Marker-based C-arm self-calibration with unknown calibration pattern

BACKGROUND

Accurate tomographic reconstructions require the knowledge of the actual acquisition geometry. Many mobile C-arm CT scanners have poorly reproducible acquisition geometries and thus need acquisition-specific calibration procedures. Most of geometric self-calibration methods based on projection data either need prior information or are limited to the estimation of a low number of geometric calibration parameters. Other self-calibration methods generally use a calibration pattern with known geometry and are hardly implementable in practice for clinical applications.

PURPOSE

We present a three-step marker based self-calibration method which does not require the prior knowledge of the calibration pattern and thus enables the use of calibration patterns with arbitrary markers positions.

METHODS

The first step of the method aims at detecting the set of markers of the calibration pattern in each projection of the CT scan and is performed using the YOLO (You Only Look Once) Convolutional Neural Network. The projected marker trajectories are then estimated by a sequential projection-wise marker association scheme based on the Linear Assignment Problem which uses Kalman filters to predict the markers 2D positions in the projections. The acquisition geometry is finally estimated from the marker trajectories using the Bundle-adjustment algorithm.

RESULTS

The calibration method has been tested on realistic simulated images of the ICRP (International Commission on Radiological Protection) phantom, using calibration patterns with 10 and 20 markers. The backprojection error was used to evaluate the self-calibration method and exhibited sub-millimeter errors. Real images of two human knees with 10 and 30 markers calibration patterns were then used to perform a qualitative evaluation of the method, which showed a remarkable artifacts reduction and bone structures visibility improvement.

CONCLUSIONS

The proposed calibration method gave promising results that pave the way to patient-specific geometric self-calibrations in clinics.

Learning curve for fusion magnetic resonance imaging targeted prostate biopsy and three-dimensional transrectal ultrasonography segmentation

OBJECTIVE

To report the learning curve of multiple operators for fusion magnetic resonance imaging (MRI) targeted biopsy and to determine the number of cases needed to achieve proficiency.

MATERIALS AND METHODS

All adult males who underwent fusion MRI targeted biopsy between February 2012 and July 2021 for clinically suspected prostate cancer (PCa) in a single centre were included. Fusion transrectal MRI targeted biopsy was performed under local anaesthesia using the Koelis platform. Learning curves for segmentation of transrectal ultrasonography (TRUS) images and the overall MRI targeted biopsy procedure were estimated with locally weighted scatterplot smoothing by computing each operator's timestamps for consecutive procedures. Non-risk-adjusted cumulative sum (CUSUM) methods were used to create learning curves for clinically significant (i.e., International Society of Urological Pathology grade ≥ 2) PCa detection.

RESULTS

Overall, 1721 patients underwent MRI targeted biopsy in our centre during the study period. The median (interquartile range) times for TRUS segmentation and for the MRI targeted biopsy procedure were 4.5 (3.5, 6.0) min and 13.2 (10.6, 16.9) min, respectively. Among the 14 operators with experience of more than 50 cases, a plateau was reached after 40 cases for TRUS segmentation time and 50 cases for overall MRI targeted biopsy procedure time. CUSUM analysis showed that the learning curve for clinically significant PCa detection required 25 to 45 procedures to achieve clinical proficiency. Pain scores ranged between 0 and 1 for 84% of patients, and a plateau phase was reached after 20 to 100 cases.

CONCLUSIONS

A minimum of 50 cases of MRI targeted biopsy are necessary to achieve clinical and technical proficiency and to reach reproducibility in terms of timing, clinically significant PCa detection, and pain.

Impact of Relative Volume Difference Between Magnetic Resonance Imaging and Three-dimensional Transrectal Ultrasound Segmentation on Clinically Significant Prostate Cancer Detection in Fusion Magnetic Resonance Imaging-targeted Biopsy

BACKGROUND

Segmentation of three-dimensional (3D) transrectal ultrasound (TRUS) images is known to be challenging, and the clinician often lacks a reliable and easy-to-use indicator to assess its accuracy during the fusion magnetic resonance imaging (MRI)-targeted prostate biopsy procedure.

