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Background: Infusion testing is an established method for assessing CSF resistance in patients with idiopathic normal pressure hydrocephalus (iNPH). To what extent the increased resistance is related to the glymphatic system is an open question. Here we introduce a computational model that includes the glymphatic system and enables us to determine the importance of (1) brain geometry, (2) intracranial pressure, and (3) physiological parameters on the outcome of and response to an infusion test. Methods: We implemented a seven-compartment multiple network porous medium model with subject specific geometries from MR images using the finite element library FEniCS. The model consists of the arterial, capillary and venous blood vessels, their corresponding perivascular spaces, and the extracellular space (ECS). Both subject specific brain geometries and subject specific infusion tests were used in the modeling of both healthy adults and iNPH patients. Furthermore, we performed a systematic study of the effect of variations in model parameters. Results: Both the iNPH group and the control group reached a similar steady state solution when subject specific geometries under identical boundary conditions was used in simulation. The difference in terms of average fluid pressure and velocity between the iNPH and control groups, was found to be less than 6% during all stages of infusion in all compartments. With subject specific boundary conditions, the largest computed difference was a 75% greater fluid speed in the arterial perivascular space (PVS) in the iNPH group compared to the control group. Changes to material parameters changed fluid speeds by several orders of magnitude in some scenarios. A considerable amount of the CSF pass through the glymphatic pathway in our models during infusion, i.e., 28% and 38% in the healthy and iNPH patients, respectively. Conclusions: Using computational models, we have found the relative importance of subject specific geometries to be less important than individual differences in resistance as measured with infusion tests and model parameters such as permeability, in determining the computed pressure and flow during infusion. Model parameters are uncertain, but certain variations have large impact on the simulation results. The computations resulted in a considerable amount of the infused volume passing through the brain either through the perivascular spaces or the extracellular space. [ABSTRACT FROM AUTHOR]

Background: Compromised cerebral blood flow can contribute to future ischemic events in patients with symptomatic carotid artery disease. However, there is limited knowledge of the effects on cerebral hemodynamics resulting from a reduced internal carotid artery (ICA) blood flow rate (BFR). Purpose: Investigate how reduced ICA‐BFR, relates to BFR in the cerebral arteries. Study Type: Prospective. Subjects: Thirty‐eight patients, age 72 ± 6 years (11 female). Field Strength/Sequence: 3‐Tesla, four‐dimensional phase‐contrast magnetic resonance imaging (4D‐PCMRI). Assessment: Patients with ischemic stroke or transient ischemic attack were evaluated regarding the degree of stenosis. 4D‐PCMRI was used to measure cerebral BFR in 38 patients with symptomatic carotid stenosis (≥50%). BFR in the cerebral arteries was assessed in two subgroups based on symptomatic ICA‐BFR: reduced ICA‐flow (<160 mL/minutes) and preserved ICA‐flow (≥160 mL/minutes). BFR laterality was defined as a difference in the paired ipsilateral‐contralateral arteries. Statistical Tests: Patients were grouped based on ICA‐BFR (reduced vs. preserved). Statistical tests (independent sample t‐test/paired t‐test) were used to compare groups and hemispheres. Significance was determined at P < 0.05. Results: The degree of stenosis was not significantly different, 80% (95% confidence interval [CI] = 73%–87%) in the reduced ICA‐flow vs. 72% (CI = 66%–76%) in the preserved ICA‐flow; P = 0.09. In the reduced ICA‐flow group, a significantly reduced BFR was found in the ipsilateral middle cerebral artery and anterior cerebral artery (A1), while significantly increased in the contralateral A1. Retrograde BFR was found in the posterior communicating artery and ophthalmic artery. Significant BFR laterality was present in all paired arteries in the reduced ICA‐flow group, contrasting the preserved ICA‐flow group (P = 0.14–0.93). Data Conclusions: 4D‐PCMRI revealed compromised cerebral BFR due to carotid stenosis, not possible to detect by solely analyzing the degree of stenosis. In patients with reduced ICA‐flow, collaterals were not sufficient to maintain symmetrical BFR distribution to the two hemispheres. Evidence Level: 2 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Over the last decade, it has become evident that cerebrospinal fluid (CSF) plays a pivotal role in brain solute clearance through perivascular pathways and interactions between the brain and meningeal lymphatic vessels. Whereas most of this fundamental knowledge was gained from rodent models, human brain clearance imaging has provided important insights into the human system and highlighted the existence of important interspecies differences. Current gold standard techniques for human brain clearance imaging involve the injection of gadolinium‐based contrast agents and monitoring their distribution and clearance over a period from a few hours up to 2 days. With both intrathecal and intravenous injections being used, which each have their own specific routes of distribution and thus clearance of contrast agent, a clear understanding of the kinetics associated with both approaches, and especially the differences between them, is needed to properly interpret the results. Because it is known that intrathecally injected contrast agent reaches the blood, albeit in small concentrations, and that similarly some of the intravenously injected agent can be detected in CSF, both pathways are connected and will, in theory, reach the same compartments. However, because of clear differences in relative enhancement patterns, both injection approaches will result in varying sensitivities for assessment of different subparts of the brain clearance system. In this opinion review article, the "EU Joint Programme – Neurodegenerative Disease Research (JPND)" consortium on human brain clearance imaging provides an overview of contrast agent pharmacokinetics in vivo following intrathecal and intravenous injections and what typical concentrations and concentration–time curves should be expected. This can be the basis for optimizing and interpreting contrast‐enhanced MRI for brain clearance imaging. Furthermore, this can shed light on how molecules may exchange between blood, brain, and CSF. [ABSTRACT FROM AUTHOR]

White matter hyperintensities (WMH), perivascular spaces (PVS) and lacunes are common MRI features of small vessel disease (SVD). However, no shared underlying pathological mechanism has been identified. We investigated whether SVD burden, in terms of WMH, PVS and lacune status, was related to changes in the cerebral arterial wall by applying global cerebral pulse wave velocity (gcPWV) measurements, a newly described marker of cerebral vascular stiffness. In a population-based cohort of 190 individuals, 66–85 years old, SVD features were estimated from T1-weighted and FLAIR images while gcPWV was estimated from 4D flow MRI data. Additionally, the gcPWV's stability to variations in field-of-view was analyzed. The gcPWV was 10.82 (3.94) m/s and displayed a significant correlation to WMH and white matter PVS volume (r = 0.29, p < 0.001; r = 0.21, p = 0.004 respectively from nonparametric tests) that persisted after adjusting for age, blood pressure variables, body mass index, ApoB/A1 ratio, smoking as well as cerebral pulsatility index, a previously suggested early marker of SVD. The gcPWV displayed satisfactory stability to field-of-view variations. Our results suggest that SVD is accompanied by changes in the cerebral arterial wall that can be captured by considering the velocity of the pulse wave transmission through the cerebral arterial network. [ABSTRACT FROM AUTHOR]

