Prestimulus EEG microstates influence visual event-related potential microstates in field maps with 47 channels

The influence of the immediate prestimulus EEG microstate (sub-second epoch of stable topography/map landscape) on the map landscape of visually evoked 47-channel event-related potential (ERP) microstates was examined using the frequent, non-target stimuli of a cognitive paradigm (12 volunteers). For the two most frequent prestimulus microstate classes (oriented left anterior-right posterior and right anterior-left posterior), ERP map series were selectively averaged. The post-stimulus ERP grand average map series was segmented into microstates; 10 were found. The centroid locations of positive and negative map areas were extracted as landscape descriptors. Significant differences (MANOVAs and t-tests) between the two prestimulus classes were found in four of the ten ERP microstates. The relative orientation of the two ERP microstate classes was the same as prestimulus in some ERP microstates, but reversed in others. — Thus, brain electric microstates at stimulus arrival influence the landscapes of the post-stimulus ERP maps and therefore, information processing; prestimulus microstate effects differed for different post-stimulus ERP microstates.

Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts

Prompted reports of recall of spontaneous, conscious experiences were collected in a no-input, no-task, no-response paradigm (30 random prompts to each of 13 healthy volunteers). The mentation reports were classified into visual imagery and abstract thought. Spontaneous 19-channel brain electric activity (EEG) was continuously recorded, viewed as series of momentary spatial distributions (maps) of the brain electric field and segmented into microstates, i.e. into time segments characterized by quasi-stable landscapes of potential distribution maps which showed varying durations in the sub-second range. Microstate segmentation used a data-driven strategy. Different microstates, i.e. different brain electric landscapes must have been generated by activity of different neural assemblies and therefore are hypothesized to constitute different functions. The two types of reported experiences were associated with significantly different microstates (mean duration 121 ms) immediately preceding the prompts; these microstates showed, across subjects, for abstract thought (compared to visual imagery) a shift of the electric gravity center to the left and a clockwise rotation of the field axis. Contrariwise, the microstates 2 s before the prompt did not differ between the two types of experiences. The results support the hypothesis that different microstates of the brain as recognized in its electric field implement different conscious, reportable mind states, i.e. different classes (types) of thoughts (mentations); thus, the microstates might be candidates for the `atoms of thought'.

Quantification of Popliteal Artery Deformation During Leg Flexion in Subjects With Peripheral Artery Disease: A Pilot Study

Purpose: To quantify the in vivo deformations of the popliteal artery during leg flexion in subjects with clinically relevant peripheral artery disease (PAD). Methods: Five patients (4 men; mean age 69 years, range 56–79) with varying calcification levels of the popliteal artery undergoing endovascular revascularization underwent 3-dimensional (3D) rotational angiography. Image acquisition was performed with the leg straight and with a flexion of 70°/20° in the knee/hip joints. The arterial centerline and the corresponding branches in both positions were segmented to create 3D reconstructions of the arterial trees. Axial deformation, twisting, and curvatures were quantified. Furthermore, the relationships between the calcification levels and the deformations were investigated. Results: An average shortening of 5.9%±2.5% and twist rate of 3.8±2.2°/cm in the popliteal artery were observed. Maximal curvatures in the straight and flexed positions were 0.12±0.04 cm−1 and 0.24±0.09 cm−1, respectively. As the severity of calcification increased, the maximal curvature in the straight position increased from 0.08 to 0.17 cm−1, while an increase from 0.17 to 0.39 cm−1 was observed for the flexed position. Axial elongations and arterial twisting were not affected by the calcification levels. Conclusion: The popliteal artery of patients with symptomatic PAD is exposed to significant deformations during flexion of the knee joint. The severity of calcification directly affects curvature, but not arterial length or twisting angles. This pilot study also showed the ability of rotational angiography to quantify the 3D deformations of the popliteal artery in patients with various levels of calcification.