OBJECTIVE

To assess the effect of the relative volume difference between 3D-TRUS and MRI segmentation on the outcome of a targeted biopsy.

DESIGN, SETTING, AND PARTICIPANTS

All adult males who underwent an MRI-targeted prostate biopsy for clinically suspected prostate cancer between February 2012 and July 2021 were consecutively included.

INTERVENTION

All patients underwent a fusion MRI-targeted prostate biopsy with a Koelis device.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Three-dimensional TRUS and MRI prostate volumes were calculated using 3D prostate models issued from the segmentations. The primary outcome was the relative segmentation volume difference (SVD) between transrectal ultrasound and MRI divided by the MRI volume (SVD = MRI volume - TRUS volume/MRI volume) and its correlation with clinically significant prostate cancer (eg, International Society of Urological Pathology [ISUP] ≥2) positiveness on targeted biopsy cores.

RESULTS AND LIMITATIONS

Overall, 1721 patients underwent a targeted biopsy resulting in a total of 5593 targeted cores. The median relative SVD was significantly lower in patients diagnosed with clinically significant prostate cancer than in those with ISUP 0-1: (6.7% [interquartile range {IQR} -2.7, 13.6] vs 8.0% [IQR 3.3, 16.4], p < 0.01). A multivariate regression analysis showed that a relative SVD of >10% of the MRI volume was associated with a lower detection rate of clinically significant prostate cancer (odds ratio = 0.74 [95% confidence interval: 0.55-0.98]; p = 0.038).

CONCLUSIONS

A relative SVD of >10% of the MRI segmented volume was associated with a lower detection rate of clinically significant prostate cancer on targeted biopsy cores. The relative SVD can be used as a per-procedure quality indicator of 3D-TRUS segmentation.

PATIENT SUMMARY

A discrepancy of ≥10% between segmented magnetic resonance imaging and transrectal ultrasound volume is associated with a reduced ability to detect significant prostate cancer on targeted biopsy cores.

Intra-operative fluorescence-based detection of positive surgical margins during radical prostatectomy: Lessons learned from a pilot ex vivo translational study

OBJECTIVES

Nerve-sparing techniques during radical prostatectomy have been associated with an increased risk of positive surgical margins. The intra-operative detection of residual prostatic tissue could help mitigate this risk. The objectives of the present study were to assess the feasibility of using an anti-prostate-specific membrane antigen (anti-PSMA) antibody conjugated with a fluorophore to characterize fresh prostate tissue as prostatic or non-prostatic for intra-operative surgical margin detection.

METHODS

Fresh prostatic tissue samples were collected from transurethral resections of the prostate (TURP) or prostate biopsies, and either immunolabelled with anti-PSMA antibody conjugated with Alexa Fluor 488 or used as controls. A dedicated, laparoscopy-compliant fluorescence device was developed for real-time fluorescence detection. Confocal microscopy was used as the gold standard for comparison. Spectral unmixing was used to distinguish specific, Alexa Fluor 488 fluorescence from nonspecific autofluorescence.

RESULTS

The average peak wavelength of the immuno-labeled TURP samples (n = 4) was 541.7 ± 0.9 nm and of the control samples (n = 4) was 540.8 ± 2.2 nm. Spectral unmixing revealed that these similar measures were explained by significant autofluorescence, linked to electrocautery. Three biopsy samples were then obtained from seven patients and also displayed significant nonspecific fluorescence, raising questions regarding the reproducibility of the fixation of the anti-PSMA antibodies on the samples. Comparing the fluorescence results with final pathology proved challenging due to the small sample size and tissue alterations.

CONCLUSIONS

This study showed similar fluorescence of immuno-labeled prostate tissue samples and controls, failing to demonstrate the feasibility of intra-operative margin detection using PSMA immuno-labeling, due to marked tissue autofluorescence. We successfully developed a fluorescence device that could be used intraoperatively in a laparoscopic setting. Use of the infrared range as well as newly available antibodies could prove interesting options for future research.

