Microbiota-mediated fine-tuning of the threshold of intestinal inflammasome activation in host-microbial mutualism

The inflammasome is a complex of proteins that controls the activity of caspase-1, pro-IL-1b and pro-IL-18. It acts in inflammatory processes and in pyropoptosis. The lower intestine is densely populated by a community of commensal bacteria that, under healthy conditions, are beneficial to the host. Some evidence suggests that the gut microbiota influences regulation of the inflammasome. Components of inflammasomes have been shown to have a protective function against development of experimental colitis, dependent on IL-18 production. However the precise mechanisms and the role of the inflammasome in maintaining a healthy host-microbial mutualism remains unknown. To address this question, we have performed axenic (GF) and gnotobiotic in vivo experiments to investigate how the inflammasome components mainly at the level of intestinal epithelial cells (IECs) are regulated under different hygiene conditions. We have established that gene expression of the inflammasome components NLRC4, NLRP3, NLRP6, NLRP12, caspase-1, ASC and IL-18 do not differ between germ-free and colonised conditions under steady-state. In contrast, induction in IL-18 was observed following infection with the pathobiont Segmented Filamentous Bacteria or the pathogen C. rodentium. Additional preliminar findings suggest that a more diverse intestinal flora, like specific pathogen-free (SPF) flora, is more efficient in inducing basal activation of the inflammasome and especially production of IL-18 by IECs, shortly after colonisation. We are also in the process of testing if basal activation of the inflammasome upon intestinal colonization with commensal bacteria helps to protect the host from potential pathobiont bacteria, like C. rodentium, SFB, Prevotella and TM7.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

A complete-pelvis segmentation framework for image-free total hip arthroplasty (THA): methodology and clinical study

Background Complete-pelvis segmentation in antero-posterior pelvic radiographs is required to create a patient-specific three-dimensional pelvis model for surgical planning and postoperative assessment in image-free navigation of total hip arthroplasty. Methods A fast and robust framework for accurately segmenting the complete pelvis is presented, consisting of two consecutive modules. In the first module, a three-stage method was developed to delineate the left hemipelvis based on statistical appearance and shape models. To handle complex pelvic structures, anatomy-specific information processing techniques were employed. As the input to the second module, the delineated left hemi-pelvis was then reflected about an estimated symmetry line of the radiograph to initialize the right hemi-pelvis segmentation. The right hemi-pelvis was segmented by the same three-stage method, Results Two experiments conducted on respectively 143 and 40 AP radiographs demonstrated a mean segmentation accuracy of 1.61±0.68 mm. A clinical study to investigate the postoperative assessment of acetabular cup orientations based on the proposed framework revealed an average accuracy of 1.2°±0.9° and 1.6°±1.4° for anteversion and inclination, respectively. Delineation of each radiograph costs less than one minute. Conclusions Despite further validation needed, the preliminary results implied the underlying clinical applicability of the proposed framework for image-free THA.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Fusion of fundus images and MRI data of the human eye

Purpose Ophthalmologists are confronted with a set of different image modalities to diagnose eye tumors e.g., fundus photography, CT and MRI. However, these images are often complementary and represent pathologies differently. Some aspects of tumors can only be seen in a particular modality. A fusion of modalities would improve the contextual information for diagnosis. The presented work attempts to register color fundus photography with MRI volumes. This would complement the low resolution 3D information in the MRI with high resolution 2D fundus images. Methods MRI volumes were acquired from 12 infants under the age of 5 with unilateral retinoblastoma. The contrast-enhanced T1-FLAIR sequence was performed with an isotropic resolution of less than 0.5mm. Fundus images were acquired with a RetCam camera. For healthy eyes, two landmarks were used: the optic disk and the fovea. The eyes were detected and extracted from the MRI volume using a 3D adaption of the Fast Radial Symmetry Transform (FRST). The cropped volume was automatically segmented using the Split Bregman algorithm. The optic nerve was enhanced by a Frangi vessel filter. By intersection the nerve with the retina the optic disk was found. The fovea position was estimated by constraining the position with the angle between the optic and the visual axis as well as the distance from the optic disk. The optical axis was detected automatically by fitting a parable on to the lens surface. On the fundus, the optic disk and the fovea were detected by using the method of Budai et al. Finally, the image was projected on to the segmented surface using the lens position as the camera center. In tumor affected eyes, the manually segmented tumors were used instead of the optic disk and macula for the registration. Results In all of the 12 MRI volumes that were tested the 24 eyes were found correctly, including healthy and pathological cases. In healthy eyes the optic nerve head was found in all of the tested eyes with an error of 1.08 +/- 0.37mm. A successful registration can be seen in figure 1. Conclusions The presented method is a step toward automatic fusion of modalities in ophthalmology. The combination enhances the MRI volume with higher resolution from the color fundus on the retina. Tumor treatment planning is improved by avoiding critical structures and disease progression monitoring is made easier.