In vitro accuracy evaluation of image-guided robot system for direct cochlear access

HYPOTHESIS A previously developed image-guided robot system can safely drill a tunnel from the lateral mastoid surface, through the facial recess, to the middle ear, as a viable alternative to conventional mastoidectomy for cochlear electrode insertion. BACKGROUND Direct cochlear access (DCA) provides a minimally invasive tunnel from the lateral surface of the mastoid through the facial recess to the middle ear for cochlear electrode insertion. A safe and effective tunnel drilled through the narrow facial recess requires a highly accurate image-guided surgical system. Previous attempts have relied on patient-specific templates and robotic systems to guide drilling tools. In this study, we report on improvements made to an image-guided surgical robot system developed specifically for this purpose and the resulting accuracy achieved in vitro. MATERIALS AND METHODS The proposed image-guided robotic DCA procedure was carried out bilaterally on 4 whole head cadaver specimens. Specimens were implanted with titanium fiducial markers and imaged with cone-beam CT. A preoperative plan was created using a custom software package wherein relevant anatomical structures of the facial recess were segmented, and a drill trajectory targeting the round window was defined. Patient-to-image registration was performed with the custom robot system to reference the preoperative plan, and the DCA tunnel was drilled in 3 stages with progressively longer drill bits. The position of the drilled tunnel was defined as a line fitted to a point cloud of the segmented tunnel using principle component analysis (PCA function in MatLab). The accuracy of the DCA was then assessed by coregistering preoperative and postoperative image data and measuring the deviation of the drilled tunnel from the plan. The final step of electrode insertion was also performed through the DCA tunnel after manual removal of the promontory through the external auditory canal. RESULTS Drilling error was defined as the lateral deviation of the tool in the plane perpendicular to the drill axis (excluding depth error). Errors of 0.08 ± 0.05 mm and 0.15 ± 0.08 mm were measured on the lateral mastoid surface and at the target on the round window, respectively (n =8). Full electrode insertion was possible for 7 cases. In 1 case, the electrode was partially inserted with 1 contact pair external to the cochlea. CONCLUSION The purpose-built robot system was able to perform a safe and reliable DCA for cochlear implantation. The workflow implemented in this study mimics the envisioned clinical procedure showing the feasibility of future clinical implementation.

Topographic bone thickness maps for Bonebridge implantations.

Bonebridge™ (BB) implantation relies on optimal anchoring of the bone-conduction implant in the temporal bone. Preoperative position planning has to account for the available bone thickness minimizing unwanted interference with underlying anatomical structures. This study describes the first clinical experience with a planning method based on topographic bone thickness maps (TBTM) for presigmoid BB implantations. The temporal bone was segmented enabling three-dimensional surface generation. Distances between the external and internal surface were color encoded and mapped to a TBTM. Suitable implant positions were planned with reference to the TBTM. Surgery was performed according to the standard procedure (n = 7). Computation of the TBTM and consecutive implant position planning took 70 min on average for a trained technician. Surgical time for implantations under passive TBTM image guidance was 60 min, on average. The sigmoid sinus (n = 5) and dura mater (n = 1) were exposed, as predicted with the TBTM. Feasibility of the TBTM method was shown for standard presigmoid BB implantations. The projection of three-dimensional bone thickness information into a single topographic map provides the surgeon with an intuitive display of the anatomical situation prior to implantation. Nevertheless, TBTM generation time has to be significantly reduced to simplify integration in clinical routine.

Insular and caudate lesions release abnormal yawning in stroke patients.

