Cristina Suárez-Mejías

Three-dimensional printed models for surgical planning of complex congenital heart defects: an international multicentre study

OBJECTIVES To evaluate the impact of 3D printed models (3D models) on surgical planning in complex congenital heart disease (CHD). METHODS A prospective case-crossover study involving 10 international centres and 40 patients with complex CHD (median age 3 years, range 1 month-34 years) was conducted. Magnetic resonance imaging and computed tomography were used to acquire and segment the 3D cardiovascular anatomy. Models were fabricated by fused deposition modelling of polyurethane filament, and dimensions were compared with medical images. Decisions after the evaluation of routine clinical images were compared with those after inspection of the 3D model and intraoperative findings. Subjective satisfaction questionnaire was provided. RESULTS 3D models accurately replicate anatomy with a mean bias of -0.27 ± 0.73 mm. Ninety-six percent of the surgeons agree or strongly agree that 3D models provided better understanding of CHD morphology and improved surgical planning. 3D models changed the surgical decision in 19 of the 40 cases. Consideration of a 3D model refined the planned biventricular repair, achieving an improved surgical correction in 8 cases. In 4 cases initially considered for conservative management or univentricular palliation, inspection of the 3D model enabled successful biventricular repair. CONCLUSIONS 3D models are accurate replicas of the cardiovascular anatomy and improve the understanding of complex CHD. 3D models did not change the surgical decision in most of the cases (21 of 40 cases, 52.5% cases). However, in 19 of the 40 selected complex cases, 3D model helped redefining the surgical approach.

3D printed cardiovascular models for surgical planning in complex congenital heart diseases

Background A precise understanding of the anatomical structures of the heart and great vessels is essential for surgical planning in order to avoid unexpected findings. Rapid prototyping techniques are used to print three-dimensional (3D) replicas of patients’ cardiovascular anatomy based on 3D clinical images such as MRI. The purpose of this study is to explore the use of 3D patient-specific cardiovascular models using rapid prototyping techniques to improve surgical planning in patients with complex congenital heart disease.

Evaluating the Child–Robot Interaction of the NAOTherapist Platform in Pediatric Rehabilitation

NAOTherapist is a cognitive robotic architecture whose main goal is to develop non-contact upper-limb rehabilitation sessions autonomously with a social robot for patients with physical impairments. In order to achieve a fluent interaction and an active engagement with the patients, the system should be able to adapt by itself in accordance with the perceived environment. In this paper, we describe the interaction mechanisms that are necessary to supervise and help the patient to carry out the prescribed exercises correctly. We also provide an evaluation focused on the child-robot interaction of the robotic platform with a large number of schoolchildren and the experience of a first contact with three pediatric rehabilitation patients. The results presented are obtained through questionnaires, video analysis and system logs, and have proven to be consistent with the hypotheses proposed in this work.

Segmentation of Retroperitoneal Tumors Using Fast Continuous Max-Flow Algorithm

In this paper a new algorithm for the segmentation of retroperitoneal tumors is presented. In this paper an accumulated gradient distance is proposed as a new regional term in the continuous max-flow algorithm. In this preliminary study, three CT images have been segmented and compared with manual segmentations. DICE, Jaccard, Sensitivity andPostive Predictive Value (PPV) indexes have been computed and their values show promising results.

Virtual reality AYRA software for preoperative planning in facial allotransplantation.

Purpose The purpose of this study was to validate a virtual reality software for the recording of anthropometric measurements as a first step towards matching donors with recipients in the preoperative planning process which precedes the harvest of a facial allograft. Methods Anthropometric measurements of both soft and bone tissue were recorded in 5 cryopreserved human heads to compare conventional analogue measurements with digital measurements obtained from 3-dimensional (3D) reconstructions produced using AYRA software. To test the degree of correlation between both measuring methods, intraclass correlation coefficient (ICC) was applied to each pair of measurements. Results ICCs calculated were greater than 0.6 (substantial or almost perfect correlation) for all of the pairs of variables, with the exception of 2 of the measurements studied in bone tissue. Conclusions In facial transplantation, preoperative planning is crucial to select an allograft whose anatomical compatibility with the recipient defect is as close as possible. The dimensions of the potential face donor must be congruent to ensure the procedure’s feasibility and the adequate insertion of the allograft into the defect. The recording of anthropometric measurements with the virtual reality software displayed an equivalent correlation to those produced using a conventional analogue method. The 3D reconstructions obtained by using a virtual reality software can play a useful role to facilitate the characterization of the donor face.