Manual Electrode Array Insertion Through a Robot-assisted Minimal Invasive Cochleostomy: Feasibility and Comparison of Two Different Electrode Array Subtypes.

HYPOTHESIS To evaluate the feasibility and the results of insertion of two types of electrode arrays in a robotically assisted surgical approach. BACKGROUND Recent publications demonstrated that robot-assisted surgery allows the implantation of free-fitting electrode arrays through a cochleostomy drilled via a narrow bony tunnel (DCA). We investigated if electrode arrays from different manufacturers could be used with this approach. METHODS Cone-beam CT imaging was performed on fivecadaveric heads after placement of fiducial screws. Relevant anatomical structures were segmented and the DCA trajectory, including the position of the cochleostomy, was defined to target the center of the scala tympani while reducing the risk of lesions to the facial nerve. Med-El Flex 28 and Cochlear CI422 electrodes were implanted on both sides, and their position was verified by cone-beam CT. Finally, temporal bones were dissected to assess the occurrence of damage to anatomical structures during DCA drilling. RESULTS The cochleostomy site was directed in the scala tympani in 9 of 10 cases. The insertion of electrode arrays was successful in 19 of 20 attempts. No facial nerve damage was observed. The average difference between the planned and the postoperative trajectory was 0.17 ± 0.19 mm at the level of the facial nerve. The average depth of insertion was 305.5 ± 55.2 and 243 ± 32.1 degrees with Med-El and Cochlear arrays, respectively. CONCLUSIONS Robot-assisted surgery is a reliable tool to allow cochlear implantation through a cochleostomy. Technical solutions must be developed to improve the electrode array insertion using this approach.

Details of left ventricular radial wall motion supporting the ventricular theory of the third heart sound obtained by cardiac MR.

OBJECTIVE Obtaining new details of radial motion of left ventricular (LV) segments using velocity-encoding cardiac MRI. METHODS Cardiac MR examinations were performed on 14 healthy volunteers aged between 19 and 26 years. Cine images for navigator-gated phase contrast velocity mapping were acquired using a black blood segmented κ-space spoiled gradient echo sequence with a temporal resolution of 13.8 ms. Peak systolic and diastolic radial velocities as well as radial velocity curves were obtained for 16 ventricular segments. RESULTS Significant differences among peak radial velocities of basal and mid-ventricular segments have been recorded. Particular patterns of segmental radial velocity curves were also noted. An additional wave of outward radial movement during the phase of rapid ventricular filling, corresponding to the expected timing of the third heart sound, appeared of particular interest. CONCLUSION The technique has allowed visualization of new details of LV radial wall motion. In particular, higher peak systolic radial velocities of anterior and inferior segments are suggestive of a relatively higher dynamics of anteroposterior vs lateral radial motion in systole. Specific patterns of radial motion of other LV segments may provide additional insights into LV mechanics. ADVANCES IN KNOWLEDGE The outward radial movement of LV segments impacted by the blood flow during rapid ventricular filling provides a potential substrate for the third heart sound. A biphasic radial expansion of the basal anteroseptal segment in early diastole is likely to be related to the simultaneous longitudinal LV displacement by the stretched great vessels following repolarization and their close apposition to this segment.

Using MDEFT MRI Sequences to Target the GPi in DBS Surgery.

