DejaVu: Intra-operative Simulation for Surgical Gesture Rehearsal

International audienceAdvances in surgical simulation and surgical augmented reality have changed the way surgeons prepare for practice and conduct medical procedures. Despite considerable interest from surgeons, the use of simulation is still predominantly confined to pre-operative training of surgical tasks and the lack of robustness of surgical augmented reality means that it is seldom used for surgical guidance. In this paper, we present DejaVu, a novel surgical simulation approach for intra-operative surgical gesture rehearsal. With DejaVu we aim at bridging the gap between pre-operative surgical simulation and crucial but not yet robust intra-operative surgical augmented reality. By exploiting intra-operative images we produce a simulation that faithfully matches the actual procedure without visual discrepancies and with an underlying physical modelling that performs real-time deformation of organs and surrounding tissues, surgeons can interact with the targeted organs through grasping, pulling or cutting to immediately rehearse their next gesture. We present results on different in vivo surgical procedures and demonstrate the feasibility of practical use of our system

Power training and postmenopausal hormone therapy affect transcriptional control of specific co-regulated gene clusters in skeletal muscle

At the moment, there is no clear molecular explanation for the steeper decline in muscle performance after menopause or the mechanisms of counteractive treatments. The goal of this genome-wide study was to identify the genes and gene clusters through which power training (PT) comprising jumping activities or estrogen containing hormone replacement therapy (HRT) may affect skeletal muscle properties after menopause. We used musculus vastus lateralis samples from early stage postmenopausal (50–57 years old) women participating in a yearlong randomized double-blind placebo-controlled trial with PT and HRT interventions. Using microarray platform with over 24,000 probes, we identified 665 differentially expressed genes. The hierarchical clustering method was used to assort the genes. Additionally, enrichment analysis of gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways was carried out to clarify whether assorted gene clusters are enriched with particular functional categories. The analysis revealed transcriptional regulation of 49 GO/KEGG categories. PT upregulated transcription in “response to contraction”—category revealing novel candidate genes for contraction-related regulation of muscle function while HRT upregulated gene expression related to functionality of mitochondria. Moreover, several functional categories tightly related to muscle energy metabolism, development, and function were affected regardless of the treatment. Our results emphasize that during the early stages of the postmenopause, muscle properties are under transcriptional modulation, which both PT and HRT partially counteract leading to preservation of muscle power and potentially reducing the risk for aging-related muscle weakness. More specifically, PT and HRT may function through improving energy metabolism, response to contraction as well as by preserving functionality of the mitochondria

Economic growth and longevity risk with adverse selection

We study the implications of adverse selection in annuity markets in a general-equilibrium model of the closed economy. Agents differ in their health type and invest their assets in the annuity market. Without informational asymmetries each agent would obtain an actuarially fair insurance. If the individual health types and total annuity purchases are unobservable to the annuity firms then there exists a pooling equilibrium in which all agents annuitize at a common rate. At this pooling rate unhealthy agents would eventually like to borrow but this would reveal their true health type. As a consequence, they rationally drop out of the market. Surprisingly, the welfare and growth effects of the informational asymmetries are rather small

Automatic segmentation of stereoelectroencephalography (SEEG) electrodes post-implantation considering bending

PURPOSE: The accurate and automatic localisation of SEEG electrodes is crucial for determining the location of epileptic seizure onset. We propose an algorithm for the automatic segmentation of electrode bolts and contacts that accounts for electrode bending in relation to regional brain anatomy. METHODS: Co-registered post-implantation CT, pre-implantation MRI, and brain parcellation images are used to create regions of interest to automatically segment bolts and contacts. Contact search strategy is based on the direction of the bolt with distance and angle constraints, in addition to post-processing steps that assign remaining contacts and predict contact position. We measured the accuracy of contact position, bolt angle, and anatomical region at the tip of the electrode in 23 post-SEEG cases comprising two different surgical approaches when placing a guiding stylet close to and far from target point. Local and global bending are computed when modelling electrodes as elastic rods. RESULTS: Our approach executed on average in 36.17 s with a sensitivity of 98.81% and a positive predictive value (PPV) of 95.01%. Compared to manual segmentation, the position of contacts had a mean absolute error of 0.38 mm and the mean bolt angle difference of [Formula: see text] resulted in a mean displacement error of 0.68 mm at the tip of the electrode. Anatomical regions at the tip of the electrode were in strong concordance with those selected manually by neurosurgeons, [Formula: see text], with average distance between regions of 0.82 mm when in disagreement. Our approach performed equally in two surgical approaches regardless of the amount of electrode bending. CONCLUSION: We present a method robust to electrode bending that can accurately segment contact positions and bolt orientation. The techniques presented in this paper will allow further characterisation of bending within different brain regions

Isolation of muscle-derived stem/progenitor cells based on adhesion characteristics to collagen-coated surfaces

Our lab developed and optimized a method, known as the modified pre-plate technique, to isolate stem/ progenitor cells from skeletal muscle. This method separates different populations of myogenic cells based on their propensity to adhere to a collagen I-coated surface. Based on their surface markers and stem-like properties, including self-renewal, multi-lineage differentiation, and ability to promote tissue regeneration, the last cell fraction or slowest to adhere to the collagen-coated surface (pre-plate 6; pp6) appears to be early, quiescent progenitor cells termed muscle-derived stem/progenitor cells (MDSPCs). The cell fractions preceding pp6 (pp1-5) are likely populations of more committed (differentiated) cells, includingfibroblast- and myoblast-like cells. This technique may be used to isolate MDSPCs from skeletal muscle of humans or mice regardless of age, sex or disease state, although the yield of MDSPCs varies with age and health. MDSPCs can be used for regeneration of a variety of tissues including bone, articular cartilage, skeletal and cardiac muscle, and nerve. MDSPCs are currently being tested in clinical trials for treatment of urinary incontinence and myocardial infarction. MDSPCs from young mice have also been demonstrated to extend life span and healthspan in mouse models of accelerated aging through an apparent paracrine/ endocrine mechanism. Here we detail methods for isolation and characterization of MDSPCs. © Springer Science+Business Media, LLC 2013