2D/3D Deep Registration Along Trajectories With Spatiotemporal Context: Application To Prostate Biopsy Navigation

OBJECTIVE

The accuracy of biopsy targeting is a major issue for prostate cancer diagnosis and therapy. However, navigation to biopsy targets remains challenging due to the limitations of transrectal ultrasound (TRUS) guidance added to prostate motion issues. This article describes a rigid 2D/3D deep registration method, which provides a continuous tracking of the biopsy location w.r.t the prostate for enhanced navigation.

METHODS

A spatiotemporal registration network (SpT-Net) is proposed to localize the live 2D US image relatively to a previously aquired US reference volume. The temporal context relies on prior trajectory information based on previous registration results and probe tracking. Different forms of spatial context were compared through inputs (local, partial or global) or using an additional spatial penalty term. The proposed 3D CNN architecture with all combinations of spatial and temporal context was evaluated in an ablation study. For providing a realistic clinical validation, a cumulative error was computed through series of registrations along trajectories, simulating a complete clinical navigation procedure. We also proposed two dataset generation processes with increasing levels of registration complexity and clinical realism.

RESULTS

The experiments show that a model using local spatial information combined with temporal information performs better than more complex spatiotemporal combination.

CONCLUSION

The best proposed model demonstrates robust real-time 2D/3D US cumulated registration performance on trajectories. Those results respect clinical requirements, application feasibility, and they outperform similar state-of-the-art methods.

SIGNIFICANCE

Our approach seems promising for clinical prostate biopsy navigation assistance or other US image-guided procedure.

Machine learning and registration for automatic seed localization in 3D US images for prostate brachytherapy

PURPOSE

New radiation therapy protocols, in particular adaptive, focal or boost brachytherapy treatments, require determining precisely the position and orientation of the implanted radioactive seeds from real-time ultrasound (US) images. This is necessary to compare them to the planned one and to adjust automatically the dosimetric plan accordingly for next seeds implantations. The image modality, the small size of the seeds, and the artifacts they produce make it a very challenging problem. The objective of the presented work is to setup and to evaluate a robust and automatic method for seed localization in three-dimensional (3D) US images.

METHODS

The presented method is based on a prelocalization of the needles through which the seeds are injected in the prostate. This prelocalization allows focusing the search on a region of interest (ROI) around the needle tip. Seeds localization starts by binarizing the ROI and removing false positives using, respectively, a Bayesian classifier and a support vector machine (SVM). This is followed by a registration stage using first an iterative closest point (ICP) for localizing the connected set of seeds (named strand) inserted through a needle, and secondly refining each seed position using sum of squared differences (SSD) as a similarity criterion. ICP registers a geometric model of the strand to the candidate voxels while SSD compares an appearance model of a single seed to a subset of the image. The method was evaluated both for 3D images of an Agar-agar phantom and a dataset of clinical 3D images. It was tested on stranded and on loose seeds.

RESULTS

Results on phantom and clinical images were compared with a manual localization giving mean errors of 1.09 ± 0.61 mm on phantom image and 1.44 ± 0.45 mm on clinical images. On clinical images, the mean errors of individual seeds orientation was 4.33 ± 8 . 51 ∘ .

CONCLUSIONS

The proposed algorithm for radioactive seed localization is robust, tested on different US images, accurate, giving small mean error values, and returns the five cylindrical seeds degrees of freedom.

Predicting the quality of surgical exposure using spatial and procedural features from laparoscopic videos

