Automated detection of absence seizures using a wearable electroencephalographic device: a phase 3 validation study and feasibility of automated behavioral testing.

OBJECTIVE: Our primary goal was to measure the accuracy of fully automated absence seizure detection, using a wearable electroencephalographic (EEG) device. As a secondary goal, we also tested the feasibility of automated behavioral testing triggered by the automated detection. METHODS: We conducted a phase 3 clinical trial (NCT04615442), with a prospective, multicenter, blinded study design. The input was the one-channel EEG recorded with dry electrodes embedded into a wearable headband device connected to a smartphone. The seizure detection algorithm was developed using artificial intelligence (convolutional neural networks). During the study, the predefined algorithm, with predefined cutoff value, analyzed the EEG in real time. The gold standard was derived from expert evaluation of simultaneously recorded full-array video-EEGs. In addition, we evaluated the patients' responsiveness to the automated alarms on the smartphone, and we compared it with the behavioral changes observed in the clinical video-EEGs. RESULTS: We recorded 102 consecutive patients (57 female, median age = 10 years) on suspicion of absence seizures. We recorded 364 absence seizures in 39 patients. Device deficiency was 4.67%, with a total recording time of 309 h. Average sensitivity per patient was 78.83% (95% confidence interval [CI] = 69.56%-88.11%), and median sensitivity was 92.90% (interquartile range [IQR] = 66.7%-100%). The average false detection rate was .53/h (95% CI = .32-.74). Most patients (n = 66, 64.71%) did not have any false alarms. The median F1 score per patient was .823 (IQR = .57-1). For the total recording duration, F1 score was .74. We assessed the feasibility of automated behavioral testing in 36 seizures; it correctly documented nonresponsiveness in 30 absence seizures, and responsiveness in six electrographic seizures. SIGNIFICANCE: Automated detection of absence seizures with a wearable device will improve seizure quantification and will promote assessment of patients in their home environment. Linking automated seizure detection to automated behavioral testing will provide valuable information from wearable devices.

Evaluation of skin prick location on the forearm using a novel skin prick automated test device.

Background: The skin prick test (SPT) is the gold standard for identifying allergic sensitization in individuals suspected of having an inhalant allergy. Recently, it was demonstrated that SPT using a novel skin prick automated test (SPAT) device showed increased reproducibility and tolerability compared to the conventional SPT, among other benefits. Objective: This study aimed to evaluate prick location bias using the novel SPAT device. Methods: A total of 118 volunteers were enrolled in this study and underwent SPATs with histamine (nine pricks) and glycerol control (one prick) solutions on the volar side of their forearms. Imaging of the skin reactions was performed using the SPAT device, and the physician determined the longest wheal diameter by visually inspecting the images using a web interface. Prick location bias was assessed along the medial vs. lateral and proximal vs. distal axes of the forearm. Results: In total, 944 histamine pricks were analyzed. Four medial and four lateral histamine pricks were grouped, and wheal sizes were compared. The longest wheal diameters were not significantly different between the medial and lateral prick locations (p = 0.41). Furthermore, the pricks were grouped by two based on their position on the proximal-distal axis of the forearm. No significant difference was observed among the four groups of analyzed prick locations (p = 0.73). Conclusion: The prick location on the volar side of the forearm did not influence wheal size in SPAT-pricked individuals.

Metformin therapy to reduce weight gain and visceral adiposity in children and adolescents with neurogenic or myogenic motor deficit.

