Surgical declarative knowledge learning: concept and acceptability study.

Improving surgical training by means of technology assistance is an important challenge that aims to directly impact surgical quality. Surgical training includes the acquisition of two categories of knowledge: declarative knowledge (i.e. 'knowing what') and procedural knowledge (i.e. 'knowing how'). It is essential to acquire both before performing any particular surgery. There are currently many tools for acquiring procedural knowledge, such as simulators. However, few approaches or tools allow a trainer to formalize and record surgical declarative knowledge, and a trainee to have easy access to it. In this paper, we propose an approach for structuring surgical declarative knowledge according to procedural knowledge and based on surgical process modeling. A dedicated software application has been implemented. We evaluated the concept and the software usability on two procedures with different medical populations: endoscopic third ventriculostomy involving 6 neurosurgeons and preparation of a surgical table for craniotomy involving 4 scrub nurses. The results of both studies show that surgical process models could be a well-adapted approach for structuring and visualizing surgical declarative knowledge. The software application was perceived by neurosurgeons and scrub nurses as an innovative tool for managing and presenting surgical knowledge. The preliminary results show that the feasibility of the proposed approach and the acceptability and usability of the corresponding software. Future experiments will study impact of such an approach on knowledge acquisition.

Impact of the complexity of surgical procedures and intraoperative interruptions on neurosurgical team workload.

BACKGROUND: Neurosurgical teams are exposed to various stressors: complexity of surgical procedures, environment, time pressure and interruptions contribute to increasing the perceived workload. OBJECTIVE: This study aimed to evaluate the impact of interruptions and surgical complexity on neurosurgical team workload. METHODS: A prospective observational study was conducted on thirty surgical procedures of graduated complexity recorded in our Department of Neurosurgery. A scale was created and used by neurosurgeons to evaluate the perceived complexity of the surgical procedure. Interruptions and severity of interruptions were noted. The workloads of the neurosurgeon, surgical assistant, scrub nurse and circulating nurse were measured on the Surgery Task Load Index (SURG-TLX) at the end of the procedure. RESULTS: A mean 24.6 interruptions per hour were recorded. The mean interference level of the interruptions was 3.5/7. Mean surgical complexity was 4.3/10. Mean sterile team workload was 43.4/100. The multiple linear regression model showed that sterile team workload increased with surgical complexity (ß=6.692, P=.0002) but decreased in spite of increases in the number of interruptions per hour (ß=-0.855, P=.027). Neurosurgeon and surgical assistant workload increased with surgical complexity (ß=11.53, P<0.0001 and ß=7.42, P=0.0007, respectively). Scrub nurse workload decreased in spite of increases in the number of interruptions per hour (ß=-1.11, P=.026). CONCLUSION: Our study suggests positive effects of some interruptions during elective neurosurgical procedures with strong team familiarity.

Postural instability and gait disorders after subthalamic nucleus deep brain stimulation in Parkinson's disease: a PET study.

INTRODUCTION: Patients with Parkinson's disease sometimes report postural instability and gait disorders (PIGD) after subthalamic nucleus deep brain stimulation (STN-DBS). Whether this is the direct consequence of DBS or the result of natural disease progression is still subject to debate. OBJECTIVE: To compare changes in brain metabolism during STN-DBS between patients with and without PIGD after surgery. METHODS: We extracted consecutive patients from a database where all Rennes Hospital patients undergoing STN-DBS are registered, with regular prospective updates of their clinical data. Patients were divided into two groups (PIGD and No PIGD) according to changes after surgery, as measured with a composite score based on the selected Unified Parkinson's Disease Rating Scale items. All patients underwent positron emission tomography with 18[F]-fluorodeoxyglucose 3 months before and after surgery. We ran an ANOVA with two factors (group: PIGD vs. No PIGD; and phase: preoperative vs. postoperative) on SPM8 to compare changes in brain metabolism between the two groups. RESULTS: Participants were 56 patients, including 10 in the PIGD group. The two groups had similar baseline (i.e., before surgery) characteristics. We found two clusters of increased metabolism in the PIGD group relative to the No PIGD group: dorsal midbrain/pons, including locomotor mesencephalic region and reticular pontine formation, and right motor cerebellum. CONCLUSION: We found different metabolic changes during DBS-STN among patients with PIGD, concerning brain regions that are already known to be involved in gait disorders in Parkinson's disease, suggesting that DBS is responsible for the appearance of PIGD.