PURPOSE : Evaluating the quality of surgical procedures is a major concern in minimally invasive surgeries. We propose a bottom-up approach based on the study of Sleeve Gastrectomy procedures, for which we analyze what we assume to be an important indicator of the surgical expertise: the exposure of the surgical scene. We first aim at predicting this indicator with features extracted from the laparoscopic video feed, and second to analyze how the extracted features describing the surgical practice influence this indicator. METHOD : Twenty-nine patients underwent Sleeve Gastrectomy performed by two confirmed surgeons in a monocentric study. Features were extracted from spatial and procedural annotations of the videos, and an expert surgeon evaluated the quality of the surgical exposure at specific instants. The features were used as input of a classifier (linear discriminant analysis followed by a support vector machine) to predict the expertise indicator. Features selected in different configurations of the algorithm were compared to understand their relationships with the surgical exposure and the surgeon's practice. RESULTS : The optimized algorithm giving the best performance used spatial features as input ([Formula: see text]). It also predicted equally the two classes of the indicator, despite their strong imbalance. Analyzing the selection of input features in the algorithm allowed a comparison of different configurations of the algorithm and showed a link between the surgical exposure and the surgeon's practice. CONCLUSION : This preliminary study validates that a prediction of the surgical exposure from spatial features is possible. The analysis of the clusters of feature selected by the algorithm also shows encouraging results and potential clinical interpretations.

Real-time tracking of surgical instruments based on spatio-temporal context and deep learning

ABSTARCT Real-time tool tracking in minimally invasive-surgery (MIS) has numerous applications for computer-assisted interventions (CAIs). Visual tracking approaches are a promising solution to real-time surgical tool tracking, however, many approaches may fail to complete tracking when the tracker suffers from issues such as motion blur, adverse lighting, specular reflections, shadows, and occlusions. We propose an automatic real-time method for two-dimensional tool detection and tracking based on a spatial transformer network (STN) and spatio-temporal context (STC). Our method exploits both the ability of a convolutional neural network (CNN) with an in-house trained STN and STC to accurately locate the tool at high speed. Then we compared our method experimentally with other four general of CAIs' visual tracking methods using eight existing online and in-house datasets, covering both in vivo abdominal, cardiac and retinal clinical cases in which different surgical instruments were employed. The experiments demonstrate that our method achieved great performance with respect to the accuracy and the speed. It can track a surgical tool without labels in real time in the most challenging of cases, with an accuracy that is equal to and sometimes surpasses most state-of-the-art tracking algorithms. Further improvements to our method will focus on conditions of occlusion and multi-instruments.

Qualitative and quantitative assessment of cartilage degeneration using full-field optical coherence tomography ex vivo

OBJECTIVE

The purpose of this study was to investigate the ability of full-field optical coherence tomography (FFOCT) to qualitatively and quantitatively evaluate cartilage degeneration using the qualitative evaluation of histology sections as the reference.

DESIGN

Thirty-three human knee cartilage samples of variable degeneration were included in the study. A closely matching histology and FFOCT image was acquired for each sample. The cartilage degeneration was qualitatively evaluated by assigning a grade to each histology and FFOCT image. The relevance of the performed grading was assessed by calculating the intra- and inter-observer reproducibility and calculating the concordance between the histology and FFOCT grades. A near-automatic algorithm was developed to quantitatively characterize the cartilage surface in each image. The correlation between the quantitative results and the reference qualitative histology was calculated.

RESULTS

An almost perfect agreement was achieved for both the intra- and inter-reproducibility of the histology and FFOCT qualitative grading (κ ≥ 0.91). A high and statistically significant level of agreement was measured between the histology and FFOCT grades (W = 0.95, P < 0.05). Strong and statistically significant correlations were measured between the quantitative results and the reference qualitative histology grades (ρ ≥ 0.75, P < 0.05).

CONCLUSIONS

We have demonstrated that FFOCT is an alternative approach to conventional optical coherence tomography (OCT) that is as well adapted for the qualitative and quantitative assessment of human cartilage as the reference gold standard - histology. This study constitutes the first promising results towards developing a new diagnostic tool in the field of osteoarthritis.

Unintended Consequences of Sensor, Signal, and Imaging Informatics: New Problems and New Solutions

OBJECTIVES

This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2016 of excellent research in the broad field of Sensor, Signal and Imaging Informatics published in the year 2015, with a focus on Unintended consequences: new problems and new solutions.

METHODS

We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2015, from the PubMed and Web of Science databases. The set of MesH keywords used was provided by experts.

