Publications

Osteosarcoma is the most common primary bone tumor, and its first line of treatment presents a high failure rate. The 5-year survival for children and teenagers with osteosarcoma is 70% (if diagnosed before it has metastasized) or 20% (if spread at the time of diagnosis), stressing the need for novel therapies. Recently, cold atmospheric plasmas (ionized gases consisting of UV-Vis radiation, electromagnetic fields and a great variety of reactive species) and plasma-treated liquids have been shown to have the potential to selectively eliminate cancer cells in different tumors through an oxidative stress-dependent mechanism. In this work, we review the current state of the art in cold plasma therapy for osteosarcoma. Specifically, we emphasize the mechanisms unveiled thus far regarding the action of plasmas on osteosarcoma. Finally, we review current and potential future approaches, emphasizing the most critical challenges for the development of osteosarcoma therapies based on this emerging technique.

JTD Keywords: cancer stem cells, cold atmospheric plasma, osteosarcoma, oxidative stress, plasma treated liquids, reactive oxygen and nitrogen species, Antineoplastic activity, Antineoplastic agent, Cancer chemotherapy, Cancer stem cell, Cancer stem cells, Cancer surgery, Cancer survival, Cell therapy, Cold atmospheric plasma, Cold atmospheric plasma therapy, Electromagnetism, Human, In vitro study, Intracellular signaling, Oncogene, Osteosarcoma, Oxidative stress, Plasma treated liquids, Reactive nitrogen species, Reactive oxygen and nitrogen species, Reactive oxygen metabolite, Review, Tumor microenvironment

Providing force feedback as relevant information in current Robot-Assisted Minimally Invasive Surgery systems constitutes a technological challenge due to the constraints imposed by the surgical environment. In this context, force estimation techniques represent a potential solution, enabling to sense the interaction forces between the surgical instruments and soft-tissues. Specifically, if visual feedback is available for observing soft-tissues’ deformation, this feedback can be used to estimate the forces applied to these tissues. To this end, a force estimation model, based on Convolutional Neural Networks and Long-Short Term Memory networks, is proposed in this work. This model is designed to process both, the spatiotemporal information present in video sequences and the temporal structure of tool data (the surgical tool-tip trajectory and its grasping status). A series of analyses are carried out to reveal the advantages of the proposal and the challenges that remain for real applications. This research work focuses on two surgical task scenarios, referred to as pushing and pulling tissue. For these two scenarios, different input data modalities and their effect on the force estimation quality are investigated. These input data modalities are tool data, video sequences and a combination of both. The results suggest that the force estimation quality is better when both, the tool data and video sequences, are processed by the neural network model. Moreover, this study reveals the need for a loss function, designed to promote the modeling of smooth and sharp details found in force signals. Finally, the results show that the modeling of forces due to pulling tasks is more challenging than for the simplest pushing actions.

JTD Keywords: Convolutional neural networks, Force estimation, LSTM networks, Robotic surgery

Robotic-assisted minimally invasive surgeries have gained a lot of popularity over conventional procedures as they offer many benefits to both surgeons and patients. Nonetheless, they still suffer from some limitations that affect their outcome. One of them is the lack of force feedback which restricts the surgeon's sense of touch and might reduce precision during a procedure. To overcome this limitation, we propose a novel force estimation approach that combines a vision based solution with supervised learning to estimate the applied force and provide the surgeon with a suitable representation of it. The proposed solution starts with extracting the geometry of motion of the heart's surface by minimizing an energy functional to recover its 3D deformable structure. A deep network, based on a LSTM-RNN architecture, is then used to learn the relationship between the extracted visual-geometric information and the applied force, and to find accurate mapping between the two. Our proposed force estimation solution avoids the drawbacks usually associated with force sensing devices, such as biocompatibility and integration issues. We evaluate our approach on phantom and realistic tissues in which we report an average root-mean square error of 0.02 N.