OBJECTIVE Recent advances in different MRI sequences have enabled direct visualization and targeting of the Globus pallidus internus (GPi) for DBS surgery. Modified Driven Equilibrium Fourier Transform (MDEFT) MRI sequences provide high spatial resolution and an excellent contrast of the basal ganglia with low distortion. In this study, we investigate if MDEFT sequences yield accurate and reliable targeting of the GPi and compare direct targeting based on MDEFT sequences with atlas-based targeting. METHODS 13 consecutive patients considered for bilateral GPi-DBS for dystonia or PD were included in this study. Preoperative targeting of the GPi was performed visually based on MDEFT sequences as well as by using standard atlas coordinates. Postoperative CT imaging was performed to calculate the location of the implanted leads as well as the active electrode(s). The coordinates of both visual and atlas based targets were compared. The stereotactic coordinates of the lead and active electrode(s) were calculated and projected on the segmented GPi. RESULTS On MDEFT sequences the GPi was well demarcated in most patients. Compared to atlas-based planning the mean target coordinates were located significantly more posterior. Subgroup analysis showed a significant difference in the lateral coordinate between dystonia (LAT = 19.33 ± 0.90) and PD patients (LAT = 20.67 ± 1.69). Projected on the segmented preoperative GPi the active contacts of the DBS electrode in both dystonia and PD patients were located in the inferior and posterior part of the structure corresponding to the motor part of the GPi. CONCLUSIONS MDEFT MRI sequences provide high spatial resolution and an excellent contrast enabling precise identification and direct visual targeting of the GPi. Compared to atlas-based targeting, it resulted in a significantly different mean location of our target. Furthermore, we observed a significant variability of the target among the PD and dystonia subpopulation suggesting accurate targeting for each individual patient.

Quantitative Analysis of Mouse Retinal Layers Using Automated Segmentation of Spectral Domain Optical Coherence Tomography Images.

PURPOSE Quantification of retinal layers using automated segmentation of optical coherence tomography (OCT) images allows for longitudinal studies of retinal and neurological disorders in mice. The purpose of this study was to compare the performance of automated retinal layer segmentation algorithms with data from manual segmentation in mice using the Spectralis OCT. METHODS Spectral domain OCT images from 55 mice from three different mouse strains were analyzed in total. The OCT scans from 22 C57Bl/6, 22 BALBc, and 11 C3A.Cg-Pde6b(+)Prph2(Rd2) /J mice were automatically segmented using three commercially available automated retinal segmentation algorithms and compared to manual segmentation. RESULTS Fully automated segmentation performed well in mice and showed coefficients of variation (CV) of below 5% for the total retinal volume. However, all three automated segmentation algorithms yielded much thicker total retinal thickness values compared to manual segmentation data (P < 0.0001) due to segmentation errors in the basement membrane. CONCLUSIONS Whereas the automated retinal segmentation algorithms performed well for the inner layers, the retinal pigmentation epithelium (RPE) was delineated within the sclera, leading to consistently thicker measurements of the photoreceptor layer and the total retina. TRANSLATIONAL RELEVANCE The introduction of spectral domain OCT allows for accurate imaging of the mouse retina. Exact quantification of retinal layer thicknesses in mice is important to study layers of interest under various pathological conditions.

Comparison of proximal femur and vertebral body strength improvements in the FREEDOM trial using an alternative finite element methodology