Abnormal yawning is an underappreciated phenomenon in patients with ischemic stroke. We aimed at identifying frequently affected core regions in the supratentorial brain of stroke patients with abnormal yawning and contributing to the anatomical network concept of yawning control. Ten patients with acute anterior circulation stroke and ≥3 yawns/15 min without obvious cause were analyzed. The NIH stroke scale (NIHSS), Glasgow Coma Scale (GCS), symptom onset, period with abnormal yawning, blood oxygen saturation, glucose, body temperature, blood pressure, heart rate, and modified Rankin scale (mRS) were assessed for all patients. MRI lesion maps were segmented on diffusion-weighted images, spatially normalized, and the extent of overlap between the different stroke patterns was determined. Correlations between the period with abnormal yawning and the apparent diffusion coefficient (ADC) in the overlapping regions, total stroke volume, NIHSS and mRS were performed. Periods in which patients presented with episodes of abnormal yawning lasted on average for 58 h. Average GCS, NIHSS, and mRS scores were 12.6, 11.6, and 3.5, respectively. Clinical parameters were within normal limits. Ischemic brain lesions overlapped in nine out of ten patients: in seven patients in the insula and in seven in the caudate nucleus. The decrease of the ADC within the lesions correlated with the period with abnormal yawing (r = -0.76, Bonferroni-corrected p = 0.02). The stroke lesion intensity of the common overlapping regions in the insula and the caudate nucleus correlates with the period with abnormal yawning. The insula might be the long sought-after brain region for serotonin-mediated yawning.

Segmentation and Recognition of Multi-Food Meal Images for Carbohydrate Counting

In this paper, we propose novel methodologies for the automatic segmentation and recognition of multi-food images. The proposed methods implement the first modules of a carbohydrate counting and insulin advisory system for type 1 diabetic patients. Initially the plate is segmented using pyramidal mean-shift filtering and a region growing algorithm. Then each of the resulted segments is described by both color and texture features and classified by a support vector machine into one of six different major food classes. Finally, a modified version of the Huang and Dom evaluation index was proposed, addressing the particular needs of the food segmentation problem. The experimental results prove the effectiveness of the proposed method achieving a segmentation accuracy of 88.5% and recognition rate equal to 87%

Landmark Detection for Fusion of Fundus and MRI Towards a Patient-Specific Multi-Modal Eye Model

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The presented article’s goal is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI which was not visible before like vessels and the macula. This article’s contributions include automatic detection of the optic disc, the fovea, the optic axis and an automatic segmentation of the vitreous humor of the eye.

3D morphometry using automated aortic segmentation in native MR angiography: an alternative to contrast enhanced MRA?

INTRODUCTION Native-MR angiography (N-MRA) is considered an imaging alternative to contrast enhanced MR angiography (CE-MRA) for patients with renal insufficiency. Lower intraluminal contrast in N-MRA often leads to failure of the segmentation process in commercial algorithms. This study introduces an in-house 3D model-based segmentation approach used to compare both sequences by automatic 3D lumen segmentation, allowing for evaluation of differences of aortic lumen diameters as well as differences in length comparing both acquisition techniques at every possible location. METHODS AND MATERIALS Sixteen healthy volunteers underwent 1.5-T-MR Angiography (MRA). For each volunteer, two different MR sequences were performed, CE-MRA: gradient echo Turbo FLASH sequence and N-MRA: respiratory-and-cardiac-gated, T2-weighted 3D SSFP. Datasets were segmented using a 3D model-based ellipse-fitting approach with a single seed point placed manually above the celiac trunk. The segmented volumes were manually cropped from left subclavian artery to celiac trunk to avoid error due to side branches. Diameters, volumes and centerline length were computed for intraindividual comparison. For statistical analysis the Wilcoxon-Signed-Ranked-Test was used. RESULTS Average centerline length obtained based on N-MRA was 239.0±23.4 mm compared to 238.6±23.5 mm for CE-MRA without significant difference (P=0.877). Average maximum diameter obtained based on N-MRA was 25.7±3.3 mm compared to 24.1±3.2 mm for CE-MRA (P<0.001). In agreement with the difference in diameters, volumes obtained based on N-MRA (100.1±35.4 cm(3)) were consistently and significantly larger compared to CE-MRA (89.2±30.0 cm(3)) (P<0.001). CONCLUSIONS 3D morphometry shows highly similar centerline lengths for N-MRA and CE-MRA, but systematically higher diameters and volumes for N-MRA.

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.