5,370 research outputs found
In vivo measurement of human brain elasticity using a light aspiration device
The brain deformation that occurs during neurosurgery is a serious issue
impacting the patient "safety" as well as the invasiveness of the brain
surgery. Model-driven compensation is a realistic and efficient solution to
solve this problem. However, a vital issue is the lack of reliable and easily
obtainable patient-specific mechanical characteristics of the brain which,
according to clinicians' experience, can vary considerably. We designed an
aspiration device that is able to meet the very rigorous sterilization and
handling process imposed during surgery, and especially neurosurgery. The
device, which has no electronic component, is simple, light and can be
considered as an ancillary instrument. The deformation of the aspirated tissue
is imaged via a mirror using an external camera. This paper describes the
experimental setup as well as its use during a specific neurosurgery. The
experimental data was used to calibrate a continuous model. We show that we
were able to extract an in vivo constitutive law of the brain elasticity: thus
for the first time, measurements are carried out per-operatively on the
patient, just before the resection of the brain parenchyma. This paper
discloses the results of a difficult experiment and provide for the first time
in-vivo data on human brain elasticity. The results point out the softness as
well as the highly non-linear behavior of the brain tissue.Comment: Medical Image Analysis (2009) accept\'
Hacia el modelado 3d de tumores cerebrales mediante endoneurosonografía y redes neuronales
Las cirugías mínimamente invasivas se han vuelto populares debido a que implican menos riesgos con respecto a las intervenciones tradicionales. En neurocirugía, las tendencias recientes sugieren el uso conjunto de la endoscopia y el ultrasonido, técnica llamada endoneurosonografía (ENS), para la virtualización 3D de las estructuras del cerebro en tiempo real. La información ENS se puede utilizar para generar modelos 3D de los tumores del cerebro durante la cirugía. En este trabajo, presentamos una metodología para el modelado 3D de tumores cerebrales con ENS y redes neuronales. Específicamente, se estudió el uso de mapas auto-organizados (SOM) y de redes neuronales tipo gas (NGN). En comparación con otras técnicas, el modelado 3D usando redes neuronales ofrece ventajas debido a que la morfología del tumor se codifica directamente sobre los pesos sinápticos de la red, no requiere ningún conocimiento a priori y la representación puede ser desarrollada en dos etapas: entrenamiento fuera de línea y adaptación en línea. Se realizan pruebas experimentales con maniquíes médicos de tumores cerebrales. Al final del documento, se presentan los resultados del modelado 3D a partir de una base de datos ENS.Minimally invasive surgeries have become popular because they reduce the typical risks of traditional interventions. In neurosurgery, recent trends suggest the combined use of endoscopy and ultrasound (endoneurosonography or ENS) for 3D virtualization of brain structures in real time. The ENS information can be used to generate 3D models of brain tumors during a surgery. This paper introduces a methodology for 3D modeling of brain tumors using ENS and unsupervised neural networks. The use of self-organizing maps (SOM) and neural gas networks (NGN) is particularly studied. Compared to other techniques, 3D modeling using neural networks offers advantages, since tumor morphology is directly encoded in synaptic weights of the network, no a priori knowledge is required, and the representation can be developed in two stages: off-line training and on-line adaptation. Experimental tests were performed using virtualized phantom brain tumors. At the end of the paper, the results of 3D modeling from an ENS database are presented
Framework for a low-cost intra-operative image-guided neuronavigator including brain shift compensation
In this paper we present a methodology to address the problem of brain tissue
deformation referred to as 'brain-shift'. This deformation occurs throughout a
neurosurgery intervention and strongly alters the accuracy of the
neuronavigation systems used to date in clinical routine which rely solely on
pre-operative patient imaging to locate the surgical target, such as a tumour
or a functional area. After a general description of the framework of our
intra-operative image-guided system, we describe a procedure to generate
patient specific finite element meshes of the brain and propose a biomechanical
model which can take into account tissue deformations and surgical procedures
that modify the brain structure, like tumour or tissue resection
Position-based Dynamics Simulator of Brain Deformations for Path Planning and Intra-Operative Control in Keyhole Neurosurgery
Many tasks in robot-assisted surgery require planning and controlling
manipulators' motions that interact with highly deformable objects. This study
proposes a realistic, time-bounded simulator based on Position-based Dynamics
(PBD) simulation that mocks brain deformations due to catheter insertion for
pre-operative path planning and intra-operative guidance in keyhole surgical
procedures. It maximizes the probability of success by accounting for
uncertainty in deformation models, noisy sensing, and unpredictable actuation.
The PBD deformation parameters were initialized on a parallelepiped-shaped
simulated phantom to obtain a reasonable starting guess for the brain white
matter. They were calibrated by comparing the obtained displacements with
deformation data for catheter insertion in a composite hydrogel phantom.
Knowing the gray matter brain structures' different behaviors, the parameters
were fine-tuned to obtain a generalized human brain model. The brain
structures' average displacement was compared with values in the literature.