RESULTS

The constant advances in medical technology allow ever more relevant diagnostic and therapeutic approaches to be designed. Nevertheless, there is a need to acquire expert knowledge of these innovations in order to identify precociously new associated problems for which new solutions need to be designed and developed.

[Rigid cystoscopy versus retrovision for adjustable peri-urethral balloons guidance: Comparison of precision thanks to a surgical navigation system]

OBJECTIVES

The main goal of our phantom study was to compare the precision of adjustable periurethral balloons positioning depending whether the guidance was obtained by retrovision or rigid cystoscopy.

MATERIAL AND METHODS

A navigation guidance system was used to localize the introduction mandrel which was equipped with tracking targets. Two ideal sites of implantation were predefined and recorded into the navigation system. The two points were placed symmetrically to the phantom reproducing the urethra. Four different users were asked to position the tip of the introduction mandrel as close as possible to the ideal site of implantation with the help of each method of guidance. For each attempt, the distance (mm) between the tip of the introduction mandrel and the ideal position was recorded by the navigation system.

RESULTS

For each method of guidance, a total of 20 attempts on each side were made by direct puncture on one side and a symmetrical contralateral puncture. For direct puncture, the median distances were 5.20 (±3.96) and 4.38 (±1.55) mm with rigid cystoscopy and retrovision respectively (P=0.29). For symmetrical contralateral puncture, the median distance were 7,19 (±3,78) and 6,86 (±2,76) mm with rigid cystoscopy and retrovision respectively (P=0,32) CONCLUSION: This study could not demonstrate any significant difference between the two guidance systems. Nevertheless, it showed that navigation guidance system could be used to compare the precision of surgical interventions.

LEVEL OF EVIDENCE

4.

Automatic Detection of Instruments in Laparoscopic Images: A First Step Towards High-level Command of Robotic Endoscopic Holders

The tracking of surgical instruments o fers interesting possibilities for the development of high-level commands for robotic camera holders in laparoscopic surgery. We have developed a new method to detect instruments in laparoscopic images which uses information on the 3D position of the insertion point of an instrument into the abdominal cavity. This information strongly constrains the search for the instrument in each endoscopic image. Hence, the instrument can be detected in near real-time using shape considerations. Early results on laparoscopic images show that the method is rapid and robust in the presence of partial occlusion and smoke. Our first experiment on a cadaver validates our approach and shows encouraging results.

Enhanced vision system for laparoscopic surgery

Laparoscopic surgery offers benefits to the patients but poses new challenges to the surgeons, including a limited field of view. In this paper, we present an innovative vision system that can be combined with a traditional laparoscope, and provides the surgeon with a global view of the abdominal cavity, bringing him or her closer to open surgery conditions. We present our first experiments performed on a testbench mimicking a laparoscopic setup: they demonstrate an important time gain in performing a complex task consisting bringing a thread into the field of view of the laparoscope.

How Sensor, Signal, and Imaging Informatics May Impact Patient Centered Care and Care Coordination

OBJECTIVE

This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2015 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2014, with a focus on patient centered care coordination.

METHODS

The two section editors performed a systematic initial selection and a double blind peer review process to select a list of candidate best papers in the domain published in 2014, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used. This selection was peer-reviewed by external reviewers.

RESULTS

The review process highlighted articles illustrating two current trends related to care coordination and patient centered care: the enhanced capacity to predict the evolution of a disease based on patient-specific information can impact care coordination; similarly, better perception of the patient and his treatment could lead to enhanced personalized care with a potential impact on care coordination.

CONCLUSIONS

This review shows the multiplicity of angles from which the question of patient-centered care can be addressed, with consequences on care coordination that will need to be confirmed and demonstrated in the future.