Analysis of brain connectivity is important for understanding how information is processed by the brain. We propose a novel Bayesian vector autoregression hierarchical model for analysing brain connectivity within resting-state functional magnetic resonance imaging, and apply it to simulated data and a real data set with subjects in different groups. Our approach models functional and effective connectivity simultaneously and allows for both group- and single-subject inference. We combine analytical marginalization with Hamiltonian Monte Carlo to obtain highly efficient posterior sampling. We show that our model gives similar inference for effective connectivity compared to models with a common covariance matrix to all subjects, but more accurate inference for functional connectivity between regions compared to models with more restrictive covariance structures. A Stan implementation of our model is available on GitHub. [ABSTRACT FROM AUTHOR]

Background: Studies indicate that brain clearance via the glymphatic system is impaired in idiopathic normal pressure hydrocephalus (INPH). This has been suggested to result from reduced cerebrospinal fluid (CSF) turnover, which could be caused by a reduced CSF formation rate. The aim of this study was to determine the formation rate of CSF in a cohort of patients investigated for INPH and compare this to a historical control cohort. Methods: CSF formation rate was estimated in 135 (75 ± 6 years old, 64/71 men/women) patients undergoing investigation for INPH. A semiautomatic CSF infusion investigation (via lumbar puncture) was performed. CSF formation rate was assessed by downregulating and steadily maintaining CSF pressure at a zero level. During the last 10 min, the required outflow to maintain zero pressure, i.e., CSF formation rate, was continuously measured. The values were compared to those of a historical reference cohort from a study by Ekstedt in 1978. Results: Mean CSF formation rate was 0.45 ± 0.15 ml/min (N = 135), equivalent to 27 ± 9 ml/hour. There was no difference in the mean (p = 0.362) or variance (p = 0.498) of CSF formation rate between the subjects that were diagnosed as INPH (N = 86) and those who were not (N = 43). The CSF formation rate in INPH was statistically higher than in the reference cohort (0.46 ± 0.15 vs. 0.40 ± 0.08 ml/min, p = 0.005), but the small difference was probably not physiologically relevant. There was no correlation between CSF formation rate and baseline CSF pressure (r = 0.136, p = 0.115, N = 135) or age (-0.02, p = 0.803, N = 135). Conclusions: The average CSF formation rate in INPH was not decreased compared to the healthy reference cohort, which does not support reduced CSF turnover. This emphasizes the need to further investigate the source and routes of the flow in the glymphatic system and the cause of the suggested impaired glymphatic clearance in INPH. [ABSTRACT FROM AUTHOR]

Blood–brain barrier (BBB) disruption may contribute to cognitive decline, but questions remain whether this association is more pronounced for certain brain regions, such as the hippocampus, or represents a whole-brain mechanism. Further, whether human BBB leakage is triggered by excessive vascular pulsatility, as suggested by animal studies, remains unknown. In a prospective cohort (N = 50; 68–84 years), we used contrast-enhanced MRI to estimate the permeability-surface area product (PS) and fractional plasma volume ( v p ), and 4D flow MRI to assess cerebral arterial pulsatility. Cognition was assessed by the Montreal Cognitive Assessment (MoCA) score. We hypothesized that high PS would be associated with high arterial pulsatility, and that links to cognition would be specific to hippocampal PS. For 15 brain regions, PS ranged from 0.38 to 0.85 (·10−3 min−1) and v p from 0.79 to 1.78%. Cognition was related to PS (·10−3 min−1) in hippocampus (β = – 2.9; p = 0.006), basal ganglia (β = – 2.3; p = 0.04), white matter (β = – 2.6; p = 0.04), whole-brain (β = – 2.7; p = 0.04) and borderline-related for cortex (β = – 2.7; p = 0.076). Pulsatility was unrelated to PS for all regions (p > 0.19). Our findings suggest PS–cognition links mainly reflect a whole-brain phenomenon with only slightly more pronounced links for the hippocampus, and provide no evidence of excessive pulsatility as a trigger of BBB disruption. [ABSTRACT FROM AUTHOR]

Purpose: Compare extracranial internal carotid artery flow rates and intracranial collateral use between conventional ≥ 50% carotid stenosis and carotid near-occlusion, and between symptomatic and asymptomatic carotid near-occlusion. Methods: We included patients with ≥ 50% carotid stenosis. Degree of stenosis was diagnosed on CTA. Mean blood flow rates were assessed with four-dimensional phase-contrast MRI. Results: We included 110 patients of which 83% were symptomatic, and 38% had near-occlusion. Near-occlusions had lower mean internal carotid artery flow (70 ml/min) than conventional ≥ 50% stenoses (203 ml/min, P <.001). Definite use of ≥ 1 collateral was found in 83% (35/42) of near-occlusions and 10% (7/68) of conventional stenoses (P <.001). However, there were no differences in total cerebral blood flow (514 ml/min vs. 519 ml/min, P =.78) or ipsilateral hemispheric blood flow (234 vs. 227 ml/min, P =.52), between near-occlusions and conventional ≥ 50% stenoses, based on phase-contrast MRI flow rates. There were no differences in total cerebral or hemispheric blood flow, or collateral use, between symptomatic and asymptomatic near-occlusions. Conclusion: Near-occlusions have lower internal carotid artery flow rates and more collateral use, but similar total cerebral blood flow and hemispheric blood flow, compared to conventional ≥ 50% carotid stenosis. [ABSTRACT FROM AUTHOR]