The aim of this randomized, placebo-controlled study was to explore the effect of metformin in children with a neurogenic or myogenic motor deficit, who are therefore prone to develop overweight, adiposity, and insulin resistance. Study participants (n = 42) had a mean age of 15.5 yr, a short stature (height -2.4 SD), a relatively high BMI (+1.7 SD), and a high body fat fraction (41.9% or +2.8 SD). Abdominal CT confirmed the high fat mass and disclosed a high fraction of visceral fat. As expected, insulin resistance was increased. As compared to placebo, metformin intake for 6 months exerted an insulin sensitizing effect and lowered weight (mean difference of 2 kg within 6 months, p = 0.007) and BMI (p = 0.016). Weight loss appeared to be primarily due to loss of visceral fat ( approximately 20% vs. placebo; p < 0.0001). Results were similar across diagnostic subgroups. In conclusion, metformin treatment for 6 months was associated with a rise in insulin sensitivity and with a reduction of visceral adiposity in children and adolescents with a primary muscle disorder or with a neural tube defect. These findings suggest that insulin resistance underpins, at least partly, the overweight and visceral adiposity of these patients, who are not necessarily obese.

Age-associated adaptations in murine adipose tissues.

Ageing is associated with an increase in visceral obesity in men and women. Although wild-type mice with a C57Bl/6 genetic background are extensively used in studies on obesity and metabolism, little information is available on age-associated changes in their adipose tissues. We have evaluated development and composition of subcutaneous (SC) and gonadal (GON) adipose tissue in male C57Bl/6 mice at the ages of 10 weeks, 12 months or 24 months, while kept on normal chow. Total body weight as well as SC and GON fat mass significantly increased between 10 weeks and 12 months, but markedly decreased again up to 24 months of age. Adipocyte size in both fat depots and blood vessel size in GON fat followed this trend. Plasma leptin levels correlated positively with body weight and SC or GON fat mass. Both 12 and 24 months old mice displayed better insulin sensitivity as compared to 10 weeks old counterparts, reflected by significantly decreased plasma levels of insulin and/or glucose. Thus, ageing of C57Bl/6 male mice is associated with a biphasic pattern (increase up to 12 months followed by a decrease up to 24 months) of body weight, SC and GON fat mass, adipocyte and blood vessel size.

Changes in left atrial anatomy due to respiration: impact on three-dimensional image integration during atrial fibrillation ablation.

INTRODUCTION: Patient respiration influences the accuracy of image integration approaches used during atrial fibrillation (AF) ablation procedures. We assessed both absolute and relative changes in left atrial (LA) and pulmonary venous (PV) anatomy due to respiration and their implications for 3D image integration. METHODS AND RESULTS: Intensity-based segmentation of the LA and PVs was performed on cardiac computed tomography (CT) images obtained during both inspiration and expiration in 16 patients referred for AF ablation. A 3D LA-PV surface model was reconstructed for each respiratory phase. Absolute and relative respiratory motion components were evaluated from corresponding landmarks in both models. The mean 3D respiratory motion distance for all four PVs was 19 +/- 9 mm. The most important motion component was in the inferior direction, with a mean inferior motion distance of 15 +/- 8 mm. The mean 3D respiratory motion of the PV centers due to relative geometrical changes was small at the ostial level (2.6 +/- 1.4 mm, 95% CI 2.3-3.0 mm) but significantly larger at the level of the first PV bifurcation (4.0 +/- 2.3 mm, 95% CI 3.4-4.6 mm, P < 0.001). Relative geometrical changes of the LA body were most pronounced in regions near the mitral valve, resulting in a changed configuration of the mitral annulus during inspiration. CONCLUSIONS: Respiration causes important movements of the PVs and LA. Relative changes in LA-PV geometry are most pronounced in the distal PVs and in the LA body near the mitral valve. Therefore, these regions should be avoided during registration of pre- and per-procedural images unless they are acquired in the same phase of respiration.

Biological image-guided radiotherapy in rectal cancer: is there a role for FMISO or FLT, next to FDG?