Using CamiTK for rapid prototyping of interactive computer assisted medical intervention applications

Computer Assisted Medical Intervention (CAMI hereafter) is a complex multi-disciplinary field. CAMI research requires the collaboration of experts in several fields as diverse as medicine, computer science, mathematics, instrumentation, signal processing, mechanics, modeling, automatics, optics, etc. CamiTK is a modular framework that helps researchers and clinicians to collaborate together in order to prototype CAMI applications by regrouping the knowledge and expertise from each discipline. It is an open-source, cross-platform generic and modular tool written in C++ which can handle medical images, surgical navigation, biomedicals simulations and robot control. This paper presents the Computer Assisted Medical Intervention ToolKit (CamiTK) and how it is used in various applications in our research team.

Sensor, signal, and imaging informatics: big data and smart health technologies

OBJECTIVES

This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2014 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2013, with a focus on Big Data and Smart Health Technologies Methods: We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2013, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used.

RESULTS

Big Data are collections of large and complex datasets which have the potential to capture the whole variability of a study population. More and more innovative sensors are emerging, allowing to enrich these big databases. However they become more and more challenging to process (i.e. capture, store, search, share, transfer, exploit) because traditional tools are not adapted anymore.

CONCLUSIONS

This review shows that it is necessary not only to develop new tools specifically designed for Big Data, but also to evaluate their performance on such large datasets.

Sensor, Signal, and Imaging Informatics: Evidence-Based Health Informatics

Objectives: This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2013 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2012.

Methods: We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2012, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used.

Results: Current research in the field of sensor signal and imaging informatics is based on innovative sensors from which relevant information (signal and imaging) can be acquired and integrated into workflow based or patient based models. This rich environment can help the medical staff in carrying out more optimal care. The demonstration of the added value of such innovations is more and more performed through evidence-based evaluations.

Conclusions: The best paper selection of articles on sensors, signal, and imaging informatics illustrates the wide spectrum covered by this field in 2012, and the attention paid to evaluations.

Sensor, signal, and imaging informatics: evidence-based health informatics

OBJECTIVES

This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2013 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2012.

METHODS

We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2012, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used.

RESULTS

Current research in the field of sensor signal and imaging informatics is based on innovative sensors from which relevant information (signal and imaging) can be acquired and integrated into workflow based or patient based models. This rich environment can help the medical staff in carrying out more optimal care. The demonstration of the added value of such innovations is more and more performed through evidence-based evaluations.

CONCLUSIONS

The best paper selection of articles on sensors, signal, and imaging informatics illustrates the wide spectrum covered by this field in 2012, and the attention paid to evaluations.

Retinal vessel cannulation with an image-guided handheld robot

Cannulation of small retinal vessels is often prohibitively difficult for surgeons, since physiological tremor often exceeds the narrow diameter of the vessel (40-120 microm). Using an active handheld micromanipulator, we introduce an image-guided robotic system that reduces tremor and provides smooth, scaled motion during the procedure. The micromanipulator assists the surgeon during the approach, puncture, and injection stages of the procedure by tracking the pipette and anatomy viewed under the microscope. In experiments performed ex vivo by an experienced retinal surgeon on 40-60 microm vessels in porcine eyes, the success rate was 29% (2/7) without the aid of the system and 63% (5/8) with the aid of the system.

Active Guidance of a Handheld Micromanipulator using Visual Servoing

In microsurgery, a surgeon often deals with anatomical structures of sizes that are close to the limit of the human hand accuracy. Robotic assistants can help to push beyond the current state of practice by integrating imaging and robot-assisted tools. This paper demonstrates control of a handheld tremor reduction micromanipulator with visual servo techniques, aiding the operator by providing three behaviors: snap-to, motion-scaling, and standoff-regulation. A stereo camera setup viewing the workspace under high magnification tracks the tip of the micromanipulator and the desired target object being manipulated. Individual behaviors activate in task-specific situations when the micromanipulator tip is in the vicinity of the target. We show that the snap-to behavior can reach and maintain a position at a target with an accuracy of 17.5 ± 0.4μm Root Mean Squared Error (RMSE) distance between the tip and target. Scaling the operator's motions and preventing unwanted contact with non-target objects also provides a larger margin of safety.

Development of miniaturized light endoscope-holder robot for laparoscopic surgery

PURPOSE

We have conducted experiments with an innovatively designed robot endoscope holder for laparoscopic surgery that is small and low cost.