JTD Keywords: Computer-assisted surgery, Deep networks, Force estimation, Visual deformation

In computer-assisted beating heart surgeries, accurate tracking of the heart's motion is of huge importance and there is a continuous need to eliminate any source of error that might disturb the tracking process. One source of error is the specular reflection that appears on the glossy surface of the heart. In this paper, we propose a robust solution for the detection and removal of specular highlights. A hybrid color attributes and wavelet based edge projection approach is applied to accurately identify the affected regions. These regions are then recovered using a dynamic search-based inpainting with adaptive windowing. Experimental results demonstrate the precision and efficiency of the proposed method. Moreover, it has a real-time performance and can be generalized to various other applications.

JTD Keywords: Heart, Image color analysis, Image edge detection, Surgery, Tracking, Wavelet transforms

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

JTD Keywords: Computer architecture, Estimation, Force, Microprocessors, Robot sensing systems, Surgery

This paper addresses the issue of lack of force feedback in robotic-assisted minimally invasive surgeries. Force is an important measure for surgeons in order to prevent intra-operative complications and tissue damage. Thus, an innovative neuro-vision based force estimation approach is proposed. Tissue surface displacement is first measured via minimization of an energy functional. A neuro approach is then used to establish a geometric-visual relation and estimate the applied force. The proposed approach eliminates the need of add-on sensors, carrying out biocompatibility studies and is applicable to tissues of any shape. Moreover, we provided an improvement from 15.14% to 56.16% over other approaches which demonstrate the potential of our proposal.

JTD Keywords: Estimation, Force, Minimally invasive surgery, Robot sensing systems, Three-dimensional displays

The lack of physiological motion compensation is a major problem in robotic-assisted cardiac surgery. Since the heart is beating while the surgeon carried out the procedure, dexterity of the surgeon’s and precision are compromised. Due to the operative space and the visibility of the surgical field are reduced, the most practical solution is the use of computer vision techniques. The lack of efficiency and robustness of the existing proposals make physiological motion compensation to be considered an open problem. In this work a novel solution to solve this problem based on the minimization of an energy functional is presented. It is described in the three-dimensional space using the l1−regularized optimization class in which cubic b-splines are used to represent the changes produced on the heart surface. Moreover, the logarithmic barrier function is applied to create an approximation of the total energy in order to avoid its non-differentiability. According to the results, this proposal is able to deal with complex deformations, requires a short computational time and gives a small error.

JTD Keywords: Beating heart surgery, Image analysis, Motion compensation

An array with all-solid-state, potentiometric, miniaturized sensors for pH and potassium was developed to be introduced into the stomach or other sectors of the digestive tract by means of flexible endoscopy. These sensors perform continuous and simultaneous measurement of extracellular pH and potassium. This detection seeks to sense ischemia in the gastric mucosa inside the stomach, an event indicative of local microvascular perfusion and tissue oxygenation status. Our array is proposed as a medical tool to identify the occurrence of the ischemia after gastrointestinal or gastroesophageal anastomosis. The stability and feasibility of the miniaturized working and reference electrodes integrated in the array were studied under in vitro conditions, and the behavior of the potassium and pH ion-selective membranes were optimized to work under acidic gastric conditions with high concentrations of HCl. The array was tested in vivo in pigs to measure the ischemia produced by clamping the blood flow into the stomach. Our results indicate that ischemic and reperfusion states can be sensed in vivo and that information on tissue damage can be collected by this sensor array. The device described here provides a miniaturized, inexpensive, and mass producible sensor array for detecting local ischemia caused by unfavorable anastomotic perfusion and will thus contribute to preventing anastomotic leakage and failure caused by tissue necrosis.

JTD Keywords: Endoscopy, Surgery, Tissue, Gastric anastomosis, Gastric conditions, Ion selective sensors, Ischemia, pH detection, Reference electrodes, Simultaneous measurement, Tissue oxygenation, Sensors

Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of l1- and l2-regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the l1-regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

JTD Keywords: Motion Compensation, Optimization, Regularization, Beating Heart Surgery, Ill-posed problem

