Vision-based Proximity Detection in Retinal Surgery

In retinal surgery, surgeons face difficulties such as indirect visualization of surgical targets, physiological tremor, and lack of tactile feedback, which increase the risk of retinal damage caused by incorrect surgical gestures. In this context, intraocular proximity sensing has the potential to overcome current technical limitations and increase surgical safety. In this paper, we present a system for detecting unintentional collisions between surgical tools and the retina using the visual feedback provided by the opthalmic stereo microscope. Using stereo images, proximity between surgical tools and the retinal surface can be detected when their relative stereo disparity is small. For this purpose, we developed a system comprised of two modules. The first is a module for tracking the surgical tool position on both stereo images. The second is a disparity tracking module for estimating a stereo disparity map of the retinal surface. Both modules were specially tailored for coping with the challenging visualization conditions in retinal surgery. The potential clinical value of the proposed method is demonstrated by extensive testing using a silicon phantom eye and recorded rabbit in vivo data.

Software-based detection of atrial fibrillation in long-term ECGs

Background Atrial fibrillation (AF) is common and may have severe consequences. Continuous long-term electrocardiogram (ECG) is widely used for AF screening. Recently, commercial ECG analysis software was launched, which automatically detects AF in long-term ECGs. It has been claimed that such tools offer reliable AF screening and save time for ECG analysis. However, this has not been investigated in a real-life patient cohort. Objective To investigate the performance of automatic software-based screening for AF in long-term ECGs. Methods Two independent physicians manually screened 22,601 hours of continuous long-term ECGs from 150 patients for AF. Presence, number, and duration of AF episodes were registered. Subsequently, the recordings were screened for AF by an established ECG analysis software (Pathfinder SL), and its performance was validated against the thorough manual analysis (gold standard). Results Sensitivity and specificity for AF detection was 98.5% (95% confidence interval 91.72%–99.96%) and 80.21% (95% confidence interval 70.83%–87.64%), respectively. Software-based AF detection was inferior to manual analysis by physicians (P < .0001). Median AF duration was underestimated (19.4 hours vs 22.1 hours; P < .001) and median number of AF episodes was overestimated (32 episodes vs 2 episodes; P < .001) by the software. In comparison to extensive quantitative manual ECG analysis, software-based analysis saved time (2 minutes vs 19 minutes; P < .001). Conclusion Owing to its high sensitivity and ability to save time, software-based ECG analysis may be used as a screening tool for AF. An additional manual confirmatory analysis may be required to reduce the number of false-positive findings.

Surgical planning tool for robotically assisted hearing aid implantation

PURPOSE : For the facilitation of minimally invasive robotically performed direct cochlea access (DCA) procedure, a surgical planning tool which enables the surgeon to define landmarks for patient-to-image registration, identify the necessary anatomical structures and define a safe DCA trajectory using patient image data (typically computed tomography (CT) or cone beam CT) is required. To this end, a dedicated end-to-end software planning system for the planning of DCA procedures that addresses current deficiencies has been developed. METHODS :    Efficient and robust anatomical segmentation is achieved through the implementation of semiautomatic algorithms; high-accuracy patient-to-image registration is achieved via an automated model-based fiducial detection algorithm and functionality for the interactive definition of a safe drilling trajectory based on case-specific drill positioning uncertainty calculations was developed. RESULTS :    The accuracy and safety of the presented software tool were validated during the conduction of eight DCA procedures performed on cadaver heads. The plan for each ear was completed in less than 20 min, and no damage to vital structures occurred during the procedures. The integrated fiducial detection functionality enabled final positioning accuracies of [Formula: see text] mm. CONCLUSIONS :    Results of this study demonstrated that the proposed software system could aid in the safe planning of a DCA tunnel within an acceptable time.

The Family Pasteurellaceae

This chapter describes the systematics and evolution of Pasteurellaceae with emphasis on new information generated since the 3rd edition of The Prokaryotes which only included chapters dealing with Haemophilus, Actinobacillus, and Pasteurella. A major source of new information for the current chapter has been provided by whole genome sequences now available for many taxa of the family. Some 100 species and species-like taxa have been documented and 18 genera of Pasteurellaceae reported so far. Members of the family include specialized commensals, potential pathogens, or pathogens of vertebrates and mainly survive poorly in other habitats including the external environment. The pathogenic members are of major importance to animal production and human health. Members of Pasteurellaceae have relatively small genomes, probably as a result of adaption to a special habitat. The most important species in veterinary microbiology include Pasteurella multocida, Actinobacillus pleuropneumoniae, [Haemophilus] parasuis, Mannheimia haemolytica, Bibersteinia trehalosi, and Avibacterium paragallinarum, while Haemophilus influenzae and Aggregatibacter actinomycetemcomitans represent the most important species as to human disease. Traditional isolation techniques are still used in both human and veterinary clinical diagnostic laboratories although genetically based diagnostic methods have replaced traditional biochemical/physiological methods for characterization and identification. For all species, MALDI-TOF can now be used as a diagnostic tool. As control and if MALDI-TOF equipment is not at hand, PCR-based specific detection is possible for Pasteurella multocida, Actinobacillus pleuropneumoniae, [Haemophilus] parasuis, Mannheimia haemolytica, Avibacterium paragallinarum, Gallibacterium anatis, Haemophilus influenzae, and Aggregatibacter actinomycetemcomitans. A lot of work has been directed towards identification of virulence factors and understanding host microbe interactions involved in disease.

