Transforming Tele-Ophthalmology: Utilizing Cloud Computing for Remote Eye Care.

BACKGROUND: Tele-ophthalmology is gaining recognition for its role in improving eye care accessibility via cloud-based solutions. The Google Cloud Platform (GCP) Healthcare API enables secure and efficient management of medical image data such as high-resolution ophthalmic images. OBJECTIVES: This study investigates cloud-based solutions' effectiveness in tele-ophthalmology, with a focus on GCP's role in data management, annotation, and integration for a novel imaging device. METHODS: Leveraging the Integrating the Healthcare Enterprise (IHE) Eye Care profile, the cloud platform was utilized as a PACS and integrated with the Open Health Imaging Foundation (OHIF) Viewer for image display and annotation capabilities for ophthalmic images. RESULTS: The setup of a GCP DICOM storage and the OHIF Viewer facilitated remote image data analytics. Prolonged loading times and relatively large individual image file sizes indicated system challenges. CONCLUSION: Cloud platforms have the potential to ease distributed data analytics, as needed for efficient tele-ophthalmology scenarios in research and clinical practice, by providing scalable and secure image management solutions.

Global sensitivity of EEG source analysis to tissue conductivity uncertainties.

Introduction: To reliably solve the EEG inverse problem, accurate EEG forward solutions based on a detailed, individual volume conductor model of the head are essential. A crucial-but often neglected-aspect in generating a volume conductor model is the choice of the tissue conductivities, as these may vary from subject to subject. In this study, we investigate the sensitivity of EEG forward and inverse solutions to tissue conductivity uncertainties for sources distributed over the whole cortex surface. Methods: We employ a detailed five-compartment head model distinguishing skin, skull, cerebrospinal fluid, gray matter, and white matter, where we consider uncertainties of skin, skull, gray matter, and white matter conductivities. We use the finite element method (FEM) to calculate EEG forward solutions and goal function scans (GFS) as inverse approach. To be able to generate the large number of EEG forward solutions, we employ generalized polynomial chaos (gPC) expansions. Results: For sources up to a depth of 4 cm, we find the strongest influence on the signal topography of EEG forward solutions for the skull conductivity and a notable effect for the skin conductivity. For even deeper sources, e.g., located deep in the longitudinal fissure, we find an increasing influence of the white matter conductivity. The conductivity variations translate to varying source localizations particularly for quasi-tangential sources on sulcal walls, whereas source localizations of quasi-radial sources on the top of gyri are less affected. We find a strong correlation between skull conductivity and the variation of source localizations and especially the depth of the reconstructed source for quasi-tangential sources. We furthermore find a clear but weaker correlation between depth of the reconstructed source and the skin conductivity. Discussion: Our results clearly show the influence of tissue conductivity uncertainties on EEG source analysis. We find a particularly strong influence of skull and skin conductivity uncertainties.

Tunable Regioselectivity in C-H-Activated Direct Arylation Reactions of Dithieno[3,2-b:2',3'-d]pyrroles.

In this study, regioselectively controlled direct arylation of dithieno[3,2-b:2,3'-d]pyrroles (DTPs) is reported. By carefully selecting the catalytic system, Pd source, ligand, and additives, we achieved either selective N-arylation or unprecedented ß-arylation and ß,ß'-diarylation of the DTP core through C-H activation when reacting unsubstituted H-DTP with 9-anthracenyl halides. For N-substituted DTPs, we obtained regioselective carboxylate-assisted arylation of the α-position(s). Consequently, depending on the catalytic system and substitution at the DTP nitrogen, we successfully synthesized novel regioselectively substituted DTPs, including N-aryl, rarely reported ß-aryl, ß,ß'-diaryl, α-aryl, and α,α'-diaryl scaffolds. These compounds can be straightforwardly prepared and further functionalized for applications as organic electronic materials.

Optical Measurement of Ligament Strain: Opportunities and Limitations for Intraoperative Application.

A feasible and precise method to measure ligament strain during surgical interventions could significantly enhance the quality of ligament reconstructions. However, all existing scientific approaches to measure in vivo ligament strain possess at least one significant disadvantage, such as the impairment of the anatomical structure. Seeking a more advantageous method, this paper proposes defining medical and technical requirements for a non-destructive, optical measurement technique. Furthermore, we offer a comprehensive review of current optical endoscopic techniques which could potentially be suitable for in vivo ligament strain measurement, along with the most suitable optical measurement techniques. The most promising options are rated based on the defined explicit and implicit requirements. Three methods were identified as promising candidates for a precise optical measurement of the alteration of a ligaments strain: confocal chromatic imaging, shearography, and digital image correlation.