A connection between two vessels or other tubular structures is known as anastomosis, one of the most common procedures in its field but, at the same time, one of the most complex suture-based techniques. This procedure requires not only a lot of skill and dexterity but also a lot of attention and plenty of concentration from the surgeon. This makes many of the actions to be performed irregularly, exposing the patient to human error resulting from the monotony. On the other hand, the field of robotics has earned itself a place in medicine, especially as assistants during a surgical intervention. Even so, medical robotics is quite young and still has not done much in the field of vessel anastomosis. Therefore, this paper presents a preliminary study of the most common suturing techniques, taking into account their typology and performance, within all the possible anastomosis procedures known. Subsequently, a detailed study of workflow and actions during an anastomosis is made, obtaining a diagram for each of the suturing techniques studied. This allows analyzing all procedures and to create a tool to find those actions and repeated tasks and/or common in all of them, indicating which of these are potential candidates for an automation study. This preliminary work focuses on finding where robotics can help to avoid rutinary tasks, which can be learned in a mechanical level and therefore, relatively easy to be automated using a robotic system or to assist the surgeon in certain tasks that need a lot of skill and attention.

JTD Keywords: Suture, Robot Assisted Surgery, Robot Knotting

This chapter focuses on the use of the finite element method in the design and exploration of spinal implants. Following an introduction to biomechanical alterations of the spine in disease and to spine finite element modelling, focus is placed on different models developed for spine treatment simulations. Despite the hindrance of working thorough representations of in vivo situations, predictions of load transfer within both the implants and the tissues simulated allow improved interpretations of known clinical outcomes, and permit the educated design of new implants. The potential of probabilistic modelling is also discussed in relation to model validation and patient-specific analyses. Finally, the latest developments in the multiphysical modelling of intervertebral discs are presented, revealing a strong potential for the study of implant-based strategies that aim to restore the functional biophysics of the spine.

JTD Keywords: Spinal implant, Finite element modelling, Spine surgery, Spine biomechanics, Tissue mechanobiology

One of the challenges of the robotics community is to develop robots that behave more and more autonomously. Therefore, it is necessary to establish new design criteria, as well as more complex methodologies supporting the analysis of associated risks. The procedure described in this paper includes civil liability as an additional criterion to validate the safety of a surgical robot. In order to understand the concept, a methodology is presented through the description of a simple case. This work aims to establish the basis for a further implementation.

JTD Keywords: Design methodology, Product development, Product liability, Safety, Robotic surgery, Cognitive robotics

Heart motion compensation is a challenging problem within medical robotics and it is still considered an open research area due to the lack of robustness. As it can be formulated as an energy minimization problem, an optimization technique is needed. The selection of an adequate method has a significant impact over the global solution. For this reason, a new methodology is presented here for solving heart motion compensation in which the central topic is oriented to increase robustness with the goal of achieving a balance between efficiency and efficacy. Particularly, genetic algorithms are used as optimization technique since they can be adapted to any real application, complex and oriented to work in real-time problems.

JTD Keywords: Genetic Algorithms, Deformation, Stochastic Optimization, Beating Heart Surgery, Robotic Assisted Surgery

This paper presents a novel teleoperation paradigm, the Virtual Robot (VR), focused on facilitating the surgeon tasks in minimally invasive robotic surgery. The VR has been conceived to increase the range of applicability of traditional master slave teleoperation architectures by means of an automatic cooperative behavior that assigns the execution of the ongoing task to the most suitable robot. From the user's point of view, the VR internal operation must be automatic and transparent. A set of evaluation indexes have been developed to obtain the suitability of each robot as well as an algorithm to determine the optimal instant of time to execute a task transfer. Several experiments demonstrate the usefulness of the VR, as well as indicates the next steps of the research.

JTD Keywords: Cameras, Collision avoidance, Indexes, Joints, Robots, Surgery, Trajectory, Medical robotics, Surgery, Telerobotics, VR internal operation, Automatic cooperative behavior, Evaluation indexes, Master slave teleoperation architectures, Minimally invasive robotic surgery, Task transfer, Virtual robot

Hydrogels are water-insoluble hydrophilic polymers used in a wide range of medical products such as, drug delivery, tissue replacement, heart surgery, gynaecology, ophthalmology, plastic surgery and orthopaedic surgery. These polymers exhibit low toxicity, reduced tissue adherence, and are highly biocompatible. A class of hydrogels, hydrolysed polyacrylonitriles, possess unique shape memory properties, which, when combined with biodurability, mechanical strength and viscoelasticity make them ideal for treating certain degenerative conditions of the spine. Animal and other in vitro studies have shown that the hydrogel is biocompatible and well tolerated by host tissues. This article focuses on two specific indications in spine surgery that demonstrate the potential of hydrogel-based technology to provide significant treatment advantages.