Large annotated datasets are required for training deep learning models, but in medical imaging data sharing is often complicated due to ethics, anonymization and data protection legislation. Generative AI models, such as generative adversarial networks (GANs) and diffusion models, can today produce very realistic synthetic images, and can potentially facilitate data sharing. However, in order to share synthetic medical images it must first be demonstrated that they can be used for training different networks with acceptable performance. Here, we therefore comprehensively evaluate four GANs (progressive GAN, StyleGAN 1–3) and a diffusion model for the task of brain tumor segmentation (using two segmentation networks, U-Net and a Swin transformer). Our results show that segmentation networks trained on synthetic images reach Dice scores that are 80%–90% of Dice scores when training with real images, but that memorization of the training images can be a problem for diffusion models if the original dataset is too small. Our conclusion is that sharing synthetic medical images is a viable option to sharing real images, but that further work is required. The trained generative models and the generated synthetic images are shared on AIDA data hub. [ABSTRACT FROM AUTHOR]

Brain age prediction from 3D MRI volumes using deep learning has recently become a popular research topic, as brain age has been shown to be an important biomarker. Training deep networks can be very computationally demanding for large datasets like the U.K. Biobank (currently 29,035 subjects). In our previous work, it was demonstrated that using a few 2D projections (mean and standard deviation along three axes) instead of each full 3D volume leads to much faster training at the cost of a reduction in prediction accuracy. Here, we investigated if another set of 2D projections, based on higher-order statistical central moments and eigenslices, leads to a higher accuracy. Our results show that higher-order moments do not lead to a higher accuracy, but that eigenslices provide a small improvement. We also show that an ensemble of such models provides further improvement. [ABSTRACT FROM AUTHOR]

Background: Stereotactic radiosurgery (SRS) can be an effective primary or adjuvant treatment option for intracranial tumors. However, it carries risks of various radiation toxicities, which can lead to functional deficits for the patients. Current inverse planning algorithms for SRS provide an efficient way for sparing organs at risk (OARs) by setting maximum radiation dose constraints in the treatment planning process. Purpose: We propose using activation maps from functional MRI (fMRI) to map the eloquent regions of the brain and define functional OARs (fOARs) for Gamma Knife SRS treatment planning. Methods: We implemented a pipeline for analyzing patient fMRI data, generating fOARs from the resulting activation maps, and loading them onto the GammaPlan treatment planning software. We used the Lightning inverse planner to generate multiple treatment plans from open MRI data of five subjects, and evaluated the effects of incorporating the proposed fOARs. Results: The Lightning optimizer designs treatment plans with high conformity to the specified parameters. Setting maximum dose constraints on fOARs successfully limits the radiation dose incident on them, but can have a negative impact on treatment plan quality metrics. By masking out fOAR voxels surrounding the tumor target it is possible to achieve high quality treatment plans while controlling the radiation dose on fOARs. Conclusions: The proposed method can effectively reduce the radiation dose incident on the eloquent brain areas during Gamma Knife SRS of brain tumors. [ABSTRACT FROM AUTHOR]

Different human leukocyte antigen (HLA) alleles associate with disease phenotypes in sarcoidosis. Peripheral blood (PB) lymphopenia is reported as more common in sarcoidosis patients with worse prognosis. The mechanisms behind are unrecognized but a PB depletion due to lymphocytes migrating to lung and/or extra pulmonary organs has been suggested. Insights into associations between HLA alleles, lung immune cells, clinical phenotype including extra pulmonary manifestations (EPM), and PB lymphopenia may provide mechanistic clues and enable adequate intervention in this patient group. In this situdy,141 treatment naïve, newly diagnosed patients were retrospectively identified in a Swedish cohort of sarcoidosis patients. Data on HLA-DRB1 alleles, lung immune cells from bronchoalveolar lavage fluid (BALF), PB lymphocytes and clinical parameters including treatment and disease course (chronic vs. resolving) were collected. The patients were followed for 2 years. PB lymphopenia associated with male sex, development of non-resolving disease, a need for first- and second-line systemic immunosuppressant treatment and HLA- DRB1*07. No correlation between BALF and PB lymphocytes, and no difference in EPM was detected between patients with and without PB lymphopenia. In conclusion, PB lymphopenia is associated with a more severe disease phenotype and carriage of the HLA-DRB1*07 allele. The results do not lend support to the hypothesis about sarcoidosis PB lymphopenia being due to a migration of PB lymphocytes to other organs. Rather, they provide a basis for future studies on the connection between HLA-DRB1*07 and PB lymphopenia mechanisms. [ABSTRACT FROM AUTHOR]

Classifying subjects as healthy or diseased using neuroimaging data has gained a lot of attention during the last 10 years, and recently, different deep learning approaches have been used. Despite this fact, there has not been any investigation regarding how 3D augmentation can help to create larger datasets, required to train deep networks with millions of parameters. In this study, deep learning was applied to derivatives from resting state functional MRI data, to investigate how different 3D augmentation techniques affect the test accuracy. Specifically, resting state derivatives from 1112 subjects in ABIDE (Autism Brain Imaging Data Exchange) preprocessed were used to train a 3D convolutional neural network (CNN) to classify each subject according to presence or absence of autism spectrum disorder. The results show that augmentation only provide minor improvements to the test accuracy. [ABSTRACT FROM AUTHOR]

Using 3D CNNs on high-resolution medical volumes is very computationally demanding, especially for large datasets like UK Biobank, which aims to scan 100,000 subjects. Here, we demonstrate that using 2D CNNs on a few 2D projections (representing mean and standard deviation across axial, sagittal and coronal slices) of 3D volumes leads to reasonable test accuracy (mean absolute error of about 3.5 years) when predicting age from brain volumes. Using our approach, one training epoch with 20,324 subjects takes 20–50 s using a single GPU, which is two orders of magnitude faster than a small 3D CNN. This speedup is explained by the fact that 3D brain volumes contain a lot of redundant information, which can be efficiently compressed using 2D projections. These results are important for researchers who do not have access to expensive GPU hardware for 3D CNNs. [ABSTRACT FROM AUTHOR]

t-distributed stochastic neighbor embedding (t-SNE) is a method for reducing high-dimensional data to a low-dimensional representation, and is mostly used for visualizing data. In parametric t-SNE, a neural network learns to reproduce this mapping. When used for EEG analysis, the data are usually first transformed into a set of features, but it is not known which features are optimal. The principle of t-SNE was used to train convolutional neural network (CNN) encoders to learn to produce both a high- and a low-dimensional representation, eliminating the need for feature engineering. To evaluate the method, the Temple University EEG Corpus was used to create three datasets with distinct EEG characters: (1) wakefulness and sleep; (2) interictal epileptiform discharges; and (3) seizure activity. The CNN encoders produced low-dimensional representations of the datasets with a structure that conformed well to the EEG characters and generalized to new data. Compared to parametric t-SNE for either a short-time Fourier transform or wavelet representation of the datasets, the developed CNN encoders performed equally well in separating categories, as assessed by support vector machines. The CNN encoders generally produced a higher degree of clustering, both visually and in the number of clusters detected by k-means clustering. The developed principle is promising and could be further developed to create general tools for exploring relations in EEG data. [ABSTRACT FROM AUTHOR]