Temperature dependent magnetorelaxometry of magnetic nanoparticle ensembles.

Magnetorelaxometry imaging (MRXI) is a non-invasive, quantitative imaging technique for magnetic nanoparticles (MNPs). The image resolution of this technique significantly depends on the relaxation amplitude (ΔB). For this work, we measured the room temperature (299 K) relaxation signals of eight commercial MNP sample systems with different magnetic properties, in both fluid and immobilized states, in order to select the most suitable sample for a particular MRXI setting. Additionally, the effect of elevated temperatures (up to hyperthermia temperature, 335 K) on the relaxation signals of four different MNP systems (Synomag, Perimag, BNF and Nanomag) in both states were investigated. The ΔBvalues of fluid samples significantly decreased with increasing temperature, and the behaviour for immobilized samples depended on their blocking temperature (TB). For samples withTB< 299 K, ΔBalso decreased with increasing temperature. Whereas for samples withTB> 299 K, the opposite behaviour was observed. These results are beneficial for improving the image resolution in MRXI and show, among the investigated systems, and for our setup, Synomag is the best candidate for futurein vitroandin vivostudies. This is due to its consistently high ΔBbetween 299 and 335 K in both states. Our findings demonstrate the feasibility of temperature imaging by MRXI.

Human-sized quantitative imaging of magnetic nanoparticles with nonlinear magnetorelaxometry.

Objective.Magnetorelaxomety imaging (MRXI) is a noninvasive imaging technique for quantitative detection of magnetic nanoparticles (MNPs). The qualitative and quantitative knowledge of the MNP distribution inside the body is a prerequisite for a number of arising biomedical applications, such as magnetic drug targeting and magnetic hyperthermia therapy. It was shown throughout numerous studies that MRXI is able to successfully localize and quantify MNP ensembles in volumes up to the size of a human head. However, deeper regions that lie far from the excitation coils and the magnetic sensors are harder to reconstruct due to the weaker signals from the MNPs in these areas. On the one hand, stronger magnetic fields need to be applied to produce measurable signals from such MNP distributions to further upscale MRXI, on the other hand, this invalidates the assumption of a linear relation between applied magnetic field and particle magnetization in the current MRXI forward model which is required for the imaging procedure.Approach.We tackle this problem by introducing a nonlinear MRXI forward model that is also valid for strong magnetic excitation fields.Main results.We demonstrate in our experimental feasibility study that scaling up the imaging region to the size of a human torso using nonlinear MRXI is possible. Despite the extreme simplicity of the imaging setup applied in this study, an immobilized MNP sample with 6.3 cm3and 12 mg Fe could be localized and quantified with an acceptable quality.Significance.A well-engineered MRXI setup could provide much better imaging qualities in shorter data acquisition times, making nonlinear MRXI a viable option for the supervision of MNP related therapies in all regions of the human body, specifically magnetic hyperthermia.

Integrating a Novel Eye Imaging System into Clinical Practice: An Open-Source DICOM Simulation Platform.

BACKGROUND: The integration of innovative imaging technologies into clinical workflows requires the utilization of a standardized data exchange format. The "Digital Imaging and Communications in Medicine" (DICOM) standard is widely used in healthcare to process and transfer medical images. However, no simulation environment is ready to use for development. The objective of this paper is to provide an open-source DICOM platform for integrating a novel ocular photography system into a clinical setting. METHODS: After a thorough analysis of the available open-source tools, a subset was selected and aligned with the U-Eyecare Profile of Integrating the Healthcare Enterprise (IHE). RESULTS: Orthanc served as a PACS with a modality worklist and the OHIF-Viewer for image retrieval. Minimal interfaces for the electronic health record and image modality were created. Docker-compose further integrates all components and simulates the network protocols DICOM Message Service Element and DICOMWeb. DISCUSSION: The platform was used to develop and integrate the developed image modality and will be further utilized for teleophthalmology and processing eye images. The platform could be useful for other researchers to integrate an image modality into a clinical environment along IHE.

