Biopsy Characteristics, Subtypes, and Prognostic Features in 107 Cases of Feline Presumed Immune-Mediated Polyneuropathy.

Inflammatory polyradiculoneuropathy (IMPN) is one of the causes of sudden onset of neuromuscular signs such as para-/tetraparesis in young cats. Even though most cases have a favorable outcome, persistent deficits, relapses, and progressive courses are occasionally seen. As clinical presentation does not always appear to predict outcome and risk of recurrence, this study was initiated to screen for prognostic biopsy findings in a large cohort of histologically confirmed IMPN cases with clinical follow-up. In total, nerve and muscle specimens of 107 cats with biopsy diagnosis of presumed autoreactive inflammatory polyneuropathy and 22 control cases were reviewed by two blinded raters for a set of 36 histological parameters. To identify patterns and subtypes of IMPN, hierarchical k-means clustering of 33 histologic variables was performed. Then, the impact of histological parameters on IMPN outcome was evaluated via an univariate analysis to identify variables for the final multivariate model. The data on immediate outcome and follow-up were collected from submitting neurologists using a purpose-designed questionnaire. Hierarchical k-means clustering sorted the tissues into 4 main categories: cluster 1 (44/129) represents a purely inflammatory IMPN picture, whereas cluster 2 (47/129) was accompanied by demyelinating features and cluster 3 (16/129) by Wallerian degeneration. Cluster 4 (22/129) reflects normal tissues from non-neuropathic control cats. Returned questionnaires provided detailed information on outcome in 63 animals. They were categorized into recovered and non-recovered. Thereby, fiber-invasive infiltrates by mononuclear cells and mild fiber loss in intramuscular nerve branches correlated with higher probabilities of recovery. Remyelination in semithin sections, on the other hand, is correlated with a less favorable outcome. Animals grouping in cluster 1 had a tendency to a higher probability of recovery compared to other clusters. In conclusion, diagnosis of feline IMPN from nerve and muscle biopsies allowed for the identification of histologic features that were positively or negatively correlated with outcome.

Clinical Course and Diagnostic Findings of Biopsy Controlled Presumed Immune-Mediated Polyneuropathy in 70 European Cats.

There is a paucity of information on the clinical course and outcome of young cats with polyneuropathy. The aim of the study was to describe the clinical features, diagnostic investigations, and outcome of a large cohort of cats with inflammatory polyneuropathy from several European countries. Seventy cats with inflammatory infiltrates in intramuscular nerves and/or peripheral nerve biopsies were retrospectively included. Information from medical records and follow up were acquired via questionnaires filled by veterinary neurologists who had submitted muscle and nerve biopsies (2011-2019). Median age at onset was 10 months (range: 4-120 months). The most common breed was British short hair (25.7%), followed by Domestic short hair (24.3%), Bengal cat (11.4%), Maine Coon (8.6%) and Persian cat (5.7%), and 14 other breeds. Male cats were predominantly affected (64.3%). Clinical signs were weakness (98.6%) and tetraparesis (75.7%) in association with decreased withdrawal reflexes (83.6%) and, less commonly, cranial nerve signs (17.1%), spinal pain/hyperesthesia (12.9%), and micturition/defecation problems (14.3%). Onset was sudden (30.1%) or insidious (69.1%), and an initial progressive phase was reported in 74.3%. Characteristic findings on electrodiagnostic examination were presence of generalized spontaneous electric muscle activity (89.6%), decreased motor nerve conduction velocity (52.3%), abnormal F-wave studies (72.4%), pattern of temporal dispersion (26.1%) and unremarkable sensory tests. The clinical course was mainly described as remittent (49.2%) or remittent-relapsing (34.9%), while stagnation, progressive course or waxing and waning were less frequently reported. Relapses were common and occurred in 35.7% of the cats' population. An overall favorable outcome was reported in 79.4% of patients. In conclusion, young age at the time of diagnosis and sudden onset of clinical signs were significantly associated with recovery (p < 0.05). Clinical and electrodiagnostic features and the remittent-relapsing clinical course resembles juvenile chronic inflammatory demyelinating polyneuropathy (CIDP), as seen in human (children/adolescents), in many aspects.

High-frequency operation of pulsatile ventricular assist devices: A computational study on circular and elliptically shaped pumps.