Current inference techniques for processing multi‐needle Langmuir probe (m‐NLP) data are often based on adaptations of the Orbital Motion‐Limited (OML) theory which relies on several simplifying assumptions. Some of these assumptions, however, are typically not well satisfied in actual experimental conditions, thus leading to uncontrolled uncertainties in inferred plasma parameters. In order to remedy this difficulty, three‐dimensional kinetic particle in cell simulations are used to construct a synthetic data set, which is used to compare and assess different m‐NLP inference techniques. Using a synthetic data set, regression‐based models capable of inferring electron density and satellite potentials from 4‐tuples of currents collected with fixed‐bias needle probes similar to those on the NorSat‐1 satellite, are trained and validated. The regression techniques presented show promising results for plasma density inferences with RMS relative errors less than 20%, and satellite potential inferences with RMS errors less than 0.2 V for potentials ranging from −6 to −1 V. The new inference approaches presented are applied to NorSat‐1 data, and compared with existing state‐of‐the‐art inference techniques. Plain Language Summary: We present a new technique for processing measurements from a set of cylindrical Langmuir probes with different fixed voltages relative to a satellite in low Earth orbit. Our approach, based on results from 3‐D simulations, does not rely on the assumptions made in currently used theoretical models, and it accounts for more physical processes than possible in theories. Our goal is to improve the accuracy of plasma density and satellite potential inferences using this type of instrument, while providing uncertainties in the inferences. Our inference models are applied to NorSat‐1 satellite data and are compared with currently used theoretical model inferences. It is found that our model inference is more consistent with satellite data. Key Points: 3‐D kinetic PIC simulations are used to simulate currents collected by multi‐needle Langmuir probe (m‐NLP) in order to create a synthetic solution libraryModels to infer physical parameters from m‐NLP measurements are constructed and assessed on the basis of synthetic and in situ data setsPromising new approaches are identified to analyze m‐NLP measurements based on simulation and in situ data [ABSTRACT FROM AUTHOR]

Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real‐time automatic analysis could support the clinical decision‐making. In this study, several deep learning models were investigated for thyroid disease classification on 2D and 3D OCT data obtained from ex vivo specimens of 22 patients undergoing surgery and diagnosed with several thyroid pathologies. Additionally, two open‐access datasets were used to evaluate the custom models. On the thyroid dataset, the best performance was achieved by the 3D vision transformer model with a Matthew's correlation coefficient (MCC) of 0.79 (accuracy = 0.90) for the normal‐versus‐abnormal classification. On the open‐access datasets, the custom models achieved the best performance (MCC > 0.88, accuracy > 0.96). Results obtained for the normal‐versus‐abnormal classification suggest OCT, complemented with deep learning‐based analysis, as a tool for real‐time automatic diseased tissue identification in thyroid surgery. [ABSTRACT FROM AUTHOR]

Objective: High cerebral arterial pulsatility index (PI), white matter lesions (WMLs), enlarged perivascular spaces (PVSs), and lacunar infarcts are common findings in the elderly population, and considered indicators of small vessel disease (SVD). Here, we investigate the potential temporal ordering among these variables, with emphasis on determining whether high PI is an early or delayed manifestation of SVD. Methods: In a population‐based cohort, 4D flow MRI data for cerebral arterial pulsatility was collected for 159 participants at baseline (age 64–68), and for 122 participants at follow‐up 5 years later. Structural MRI was used for WML and PVS segmentation, and lacune identification. Linear mixed‐effects (LME) models were used to model longitudinal changes testing for pairwise associations, and latent change score (LCS) models to model multiple relationships among variables simultaneously. Results: Longitudinal 5‐year increases were found for WML, PVS, and PI. Cerebral arterial PI at baseline did not predict changes in WML or PVS volume. However, WML and PVS volume at baseline predicted 5‐year increases in PI. This was shown for PI increases in relation to baseline WML and PVS volumes using LME models (R ≥ 0.24; p < 0.02 and R ≥ 0.23; p < 0.03, respectively) and LCS models (β = 0.28; p = 0.015 and β = 0.28; p = 0.009, respectively). Lacunes at baseline were unrelated to PI. Interpretation: In healthy older adults, indicators of SVD are related in a lead–lag fashion, in which the expression of WML and PVS precedes increases in cerebral arterial PI. Hence, we propose that elevated PI is a relatively late manifestation, rather than a risk factor, for cerebral SVD. ANN NEUROL 2022;92:871–881 [ABSTRACT FROM AUTHOR]

In the application of deep learning on optical coherence tomography (OCT) data, it is common to train classification networks using 2D images originating from volumetric data. Given the micrometer resolution of OCT systems, consecutive images are often very similar in both visible structures and noise. Thus, an inappropriate data split can result in overlap between the training and testing sets, with a large portion of the literature overlooking this aspect. In this study, the effect of improper dataset splitting on model evaluation is demonstrated for three classification tasks using three OCT open-access datasets extensively used, Kermany's and Srinivasan's ophthalmology datasets, and AIIMS breast tissue dataset. Results show that the classification performance is inflated by 0.07 up to 0.43 in terms of Matthews Correlation Coefficient (accuracy: 5% to 30%) for models tested on datasets with improper splitting, highlighting the considerable effect of dataset handling on model evaluation. This study intends to raise awareness on the importance of dataset splitting given the increased research interest in implementing deep learning on OCT data. [ABSTRACT FROM AUTHOR]