Fully Automatic CT Segmentation for Computer-Assisted Pre-operative Planning of Hip Arthroscopy

Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assisted pre-operative planning of hip arthroscopy is addressed. We present a method for a fully automatic image segmentation of a hip joint. Our method works by combining fast random forest (RF) regression based landmark detection, atlas-based segmentation, with articulated statistical shape model (aSSM) based hip joint reconstruction. The two fundamental contributions of our method are: (1) An improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the atlas-based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Validation on 30 hip CT images show that our method achieves high performance in segmenting pelvis, left proximal femur, and right proximal femur surfaces with an average accuracy of 0.59 mm, 0.62 mm, and 0.58 mm, respectively.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

FACTS: Fully Automatic CT Segmentation of a Hip Joint

Extraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications.

Fully Automatic Segmentation of Hip CT Images

Automatic segmentation of the hip joint with pelvis and proximal femur surfaces from CT images is essential for orthopedic diagnosis and surgery. It remains challenging due to the narrowness of hip joint space, where the adjacent surfaces of acetabulum and femoral head are hardly distinguished from each other. This chapter presents a fully automatic method to segment pelvic and proximal femoral surfaces from hip CT images. A coarse-to-fine strategy was proposed to combine multi-atlas segmentation with graph-based surface detection. The multi-atlas segmentation step seeks to coarsely extract the entire hip joint region. It uses automatically detected anatomical landmarks to initialize and select the atlas and accelerate the segmentation. The graph based surface detection is to refine the coarsely segmented hip joint region. It aims at completely and efficiently separate the adjacent surfaces of the acetabulum and the femoral head while preserving the hip joint structure. The proposed strategy was evaluated on 30 hip CT images and provided an average accuracy of 0.55, 0.54, and 0.50 mm for segmenting the pelvis, the left and right proximal femurs, respectively.

Sensitive and rapid detection of ganciclovir resistance by PCR based MALDI-TOF analysis

Cytomegalovirus (CMV) infection is associated with significant morbidity and mortality in transplant recipients. Resistance against ganciclovir is increasingly observed. According to current guidelines, direct drug resistance testing is not always performed due to high costs and work effort, even when resistance is suspected.

The performance of conventional and fluorescence-based methods for occlusal caries detection: an in vivo study with histologic validation

The authors conducted an in vivo study to determine clinical cutoffs for a laser fluorescence (LF) device, an LF pen and a fluorescence camera (FC), as well as to evaluate the clinical performance of these methods and conventional methods in detecting occlusal caries in permanent teeth by using the histologic gold standard for total validation of the sample.

Detection of Mycoplasma mycoides subsp. mycoides SC in bronchoalveolar lavage fluids of cows based on a TaqMan real-time PCR discriminating wild type strains from an lppQ(-) mutant vaccine strain used for DIVA-strategies

Contagious bovine pleuropneumonia (CBPP) is the most serious cattle disease in Africa, caused by Mycoplasma mycoides subsp. mycoides small-colony type (SC). CBPP control strategies currently rely on vaccination with a vaccine based on live attenuated strains of the organism. Recently, an lppQ(-) mutant of the existing vaccine strain T1/44 has been developed (Janis et al., 2008). This T1lppQ(-) mutant strain is devoid of lipoprotein LppQ, a potential virulence attribute of M. mycoides subsp. mycoides SC. It is designated as a potential live DIVA (Differentiating Infected from Vaccinated Animals) vaccine strain allowing both serological and etiological differentiation. The present paper reports on the validation of a control strategy for CBPP in cattle, whereby a TaqMan real-time PCR based on the lppQ gene has been developed for the direct detection of M. mycoides subsp. mycoides SC in ex vivo bronchoalveolar lavage fluids of cows and for the discrimination of wild type strains from the lppQ(-) mutant vaccine strain.

Non-invasive gene-expression-based detection of well-developed collateral function in individuals with and without coronary artery disease

BACKGROUND: In patients with coronary artery disease (CAD), a well grown collateral circulation has been shown to be important. The aim of this prospective study using peripheral blood monocytes was to identify marker genes for an extensively grown coronary collateral circulation. METHODS: Collateral flow index (CFI) was obtained invasively by angioplasty pressure sensor guidewire in 160 individuals (110 patients with CAD, and 50 individuals without CAD). RNA was extracted from monocytes followed by microarray-based gene-expression analysis. 76 selected genes were analysed by real-time polymerase chain reaction (PCR). A receiver operating characteristics analysis based on differential gene expression was then performed to separate individuals with poor (CFI<0.21) and well-developed collaterals (CFI>or=0.21) Thereafter, the influence of the chemokine MCP-1 on the expression of six selected genes was tested by PCR. RESULTS: The expression of 203 genes significantly correlated with CFI (p = 0.000002-0.00267) in patients with CAD and 56 genes in individuals without CAD (p = 00079-0.0430). Biological pathway analysis revealed 76 of those genes belonging to four different pathways: angiogenesis, integrin-, platelet-derived growth factor-, and transforming growth factor beta-signalling. Three genes in each subgroup differentiated with high specificity among individuals with low and high CFI (>or=0.21). Two out of these genes showed pronounced differential expression between the two groups after cell stimulation with MCP-1. CONCLUSIONS: Genetic factors play a role in the formation and the preformation of the coronary collateral circulation. Gene expression analysis in peripheral blood monocytes can be used for non-invasive differentiation between individuals with poorly and with well grown collaterals. MCP-1 can influence the arteriogenic potential of monocytes.