Comparative validation of single-shot optical techniques for laparoscopic 3-D surface reconstruction.

Intra-operative imaging techniques for obtaining the shape and morphology of soft-tissue surfaces in vivo are a key enabling technology for advanced surgical systems. Different optical techniques for 3-D surface reconstruction in laparoscopy have been proposed, however, so far no quantitative and comparative validation has been performed. Furthermore, robustness of the methods to clinically important factors like smoke or bleeding has not yet been assessed. To address these issues, we have formed a joint international initiative with the aim of validating different state-of-the-art passive and active reconstruction methods in a comparative manner. In this comprehensive in vitro study, we investigated reconstruction accuracy using different organs with various shape and texture and also tested reconstruction robustness with respect to a number of factors like the pose of the endoscope as well as the amount of blood or smoke present in the scene. The study suggests complementary advantages of the different techniques with respect to accuracy, robustness, point density, hardware complexity and computation time. While reconstruction accuracy under ideal conditions was generally high, robustness is a remaining issue to be addressed. Future work should include sensor fusion and in vivo validation studies in a specific clinical context. To trigger further research in surface reconstruction, stereoscopic data of the study will be made publically available at www.open-CAS.com upon publication of the paper.

A cognitive engineering framework for the specification of information requirements in medical imaging: application in image-guided neurosurgery.

PURPOSE: This study proposes a framework coming from cognitive engineering, which makes it possible to define what information content has to be displayed or emphasised from medical imaging, for assisting clinicians according to their level of expertise in the domain. METHOD: We designed a rating scale to assess visualisation systems in image-guided neurosurgery with respect to the depiction of the neurosurgical work domain. This rating scale was based on a neurosurgical work domain analysis. This scale has been used to evaluate visualisation modes among neurosurgeons, residents and engineers. We asked five neurosurgeons, ten medical residents and ten engineers to rate two visualisation modes from the same data (2D MR image vs. 3D computerised image). With this method, the amount of abstract and concrete work domain information displayed by each visualisation mode can be measured. RESULTS: A global difference in quantities of perceived information between both images was observed. Surgeons and medical residents perceived significantly more information than engineers for both images. Unlike surgeons, however, the amount of information perceived by residents and engineers significantly decreased as information abstraction increased. CONCLUSIONS: We demonstrated the possibility of measuring the amount of work domain information displayed by different visualisation modes of medical imaging according to different user profiles. Engineers in charge of the design of medical image-guided surgical systems did not perceive the same set of information as surgeons or even medical residents. This framework can constitute a user-oriented approach to evaluate the amount of perceived information from image-guided surgical systems and support their design from a cognitive engineering point of view.

Augmented environments for minimally invasive therapy: implementation barriers from technology to practice.

Augmented environments for medical applications have been explored and developed in an effort to enhance the clinician's view of anatomy and facilitate the performance of minimally invasive procedures. These environments must faithfully represent the real surgical field and require seamless integration of pre- and intra-operative imaging, surgical instrument tracking and display technology into a common framework centered around the patient. However, few image guidance environments have been successfully translated into clinical use. Several challenges that contribute to the slow progress of integrating such environments into clinical practice are discussed here in terms of both technical and clinical limitations.

A framework for the recognition of high-level surgical tasks from video images for cataract surgeries.

The need for a better integration of the new generation of computer-assisted-surgical systems has been recently emphasized. One necessity to achieve this objective is to retrieve data from the operating room (OR) with different sensors, then to derive models from these data. Recently, the use of videos from cameras in the OR has demonstrated its efficiency. In this paper, we propose a framework to assist in the development of systems for the automatic recognition of high-level surgical tasks using microscope videos analysis. We validated its use on cataract procedures. The idea is to combine state-of-the-art computer vision techniques with time series analysis. The first step of the framework consisted in the definition of several visual cues for extracting semantic information, therefore, characterizing each frame of the video. Five different pieces of image-based classifiers were, therefore, implemented. A step of pupil segmentation was also applied for dedicated visual cue detection. Time series classification algorithms were then applied to model time-varying data. Dynamic time warping and hidden Markov models were tested. This association combined the advantages of all methods for better understanding of the problem. The framework was finally validated through various studies. Six binary visual cues were chosen along with 12 phases to detect, obtaining accuracies of 94%.

Surgical models for computer-assisted neurosurgery.