Innovation has become increasingly important for most industries to cope with rapid technological changes as well as changing societal needs. Even though there are many sectors with specific needs when it comes to supporting innovation, the medical technology sector is facing several unique challenges that both increases the lead-time from idea to finished product and decreases the number of innovations that are developed. This paper presents a proposed innovation guide that has been developed and evaluated as a support for the innovation process within medical technology research. The guide takes the unique characteristics of the medical technology sector into account and serves as a usable guide for the innovator. The complete guide contains both a structure for the process and a usable web application to support the journey from idea to finished products and services. The paper also includes a new readiness level, Sect. 4.2 to provide support both when developing and determining the readiness for clinical implementation of a medical technology innovation. [ABSTRACT FROM AUTHOR]

Background: The pressure difference between the eye and brain in upright postures may be affected by compartmentalization of the optic nerve subarachnoid space (ONSAS). Both pressure and deformation will depend on the microstructures of the ONSAS, and most likely also on ocular glymphatic clearance. Studying these factors could yield important knowledge regarding the translaminar pressure difference, which is suspected to play a role in normal-tension glaucoma. Methods: A compartment model coupling the ONSAS with the craniospinal CSF system was used to investigate the effects of microstructures on the pressure transfer through the ONSAS during a posture change from supine to upright body postures. ONSAS distensibility was based on MRI measurements. We also included ocular glymphatic flow to investigate how local pressure gradients alter this flow with changes in posture. Results: A compartmentalization of the ONSAS occurred in the upright posture, with ONSAS porosity (degree of microstructural content) affecting the ONSAS pressure (varying the supine/baseline porosity from 1.0 to 0.75 yielded pressures between − 5.3 and − 2 mmHg). Restricting the minimum computed porosity (occurring in upright postures) to 0.3 prevented compartmentalization, and the ONSAS pressure could equilibrate with subarachnoid space pressure (− 6.5 mmHg) in ≤ 1 h. The ocular glymphatics analysis predicted that substantial intraocular-CSF flows could occur without substantial changes in the ONSAS pressure. The flow entering the ONSAS in supine position (both from the intraocular system and from the cranial subarachnoid space) exited the ONSAS through the optic nerve sheath, while in upright postures the flow through the ONSAS was redirected towards the cranial subarachnoid space. Conclusions: Microstructures affect pressure transmission along the ONSAS, potentially contributing to ONSAS compartmentalization in upright postures. Different pathways for ocular glymphatic flow were predicted for different postures. [ABSTRACT FROM AUTHOR]

Visualizing medical images from patients as physical 3D models (phantom models) have many roles in the medical field, from education to preclinical preparation and clinical research. However, current phantom models are generally generic, expensive, and time-consuming to fabricate. Thus, there is a need for a cost- and time-efficient pipeline from medical imaging to patient-specific phantom models. In this work, we present a method for creating complex 3D sacrificial molds using an off-the-shelf water-soluble resin and a low-cost desktop 3D printer. This enables us to recreate parts of the cerebral arterial tree as a full-scale phantom model ( 10 × 6 × 4 cm) in transparent silicone rubber (polydimethylsiloxane, PDMS) from computed tomography angiography images (CTA). We analyzed the model with magnetic resonance imaging (MRI) and compared it with the patient data. The results show good agreement and smooth surfaces for the arteries. We also evaluate our method by looking at its capability to reproduce 1 mm channels and sharp corners. We found that round shapes are well reproduced, whereas sharp features show some divergence. Our method can fabricate a patient-specific phantom model with less than 2 h of total labor time and at a low fabrication cost. [ABSTRACT FROM AUTHOR]

Sarcoidosis is a systemic inflammatory disease mainly affecting the lungs. The hallmark of sarcoidosis are granulomas that are surrounded by activated T cells, likely targeting the disease‐inducing antigen. IFNγ‐producing Th1 and Th17.1 T cells are elevated in sarcoidosis and associate with disease progression. Monocytes and dendritic cells (DCs) are antigen‐presenting cells (APCs) and required for T cell activation. Several subsets of monocytes and DCs with different functions were identified in sarcoidosis. However, to what extent different monocyte and DC subsets can support activation and skewing of T cells in sarcoidosis is still unclear. In this study, we performed a transcriptional and functional side‐by‐side comparison of sorted monocytes and DCs from matched blood and bronchoalveolar lavage (BAL) fluid of sarcoidosis patients. Transcriptomic analysis of all subsets showed upregulation of genes related to T cell activation and antigen presentation in DCs compared with monocytes. Allogeneic T cell proliferation was higher after coculture with monocytes and DCs from blood compared with BAL and DCs induced more T cell proliferation compared with monocytes. After coculture, proliferating T cells showed high expression of the transcription factor Tbet and IFNγ production. We also identified Tbet and RORγt coexpressing T cells that mainly produced IFNγ. Our data show that DCs rather than monocytes from sarcoidosis patients have the ability to activate and polarize T cells towards Th1 and Th17.1 cells. This study provides a useful in vitro tool to better understand the contribution of monocytes and DCs to T cell activation and immunopathology in sarcoidosis. [ABSTRACT FROM AUTHOR]

Objectives: Previous studies showed a strong association between sarcoidosis and heart failure (HF) but did not consider risk stratification or risk factors to identify useful aetiological insights. We estimated overall and stratified HRs and identified risk factors for HF in sarcoidosis.Methods: Sarcoidosis cases were identified from the Swedish National Patient Register (NPR; ≥2 International Classification of Diseases-coded visits, 2003-2013) and matched to general population comparators. They were followed for HF in the NPR. Treated were cases who were dispensed ≥1 immunosuppressant ±3 months from the first sarcoidosis visit (2006-2013). Using Cox models, we estimated HRs adjusted for demographics and comorbidity and identified independent risk factors of HF together with their attributable fractions (AFs).Results: During follow-up, 204 of 8574 sarcoidosis cases and 721 of 84 192 comparators were diagnosed with HF (rate 2.2 vs 0.7/1000 person-years, respectively). The HR associated with sarcoidosis was 2.43 (95% CI 2.06 to 2.86) and did not vary by age, sex or treatment status. It was higher during the first 2 years after diagnosis (HR 3.7 vs 1.9) and in individuals without a history of ischaemic heart disease (IHD; HR 2.7 vs 1.7). Diabetes, atrial fibrillation and other arrhythmias were the strongest independent clinical predictors of HF (HR 2.5 each, 2-year AF 20%, 16% and 12%, respectively).Conclusions: Although low, the HF rate was more than twofold increased in sarcoidosis compared with the general population, particularly right after diagnosis. IHD history cannot solely explain these risks, whereas ventricular arrhythmias indicating cardiac sarcoidosis appear to be a strong predictor of HF in sarcoidosis. [ABSTRACT FROM AUTHOR]