Predicting prediction: A systematic workflow to analyze factors affecting the classification performance in genomic biomarker discovery.

High throughput technologies in genomics enable the analysis of small alterations in gene expression levels. Patterns of such deviations are an important starting point for the discovery and verification of new biomarker candidates. Identifying such patterns is a challenging task that requires sophisticated machine learning approaches. Currently, there are a variety of classification models, and a common approach is to compare the performance and select the best one for a given classification problem. Since the association between the features of a data set and the performance of a particular classification method is still not fully understood, the main contribution of this work is to provide a new methodology for predicting the prediction results of different classifiers in the field of biomarker discovery. We propose here a three-steps computational workflow that includes an analysis of the data set characteristics, the calculation of the classification accuracy and, finally, the prediction of the resulting classification error. The experiments were carried out on synthetic and microarray datasets. Using this method, we showed that the predictability strongly depends on the discriminatory ability of the features, e.g., sets of genes, in two or multi-class datasets. If a dataset has a certain discriminatory ability, this method enables prediction of the classification performance before applying a learning model. Thus, our results contribute to a better understanding of the relationship between dataset characteristics and the corresponding performance of a machine learning method, and suggest the optimal classification method for a given dataset based on its discriminatory ability.

Developing magnetorelaxometry imaging for human applications.

Objective.Magnetic nanoparticles (MNPs) are a promising tool in biomedical applications such as cancer therapy and diagnosis, where localization and quantification of MNP distributions are often mandatory. This can be obtained by magnetorelaxometry imaging (MRXI).Approach.In this work, the capability of MRXI for quantitative imaging of MNP inside larger volumes such as a human head is investigated. We developed a human head phantom simulating a glioblastoma multiforme (GBM) tumor containing MNP for magnetic hyperthermia treatment. The sensitivity of our MRXI setup for detection of MNP concentrations in the range of 3-19 mg cm-3was studied.Main result.The results show the high capability of MRXI to detect MNPs in a human head sized volume. Superficial sources with a concentration larger than 12 mg cm-3could be reconstructed with a resulotion of about 1 cm-3.Significance.The reconstruction of the MNP distribution, mimicking a GBM tumor of 7 cm3volume with clinically relevant iron concentration, demonstrates thein vivofeasibility of MRXI in humans.

Computer Simulation of the Electrical Stimulation of the Human Vestibular System: Effects of the Reactive Component of Impedance on Voltage Waveform and Nerve Selectivity.

The vestibular system is responsible for our sense of balance and spatial orientation. Recent studies have shown the possibility of partially restoring the function of this system using vestibular implants. Electrical modeling is a valuable tool in assisting the development of these implants by analyzing stimulation effects. However, previous modeling approaches of the vestibular system assumed quasi-static conditions. In this work, an extended modeling approach is presented that considers the reactive component of impedance and the electrode-tissue interface and their effects are investigated in a 3D human vestibular computer model. The Fourier finite element method was employed considering the frequency-dependent electrical properties of the different tissues. The electrode-tissue interface was integrated by an instrumental electrode model. A neuron model of myelinated fibers was employed to predict the nerve responses to the electrical stimulus. Morphological changes of the predicted voltage waveforms considering the dielectric tissue properties were found compared to quasi-static simulations, particularly during monopolar electrode configuration. Introducing the polarization capacitance and the scar tissue around the electrode in combination with a power limitation leads to a considerable current reduction applied through the active electrode and, consequently, to reduced voltage amplitudes of the stimulus waveforms. The reactive component of impedance resulted in better selectivity for the excitation of target nerves compared to the quasi-static simulation at the expense of slightly increased stimulus current amplitudes. We conclude that tissue permittivity and effects of the electrode-tissue interface should be considered to improve the accuracy of the simulations.

Data Exchange Standards in Teleophthalmology: Current and Future Developments.

BACKGROUND: Teleophthalmology services are considered capable of supporting screening, early diagnosis, and monitoring of leading causes of blindness on a global scale. Therefore, standards and best practices are needed to seamlessly exchange medical ocular images and related data among relevant stakeholders with maximum interoperability. OBJECTIVES: This paper provides an overview of current standards in the field of store-and-forward teleophthalmology data exchange and further developments in this area. METHODS: A literature review was conducted for healthcare standards with a focus on data exchange in ophthalmology. RESULTS: IHE, HL7 FHIR, DICOM, and clinical terminologies are considered the most important standards, providing distinct concepts, solutions, and guidelines for ophthalmology. CONCLUSION: Available standards provide the necessary base for teleophthalmology on technical and semantic interoperability, but practical use is limited due to missing process interoperability resulting in proprietary interfaces of vendors and rejection by ophthalmologists. Further investigations should analyze processual needs on ophthalmology data exchange standards.