PURPOSE: The purpose of this study is to investigate the use of PET/CT with fluorodeoxyglucose (FDG), fluorothymidine (FLT) and fluoromisonidazole (FMISO) for radiotherapy (RT) target definition and evolution in rectal cancer. MATERIALS AND METHODS: PET/CT was performed before and during preoperative chemoradiotherapy (CRT) in 15 patients with resectable rectal cancer. PET signals were delineated and CT images on the different time points were non-rigidly registered. Mismatch analyses were carried out to quantify the overlap between FDG and FLT or FMISO tumour volumes (TV) and between PET TVs over time. RESULTS: Ninety sequential PET/CT images were analyzed. The mean FDG, FLT and FMISO-PET TVs showed a tendency to shrink during preoperative CRT. On each time point, the mean FDG-PET TV was significantly larger than the FMISO-PET TV but not significantly larger than the mean FLT-PET TV. There was a mean 65% mismatch between the FMISO and FDG TVs obtained before and during CRT. FLT TVs corresponded better with the FDG TVs (25% mismatch before and 56% during CRT). During CRT, on average 61% of the mean FDG TV (7 cc) overlapped with the baseline mean TV (15.5 cc) (n=15). For FLT, the TV overlap was 49% (n=5) and for FMISO only 20% of the TV during CRT remained inside the contour at baseline (n=10). CONCLUSION: FDG, FLT and FMISO-PET reflect different functional characteristics that change during CRT in rectal cancer. FLT and FDG show good spatial correspondence, while FMISO seems less reliable due to the non-specific FMISO uptake in normoxic tissue and tracer diffusion through the bowel wall. FDG and FLT-PET/CT imaging seem most appropriate to integrate in preoperative RT for rectal cancer.

Functional magnetic resonance imaging: cerebral function alterations in subthreshold and suprathreshold spinal cord stimulation.

BACKGROUND AND PURPOSE: Failed back surgery syndrome (FBSS) is a common and devastating chronic neuropathic pain disorder. Conventional spinal cord stimulation (SCS) applies electrical suprathreshold pulses to the spinal cord at a frequency of 40-60 Hz and relieves pain in FBSS patients. During the last decade, two major changes have emerged in the techniques of stimulating the spinal cord: paresthesia-free or subthreshold stimulation and administration of higher frequency or higher amounts of energy to the spinal cord. Despite the positive clinical results, the mechanism of action remains unclear. A functional MRI (fMRI) study was conducted to investigate the brain alterations during subthreshold and suprathreshold stimulation at different frequencies. METHODS: Ten subjects with FBSS, treated with externalized SCS, received randomly four different stimulation frequencies (4 Hz, 60 Hz, 500 Hz, and 1 kHz) during four consecutive days. At every frequency, the patient underwent sub- and suprathreshold stimulation. Cerebral activity was monitored and assessed using fMRI. RESULTS: Suprathreshold stimulation is generally accompanied with more activity than sub-threshold SCS. Suprathreshold SCS resulted in increased bilateral activation of the frontal cortex, thalamus, pre- and postcentral gyri, basal ganglia, cingulate gyrus, insula, thalamus, and claustrum. We observed deactivation of the bilateral parahippocampus, amygdala, precuneus, posterior cingulate gyrus, postcentral gyrus, and unilateral superior temporal gyrus. CONCLUSION: Suprathreshold stimulation resulted in greater activity (both activation and deactivation) of the frontal brain regions; the sensory, limbic, and motor cortices; and the diencephalon in comparison with subthreshold stimulation. Each type of frequency at suprathreshold stimulation was characterized by an individual activation pattern.

Minimal shape and intensity cost path segmentation.

A new generic model-based segmentation algorithm is presented, which can be trained from examples akin to the active shape model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Whereas ASM alternates between shape and intensity information during search, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized noniteratively using dynamic programming, without the need for initialization. The algorithm was validated for segmentation of anatomical structures in chest and hand radiographs. In each experiment, the presented method had a significant higher performance when compared to the ASM schemes. As the method is highly effective, optimally suited for pathological cases and easy to implement, it is highly useful for many medical image segmentation tasks.

Nonrigid registration for subtraction CT angiography applied to the carotids and cranial arteries.