Alterations in cerebral blood flow are common in several neurological diseases among the elderly including stroke, cerebral small vessel disease, vascular dementia, and Alzheimer's disease. 4D flow magnetic resonance imaging (MRI) is a relatively new technique to investigate cerebrovascular disease, and makes it possible to obtain time‐resolved blood flow measurements of the entire cerebral arterial venous vasculature and can be used to derive a repertoire of hemodynamic biomarkers indicative of cerebrovascular health. The information that can be obtained from one single 4D flow MRI scan allows both the investigation of aberrant flow patterns at a focal location in the vasculature as well as estimations of brain‐wide disturbances in blood flow. Such focal and global hemodynamic biomarkers show the potential of being sensitive to impending cerebrovascular disease and disease progression and can also become useful during planning and follow‐up of interventions aiming to restore a normal cerebral circulation. Here, we describe 4D flow MRI approaches for analyzing the cerebral vasculature. We then survey key hemodynamic biomarkers that can be reliably assessed using the technique. Finally, we highlight cerebrovascular diseases where one or multiple hemodynamic biomarkers are of central interest. [ABSTRACT FROM AUTHOR]

Introduction: The treatment of hydrocephalus has been a topic of intense research ever since the first clinically successful use of a valved cerebrospinal fluid shunt 72 years ago. While ample studies elucidating different phenomena impacting this treatment exist, there are still gaps to be filled. Specifically, how intracranial, intrathecal, arterial, and venous pressures react and communicate with each other simultaneously. Methods: An in-vivo sheep trial (n = 6) was conducted to evaluate and quantify the communication existing within the cranio-spinal, arterial, and venous systems (1 kHz sampling frequency). Standardized intrathecal infusion testing was performed using an automated infusion apparatus, including bolus and constant pressure infusions. Bolus infusions entailed six lumbar intrathecal infusions of 2 mL Ringer's solution. Constant pressure infusions were comprised of six regulated pressure steps of 3.75 mmHg for periods of 7 min each. Mean pressure reactions, pulse amplitude reactions, and outflow resistance were calculated. Results: All sheep showed intracranial pressure reactions to acute increases of intrathecal pressure, with four of six sheep showing clear cranio-spinal communication. During bolus infusions, the increases of mean pressure for intrathecal, intracranial, arterial, and venous pressure were 16.6 ± 0.9, 15.4 ± 0.8, 3.9 ± 0.8, and 0.1 ± 0.2 mmHg with corresponding pulse amplitude increases of 2.4 ± 0.3, 1.3 ± 0.3, 1.3 ± 0.3, and 0.2 ± 0.1 mmHg, respectively. During constant pressure infusions, mean increases from baseline were 14.6 ± 3.8, 15.5 ± 4.2, 4.2 ± 8.2, and 3.2 ± 2.4 mmHg with the corresponding pulse amplitude increases of 2.5 ± 3.6, 2.5 ± 3.0, 7.7 ± 4.3, and 0.7 ± 2.0 mmHg for intrathecal, intracranial, arterial, and venous pulse amplitude, respectively. Outflow resistances were calculated as 51.6 ± 7.8 and 77.8 ± 14.5 mmHg/mL/min for the bolus and constant pressure infusion methods, respectively—showing deviations between the two estimation methods. Conclusions: Standardized infusion tests with multi-compartmental pressure recordings in sheep have helped capture distinct reactions between the intrathecal, intracranial, arterial, and venous systems. Volumetric pressure changes in the intrathecal space have been shown to propagate to the intraventricular and arterial systems in our sample, and to the venous side in individual cases. These results represent an important step into achieving a more complete quantitative understanding of how an acute rise in intrathecal pressure can propagate and influence other systems. [ABSTRACT FROM AUTHOR]

Intracranial arterial stiffening is a potential early marker of emerging cerebrovascular dysfunction and could be mechanistically involved in disease processes detrimental to brain function via several pathways. A prominent consequence of arterial wall stiffening is the increased velocity at which the systolic pressure pulse wave propagates through the vasculature. Previous non-invasive measurements of the pulse wave propagation have been performed on the aorta or extracranial arteries with results linking increased pulse wave velocity to brain pathology. However, there is a lack of intracranial "target-organ" measurements. Here we present a 4D flow MRI method to estimate pulse wave velocity in the intracranial vascular tree. The method utilizes the full detectable branching structure of the cerebral vascular tree in an optimization framework that exploits small temporal shifts that exists between waveforms sampled at varying depths in the vasculature. The method is shown to be stable in an internal consistency test, and of sufficient sensitivity to robustly detect age-related increases in intracranial pulse wave velocity. [ABSTRACT FROM AUTHOR]