Experimental demonstration of improved magnetorelaxometry imaging performance using optimized coil configurations.

BACKGROUND: Magnetorelaxometry imaging is an experimental imaging technique capable of reconstructing magnetic nanoparticle distributions inside a volume noninvasively and with high specificity. Thus, magnetorelaxometry imaging is a promising candidate for monitoring a number of therapeutical approaches that employ magnetic nanoparticles, such as magnetic drug targeting and magnetic hyperthermia, to guarantee their safety and efficacy. Prior to a potential clinical application of this imaging modality, it is necessary to optimize magnetorelaxometry imaging systems to produce reliable imaging results and to maximize the reconstruction accuracy of the magnetic nanoparticle distributions. Multiple optimization approaches were already applied throughout a number of simulation studies, all of which yielded increased imaging qualities compared to intuitively designed measurement setups. PURPOSE: None of these simulative approaches was conducted in practice such that it still remains unclear if the theoretical results are achievable in an experimental setting. In this study, we demonstrate the technical feasibility and the increased reconstruction accuracy of optimized coil configurations in two distinct magnetorelaxometry setups. METHODS: The electromagnetic coil positions and radii of a cuboidal as well as a cylindrical magnetorelaxometry imaging setup are optimized by minimizing the system matrix condition numbers of their corresponding linear forward models. The optimized coil configurations are manufactured alongside with two regular coil grids. Magnetorelaxometry measurements of three cuboidal and four cylindrical magnetic nanoparticle phantoms are conducted, and the resulting reconstruction qualities of the optimized and the regular coil configurations are compared. RESULTS: The computed condition numbers of the optimized coil configurations are approximately one order of magnitude lower compared to the regular coil grids. The reconstruction results show that for both setups, every phantom is recovered more accurately by the optimized coil configurations compared to the regular coil grids. Additionally, the optimized coil configurations yield better signal qualities. CONCLUSIONS: The presented experimental study provides a proof of the practicality and the efficacy of optimizing magnetorelaxometry imaging systems with respect to the condition numbers of their system matrices, previously only demonstrated in simulations. From the promising results of our study, we infer that the minimization of the system matrix condition number will also enable the practical optimization of other design parameters of magnetorelaxometry imaging setups (e.g., sensor configuration, coil currents, etc.) in order to improve the achievable reconstruction qualities even further, eventually paving the way towards clinical application of this imaging modality.

Unsupervised Learning for Hydrogen Breath Tests.

Hydrogen breath tests are a well-established method to help diagnose functional intestinal disorders such as carbohydrate malabsorption or small intestinal bacterial overgrowth. In this work we apply unsupervised machine learning techniques to analyze hydrogen breath test datasets. We propose a method that uses 26 internal cluster validation measures to determine a suitable number of clusters. In an induced external validation step we use a predefined categorization proposed by a medical expert. The results indicate that the majority of the considered internal validation indexes was not able to produce a reasonable clustering. Considering a predefined categorization performed by a medical expert, a novel shape-based method obtained the highest external validation measure in terms of adjusted rand index. The predefined clusterings constitute the basis of a supervised machine learning step that is part of our ongoing research.

Pulsed Optically Pumped Magnetometers: Addressing Dead Time and Bandwidth for the Unshielded Magnetorelaxometry of Magnetic Nanoparticles.

