9,090 research outputs found
Computer- and robot-assisted Medical Intervention
Medical robotics includes assistive devices used by the physician in order to
make his/her diagnostic or therapeutic practices easier and more efficient.
This chapter focuses on such systems. It introduces the general field of
Computer-Assisted Medical Interventions, its aims, its different components and
describes the place of robots in that context. The evolutions in terms of
general design and control paradigms in the development of medical robots are
presented and issues specific to that application domain are discussed. A view
of existing systems, on-going developments and future trends is given. A
case-study is detailed. Other types of robotic help in the medical environment
(such as for assisting a handicapped person, for rehabilitation of a patient or
for replacement of some damaged/suppressed limbs or organs) are out of the
scope of this chapter.Comment: Handbook of Automation, Shimon Nof (Ed.) (2009) 000-00
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
Robot Autonomy for Surgery
Autonomous surgery involves having surgical tasks performed by a robot
operating under its own will, with partial or no human involvement. There are
several important advantages of automation in surgery, which include increasing
precision of care due to sub-millimeter robot control, real-time utilization of
biosignals for interventional care, improvements to surgical efficiency and
execution, and computer-aided guidance under various medical imaging and
sensing modalities. While these methods may displace some tasks of surgical
teams and individual surgeons, they also present new capabilities in
interventions that are too difficult or go beyond the skills of a human. In
this chapter, we provide an overview of robot autonomy in commercial use and in
research, and present some of the challenges faced in developing autonomous
surgical robots
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Getting the best outcomes from epilepsy surgery.
Neurosurgery is an underutilized treatment that can potentially cure drug-refractory epilepsy. Careful, multidisciplinary presurgical evaluation is vital for selecting patients and to ensure optimal outcomes. Advances in neuroimaging have improved diagnosis and guided surgical intervention. Invasive electroencephalography allows the evaluation of complex patients who would otherwise not be candidates for neurosurgery. We review the current state of the assessment and selection of patients and consider established and novel surgical procedures and associated outcome data. We aim to dispel myths that may inhibit physicians from referring and patients from considering neurosurgical intervention for drug-refractory focal epilepsies. Ann Neurol 2018;83:676-690
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
Proof of Concept: Wearable Augmented Reality Video See-Through Display for Neuro-Endoscopy
In mini-invasive surgery and in endoscopic procedures, the surgeon operates without a direct visualization of the patient’s anatomy. In image-guided surgery, solutions based on wearable augmented reality (AR) represent the most promising ones. The authors describe the characteristics that an ideal Head Mounted Display (HMD) must have to guarantee safety and accuracy in AR-guided neurosurgical interventions and design the ideal virtual content for guiding crucial task in neuro endoscopic surgery. The selected sequence of AR content to obtain an effective guidance during surgery is tested in a Microsoft Hololens based app
A new head-mounted display-based augmented reality system in neurosurgical oncology: a study on phantom
Purpose: Benefits of minimally invasive neurosurgery mandate the development of ergonomic paradigms for neuronavigation. Augmented Reality (AR) systems can overcome the shortcomings of commercial neuronavigators. The aim of this work is to apply a novel AR system, based on a head-mounted stereoscopic video see-through display, as an aid in complex neurological lesion targeting. Effectiveness was investigated on a newly designed patient-specific head mannequin featuring an anatomically realistic brain phantom with embedded synthetically created tumors and eloquent areas. Materials and methods: A two-phase evaluation process was adopted in a simulated small tumor resection adjacent to Brocaâ\u80\u99s area. Phase I involved nine subjects without neurosurgical training in performing spatial judgment tasks. In Phase II, three surgeons were involved in assessing the effectiveness of the AR-neuronavigator in performing brain tumor targeting on a patient-specific head phantom. Results: Phase I revealed the ability of the AR scene to evoke depth perception under different visualization modalities. Phase II confirmed the potentialities of the AR-neuronavigator in aiding the determination of the optimal surgical access to the surgical target. Conclusions: The AR-neuronavigator is intuitive, easy-to-use, and provides three-dimensional augmented information in a perceptually-correct way. The system proved to be effective in guiding skin incision, craniotomy, and lesion targeting. The preliminary results encourage a structured study to prove clinical effectiveness. Moreover, our testing platform might be used to facilitate training in brain tumour resection procedures
Advanced cranial navigation
Neurosurgery is performed with extremely low margins of error. Surgical inaccuracy may
have disastrous consequences. The overall aim of this thesis was to improve accuracy in
cranial neurosurgical procedures by the application of new technical aids. Two technical
methods were evaluated: augmented reality (AR) for surgical navigation (Papers I-II) and the
optical technique of diffuse reflectance spectroscopy (DRS) for real-time tissue identification
(Papers III-V).
