-operative virtual and physical simulation in neurosurgery. The main aim is also to introduce these practices and standards to neurosurgeons and clinical engineers interested in learning and implementing cost-effective in-house preoperative surgical planning processes. To assess the validity of the proposed scheme, four clinical cases of preoperative planning of brain cancer surgery are reported and discussed. Our preliminary results showed that the proposed methodology can be applied effectively in the neurosurgical clinical practice both in terms of affordability and in terms of simulation realism and efficacy.

Metrological and Critical Characterization of the Intel D415 Stereo Depth Camera.

Low-cost RGB-D cameras are increasingly being used in several research fields, including human⁻machine interaction, safety, robotics, biomedical engineering and even reverse engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras have proven to be among the most suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e., ~160⁻10,000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations for the RealSense D415. In particular, tests are carried out to assess the device performance in the near range (i.e., 100⁻1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e., the German VDI/VDE 2634 Part 2) with a number of literature-based strategies. Performance analysis is finally compared against the latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in reverse engineering applications.