In this paper, we outline a way to improve computer-assisted neurosurgery using surgical models along with patient-specific models built from multimodal images. We propose a methodological framework for surgical models that include the definition of a surgical ontology, the development of software for describing surgical procedures based on this ontology and the analysis of these descriptions to generate knowledge about surgical practice. Knowledge generation is illustrated by two studies. One hundred fifty-nine patients who underwent brain tumor surgery were described from postoperative reports using the surgical ontology. First, from a subset of 106 surgical cases, we computed a decision tree using a prediction approach that gave probability in terms of operating room patient positioning percentages and according to tumor location within one or more lobes. Second, from the whole set of 159 surgical cases, we identified 6 clusters describing families of cases according to pathology-related parameters. Results from both studies showed possible prediction of parts of the surgical procedure from pathology-related characteristics of the patient. Surgical models enable surgical knowledge to be made explicit, facilitating the surgical decision-making process and surgical planning and improving the human-computer interface during surgery.

ElePhant--an anatomical electronic phantom as simulation-system for otologic surgery.

This paper describes the ElePhant (Electronic Phantom)-an anatomical correct simulation system based on 3D rapid prototyping models for the otologic intervention "Mastoidectomy". The anatomical structures of the head are created with plaster as base material using 3D-printing as rapid prototyping technology (RPT). Structures at risk, represented by electrically conductible material and fiber optics, are realized as an electric circuit and can be detected during the simulation of the surgical procedure. An accuracy study of 15 identical RPT-models compared to the 3D reconstructed CT-dataset of the patient showed that the mean accuracy is lower than the reconstructed CT layer thickness of 0.5 mm. An evaluation study of the ElePhant-system for "Mastoidectomy" was performed by 7 ENT-surgeons. The mean value of the study questionnaire (evaluation range from -2 (not at all) to +2 (very good)) was +1.2. The results showed that the ElePhant can simulate "Mastoidectomy" realistically. It is especially suitable for the simulation of the correct representation and position of the anatomical structures, realistic operation setting, and realistic milling properties of the bone structure. Furthermore it is applicable for training of surgeons.

Does subthalamic nucleus stimulation affect the frontal limbic areas? A single-photon emission computed tomography study using a manual anatomical segmentation method.

Among the basal ganglia nuclei, the subthalamic nucleus (STN) is considered to play a major role in output modulation. The STN represents a relay of the motor cortico-basal ganglia-thalamo-cortical circuit and has become the standard surgical target for treating Parkinson's patients with long-term motor fluctuations and dyskinesia. But chronic bilateral stimulation of the STN produces cognitive effects. According to animal and clinical studies, the STN also appears to have direct or indirect connections with the frontal associative and limbic areas. This prospective study was conducted to analyse regional cerebral blood flow changes in single-photon emission computed tomography imaging of six Parkinson's patients before and after STN stimulation. We particularly focused on the dorsolateral prefrontal cortex and the frontal limbic areas using a manual anatomical MRI segmentation method. We defined nine regions of interest, segmenting each MR slice to quantify the regional cerebral blood flow on pre- and postoperative SPECT images. We normalised the region-of-interest-based measurements to the entire brain volume. The patients showed increased activation during STN stimulation in the dorsolateral prefrontal cortex bilaterally and no change in the anterior cingulate and orbito-frontal cortices. In our study, STN stimulation induced activation of premotor and associative frontal areas. Further studies are needed to underline involvement of the STN with the so-called limbic system.

Detection of inter-hemispheric asymmetries of brain perfusion in SPECT.

Technetium-99m HMPAO and technetium-99m ECD single photon emission computed tomography (SPECT) imaging is commonly used to highlight brain regions with altered perfusion. It is particularly useful in the investigation of intractable partial epilepsy. However, SPECT suffers from poor spatial resolution that makes interpretation difficult. In this context, we propose an unsupervised voxel neighbourhood based method to assist the detection of significant functional inter-hemispheric asymmetries in brain SPECT, using anatomical information from MRI. For each MRI voxel, the anatomically homologous voxel in the contralateral hemisphere is identified. Both homologous voxel coordinates are then mapped into the SPECT volume using SPECT-MRI registration. Neighbourhoods are then defined around each SPECT voxel and compared to obtain a volume of inter-hemispheric differences. A volume including only the statistically significant inter-hemispheric differences is deduced from this volume using a non-parametric approach. The method was validated using realistic analytical simulated SPECT data including known asymmetries (in size and amplitude) as ground truth (gold standard). Detection performance was assessed using an ROC (receiver operating characteristic) approach based on the measures of the overlap between known and detected asymmetries. Validation with computer-simulated data demonstrates the ability to detect asymmetric zones with relatively small extension and amplitude. The registration of these detected functional asymmetries on the MRI enables good anatomical localization to be achieved.