RATIONALE AND OBJECTIVES: Computed tomography angiography (CTA) is an established tool for vascular imaging. However, high-intensity nonvascular structures in the contrast image can seriously hamper luminal visualization. This is an issue for three-dimensional visualization, where high-intensity structures might cover the underlying vasculature. But also in two dimensions, calcified plaques adjacent to the contrast-enhanced vessel lumen impede correct determination of the vessel boundary. High-intensity structures can be eliminated using subtraction CTA, where a native image is subtracted from the contrast image. However, patient and organ motion limits the widespread application of this technique. We propose to use nonrigid image registration to solve this problem. MATERIALS AND METHODS: For each patient, a native image and a contrast image are recorded, respectively, before and after contrast administration. The native image is registered to the contrast image using an automatic intensity-based nonrigid three-dimensional registration algorithm. Both images are merged in a fused image, allowing the user to switch between a view of the arteries, the bone or both. The procedure has been applied to 95 patients. RESULTS: In all cases, subtraction CTA using nonrigid registration allows for a significantly better artifacts removal than subtraction CTA without registration. Image quality of all images was judged adequate for clinical use. The average total processing time for each dataset is about 30 minutes. CONCLUSION: Nonrigid registration can allow for a great reduction in subtraction artifacts for subtraction CTA, resulting in a clear view of the vasculature.

Computerized craniofacial reconstruction using CT-derived implicit surface representations.

In forensic craniofacial reconstruction, facial features of an unknown individual are estimated from an unidentified skull, based on a mixture of experimentally obtained guidelines on the relationship between soft tissues and the underlying skeleton. In this paper, we investigate the possibility of using full 3D cross-sectional CT images for establishing a reference database of densely sampled distances between the external surfaces of the skull and head for automated craniofacial reconstruction. For each CT image in the reference database, the hard tissue (skull) and soft tissue (head) volumes are automatically segmented and transformed into signed distance transform (sDT) images, representing for each voxel in this image the Euclidean distance to the closest point on the skull and head surface, respectively, distances being positive (negative) for voxels inside (outside) the skull/head. Multiple craniofacial reconstructions are obtained by first warping each reference skull sDT maps to the target skull sDT using a B-spline based free form deformation algorithm and subsequently applying these warps to the reference head sDT maps. A single reconstruction of the target head surface is defined as the zero level set of the arithmetic average of all warped reference head sDT maps, but other reconstructions are possible, biasing the result to subject specific attributes (age, BMI, gender). Both qualitative and quantitative tests (measuring the similarity between the 3D reconstructed and corresponding original head surface) on a small (N = 20) database are presented to proof the validity of the concept.

Fine grained osseointegrative coating improves biocompatibility of PEEK in heterotopic sheep model.

BACKGROUND AND AIM: Polyetheretherketone (PEEK) materials already have been used successfully in orthopedic and especially spine surgery. PEEK is radiolucent and comparable with bone regarding elasticity. However, PEEK is inert and the adhesion of PEEK implants to bone tissue proceeds slowly because of their relatively low biocompatibility. The aim of the study is to evaluate the effect of titanium and CaP coating on the adhesion of bone tissue. MATERIAL AND METHODS: Six adult sheep (body weight 57.6 ± 3.9 kg) were included in this study. Three different types of cylindrical dowels (12 mm length x 8 mm diameter) were implanted in long bones (tibia and femur): PEEK dowels without coating (the control group), and PEEK dowels with a nanocoating of calcium phosphate (CaP group) or titanium (titanium group). Animals were sacrificed after 6, 12 and 26 weeks. Dowels were explanted for micro CT and histology. RESULTS: Bone implant contact (BIC) ratio was significantly higher in the titanium versus control groups in the 6 to 12 weeks period (p = 0.03). The ratio between bone volume and tissue volume (BV/TV) was significantly higher in titanium versus control in the 6 to 12 weeks period (p = 0.02). A significant correlation between BIC and BV/TV was seen (r = 0.85, p < 0.05). CONCLUSION: Coating of PEEK dowels with a nanocoating of titanium has beneficial effects on adhesion of bone tissue.

Effects of rigid and non-rigid image registration on test-retest variability of quantitative [18F]FDG PET/CT studies.

