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Improvement of image guided surgery systems requires a better anticipation of the surgical procedure. This anticipation may be provided by a better understanding of surgical procedures and/or the use of information models related to neurosurgical procedures. We are introducing a generic model of surgical procedures 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. Each step is defined by an action; the model assigns to each surgical step a list of image entities extracted from multimodal preoperative images (anatomical and/or functional images) which are relevant to the performance of that particular step. The model has been built in two phases: creation and consolidation. Besides, a planning software prototype based on the generic model has been built. The resulting generic model is described by an UML class diagram and textual description. Some initial benefits of this approach can already be outlined: improvement of multimodal information management, enhancement of the preparation and the guidance of the surgical act.

Detecting tools in surgical videos is an important ingredient for context-aware computer-assisted surgical systems. To this end, we present a new surgical tool detection dataset and a method for joint tool detection and pose estimation in 2d images. Our two-stage pipeline is data-driven and relaxes strong assumptions made by previous works regarding the geometry, number, and position of tools in the image. The first stage classifies each pixel based on local appearance only, while the second stage evaluates a tool-specific shape template to enforce global shape. Both local appearance and global shape are learned from training data. Our method is validated on a new surgical tool dataset of 2 476 images from neurosurgical microscopes, which is made freely available. It improves over existing datasets in size, diversity and detail of annotation. We show that our method significantly improves over competitive baselines from the computer vision field. We achieve 15% detection miss-rate at 10^-1 false positives per image (for the suction tube) over our surgical tool dataset. Results indicate that performing semantic labelling as an intermediate task is key for high quality detection. [ABSTRACT FROM PUBLISHER]

Purpose: A rare case of intradiploic growing fracture of the occipital bone is presented. Examination of this case and literature review was carried out to find significant specific features of such a rare condition. Case: A 4-year-old boy was operated on for a huge occipital intradiploic growing skull fracture. His medical history, surgical management, and postoperative course are presented. Literature review: A computer literature search using the Medline database revealed 31 well-documented cases. Conclusions: Special attention must be paid to skull fractures in childhood when occurring near CSF large spaces, especially if ventricle enlargement, suggesting that hydrocephalus is present. Surgeons should evaluate hydrocephalus before treating such lesions in order to improve surgical result and postoperative clinical evolution. [ABSTRACT FROM AUTHOR]

The authors present the case of a 13-year-old boy who experienced frequent disabling episodes of typical postural induced headaches, which revealed a Chiari I malformation, syringomyelia and cervical spinal cord edema. This boy had received a valveless lumboperitoneal (LP) shunt at the age of 18 months for macrocephaly. At this time, cranial CT scan showed moderate enlargement of the subarachnoid spaces without hydrocephalus or tonsillar herniation. The LP shunt was clamped but the patient experienced signs of brain stem dysfunction and increased intracranial pressure. Finally, an adjustable valve (110 mm Hg) was inserted and all the symptoms resolved. Although some authors consider LP shunt as a safe and effective procedure even in the pediatric population, our case reminds us that these shunts, especially when valveless, may expose the patient to the risk of symptomatic acquired Chiari I malformation and syringomyelia consecutive to a chronic spinal CSF leakage. Copyright © 2008 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Undesirable events in the neurosurgery operating theater have less often been the result of a technical error than of a dysfunction linked to nontechnical skills (NTSs). The essential aim of our study was to perform a systematic review of the reported data on NTS in neurosurgery. Our secondary objective was to identify the NTSs more specific to neurosurgery to define the training needs of neurosurgery trainees. The MEDLINE and Cochrane Database of Systematic Reviews were searched according to the PRISMA (preferred reporting items for systematic reviews and meta-analysis) guidelines. The search initially identified 2132 reports, of which 21 were eligible for systematic study. Data were extracted from the report regarding study design, sample size, NTSs assessed, and assessment tools, and the key results were collected. Interpersonal skills (communication, teamwork), cognitive skills (decision making, situational awareness), and personal resource factors (coping with stress or fatigue) were specifically identified. No study had used assessment tools such as NOTECHS (nontechnical skills), NOTSS (nontechnical skills for surgeons), or OTAS (observational teamwork assessment for surgery). They were performed in a real environment in 11 cases, in a simulated environment in 9, and during theoretical teaching in 1 case. Very few studies have been performed concerning neurosurgical NTSs, despite the increasing the number of studies during the past few years on NTSs in other domains of surgery. Society has been concentrating more and more on the quality and safety of medical care. The development and application of NTS assessment tools is, therefore, essential to provide assistance in the training of future neurosurgeons. [ABSTRACT FROM AUTHOR]

Objective: More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the prediction of the possible next task that a surgeon is going to perform during surgery.Material and Method: We formulate the problem as finding the optimal registration of a partial sequence to a complete reference sequence of surgical activities. We propose an efficient algorithm to find the optimal partial alignment and a prediction system using maximum a posteriori probability estimation and filtering. We also introduce a weighting scheme allowing to improve the predictions by taking into account the relative similarity between the current surgery and a set of pre-recorded surgeries.Results: Our method is evaluated on two types of neurosurgical procedures: lumbar disc herniation removal and anterior cervical discectomy. Results show that our method outperformed the state of the art by predicting the next task that the surgeon will perform with 95% accuracy.Conclusions: This work shows that, even from the low-level description of surgeries and without other sources of information, it is often possible to predict the next surgical task when the conditions are consistent with the previously recorded surgeries. We also showed that our method is able to assess when there is actually a large divergence between the predictions and decide that it is not reasonable to make a prediction. [ABSTRACT FROM AUTHOR]

Objective Surgery is one of the riskiest and most important medical acts that is performed today. Understanding the ways in which surgeries are similar or different from each other is of major interest. Desires to improve patient outcomes and surgeon training, and to reduce the costs of surgery, all motivate a better understanding of surgical practices. To facilitate this, surgeons have started recording the activities that are performed during surgery. New methods have to be developed to be able to make the most of this extremely rich and complex data. The objective of this work is to enable the simultaneous comparison of a set of surgeries, in order to be able to extract high-level information about surgical practices. Materials and method We introduce non-linear temporal scaling (NLTS): a method that finds a multiple alignment of a set of surgeries. Experiments are carried out on a set of lumbar disc neurosurgeries. We assess our method both on a highly standardised phase of the surgery (closure) and on the whole surgery. Results Experiments show that NLTS makes it possible to consistently derive standards of surgical practice and to understand differences between groups of surgeries. We take the training of surgeons as the common theme for the evaluation of the results and highlight, for example, the main differences between the practices of junior and senior surgeons in the removal of a lumbar disc herniation. Conclusions NLTS is an effective and efficient method to find a multiple alignment of a set of surgeries. NLTS realigns a set of sequences along their intrinsic timeline, which makes it possible to extract standards of surgical practices. [ABSTRACT FROM AUTHOR]