Neurosurgery and brain shift: review of the state of the art and main contributions of robotics

Este artículo presenta una revisión acerca de la neurocirugía, los asistentes robóticos en este tipo de procedimiento, y el tratamiento que se le da al problema del desplazamiento que sufre el tejido cerebral, incluyendo las técnicas para la obtención de imágenes médicas. Se abarca de manera especial el fenómeno del desplazamiento cerebral, comúnmente conocido como brain shift, el cual causa pérdida de referencia entre las imágenes preoperatorias y los volúmenes a tratar durante la cirugía guiada por imágenes médicas. Hipotéticamente, con la predicción y corrección del brain shift sobre el sistema de neuronavegación, se podrían planear y seguir trayectorias de mínima invasión, lo que conllevaría a minimizar el daño a los tejidos funcionales y posiblemente a reducir la morbilidad y mortalidad en estos delicados y exigentes procedimientos médicos, como por ejemplo, en la extirpación de un tumor cerebral. Se mencionan también otros inconvenientes asociados a la neurocirugía y se muestra cómo los sistemas robotizados han ayudado a solventar esta problemática. Finalmente se ponen en relieve las perspectivas futuras de esta rama de la medicina, la cual desde muchas disciplinas busca tratar las dolencias del principal órgano del ser humano.This paper presents a review about neurosurgery, robotic assistants in this type of procedure, and the approach to the problem of brain tissue displacement, including techniques for obtaining medical images. It is especially focused on the phenomenon of brain displacement, commonly known as brain shift, which causes a loss of reference between the preoperative images and the volumes to be treated during image-guided surgery. Hypothetically, with brain shift prediction and correction for the neuronavigation system, minimal invasion trajectories could be planned and shortened. This would reduce damage to functional tissues and possibly lower the morbidity and mortality in delicate and demanding medical procedures such as the removal of a brain tumor. This paper also mentions other issues associated with neurosurgery and shows the way robotized systems have helped solve these problems. Finally, it highlights the future perspectives of neurosurgery, a branch of medicine that seeks to treat the ailments of the main organ of the human body from the perspective of many disciplines

Comparison of the Effectiveness of Two Types of Single Port Minimal Invasive Neurosurgical Robots to Ablation and Resection of Brain Tumor

Background: Using minimally invasive neurosurgical robots is one of the most desirable ablation methods and resection of brain tumors. In this study, forward kinematics and Jacobian matrix calculated for two single-port robots for comparing the effectiveness of two types of single port minimal invasive surgical robots to ablation and resection of brain tumorMethods: The motion analysis of robots type 1 and 2 has compared to each other. Ablation manipulator in robot type 1 has five degrees of freedom, but in robot type 2, three revolute degrees of freedom of this manipulator has replaced with a revolute joint perpendicular to the previous three revolute joints.Results: Results showed that for resection surgery, in the same conditions, robot type 2 damaged 58.9 mm3 more of cerebral cortex tissue than robot type 1 to resect the brain tumors. To establish a static balance, robot type 2 needs to tolerate at least 41% more internal loading than robot type 1. The maximum velocity for robot type 1 in the contact location between the end-effector and the tumor is 1.7 times more than robot type 2. The maximum end-effector force of robot type 1 to apply the tumor for ablation surgery is more than 1.8 times in robot type 2, but the maximum moment and power for ablation surgery and resection of these two robots were the same less than 1% difference.Conclusion: Despite the more straightforward mechanism, a minimum number of joints, and better kinematics range of robot type 2, robot types 1 has the possibility for transformation, establishes the static balancing, and does a better ablation surgery with less damage to the brain

Transoral Robotic Surgery Applied to the Skull Base

Skull base surgery has been developed with transsphenoidal approaches to reach the sella and especially the pituitary tumors. Transnasal endoscopic technique has become the gold standard for many years. Indeed, the intraoperative view with specific endoscope is very good, and thus the gross total of pituitary adenomas removal rates have been increased. Nevertheless, why has not this technique been challenged, especially given the potential rhinologic side effects and 2D vision? Robotic surgery with the da Vinci system is now well known all over the world. Transoral robotic surgery (TORS) is also commonly used in head and neck cancer with satisfying results. In this ENT approach, the da Vinci videoendoscope looks downward; we had the idea to place it behind the hard palate in order to look upward. Therefore, from cadaveric studies to clinical “première mondiale,” we developed an innovative TORS to reach the sella and to remove pituitary tumors

Intraoperative Image Guidance in Neurosurgery: Development, Current Indications, and Future Trends

Introduction. As minimally invasive surgery becomes the standard of care in neurosurgery, it is imperative that surgeons become skilled in the use of image-guided techniques. The development of image-guided neurosurgery represents a substantial improvement in the microsurgical treatment of tumors, vascular malformations, and other intracranial lesions. Objective. There have been numerous advances in neurosurgery which have aided the neurosurgeon to achieve accurate removal of pathological tissue with minimal disruption of surrounding healthy neuronal matter including the development of microsurgical, endoscopic, and endovascular techniques. Neuronavigation systems and intraoperative imaging should improve success in cranial neurosurgery. Additional functional imaging modalities such as PET, SPECT, DTI (for fiber tracking), and fMRI can now be used in order to reduce neurological deficits resulting from surgery; however the positive long-term effect remains questionable for many indications. Method. PubMed database search using the search term “image guided neurosurgery.” More than 1400 articles were published during the last 25 years. The abstracts were scanned for prospective comparative trials. Results and Conclusion. 14 comparative trials are published. To date significant data amount show advantages in intraoperative accuracy influencing the perioperative morbidity and long-term outcome only for cerebral glioma surgery