BACKGROUND: [18F]fluoro-2-deoxy-D-glucose ([18F]FDG) positron emission tomography (PET) is a valuable tool for monitoring response to therapy in oncology. In longitudinal studies, however, patients are not scanned in exactly the same position. Rigid and non-rigid image registration can be applied in order to reuse baseline volumes of interest (VOI) on consecutive studies of the same patient. The purpose of this study was to investigate the impact of various image registration strategies on standardized uptake value (SUV) and metabolic volume test-retest variability (TRT). METHODS: Test-retest whole-body [18F]FDG PET/CT scans were collected retrospectively for 11 subjects with advanced gastrointestinal malignancies (colorectal carcinoma). Rigid and non-rigid image registration techniques with various degrees of locality were applied to PET, CT, and non-attenuation corrected PET (NAC) data. VOI were drawn independently on both test and retest scans. VOI drawn on test scans were projected onto retest scans and the overlap between projected VOI and manually drawn retest VOI was quantified using the Dice similarity coefficient (DSC). In addition, absolute (unsigned) differences in TRT of SUVmax, SUVmean, metabolic volume and total lesion glycolysis (TLG) were calculated in on one hand the test VOI and on the other hand the retest VOI and projected VOI. Reference values were obtained by delineating VOIs on both scans separately. RESULTS: Non-rigid PET registration showed the best performance (median DSC: 0.82, other methods: 0.71-0.81). Compared with the reference, none of the registration types showed significant absolute differences in TRT of SUVmax, SUVmean and TLG (p > 0.05). Only for absolute TRT of metabolic volume, significant lower values (p < 0.05) were observed for all registration strategies when compared to delineating VOIs separately, except for non-rigid PET registrations (p = 0.1). Non-rigid PET registration provided good volume TRT (7.7%) that was smaller than the reference (16%). CONCLUSION: In particular, non-rigid PET image registration showed good performance similar to delineating VOI on both scans separately, and with smaller TRT in metabolic volume estimates.

Fuzzy multi-class statistical modeling for efficient total lesion metabolic activity estimation from realistic PET images.

18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) has become the de facto standard for current clinical therapy follow up evaluations. In pursuit of robust biomarkers for predicting early therapy response, an efficient marker quantification procedure is certainly a necessity. Among various PET derived markers, the clinical investigations indicated that the total lesion metabolic activity (TLA) of a tumor lesion has a good prognostic value in several longitudinal studies. We utilize a fuzzy multi-class modeling using a stochastic expectation maximization (SEM) algorithm to fit a finite mixture model (FMM) to the PET image. We then propose a direct estimation formula for TLA and SUVmean from this multi-class statistical model. In order to evaluate our proposition, a realistic liver lesion is simulated and reconstructed. All results were evaluated with reference to the ground truth knowledge. Our experimental study conveys that the proposed method is robust enough to handle background heterogeneities in realistic scenarios.

Comparison of a new methodology for the assessment of 3D myocardial strain from volumetric ultrasound with 2D speckle tracking.

An alternative approach to extract 3D myocardial strain based on elastic registration of the ultrasound images (3DSE) was developed by our lab. The aim of the present study was to test its clinical performance by comparing strain values obtained by 3DSE with the ones obtained with 2D speckle tracking (2DST). Standard 2D B-mode and volumetric datasets were acquired in 12 patients with coronary heart disease (CHD) and in 12 control subjects. Longitudinal (ε(LL)), circumferential (ε(CC)) and radial (ε(RR)) strain values were obtained from 2D datasets using commercially available 2DST software and from volumetric datasets using the 3DSE approach. 3DSE provided lower strain values than 2DST. With both approaches global ε(LL) and ε(CC) were significantly lower in patients with CHD than in controls. Global ε(LL) and ε(CC) correlated well between both methods (R = 0.83, R = 0.86, respectively), while segmental correlations were moderate [R = 0.63 (ε(LL)), R = 0.41 (ε(CC))]. The highest differences in ε(LL) values obtained by the two methods and the highest number of erroneous ε(LL) with 3DSE were observed in the basal LV segments. This study shows that in real-life datasets our 3DSE method provides global and regional ε(LL) and ε(CC) values that are comparable with the ones obtained from 2DST, even though they are not interchangeable with each other. As only a single acquisition is required, 3D methods may offer advantages over the current 2D techniques. However, the accuracy of the 3DSE can still be improved by solving the problems that appear with deformation estimation in the basal segments.