Segmentation of Muscles in CT Volumes Using a Continuous Convex Relaxation Approach

Segmentation of muscles in CT volumes is a complicated task even for experts due to their Hounsfield values, which are close to those of surrounding organs. Surgeons and physicians usually prefer to segment them manually due to the lack of efficient tools in implementing a correct segmentation. This is a very time-consuming task, as CT volumes can contain even hundreds of 2D slices. In this paper an algorithm to implement the segmentation of skeletal muscle structures have been developed. 30 CT images belonging to different patients have been used to assess the tool. Results in terms of efficiency and computational times are promising providing DICE and sensitivity coefficients higher than 0.87.

Virtual reality simulation training and assisted surgery: AYRA: Virtual and physical biomodels in surgery

In this paper we present a surgical application based on virtual reality called AYRA. AYRA allows surgeons training, planning and optimization of surgical procedures. AYRA was developed under a research, development and innovation project financed by the Andalusia Department of Health called VirSSPA. AYRA is very important for the health organization since the surgeons can be trained and helped by AYRA in decision making issues. Nowadays AYRA has been successfully used in more than 489 real cases and surgeons have declared their satisfaction with the results. After proving its efficiency it has been introduced in the clinical practice during the surgical planning sessions at the Virgen del Rocío University Hospital. For example, the use of AYRA reduces by 45 % the complication rate and in two hours the operating room time in breast microvascular reconstruction by DIEAP free flap. The success rate is increased because physicians can see the exact anatomy of the case and the extent of the injury that the patient suffers before proceeding with the surgery. In addition, surgeons can see and interact in 3D with other similar cases made in AYRA by other surgeon colleagues, thus promoting the training of surgeons and the knowledge transfer in this field.

Joint segmentation of bones and muscles using an intensity and histogram-based energy minimization approach

BACKGROUND AND OBJECTIVES The segmentation of muscle and bone structures in CT is of interest to physicians and surgeons for surgical planning, disease diagnosis and/or the analysis of fractures or bone/muscle densities. Recently, the issue has been addressed in many research works. However, most studies have focused on only one of the two tissues and on the segmentation of one particular bone or muscle. This work addresses the segmentation of muscle and bone structures in 3D CT volumes. METHODS The proposed bone and muscle segmentation algorithm is based on a three-label convex relaxation approach. The main novelty is that the proposed energy function to be minimized includes distance to histogram models of bone and muscle structures combined with gray-level information. RESULTS 27 CT volumes corresponding to different sections from 20 different patients were manually segmented and used as ground-truth for training and evaluation purposes. Different metrics (Dice index, Jaccard index, Sensitivity, Specificity, Positive Predictive Value, accuracy and computational cost) were computed and compared with those used in some state-of-the art algorithms. The proposed algorithm outperformed the other methods, obtaining a Dice coefficient of 0.88 ± 0.14, a Jaccard index of 0.80 ± 0.19, a Sensitivity of 0.94 ± 0.15 and a Specificity of 0.95 ± 0.04 for bone segmentation, and 0.78 ± 0.12, 0.65 ± 0.16, 0.94 ± 0.04 and 0.95 ± 0.04 for muscle tissue. CONCLUSIONS A fast, generalized method has been presented for segmenting muscle and bone structures in 3D CT volumes using a multilabel continuous convex relaxation approach. The results obtained show that the proposed algorithm outperforms some state-of-the art methods. The algorithm will help physicians and surgeons in surgical planning, disease diagnosis and/or the analysis of fractures or bone/muscle densities.

Validation of a method for retroperitoneal tumor segmentation

PurposeIn 2005, an application for surgical planning called AYRA