Robotically Steered Needles: A Survey of Neurosurgical Applications and Technical Innovations

This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue shift estimation through imaging scans acquired during the procedure, and simulation-based prediction. Neurosurgical scenarios tend to emphasize straight needles so far, and span deep-brain stimulation (DBS), stereoelectroencephalography (SEEG), intracerebral drug delivery (IDD), stereotactic brain biopsy (SBB), stereotactic needle aspiration for hematoma, cysts and abscesses, and brachytherapy as well as thermal ablation of brain tumors and seizure-generating regions. We emphasize therapeutic considerations and complications that have been documented in conjunction with these applications

Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning

Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor surgery for malignant invasive brain tumors because of its subcellular dimension resolution. Despite its promising diagnostic potential, interpreting the gray tone fluorescence images can be difficult for untrained users. In this review, we provide a detailed description of bioinformatical analysis methodology of CLE images that begins to assist the neurosurgeon and pathologist to rapidly connect on-the-fly intraoperative imaging, pathology, and surgical observation into a conclusionary system within the concept of theranostics. We present an overview and discuss deep learning models for automatic detection of the diagnostic CLE images and discuss various training regimes and ensemble modeling effect on the power of deep learning predictive models. Two major approaches reviewed in this paper include the models that can automatically classify CLE images into diagnostic/nondiagnostic, glioma/nonglioma, tumor/injury/normal categories and models that can localize histological features on the CLE images using weakly supervised methods. We also briefly review advances in the deep learning approaches used for CLE image analysis in other organs. Significant advances in speed and precision of automated diagnostic frame selection would augment the diagnostic potential of CLE, improve operative workflow and integration into brain tumor surgery. Such technology and bioinformatics analytics lend themselves to improved precision, personalization, and theranostics in brain tumor treatment.Comment: See the final version published in Frontiers in Oncology here: https://www.frontiersin.org/articles/10.3389/fonc.2018.00240/ful

DESIGN, DEVELOPMENT, AND EVALUATION OF A MRI-GUIDED NEUROSURGICAL INTRACRANIAL ROBOT

Brain tumors are among the most feared complications of cancer. Their treatment is challenging because of the lack of good imaging modality and the inability to remove the complete tumor. To overcome this limitation, we propose to develop a Magnetic Resonance Imaging (MRI)-compatible neurosurgical robot. The robot can be operated under continuous MRI, and the Magnetic Resonance (MR) images can be used to supplement physicians' visual capabilities, resulting in precise tumor removal. We have developed two prototypes of the Minimally Invasive Neurosurgical Intracranial Robot (MINIR) using MRI compatible materials and shape memory alloy (SMA) actuators. The major difference between the two robots is that one uses SMA wire actuators and the other uses SMA spring actuators combined with the tendon-sheath mechanism. Due to space limitation inside the robot body and the strong magnetic field in the MRI scanner, most sensors cannot be used inside the robot body. Hence, one possible approach is to rely on image feedback to control the motion of the robot. In this research, as a preliminary approach, we have relied on image feedback from a camera to control the motion of the robot. Since the image tracking algorithm may fail in some situations, we also developed a temperature feedback control scheme which served as a backup controller for the robot. Experimental results demonstrated that both image feedback and temperature feedback can be used reliably to control the joint motion of the robots. A series of MRI compatibility tests were performed to evaluate the MRI compatibility of the robots and to assess the degradation in image quality. The experimental results demonstrated that the robots are MRI compatible and created no significant image distortion in the MR images during actuation. The accomplishments presented in this dissertation represent a significant development of using SMA actuators to actuate MRI-compatible robots. It is anticipated that, in the future, continuous MR imaging would be used reliably to control the motion of the robot. It is aspired that the robot design and the control methods of SMA actuators developed in this research can be utilized in practical applications

Intraoperative Navigation Systems for Image-Guided Surgery

Recent technological advancements in medical imaging equipment have resulted in a dramatic improvement of image accuracy, now capable of providing useful information previously not available to clinicians. In the surgical context, intraoperative imaging provides a crucial value for the success of the operation. Many nontrivial scientific and technical problems need to be addressed in order to efficiently exploit the different information sources nowadays available in advanced operating rooms. In particular, it is necessary to provide: (i) accurate tracking of surgical instruments, (ii) real-time matching of images from different modalities, and (iii) reliable guidance toward the surgical target. Satisfying all of these requisites is needed to realize effective intraoperative navigation systems for image-guided surgery. Various solutions have been proposed and successfully tested in the field of image navigation systems in the last ten years; nevertheless several problems still arise in most of the applications regarding precision, usability and capabilities of the existing systems. Identifying and solving these issues represents an urgent scientific challenge. This thesis investigates the current state of the art in the field of intraoperative navigation systems, focusing in particular on the challenges related to efficient and effective usage of ultrasound imaging during surgery. The main contribution of this thesis to the state of the art are related to: Techniques for automatic motion compensation and therapy monitoring applied to a novel ultrasound-guided surgical robotic platform in the context of abdominal tumor thermoablation. Novel image-fusion based navigation systems for ultrasound-guided neurosurgery in the context of brain tumor resection, highlighting their applicability as off-line surgical training instruments. The proposed systems, which were designed and developed in the framework of two international research projects, have been tested in real or simulated surgical scenarios, showing promising results toward their application in clinical practice