Denosumab reduced the incidence of new fractures in postmenopausal women with osteoporosis by 68% at the spine and 40% at the hip over 36 months compared with placebo in the FREEDOM study. This efficacy was supported by improvements from baseline in vertebral (18.2%) strength in axial compression and femoral (8.6%) strength in sideways fall configuration at 36 months, estimated in Newtons by an established voxel-based finite element (FE) methodology. Since FE analyses rely on the choice of meshes, material properties, and boundary conditions, the aim of this study was to independently confirm and compare the effects of denosumab on vertebral and femoral strength during the FREEDOM trial using an alternative smooth FE methodology. Unlike the previous FE study, effects on femoral strength in physiological stance configuration were also examined. QCT data for the proximal femur and two lumbar vertebrae were analyzed by smooth FE methodology at baseline, 12, 24, and 36 months for 51 treated (denosumab) and 47 control (placebo) subjects. QCT images were segmented and converted into smooth FE models to compute bone strength. L1 and L2 vertebral bodies were virtually loaded in axial compression and the proximal femora in both fall and stance configurations. Denosumab increased vertebral body strength by 10.8%, 14.0%, and 17.4% from baseline at 12, 24, and 36 months, respectively (p < 0.0001). Denosumab also increased femoral strength in the fall configuration by 4.3%, 5.1%, and 7.2% from baseline at 12, 24, and 36 months, respectively (p < 0.0001). Similar improvements were observed in the stance configuration with increases of 4.2%, 5.2%, and 5.2% from baseline (p ≤ 0.0007). Differences between the increasing strengths with denosumab and the decreasing strengths with placebo were significant starting at 12 months (vertebral and femoral fall) or 24 months (femoral stance). Using an alternative smooth FE methodology, we confirmed the significant improvements in vertebral body and proximal femur strength previously observed with denosumab. Estimated increases in strength with denosumab and decreases with placebo were highly consistent between both FE techniques.

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

Characterization of Chelonus inanitus polydnavirus segments: sequences and analysis, excision site and demonstration of clustering

Polydnaviruses (genera Ichnovirus and Bracovirus) have a segmented genome of circular double-stranded DNA molecules, replicate in the ovary of parasitic wasps and are essential for successful parasitism of the host. Here we show the first detailed analysis of various segments of a bracovirus, the Chelonus inanitus virus (CiV). Four segments were sequenced and two of them, CiV12 and CiV14, were found to be closely related while CiV14.5 and CiV16.8 were unrelated. CiV12, CiV14.5 and CiV16.8 are unique while CiV14 occurs also nested in another larger segment. All four segments are predicted to contain genes and predictions could be substantiated in most cases. Comparison with databases revealed no significant similarities at either the nucleotide or amino acid level. Inverted repeats with identities between 77% and 92% and lengths between 26 bp and 100 bp were found on all segments outside of predicted genes. Hybridization experiments indicate that CiV12 and CiV14 are both flanked by other virus segments, suggesting that proviral CiV segments are clustered in the genome of the wasp. The integration/excision site of CiV14 was analysed and compared to that of CiV12. On both termini of proviral CiV12 and CiV14 as well as in the excised circular molecule and the rejoined DNA a very similar repeat of 14 bp was found. A model to illustrate where the terminal repeats might recombine to yield the circular molecule is presented. Excision of CiV12 and CiV14 is restricted to the female and sets in at a very specific time-point in pupal-adult development.

Presence of polydnavirus transcripts in an egg-larval parasitoid and its lepidopterous host

The parasitoid Chelonus inanitus (Braconidae, Hymenoptera) oviposits into eggs of Spodoptera littoralis (Noctuidae, Lepidoptera) and, along with the egg, also injects polydnaviruses and venom, which are prerequisites for successful parasitoid development. The parasitoid larva develops within the embryonic and larval stages of the host, which enters metamorphosis precociously and arrests development in the prepupal stage. Polydnaviruses are responsible for the developmental arrest and interfere with the host's endocrine system in the last larval instar. Polydnaviruses have a segmented genome and are transmitted as a provirus integrated in the wasp's genome. Virions are only formed in female wasps and no virus replication is seen in the parasitized host. Here it is shown that very small amounts of viral transcripts were found in parasitized eggs and early larval instars of S. littoralis. Later on, transcript quantities increased and were highest in the late last larval instar for two of the three viral segments tested and in the penultimate to early last larval instar for the third segment. These are the first data on the occurrence of viral transcripts in the host of an egg-larval parasitoid and they are different from data reported for hosts of larval parasitoids, where transcript levels are already high shortly after parasitization. The analysis of three open reading frames by RT-PCR revealed viral transcripts in parasitized S. littoralis and in female pupae of C. inanitus, indicating the absence of host specificity. For one open reading frame, transcripts were also seen in male pupae, suggesting transcription from integrated viral DNA.

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.