The simulator's numerical model uses a novel approach with respect to the
literature, and it has proved to be a close match with real brain deformations
through validation using recorded deformation data of in-vivo animal trials
with a mean mismatch of 4.732.15%. The stability, accuracy, and real-time
performance make this model suitable for creating a dynamic environment for KN
path planning, pre-operative path planning, and intra-operative guidance.Comment: 8 pages, 8 figures. This article has been accepted for publication in
a future issue of IEEE Robotics and Automation Letters, but has not been
fully edited. Content may change prior to final publication. 2377-3766 (c)
2021 IEEE. Personal use is permitted, but republication/redistribution
requires IEEE permission. A. Segato and C. Di Vece equally contribute
A Novel Bio-Inspired Insertion Method for Application to Next Generation Percutaneous Surgical Tools
The use of minimally invasive techniques can dramatically improve patient outcome from neurosurgery, with less risk, faster recovery, and better cost effectiveness when compared to conventional surgical intervention. To achieve this, innovative surgical techniques and new surgical instruments have been developed. Nevertheless, the simplest and most common interventional technique for brain surgery is needle insertion for either diagnostic or therapeutic purposes.
The work presented in this thesis shows a new approach to needle insertion into soft tissue, focussing on soft tissue-needle interaction by exploiting microtextured topography and the unique mechanism of a reciprocating motion inspired by the ovipositor of certain parasitic wasps. This thesis starts by developing a brain-like phantom which I was shown to have mechanical properties similar to those of neurological tissue during needle insertion. Secondly, a proof-of-concept of the bio-inspired insertion method was undertaken. Based on this finding, the novel method of a multi-part probe able to penetrate a soft substrate by reciprocal motion of each segment is derived. The advantages of the new insertion method were investigated and compared with a conventional needle insertion in terms of needle-tissue interaction. The soft tissue deformation and damage were also measured by exploiting the method of particle image velocimetry. Finally, the thesis proposes the possible clinical application of a biologically-inspired surface topography for deep brain electrode implantation.
As an adjunct to this work, the reciprocal insertion method described here fuelled the research into a novel flexible soft tissue probe for percutaneous intervention, which is able to steer along curvilinear trajectories within a compliant medium. Aspects of this multi-disciplinary research effort on steerable robotic surgery are presented, followed by a discussion of the implications of these findings within the context of future work
A method for the assessment of time-varying brain shift during navigated epilepsy surgery
Image guidance is widely used in neurosurgery. Tracking systems (neuronavigators) allow registering the preoperative image space to the surgical space. The localization accuracy is influenced by technical and clinical factors, such as brain shift. This paper aims at providing quantitative measure of the time-varying brain shift during open epilepsy surgery, and at measuring the pattern of brain deformation with respect to three potentially meaningful parameters: craniotomy area, craniotomy orientation and gravity vector direction in the images reference frame
A surface registration approach for video-based analysis of intraoperative brain surface deformations.
Anatomical intra operative deformation is a major limitation of accuracy in image guided neurosurgery. Approaches to quantify these deforamations based on 3D reconstruction of surfaces have been introduced. For accurate quantification of surface deformation, a robust surface registration method is required. In this paper,
we propose a new surface registration for video-based analysis of intraoperative brain deformations. This registration method includes three terms: the first term is related to image intensities, the second to Euclidean distance and the third to anatomical landmarks continuously tracked in 2D video. This new surface registration method can be used with any cortical surface textured point cloud computed by stereoscopic or laser range approaches. We have shown the global method, including textured point cloud
reconstruction, had a precision within 2 millimeters, which is within the usual rigid registration error of the neuronavigation system before deformations
Doctor of Philosophy
dissertationThe cerebrovasculature is vital in maintaining health in the brain, but can be damaged by traumatic brain injury (TBI). Even in cases without hemorrhage, vessels are deformed with the surrounding tissue. Subfailure deformation could result in altered mechanical properties and dysfunction of these vessels. This dissertation aims to provide a better understanding of the biaxial mechanical properties of cerebral arteries, as well as determine mechanical stretch thresholds which produce ultimate failure and subfailure alteration of mechanical properties or vessel function. Three in vitro studies were undertaken. Passive biaxial mechanical properties under physiological loading, as well as failure properties of rat middle cerebral arteries (MCAs), were measured and compared to those of human pial arteries. Best fit parameters for a Fung type strain energy function are provided for the biaxial mechanical properties. Rat MCAs are stiffer in the axial direction than the circumferential, but less stiff in both directions than human arteries. Rat MCAs also exhibit a lower ultimate failure stress but higher failure stretch. The effect of subfailure axial overstretch on the contractile behavior of smooth muscle cells (SMCs) in rat MCAs was investigated. Potassium dose response tests were conducted before and after a single axial overstretch, with varying magnitude and strain rate. Overstretches beyond a threshold of both magnitude and strain rate significantly reduced SMC contraction relative to time-matched controls, mirrored by an increase in potassium concentration required to evoke the half maximal contraction. The effect of subfailure axial overstretch on passive mechanical properties in sheep MCAs was investigated. Axial response was measured before and after a single quasi-static overstretch of various magnitudes. Post-overstretch, samples showed persistent softening (lower stress values at a given level of stretch). Softening was only observed above an overstretch threshold, and then increased with overstretch severity until a second threshold was reached, above which softening did not increase until failure. This dissertation provides improved understanding of cerebrovascular mechanics and relationships between such data acquired from animals and humans. It also provides insight into the potential role of subfailure cerebrovascular damage in disease states associated with TBI, such as second impact syndrome and strok
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