Magnetic nanoparticles (MNP) offer a large variety of promising applications in medicine thanks to their exciting physical properties, e.g., magnetic hyperthermia and magnetic drug targeting. For these applications, it is crucial to quantify the amount of MNP in their specific binding state. This information can be obtained by means of magnetorelaxometry (MRX), where the relaxation of previously aligned magnetic moments of MNP is measured. Current MRX with optically pumped magnetometers (OPM) is limited by OPM recovery time after the shut-off of the external magnetic field for MNP alignment, therewith preventing the detection of fast relaxing MNP. We present a setup for OPM-MRX measurements using a commercially available pulsed free-precession OPM, where the use of a high power pulsed pump laser in the sensor enables a system recovery time in the microsecond range. Besides, magnetometer raw data processing techniques for Larmor frequency analysis are proposed and compared in this paper. Due to the high bandwidth (≥100 kHz) and high dynamic range of our OPM, a software gradiometer in a compact enclosure allows for unshielded MRX measurements in a laboratory environment. When operated in the MRX mode with non-optimal pumping performance, the OPM shows an unshielded gradiometric noise floor of about 600 fT/cm/Hz for a 2.3 cm baseline. The noise floor is flat up to 1 kHz and increases then linearly with the frequency. We demonstrate that quantitative unshielded MRX measurements of fast relaxing, water suspended MNP is possible with the novel OPM-MRX concept, confirmed by the accurately derived iron amount ratios of MNP samples. The detection limit of the current setup is about 1.37 µg of iron for a liquid BNF-MNP-sample (Bionized NanoFerrite) with a volume of 100 µL.

A Computer Model for Patient Individual Parametrizing of Ventricular Tachycardia Termination Algorithms.

BACKGROUND: Antitachycardial pacing (ATP) is a painless method for terminating ventricular tachycardias (VT) which would otherwise be treated using a painful high energy shock. However, it is well known that not each VT can be successfully terminated by ATP. Furthermore, ATP can be parametrized in several ways using scan, ramp or scan ramp approaches and can be applied in the right ventricle or in both ventricles (biventricular). In this work, we investigate the therapeutically most convenient ATP protocol based on a computer simulation using a patient individual model. METHODS: A patient individual model generated from a 3D/4D data set and a hybrid automaton was used for modeling and simulation of different VT scenarios. On the different VTs (from cycle length 288 ms up to 408 ms) different ATP approaches derived from the ADVANCE-CRT trial were applied in order to determine the effectiveness of these approaches. RESULTS: In this computer simulation study we were able to verify and validate the results from the ADVANCE-CRT trial. Biventricular ATP does not prove to be more effective than RV ATP but has a slight advantage in terminating fast VTs. CONCLUSIONS: The availability of a patient individual model and knowledge about the ischemic area and the underlying mechanism of the VTs will allow the use of these models to optimize ATP management.

Quantitative 2D Magnetorelaxometry Imaging of Magnetic Nanoparticles using Optically Pumped Magnetometers.

For biomagnetical applications exploiting physical properties of magnetic nanoparticles (MNP), e.g., magnetic hyperthermia, knowledge about the quantitative spatial MNP distribution is crucial, which can be extracted by magnetorelaxometry (MRX) imaging. In this paper, we present quantification, quantitative 1D reconstruction, and quantitative 2D imaging of MNP by exploiting optically pumped magnetometers for MRX. While highlighting the potential of commercially available optically pumped magnetometers (OPM) for MRXI, we discuss current limitations of the used OPM. We show, that with our OPM setup, MNP can be precisely quantified with iron amounts down to ≈ 6 g , which can be improved easily. With a 1D-reconstruction setup, point-like and complex MNP phantoms can be reconstructed quantitatively with high precision and accuracy. We show that with our developed 2D MRX imaging setup, which measures 12 c m by 8 c m , point-like MNP distributions with clinically relevant iron concentrations can be reconstructed precisely and accurately. Our 2D setup has the potential to be easily extended to a tomography styled (and thus slice-selective) 3D scanner, by adding a mechanical axis to the phantom.

Ensemble Based Approach for Time Series Classification in Metabolomics.

BACKGROUND: Machine learning is one important application in the area of health informatics, however classification methods for longitudinal data are still rare. OBJECTIVES: The aim of this work is to analyze and classify differences in metabolite time series data between groups of individuals regarding their athletic activity. METHODS: We propose a new ensemble-based 2-tier approach to classify metabolite time series data. The first tier uses polynomial fitting to generate a class prediction for each metabolite. An induced classifier (k-nearest-neighbor or naïve bayes) combines the results to produce a final prediction. Metabolite levels of 47 individuals undergoing a cycle ergometry test were measured using mass spectrometry. RESULTS: In accordance with our previous work the statistical results indicate strong changes over time. We found only small but systematic differences between the groups. However, our proposed stacking approach obtained a mean accuracy of 78% using 10-fold cross-validation. CONCLUSION: Our proposed classification approach allows a considerable classification performance for time series data with small differences between the groups.