Objective: A clinically feasible, non-invasive method to quantify blood flow, hemodynamics, and collateral flow in the vertebrobasilar arterial tree is missing. The objective of this study was to evaluate the feasibility of quantifying blood flow and blood flow patterns using 4D flow magnetic resonance imaging (MRI) in consecutive patients after an ischemic stroke in the posterior circulation. We also explore if 4D-flow, analyzed in conjunction with computed tomography angiography (CTA), has potential as a diagnostic tool in posterior circulation stroke. Methods: Twenty-five patients (mean age 62 years; eight women) with acute ischemic stroke in the posterior circulation were investigated. At admission, all patients were examined with CTA followed by MRI (4D flow MRI and diffusion-weighted sequences) at median 4 days after the presenting event. Based on the classification of Caplan, patients were divided into proximal/middle (n = 16) and distal territory infarcts (n = 9). Absolute and relative blood flow rates were calculated for internal carotid arteries (ICA), vertebral arteries (VA), basilar artery (BA), posterior cerebral arteries (P1 and P2), and the posterior communicating arteries (Pcom). In a control group consisting of healthy elderly, the 90th and 10th percentiles of flow were calculated in order to define normal, increased, or decreased blood flow in each artery. "Major hemodynamic disturbance" was defined as low BA flow and either low P2 flow or high Pcom flow. Various minor hemodynamic disturbances were also defined. Blood flow rates were compared between groups. In addition, a comprehensive analysis of each patient's blood flow profile was performed by assessing relative blood flow rates in each artery in conjunction with findings from CTA. Results: There was no difference in total cerebral blood flow between patients and controls [604 ± 117 ml/min vs. 587 ± 169 ml/min (mean ± SD), p = 0.39] or in total inflow to the posterior circulation (i.e., the sum of total VA and Pcom flows, 159 ± 63 ml/min vs. 164 ± 52 ml/min, p = 0.98). In individual arteries, there were no significant differences between patients and controls in absolute or relative flow. However, patients had larger interindividual relative flow variance in BA, P1, and P2 (p = 0.01, <0.01, and 0.02, respectively). Out of the 16 patients that had proximal/middle territory infarcts, nine had CTA findings in VA and/or BA generating five with major hemodynamic disturbance identified with 4D flow MRI. For those without CTA findings, seven had no or minor 4D flow MRI hemodynamic disturbance. Among nine patients with distal territory infarcts, one had major hemodynamic disturbances, while the remaining had minor disturbances. Conclusion: 4D flow MRI contributed to the identification of the patients who had major hemodynamic disturbances from the vascular pathologies revealed on CTA. We thus conclude that 4D flow MRI could add valuable hemodynamic information when used in conjunction with CTA. [ABSTRACT FROM AUTHOR]

Purpose: To examine feasibility of phase‐contrast magnetic resonance imaging (PCMRI) and to assess blood flow rate in the ophthalmic artery (OA) in patients with normal tension glaucoma (NTG) compared with healthy controls. Methods: Sixteen patients with treated NTG and 16 age‐ and sex‐matched healthy controls underwent PCMRI using a 3‐Tesla scanner and ophthalmological examinations. OA blood flow rate was measured using a 2D PCMRI sequence with a spatial resolution of 0.35 mm2. Results: The blood flow rate in the NTG group was 9.6 ± 3.9 ml/min [mean ± SD] compared with 11.9 ± 4.8 ml/min in the control group. Resistance Index (RI) and Pulsatility Index (PI) were 0.73 ± 0.08 and 1.36 ± 0.29, respectively, in the NTG group and 0.68 ± 0.13 and 1.22 ± 0.40, respectively, in the healthy group. The mean visual field index (VFI) was 46% ± 25 for the worse NTG eyes. The measured differences observed between the NTG group and the control group in blood flow rate (p = 0.12), RI (p = 0.18) and PI (p = 0.27) were non‐significant. Conclusions: This case–control study, using PCMRI, showed a slight, but non‐significant, reduction in OA blood flow rate in the NTG patients compared with the healthy controls. These results indicate that blood flow may be of importance in the pathogenesis of NTG. Considering that only a limited portion of the total OA blood flow supplies the ocular system and the large inter‐individual differences, a larger study or more advanced PCMRI technique might give the answer. [ABSTRACT FROM AUTHOR]

Microvascular damage in the hippocampus is emerging as a central cause of cognitive decline and dementia in aging. This could be a consequence of age-related decreases in vascular elasticity, exposing hippocampal capillaries to excessive cardiac-related pulsatile flow that disrupts the blood-brain barrier and the neurovascular unit. Previous studies have found altered intracranial hemodynamics in cognitive impairment and dementia, as well as negative associations between pulsatility and hippocampal volume. However, evidence linking features of the cerebral arterial flow waveform to hippocampal function is lacking. We used a high-resolution 4D flow MRI approach to estimate global representations of the time-resolved flow waveform in distal cortical arteries and in proximal arteries feeding the brain in healthy older adults. Waveform-based clustering revealed a group of individuals featuring steep systolic onset and high amplitude that had poorer hippocampus-sensitive episodic memory (p = 0.003), lower whole-brain perfusion (p = 0.001), and weaker microvascular low-frequency oscillations in the hippocampus (p = 0.035) and parahippocampal gyrus (p = 0.005), potentially indicating compromised neurovascular unit integrity. Our findings suggest that aberrant hemodynamic forces contribute to cerebral microvascular and hippocampal dysfunction in aging. [ABSTRACT FROM AUTHOR]

The 6‐month infection risk was 43% lower in patients with sarcoidosis who initiated methotrexate compared to those who started azathioprine. Our findings suggest that unless contraindications exist, methotrexate should be preferred over azathioprine as the primary steroid‐sparing choice in individuals with sarcoidosis. Background and objective: No clinical trial has examined the risk of infection associated methotrexate and azathioprine, two advocated treatments for sarcoidosis. We aimed to compare the 6‐month risk of infection after the initiation of methotrexate or azathioprine. Methods: We conducted a retrospective target trial emulation using Swedish pre‐existing data. We searched for eligible participants who were dispensed methotrexate or azathioprine in the Prescribed Drug Register (PDR) every day between January 2007 and June 2013. Adults were eligible if they had ≥2 ICD‐coded visits for sarcoidosis in the National Patient Register (NPR) and were dispensed ≥1 systemic corticosteroid but no methotrexate or azathioprine in the past 6 months (PDR). Within 6 months of methotrexate or azathioprine initiation, diagnosis of infectious disease was identified (visit in the NPR where infectious disease was the primary diagnosis). We estimated RR and risk differences comparing methotrexate (n = 667) to azathioprine initiations (n = 259) using targeted maximum likelihood estimation (TMLE) adjusting for demographic factors, comorbidity and sarcoidosis severity proxies. Results: There were 43 infections in the methotrexate group (adjusted 6‐month risk 6.8%) and 29 infections in the azathioprine group (12.0%). The RR for infectious disease at 6 months associated with methotrexate compared to azathioprine initiation was 0.57 (95% CI: 0.39, 0.82) and the risk difference was −5.2% (95% CI: −8.5%, −1.8%). The RR at 9 months was attenuated to 0.77 (95% CI: 0.52, 1.14). Conclusion: Methotrexate appears to be associated with a lower risk of infection in sarcoidosis than azathioprine, but randomized trials should confirm this finding. [ABSTRACT FROM AUTHOR]