MATERIALS AND METHODS

A compact light endoscope robot (LER) that is placed on the patient's skin and can be used with the patient in the lateral or dorsal supine position was tested on cadavers and laboratory pigs in order to allow successive modifications. The current control system is based on voice recognition. The range of vision is 360 degrees with an angle of 160 degrees . Twenty-three procedures were performed.

RESULTS

The tests made it possible to advance the prototype on a variety of aspects, including reliability, steadiness, ergonomics, and dimensions. The ease of installation of the robot, which takes only 5 minutes, and the easy handling made it possible for 21 of the 23 procedures to be performed without an assistant.

CONCLUSION

The LER is a camera holder guided by the surgeon's voice that can eliminate the need for an assistant during laparoscopic surgery. The ease of installation and manufacture should make it an effective and inexpensive system for use on patients in the lateral and dorsal supine positions. Randomized clinical trials will soon validate a new version of this robot prior to marketing.

Automatic localization of laparoscopic instruments for the visual servoing of an endoscopic camera holder

The use of a robotized camera holder in laparoscopic surgery allows a surgeon to control the endoscope without the intervention of an assistant. Today, the orders that the surgeon can give to robotized camera holders remain limited. In order to provide higher level interactions between the surgeon and a robotized camera holder, we have developed a new method for the automatic tracking of laparoscopic instruments which works in near real-time. The method is based on the measurement of the 3D positions of the insertion points of the instruments in the abdominal cavity and a simple shape model of the laparoscopic instruments. We present the results of our first experimentation on a cadaver.

[Preclinical development of the TIMC LER (light endoscope robot)]

INTRODUCTION

The authors participated in the development of an innovative endoscope robot in laparoscopic surgery designed by TIMC-GMCAO, providing a solution to the disadvantages of currently available systems, i.e. their cost and large dimensions.

MATERIAL AND METHODS

A compact robot (LER) placed on the patient's skin that can be used in the lateral and dorsal supine position was tested on cadavres and laboratory pigs in order to allow successive modifications. The current control system is based on voice recognition. The amplitude of vision is 360 degrees with an angle of 160 degrees. Twenty three procedures were performed (2 radical prostatectomies, 4 pelvic lymph node dissections, 6 nephrectomies, 2 adrenalectomies, 3 cholecystectomies, 1 small bowel resection-anastomosis, 1 cystectomy, 1 splenectomy, and 3 appendicectomies).

RESULTS

Among the various control systems tested, we adopted voice recognition on the basis of its intuitive nature and the fact that it leaves one hand free. In the light of these studies, several aspects of the prototype were modified: reliability, fixation, ergonomy and dimensions. The ease of installation, which takes only 5 minutes, and the easy handling of the robot allowed 21 out of 23 laparoscopic procedures to be performed without the need for an assistant.

CONCLUSION

The LER robot is an endoscope robot guided by the surgeon's voice that can eliminate the need for an assistant to hold the camera during laparoscopic surgery in the lateral and dorsal supine positions. The ease of installation and manufacture should make this an effective and inexpensive system. The gain in operating time was not evaluated during these trials on cadavres and pigs, as various prototypes were tested and several problems of reliability were successively resolved. Ongoing randomized, prospective clinical trials should soon validate this robot prior to marketing.

A model for predicting dissolved organic carbon distribution in a reservoir water using fluorescence spectroscopy

A number of water treatment works (WTW) in the north of England (UK) have experienced problems in reducing the dissolved organic carbon (DOC) present in the water to a sufficiently low level. The problems are experienced in autumn/winter when the colour increases and the coagulant dose at the WTW needs to be increased in order to achieve sufficient colour removal. However, the DOC content of the water varies little throughout the year. To investigate this further, the water was fractionated using resin adsorption techniques into its hydrophobic (fulvic and humic acid fractions) and hydrophilic (acid and non-acid fractions) components. The fractionation process yields useful information on the changing concentration of each fraction but is time consuming and labour intensive. Here, a method of rapidly determining fraction concentration was developed using fluorescence spectroscopy. The model created used synchronous spectra of fractionated material compared against bulk water spectra and predicted the fraction concentrations to within 10% for a specific water. The model was unable to predict fraction concentrations for waters from a different watershed.