Regional cardiac motion and strain estimation in three-dimensional echocardiography: a validation study in thick-walled univentricular phantoms.

Automatic quantification of regional left ventricular deformation in volumetric ultrasound data remains challenging. Many methods have been proposed to extract myocardial motion, including techniques using block matching, phase-based correlation, differential optical flow methods, and image registration. Our lab previously presented an approach based on elastic registration of subsequent volumes using a B-spline representation of the underlying transformation field. Encouraging results were obtained for the assessment of global left ventricular function, but a thorough validation on a regional level was still lacking. For this purpose, univentricular thick-walled cardiac phantoms were deformed in an experimental setup to locally assess strain accuracy against sonomicrometry as a reference method and to assess whether regions containing stiff inclusions could be detected. Our method showed good correlations against sonomicrometry: r(2) was 0.96, 0.92, and 0.84 for the radial (ε(RR)), longitudinal (ε(LL)), and circumferential (ε(CC)) strain, respectively. Absolute strain errors and strain drift were low for ε(LL) (absolute mean error: 2.42%, drift: -1.05%) and ε(CC) (error: 1.79%, drift: -1.33%) and slightly higher for ε(RR) (error: 3.37%, drift: 3.05%). The discriminative power of our methodology was adequate to resolve full transmural inclusions down to 17 mm in diameter, although the inclusion-to-surrounding tissue stiffness ratio was required to be at least 5:2 (absolute difference of 39.42 kPa). When the inclusion-to-surrounding tissue stiffness ratio was lowered to approximately 2:1 (absolute difference of 22.63 kPa), only larger inclusions down to 27 mm in diameter could still be identified. Radial strain was found not to be reliable in identifying dysfunctional regions.

Evaluation of registration methods on thoracic CT: the EMPIRE10 challenge.

EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.

Nonrigid image registration using conditional mutual information.

Maximization of mutual information (MMI) is a popular similarity measure for medical image registration. Although its accuracy and robustness has been demonstrated for rigid body image registration, extending MMI to nonrigid image registration is not trivial and an active field of research. We propose conditional mutual information (cMI) as a new similarity measure for nonrigid image registration. cMI starts from a 3-D joint histogram incorporating, besides the intensity dimensions, also a spatial dimension expressing the location of the joint intensity pair. cMI is calculated as the expected value of the cMI between the image intensities given the spatial distribution. The cMI measure was incorporated in a tensor-product B-spline nonrigid registration method, using either a Parzen window or generalized partial volume kernel for histogram construction. cMI was compared to the classical global mutual information (gMI) approach in theoretical, phantom, and clinical settings. We show that cMI significantly outperforms gMI for all applications.

Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification.

In this paper, a specific method is presented to facilitate the semi-automatic segmentation of liver tumors and liver metastases in CT images. Accurate and reliable segmentation of tumors is essential for the follow-up of cancer treatment. The core of the algorithm is a level set method. The initialization is generated by a spiral-scanning technique based on dynamic programming. The level set evolves according to a speed image that is the result of a statistical pixel classification algorithm with supervised learning. This method is tested on CT images of the abdomen and compared with manual delineations of liver tumors. The described method outperformed the semi-automatic methods of the other participants of the "3D Liver Tumor Segmentation Challenge 2008". Evaluating the algorithm on the provided test data leads to an average overlap error of 32.6% and an average volume difference of 17.9%. The average, the RMS and the maximum surface distance are 2.0, 2.6 and 10.1 mm, respectively.