A methodology for generating normal and pathological brain perfusion SPECT images for evaluation of MRI/SPECT fusion methods: application in epilepsy.

Quantitative evaluation of brain MRI/SPECT fusion methods for normal and in particular pathological datasets is difficult, due to the frequent lack of relevant ground truth. We propose a methodology to generate MRI and SPECT datasets dedicated to the evaluation of MRI/SPECT fusion methods and illustrate the method when dealing with ictal SPECT. The method consists in generating normal or pathological SPECT data perfectly aligned with a high-resolution 3D T1-weighted MRI using realistic Monte Carlo simulations that closely reproduce the response of a SPECT imaging system. Anatomical input data for the SPECT simulations are obtained from this 3D T1-weighted MRI, while functional input data result from an inter-individual analysis of anatomically standardized SPECT data. The method makes it possible to control the 'brain perfusion' function by proposing a theoretical model of brain perfusion from measurements performed on real SPECT images. Our method provides an absolute gold standard for assessing MRI/SPECT registration method accuracy since, by construction, the SPECT data are perfectly registered with the MRI data. The proposed methodology has been applied to create a theoretical model of normal brain perfusion and ictal brain perfusion characteristic of mesial temporal lobe epilepsy. To approach realistic and unbiased perfusion models, real SPECT data were corrected for uniform attenuation, scatter and partial volume effect. An anatomic standardization was used to account for anatomic variability between subjects. Realistic simulations of normal and ictal SPECT deduced from these perfusion models are presented. The comparison of real and simulated SPECT images showed relative differences in regional activity concentration of less than 20% in most anatomical structures, for both normal and ictal data, suggesting realistic models of perfusion distributions for evaluation purposes. Inter-hemispheric asymmetry coefficients measured on simulated data were found within the range of asymmetry coefficients measured on corresponding real data. The features of the proposed approach are compared with those of other methods previously described to obtain datasets appropriate for the assessment of fusion methods.

Model of surgical procedures for multimodal image-guided neurosurgery.

OBJECTIVE: Improvement of the planning stage of image-guided surgery requires a better anticipation of the surgical procedure and its anatomical and functional environment. This anticipation should be provided by acquisition of multimodal medical images of the patient and by a better understanding of surgical procedures. In this paper, we propose improvements to the planning and performance of multimodal image-guided neurosurgery through the use of information models related to neurosurgical procedures. MATERIALS AND METHODS: A new generic model of surgical procedures is introduced in the context of multimodal image-guided craniotomies. The basic principle of the model is to break down the surgical procedure into a sequence of steps defining the surgical script. In the model, a step is defined by an action. The model assigns to each surgical step a list of image entities extracted from multimodal preoperative images (i.e., anatomical and/or functional images) which are relevant to the performance of that particular step. A semantic validation of the model was performed by instantiating the model entities for 29 surgical procedures. RESULTS: The resulting generic model is described by a UML class diagram and a textual description. The validation showed the relevance of the model, confirming the main underlying assumptions. It also provided some leads to improve the model. CONCLUSION: While further validation is needed, the initial benefits of this approach can already be outlined. It should add real value to the different levels of image-guided surgery, from preprocessing to planning, as well as during surgery. Models of surgical procedures can manage image data according to the surgical script, which should lead to better anticipation of surgery through the development of simulation tools. Furthermore, the models may improve the performance of surgery using microscope-based neuronavigation systems by making it possible to adapt both visualization and interaction features of multimodal preoperative images according to the model.

Role of the mode of sensory stimulation in presurgical brain mapping in which functional magnetic resonance imaging is used.