Minimally invasive skull-base endoscopy has several potential benefits compared to
traditional craniotomy, but approaching the skull base through this route implies that at-risk
organs and surgical targets are covered by bone and out of the surgeon’s direct line of sight.
In Paper I, a new application for AR-navigated endoscopic skull-base surgery, based on an
augmented-reality surgical navigation (ARSN) system, was developed. The accuracy of the
system, defined by mean target registration error (TRE), was evaluated and found to be
0.55±0.24 mm, the lowest value reported error in the literature.
As a first step toward the development of a cranial application for AR
navigation, in Paper II this ARSN system was used to enable insertions of biopsy needles
and external ventricular drainages (EVDs). The technical accuracy (i.e., deviation from the
target or intended path) and efficacy (i.e., insertion time) were assessed on a 3D-printed
realistic, anthropomorphic skull and brain phantom; Thirty cranial biopsies and 10 EVD
insertions were performed. Accuracy for biopsy was 0.8±0.43 mm with a median insertion
time of 149 (87-233) seconds, and for EVD accuracy was 2.9±0.8 mm at the tip with a median
angular deviation of 0.7±0.5° and a median insertion time of 188 (135-400) seconds.
Glial tumors grow diffusely in the brain, and patient survival is correlated with
the extent of tumor removal. Tumor borders are often invisible. Resection beyond borders as
defined by conventional methods may further improve a patient’s prognosis. In Paper III,
DRS was evaluated for discrimination between glioma and normal brain tissue ex vivo. DRS
spectra and histology were acquired from 22 tumor samples and 9 brain tissue samples
retrieved from 30 patients. Sensitivity and specificity for the detection of low-grade gliomas
were 82.0% and 82.7%, respectively, with an AUC of 0.91.
Acute ischemic stroke caused by large vessel occlusion is treated with
endovascular thrombectomy, but treatment failure can occur when clot composition and
thrombectomy technique are mismatched. Intra-procedural knowledge of clot composition
could guide the choice of treatment modality. In Paper IV, DRS, in vivo, was evaluated for
intravascular clot characterization. Three types of clot analogs, red blood cell (RBC)-rich,
fibrin-rich and mixed clots, were injected into the external carotids of a domestic pig. An
intravascular DRS probe was used for in-situ measurements of clots, blood, and vessel walls,
and the spectral data were analyzed. DRS could differentiate clot types, vessel walls, and
blood in vivo (p<0,001). The sensitivity and specificity for detection were 73.8% and 98.8%
for RBC clots, 100% and 100% for mixed clots, and 80.6% and 97.8% for fibrin clots,
respectively.
Paper V evaluated DRS for characterization of human clot composition ex
vivo: 45 clot units were retrieved from 29 stroke patients and examined with DRS and
histopathological evaluation. DRS parameters correlated with clot RBC fraction (R=81,
p<0.001) and could be used for the classification of clot type with sensitivity and specificity
rates for the detection of RBC-rich clots of 0.722 and 0.846, respectively. Applied in an
intravascular probe, DRS may provide intra-procedural information on clot composition to
improve endovascular thrombectomy efficiency
Intraoperative detection of blood vessels with an imaging needle during neurosurgery in humans
Intracranial hemorrhage can be a devastating complication associated with needle biopsies of the brain. Hemorrhage can occur to vessels located adjacent to the biopsy needle as tissue is aspirated into the needle and removed. No intraoperative technology exists to reliably identify blood vessels that are at risk of damage. To address this problem, we developed an “imaging needle” that can visualize nearby blood vessels in real time. The imaging needle contains a miniaturized optical coherence tomography probe that allows differentiation of blood flow and tissue. In 11 patients, we were able to intraoperatively detect blood vessels (diameter, \u3e500 μm) with a sensitivity of 91.2% and a specificity of 97.7%. This is the first reported use of an optical coherence tomography needle probe in human brain in vivo. These results suggest that imaging needles may serve as a valuable tool in a range of neurosurgical needle interventions
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