An internal carotid artery (ICA) stenosis can potentially decrease the perfusion pressure to the brain. In this study, computational fluid dynamics (CFD) was used to study if there was a hemispheric pressure laterality between the contra- and ipsilateral middle cerebral artery (MCA) in patients with a symptomatic ICA stenosis. We further investigated if this MCA pressure laterality (ΔPMCA) was related to the hemispheric flow laterality (ΔQ) in the anterior circulation, i.e., ICA, proximal MCA and the proximal anterior cerebral artery (ACA). Twenty-eight patients (73±6 years, range 59–80 years, 21 men) with symptomatic ICA stenosis were included. Flow rates were measured using 4D flow MRI data (PC-VIPR) and vessel geometries were obtained from computed tomography angiography. The ΔPMCA was calculated from CFD, where patient-specific flow rates were applied at all input- and output boundaries. The ΔPMCA between the contra- and ipsilateral side was 6.4±8.3 mmHg (p<0.001) (median 3.9 mmHg, range -1.3 to 31.9 mmHg). There was a linear correlation between the ΔPMCA and ΔQICA (r = 0.85, p<0.001) and ΔQACA (r = 0.71, p<0.001), respectively. The correlation to ΔQMCA was weaker (r = 0.47, p = 0.011). In conclusion, the MCA pressure laterality obtained with CFD, is a promising physiological biomarker that can grade the hemodynamic disturbance in patients with a symptomatic ICA stenosis. [ABSTRACT FROM AUTHOR]

Recent reports have suggested that age-related arterial stiffening and excessive cerebral arterial pulsatility cause blood–brain barrier breakdown, brain atrophy and cognitive decline. This has spurred interest in developing non-invasive methods to measure pulsatility in distal vessels, closer to the cerebral microcirculation. Here, we report a method based on four-dimensional (4D) flow MRI to estimate a global composite flow waveform of distal cerebral arteries. The method is based on finding and sampling arterial waveforms from thousands of cross sections in numerous small vessels of the brain, originating from cerebral cortical arteries. We demonstrate agreement with internal and external reference methods and show the ability to capture significant increases in distal cerebral arterial pulsatility as a function of age. The proposed approach can be used to advance our understanding regarding excessive arterial pulsatility as a potential trigger of cognitive decline and dementia. [ABSTRACT FROM AUTHOR]

Findings from molecular studies suggesting that several infectious agents cause sarcoidosis are intriguing yet conflicting and likely biased due to their cross-sectional design. As done in other inflammatory diseases to overcome this issue, prospectively-collected register data could be used, but reverse causation is a threat when the onset of disease is difficult to establish. We investigated the association between infectious diseases and sarcoidosis to understand if they are etiologically related. We conducted a nested case–control study (2009–2013) using incident sarcoidosis cases from the Swedish National Patient Register (n = 4075) and matched general population controls (n = 40,688). Infectious disease was defined using inpatient/outpatient visits and/or antimicrobial dispensations starting 3 years before diagnosis/matching. Adjusted odds ratios (aOR) of sarcoidosis were estimated using conditional logistic regression and tested for robustness assuming the presence of reverse causation bias. The aOR of sarcoidosis associated with history of infectious disease was 1.19 (95% confidence interval [CI] 1.09, 1.29; 21% vs. 16% exposed cases and controls, respectively). Upper respiratory and ocular infections conferred the highest OR. Findings were similar when we altered the infection definition or varied the infection-sarcoidosis latency period (1–7 years). In bias analyses assuming one in 10 infections occurred because of preclinical sarcoidosis, the observed association was completely attenuated (aOR 1.02; 95% CI 0.90, 1.15). Our findings, likely induced by reverse causation due to preclinical sarcoidosis, do not support the hypothesis that common symptomatic infectious diseases are etiologically linked to sarcoidosis. Caution for reverse causation bias is required when the real disease onset is unknown. [ABSTRACT FROM AUTHOR]

Background: Four-dimensional flow magnetic resonance imaging (4D flow MRI) enables efficient investigation of cerebral blood flow pulsatility in the cerebral arteries. This is important for exploring hemodynamic mechanisms behind vascular diseases associated with arterial pulsations.Purpose: To investigate the feasibility of pulsatility assessments with 4D flow MRI, its agreement with reference two-dimensional phase-contrast MRI (2D PC-MRI) measurements, and to demonstrate how 4D flow MRI can be used to assess cerebral arterial compliance and cerebrovascular resistance in major cerebral arteries.Study Type: Prospective.Subjects: Thirty-five subjects (20 women, 79 ± 5 years, range 70-91 years).Field Strength/sequence: 4D flow MRI (PC-VIPR) and 2D PC-MRI acquired with a 3T scanner.Assessment: Time-resolved flow was assessed in nine cerebral arteries. From the pulsatile flow waveform in each artery, amplitude (ΔQ), volume load (ΔV), and pulsatility index (PI) were calculated. To reduce high-frequency noise in the 4D flow MRI data, the flow waveforms were low-pass filtered. From the total cerebral blood flow, total PI (PItot ), total volume load (ΔVtot ), cerebral arterial compliance (C), and cerebrovascular resistance (R) were calculated.Statistical Tests: Two-tailed paired t-test, intraclass correlation (ICC).Results: There was no difference in ΔQ between 4D flow MRI and the reference (0.00 ± 0.022 ml/s, mean ± SEM, P = 0.97, ICC = 0.95, n = 310) with a cutoff frequency of 1.9 Hz and 15 cut plane long arterial segments. For ΔV, the difference was -0.006 ± 0.003 ml (mean ± SEM, P = 0.07, ICC = 0.93, n = 310) without filtering. Total R was 11.4 ± 2.41 mmHg/(ml/s) (mean ± SD) and C was 0.021 ± 0.009 ml/mmHg (mean ± SD). ΔVtot was 1.21 ± 0.29 ml (mean ± SD) with an ICC of 0.82 compared with the reference. PItot was 1.08 ± 0.21 (mean ± SD).Data Conclusion: We successfully assessed 4D flow MRI cerebral arterial pulsatility, cerebral arterial compliance, and cerebrovascular resistance. Averaging of multiple cut planes and low-pass filtering was necessary to assess accurate peak-to-peak features in the flow rate waveforms.Level Of Evidence: 2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1516-1525. [ABSTRACT FROM AUTHOR]