Pulsatile positive displacement pumps as ventricular assist devices were gradually replaced by rotary devices due to their large volume and high adverse event rates. Nevertheless, pulsatile ventricular assist devices might be beneficial with regard to gastrointestinal bleeding and cardiac recovery. Therefore, aim of this study was to investigate the flow field in new pulsatile ventricular assist devices concepts with an increased pump frequency, which would allow lower stroke volumes to reduce the pump size. We developed a novel elliptically shaped pulsatile ventricular assist devices, which we compared to a design based on a circular shape. The pump size was adjusted to deliver similar flow rates at pump frequencies of 80, 160, and 240 bpm. Through a computational fluid dynamics study, we investigated flow patterns, residence times, and wall shear stresses for different frequencies and pump sizes. A pump size reduction by almost 50% is possible when using a threefold pump frequency. We show that flow patterns inside the circular pump are frequency dependent, while they remain similar for the elliptic pump. With slightly increased wall shear stresses for higher frequencies, maximum wall shear stresses on the pump housing are higher for the circular design (42.2 Pa vs 18.4 Pa). The calculated blood residence times within the pump decrease significantly with increasing pump rates. A smaller pump size leads to a slight increase of wall shear stresses and a significant improvement of residence times. Hence, high-frequency operation of pulsatile ventricular assist devices, especially in combination with an elliptical shape, might be a feasible mean to reduce the size, without any expectable disadvantages in terms of hemocompatibility.

Fully automated detection of the counting area in blood smears for computer aided hematology.

For medical diagnosis, blood is an indispensable indicator for a wide variety of diseases, i.e. hemic, parasitic and sexually transmitted diseases. A robust detection and exact segmentation of white blood cells (leukocytes) in stained blood smears of the peripheral blood provides the base for a fully automated, image based preparation of the so called differential blood cell count in the context of medical laboratory diagnostics. Especially for the localization of the blood cells and in particular for the segmentation of the cells it is necessary to detect the working area of the blood smear. In this contribution we present an approach for locating the so called counting area on stained blood smears that is the region where cells are predominantly separated and do not interfere with each other. For this multiple images of a blood smear are taken and analyzed in order to select the image corresponding to this area. The analysis involves the computation of an unimodal function from image content that serves as indicator for the corresponding image. This requires a prior segmentation of the cells that is carried out by a binarization in the HSV color space. Finally, the indicator function is derived from the number of cells and the cells' surface area. Its unimodality guarantees to find a maximum value that corresponds to the counting areas image index. By this, a fast lookup of the counting area is performed enabling a fully automated analysis of blood smears for medical diagnosis. For an evaluation the algorithm's performance on a number of blood smears was compared with the ground truth information that has been defined by an adept hematologist.

A uniform, raytracing-based imaging model for rigid and fiber-optic endoscopy.

Modern techniques for medical diagnosis and therapy make considerable use of endoscopes. Unfortunately, the wide-angle characteristic of endoscopes introduce severe aberrations such as chromatic aberration, geometric distortion or comb-structure to the images. The aberrations hinder or at worst prevent the application of fundamental image processing techniques for an appropriate image analysis. In this paper, we propose a uniform ray-tracing based image model for rigid as well as fiber-optic endoscopes. This model enables an objective assessment of algorithms that rely on the image formation using physically correct and thus valid ground truth data.

Evaluation of spatial interpolation strategies for the removal of comb-structure in fiber-optic images.

Modern techniques for medical diagnosis and therapy in minimal invasive surgery scenarios as well as industrial inspection make considerable use of flexible, fiberoptic endoscopes in order to gain visual access to holes, hollows, antrums and cavities that are difficult to enter and examine. Unfortunately, fiber-optic endoscopes exhibit artifacts in the images that hinder or at worst prevent fundamental image analysis techniques. The dark comb-like artifacts originate from the opaque cladding layer surrounding each single fiber in the image conductor. Although the removal of comb structure is crucial for fiber-optic image analysis, literature covers only a few approaches. Those are based on Fourier analysis and make use of spectral masking or they operate in the spatial domain and rely on interpolation. In this paper, we concentrate on the latter type and introduce interpolation concepts known from related disciplines to the task of comb structure removal. For a quantitative evaluation, we perform experiments with real images as well as with bivariate test functions and rate an algorithm's performance in terms of the normalized root mean square error - a quality metric that it is most commonly used in signal processing for this purpose. Hence, this paper counters the fact that literature lacks an objective performance comparison of the state-of-the-art interpolation based approaches for this type of application.

Texture-based computer-assisted diagnosis for fiberscopic images.