Model-Based Vestibular Afferent Stimulation: Evaluating Selective Electrode Locations and Stimulation Waveform Shapes.

A dysfunctional vestibular system can be a severe detriment to the quality of life of a patient. Recent studies have shown the feasibility for a vestibular implant to restore rotational sensation via electrical stimulation of vestibular ampullary nerves. However, the optimal stimulation site for selective elicitation of the desired nerve is still unknown. We realized a finite element model on the basis of µCT scans of a human inner ear and incorporated naturally distributed, artificial neural trajectories. A well-validated neuron model of myelinated fibers was incorporated to predict nerve responses to electrical stimulation. Several virtual electrodes were placed in locations of interest inside the bony labyrinth (intra-labyrinthine) and inside the temporal bone, near the target nerves (extra-labyrinthine), to determine preferred stimulation sites and electrode insertion depths. We investigated various monopolar and bipolar electrode configurations as well as different pulse waveform shapes for their ability to selectively stimulate the target nerve and for their energy consumption. The selectivity was evaluated with an objective measure of the fiber recruitment. Considerable differences of required energy and achievable selectivity between the configurations were observed. Bipolar, intra-labyrinthine electrodes provided the best selectivities but also consumed the highest amount of energy. Bipolar, extra-labyrinthine configurations did not offer any advantages compared to the monopolar approach. No selective stimulation could be performed with the monopolar, intra-labyrinthine approach. The monopolar, extra-labyrinthine electrodes required the least energy for satisfactory selectivities, making it the most promising approach for functional vestibular implants. Different pulse waveform shapes did not affect the achieved selectivity considerably but shorter pulse durations showed consistently a more selective activation of the target nerves. A cathodic, centered triangular waveform shape was identified as the most energy-efficient of the tested shapes. Based on these simulations we are able to recommend the monopolar, extra-labyrinthine stimulation approach with cathodic, centered triangular pulses as good trade-off between selectivity and energy consumption. Future implant designs could benefit from the findings presented here.

Experimental Characterization and Correlation of Mayer Waves in Retinal Vessel Diameter and Arterial Blood Pressure.

Retinal vessels show various biological temporal variations that can impact diagnosis using a static vessel analysis. In this study, Mayer waves in the retinal vessel diameter and arterial blood pressure (BP) signals were characterized, and the temporal correlation between these two modalities was investigated. The arterial and venous vessel diameters and arterial BP were recorded simultaneously on human subjects. The obtained vessel diameters showed vasomotion amplitudes over time. The vessel diameter and BP signals contained multiple signals in the frequency domain and varied over time. The signal characteristics were similar within the measurements. The BP and arterial and venous vessel diameters were correlated. The highest correlation values between the signals were observed for shifts of 1 or 0 periods. The spectrum and amplitudes of the Mayer waves showed a high variability. The Mayer waves in the retinal vessel diameters showed the same characteristics as those in the arterial BP. A temporal dependency between the oscillations in the arterial BP and retinal vessel diameters was shown.

MNE Scan: Software for real-time processing of electrophysiological data.

BACKGROUND: Magnetoencephalography (MEG) and Electroencephalography (EEG) are noninvasive techniques to study the electrophysiological activity of the human brain. Thus, they are well suited for real-time monitoring and analysis of neuronal activity. Real-time MEG/EEG data processing allows adjustment of the stimuli to the subject's responses for optimizing the acquired information especially by providing dynamically changing displays to enable neurofeedback. NEW METHOD: We introduce MNE Scan, an acquisition and real-time analysis software based on the multipurpose software library MNE-CPP. MNE Scan allows the development and application of acquisition and novel real-time processing methods in both research and clinical studies. The MNE Scan development follows a strict software engineering process to enable approvals required for clinical software. RESULTS: We tested the performance of MNE Scan in several device-independent use cases, including, a clinical epilepsy study, real-time source estimation, and Brain Computer Interface (BCI) application. COMPARISON WITH EXISTING METHOD(S): Compared to existing tools we propose a modular software considering clinical software requirements expected by certification authorities. At the same time the software is extendable and freely accessible. CONCLUSION: We conclude that MNE Scan is the first step in creating a device-independent open-source software to facilitate the transition from basic neuroscience research to both applied sciences and clinical applications.