Transesophageal echocardiography in patients with ischemic stroke accurately detects significant coronary artery stenosis and often changes management

OBJECTIVES

TEE is performed in many patients with ischemic stroke, and it is possible to examine the proximal coronaries by TEE in these patients. Our purpose was to (1) determine the accuracy of transesophageal echocardiography (TEE) in the diagnosis of proximal coronary stenosis in patients with ischemic stroke and (2) show that TEE detection of proximal coronary stenosis changed management in a substantial number of patients.

METHODS

Thirty-two patients with ischemic stroke undergoing TEE, in whom the proximal coronaries were examined and who had angiographic results available, were studied.

RESULTS

Proximal coronaries were visualized as follows: left main (LM) in 31 (97%), left anterior descending (LAD) in 32 (100%), left circumflex (LCx) in 30 (94%) and right coronary artery (RCA) in 21 (66%). The sensitivity and specificity of TEE in diagnosing significant coronary stenosis in visualized vessels were as follows: LM 100% and 100%, LAD 100% and 95%, LCx 100% and 96%, and RCA 100% and 100%, respectively. When visualized and nonvisualized segments were considered, TEE detected significant stenosis as follows: 4 of 5 in the LM (80%), 13 of 13 in the LAD (100%), 2 of 3 in the LCx (66%), and 2 of 8 in the RCA (25%). Of the 32 patients, TEE results changed management in 17 patients (53%). Angiographic findings resulted in 10 of the 17 patients (59%) undergoing revascularization.

CONCLUSIONS

TEE was very accurate in diagnosing significant coexisting coronary artery disease in patients with ischemic stroke. TEE diagnosis of these lesions prompted coronary angiography and subsequent revascularization in a substantial number of patients.

Transesophageal echocardiographic assessment of coronary stenosis: a decade of experience

Coronary artery imaging is routinely obtained invasively at cardiac catheterization through coronary angiography. This remains the gold standard, but with advances in ultrasound technology, electron beam computed tomography, and magnetic resonance imaging, newer noninvasive methodologies are achieving greater success at imaging the coronary anatomy. This review is meant to highlight the important accomplishments from transesophageal echocardiographic (TEE) investigations that have studied the coronary arteries. The specific technique for optimally imaging the coronaries with high frequency transducers, color and conventional Doppler, in addition to contrast-enhanced methods, will be analyzed. Importantly, this article serves as a reminder to echocardiographers and cardiologists that excellent, clinically relevant information of the coronary arteries can be obtained routinely during TEE. This technique is part of the trend noted by the other authors in this special edition; that is, echocardiography is becoming the gold standard of the new millennium for many diagnostic areas, even coronary angiography.

Sensitivity test on Neisseria meningitidis strains to antimicrobial drugs

1. The Authors present the antibiotic sensitivity pattern of 62 Neisseria meningitidis strains isolated in Northern Ghana (Bawku, Navrongo, Bolgatanga and Nalerigu) in February-March, 1973. The following antibiotics or chemotherapeutic drugs were effective in vitro: Penicillin 100%, Ampicillin 100%, Chloramphenicol 100%, Tetracycline 100%, Erythromycin 100% (Nalidixic acid 100%, Nitrofurantion 100%), and the following were less effective: Streptomycin 61.2%, Novobiocin 100% (weakly sensitive), Oleandomycin 95.1% (weakly sensitive), Septrin 87%, Sulphafurazole 91.9%, Sulphadiazine 91.9%. All the isolates were Colistin resistant. 2. The sex and age distribution of patients with positive culture for Neisseria meningitidis shows the preponderance of males over females and the dominance of the group of 5-15 years of age over the other age groups. These results are in good agreement with previous data collected in other countries of the "meningitis belt".