JTD Keywords: Biocompatibility, Degenerative disc disease, Hydrolysed polyacrylonitrile, Minimally invasive surgery, Shape memory hydrogel, Spinal stenosis

Study Design: Clinical series of patients with degenerative disk disease undergoing an endoscopic posterolateral transforaminal procedure that used a reaming foraminoplasty technique to enlarge the foramen coupled with insertion of the B-Twin expandable spacer. Objectives: This retrospective analysis of 107 consecutive patients sought to assess the outcome of this surgical procedure. Summary of Background Data: Reamed endoscopic foraminoplasty under direct endoscopic vision has been shown to be suitable for extremely collapsed disks (> 50% total disk height) despite the difficult access, especially at L5-S1. The authors tried to investigate the efficacy of an expandable spacer being inserted by the endoscopic transforaminal approach to solve foraminal stenosis without bone fusion techniques. Methods: The procedure consists of bone reaming under direct endoscopic control to wide the foramen followed by insertion of the B-Twin expandable device as a disk spacer to restore partially or to maintain the height of the collapsed disk. Outcome measures included visual analog scale (VAS) for pain, the Oswestry Disability Index (ODI) for functional disability, and radioimaging studies. Results: Mean follow-up was 27.2 months. Clinical outcome was considered excellent in 64 patients, good in 25, fair in 10, and poor in 8. Results were similar in single and double B-Twin spacer insertions. Postoperative mean values for VAS and ODI scores improved significantly as compared with preoperative data. Mean VAS and ODI scores were significantly higher in patients with fair or poor results than in those with excellent or good outcome. In 2 cases, clear signs of end plate bone resorption in the control computed tomographic scans at 6 months and 12 months leading to a substantial loss of disk height were documented. Conclusions: This preliminary study has shown the efficacy of an endoscopic surgical technique for the treatment of foraminal stenosis in extremely collapsed disks.

JTD Keywords: Foraminal stenosis, B-twin expandable spacer, Endoscopic foraminoplasty, Minimally invasive surgery, Surgical technique, Spinal spacer, Lumbar, Diskectomy, Fusion, Discectomy

Management of snoring is part of the treatment offered to patients with obstructive sleep apnea syndrome. In patients who do not have this syndrome, however, snoring should be treated according to the severity of the condition. General or specific therapeutic measures should be applied to snorers that have concomitant cardiovascular disease or unrefreshing sleep and in cases in which an individual's snoring disturbs his/her partner's sleep. The present review examines the treatments currently available for snorers and the current state of knowledge regarding each option. It will also focus on the possible indications of these treatments and evaluate their effectiveness.

JTD Keywords: Simple snoring, Treatment, General measures, Surgery

Continuous advances on diagnostic techniques based on medical images, as well as the incorporation of new techniques in surgical instruments are progressively changing the new surgical procedures. Also, new minimally invasive techniques, which are currently highly consolidated, have produced significant advances, both from the technological and from the surgical treatment perspectives. The limitations that the manual realization of surgical interventions implies, in what refers to precision and accessibility, can be tackled with the help of robotics. In the same way, sensor based robot control techniques are opening new possibilities for the introduction of more improvements in these procedures, either relying on teleoperation, in which the surgeon and the robot establish their best synergy to get the optimal results, or by means of the automation of some specific actions or tasks. In this article the effect of robotics in the evolution of surgical techniques is described. Starting with a review of the robotics application fields, the article continues analyzing the methods and technologies involved in the process of robotizing surgical procedures, as well as the surgeon-robot interaction systems.

JTD Keywords: Robotics, Medical Applications, Teleoperation, Biomedical Systems, Computer Aided Surgery, Human-Machine Interaction