OBJECT: The aim of this study was to evaluate different types of sensory stimulation used to distinguish between microvasculature and venous drainage on functional magnetic resonance (fMR) images with blood oxygen level-dependent (BOLD) contrast. METHODS: Seven volunteers received three sensory stimulations. One consisted of small discontinuous automated pokes to the ventral aspect of the right thumbtip. The other two were delivered by the investigator, who vigorously brushed the ventral aspect of the right thumbtip either alone or in combination with the thenar region. Seven contiguous axial slices of the head were acquired using echoplanar fMR imaging during each mode of stimulation. Boxcar analysis and Student's t-test were performed. Cluster analysis was used to determine significant differences between rest and activation phases. The major findings were 1) that a discontinuous sensory stimulation involving a small skin area was able to evoke a limited activated area in the postcentral gyrus with a low activation index (AI [2%]); 2) that this limited activated area was included in the activated area elicited by the continuous sensory stimulations; and 3) that this also evoked multiple activated areas exhibiting AIs of either approximately 2% or greater than 5%. This indicated that the limited discontinuous tactile stimulation evoked a BOLD-contrast fMR image essentially of microvasculature, whereas the more extensive continuous stimulations evoked a BOLD-contrast fMR image in both microvasculature and venous drainage. CONCLUSIONS: Different sensory stimulations are necessary to differentiate primary sensory cortex from venous drainage for presurgical brain mapping.

A data fusion environment for multimodal and multi-informational neuronavigation.

OBJECTIVE: Part of the planning and performance of neurosurgery consists of determining target areas, areas to be avoided, landmark areas, and trajectories, all of which are components of the surgical script. Nowadays, neurosurgeons have access to multimodal medical imaging to support the definition of the surgical script. The purpose of this paper is to present a software environment developed by the authors that allows full multimodal and multi-informational planning as well as neuronavigation for epilepsy and tumor surgery. MATERIALS AND METHODS: We have developed a data fusion environment dedicated to neuronavigation around the Surgical Microscope Neuronavigator system (Carl Zeiss, Oberkochen, Germany). This environment includes registration, segmentation, 3D visualization, and interaction-applied tools. It provides the neuronavigation system with the multimodal information involved in the definition of the surgical script: lesional areas, sulci, ventricles segmented from magnetic resonance imaging (MRI), vessels segmented from magnetic resonance angiography (MRA), functional areas from magneto-encephalography (MEG), and functional magnetic resonance imaging (fMRI) for somatosensory, motor, or language activation. These data are considered to be relevant for the performance of the surgical procedure. The definition of each entity results from the same procedure: registration to the anatomical MRI data set (defined as the reference data set), segmentation, fused 3D display, selection of the relevant entities for the surgical step, encoding in 3D surface-based representation, and storage of the 3D surfaces in a file recognized by the neuronavigation software (STP 3.4, Leibinger; Freiburg, Germany). RESULTS: Multimodal neuronavigation is illustrated with two clinical cases for which multimodal information was introduced into the neuronavigation system. Lesional areas were used to define and follow the surgical path, sulci and vessels helped identify the anatomical environment of the surgical field, and, finally, MEG and fMRI functional information helped determine the position of functional high-risk areas. CONCLUSION: In this short evaluation, the ability to access preoperative multi-functional and anatomical data within the neuronavigation system was a valuable support for the surgical procedure.

[Sulcal identification and neuronavigation in supratentorial cavernoma surgery]. / Repérage sulcal et neuronavigation dans la chirurgie des cavernomes supratentoriels.

We present the use of cortical sulci, segmented from magnetic resonance imaging, in image guided neurosurgery. Sulcal information was transferred to a surgical microscope with enhanced reality features. This assistance was used for the resection of supratentorial cavernomas (7 patients). Sulci were semi-automatically segmented from 3D MRI data sets. Sulci close to the cavernoma were selected and transferred to the neuronavigation system which allows the superimposition of graphics into the right ocular of the microscope. Selected sulci were displayed on the workstation and superimposed into the ocular of the microscope. Cortical sulci proved to be useful for the recognition of the anatomical environment. The superimposed sulci helped to optimize location and size of the skin incision as well as to guide the access to the cavernoma by using the course of a sulcus as indirect trajectory.

A ray-traced texture mapping for enhanced virtuality in image-guided neurosurgery.

3D imaging systems and algorithms give virtual representations of the real world. New emergent hardware systems can combine virtual information and the real world. Virtual and real information must be also visually confronted in order to facilitate our comprehension of the data. We propose a solution which entails the superimposition of a real image of the anatomical areas visualised in a surgical operation with 3D digital data sets. Unlike other solutions which display virtual images in the real world, our method involves ray traced texture mapping which displays real images in a computed world.