Flexible endoscopes based on fiber bundles are still widely used despite the recent success of so-called tipchip endoscopes. This is partly due to the costs and that for extremely thin diameters (below 3 mm) there are still only fiberscopes available. Due to the inevitable artifacts caused by the transition from the fiber bundles to the sensor chip, image and texture analysis algorithms are severely handicapped. Therefore, texture-based computer-assisted diagnosis (CAD) systems could not be used in such domains without image preprocessing. We describe a CAD system approach that includes an image filtering algorithm to remove the fiber image artifacts first and then applies conventional color texture algorithms that have been applied to other endoscopic disciplines in the past. The concept is evaluated on an image database with artificially rendered fiber artifacts so that ground truth information is available.

Efficient large scale image stitching for virtual microscopy.

We describe a weighted least squares based global registration method for creating virtual slides. In microscopy a large number of fields of view is required to capture a complete slide. These fields of view are aligned in such a way that a globally consistent virtual slide is formed. The positioning accuracy of the presented algorithm is evaluated using a new method based on synthetic virtual slides. Using these synthetic virtual slides it is now possible to give a ground truth about the positioning accuracy of stitching algorithm for virtual microscopy. Our algorithm has been evaluated on these synthetic slides and it can be shown that on average, each image exhibits a mean deviation of 0.8 pixel with respect to the correct position. Additionally the presented algorithm has been evaluated on several real world examples.

Improving the accuracy of feature extraction for flexible endoscope calibration by spatial super resolution.

Many applications in the domain of medical as well as industrial image processing make considerable use of flexible endoscopes - so called fiberscopes - to gain visual access to holes, hollows, antrums and cavities that are difficult to enter and examine. For a complete exploration and understanding of an antrum, 3d depth information might be desirable or yet necessary. This often requires the mapping of 3d world coordinates to 2d image coordinates which is estimated by camera calibration. In order to retrieve useful results, the precise extraction of the imaged calibration pattern's markers plays a decisive role in the camera calibration process. Unfortunately, when utilizing fiberscopes, the image conductor introduces a disturbing comb structure to the images that anticipates a (precise) marker extraction. Since the calibration quality crucially depends on subpixel-precise calibration marker positions, we apply static comb structure removal algorithms along with a dynamic spatial resolution enhancement method in order to improve the feature extraction accuracy. In our experiments, we demonstrate that our approach results in a more accurate calibration of flexible endoscopes and thus allows for a more precise reconstruction of 3d information from fiberoptic images.

Physically motivated enhancement of color images for fiber endoscopy.

Fiber optics are widely used in flexible endoscopes which are indispensable for many applications in diagnosis and therapy. Computer-aided use of fiberscopes requires a digital sensor mounted at the proximal end. Most commercially available cameras for endoscopy provide the images by means of a regular grid of color filters what is known as the Bayer Pattern. Hence, the images suffer from false colored spatial moiré, which is further stressed by the downgrading fiber optic transmission yielding a honey comb pattern. To solve this problem we propose a new approach that extends the interpolation between known intensities of registered fibers to multi channel color applications. The inventive idea takes into account both the Gaussian intensity distribution of each fiber and the physical color distribution of the Bayer pattern. Individual color factors for interpolation of each fiber area make it possible to simultaneously remove both the comb structure from the fiber bundle as well as the Bayer pattern mosaicking from the sensor while preserving depicted structures and textures in the scene.

Automatic adaptive enhancement for images obtained with fiberscopic endoscopes.

Modern techniques for medical diagnostics and therapy in keyhole surgery scenarios as well as technical inspection make use of flexible endoscopes. Their characteristic bendable image conductor consists of a very limited number of coated fibers, which leads to so-called comb structure. This effect has a negative impact on further image processing steps such as feature tracking because these overlaid image structures are wrongly detected as image features. With respect to these tasks, we propose an automatic approach to generate optimal spectral filter masks for enhancement of fiberscopic images. We apply the Nyquist-Shannon sampling theorem to the spectrum of fiberscopically acquired images to obtain parameters for optimal filter mask calculation. This can be done automatically and independently of scale and resolution of the image conductor as well as type and resolution of the image sensor. We designed and verified simple rotation invariant masks as well as star-shaped rotation variant masks that contain information about orientation between the fiberscope and sensor. A subjective survey among experts between different modes of filtering certified the best results to the adapted star-shaped mask for high-quality glass fiberscopes. We furthermore define an objective metric to evaluate the results of different filter approaches, which verifies the results of the subjective survey. The proposed approach enables the automated reduction of fiberscopic comb structure. It is adaptive to arbitrary endoscope and sensor combinations. The results give the prospect of a large field of possible applications to reduce fiberscopic structure both for visual optimization in clinical environments and for further digital imaging tasks.