Brainstorm-DUNEuro: An integrated and user-friendly Finite Element Method for modeling electromagnetic brain activity.

Human brain activity generates scalp potentials (electroencephalography - EEG), intracranial potentials (iEEG), and external magnetic fields (magnetoencephalography - MEG). These electrophysiology (e-phys) signals can often be measured simultaneously for research and clinical applications. The forward problem involves modeling these signals at their sensors for a given equivalent current dipole configuration within the brain. While earlier researchers modeled the head as a simple set of isotropic spheres, today's magnetic resonance imaging (MRI) data allow for a detailed anatomic description of brain structures and anisotropic characterization of tissue conductivities. We present a complete pipeline, integrated into the Brainstorm software, that allows users to automatically generate an individual and accurate head model based on the subject's MRI and calculate the electromagnetic forward solution using the finite element method (FEM). The head model generation is performed by integrating the latest tools for MRI segmentation and FEM mesh generation. The final head model comprises the five main compartments: white-matter, gray-matter, CSF, skull, and scalp. The anisotropic brain conductivity model is based on the effective medium approach (EMA), which estimates anisotropic conductivity tensors from diffusion-weighted imaging (DWI) data. The FEM electromagnetic forward solution is obtained through the DUNEuro library, integrated into Brainstorm, and accessible with either a user-friendly graphical interface or scripting. With tutorials and example data sets available in an open-source format on the Brainstorm website, this integrated pipeline provides access to advanced FEM tools for electromagnetic modeling to a broader neuroscience community.

[End-of-life care in a rural small-town region in Lower Saxony: a retrospective cross-sectional analysis based on routinely collected general practice data]. / Versorgung von Menschen am Lebensende in einer ländlich-kleinstädtischen Region Niedersachsens: eine retrospektive Querschnittsanalyse auf Basis hausärztlicher Routinedaten.

INTRODUCTION: Up to 90% of people at the end of life are in need of palliative care. The majority can be cared for within general outpatient palliative care (AAPV) by general practitioners. Previous studies have described outpatient palliative care to fall short behind the estimated needs and to be initiated rather late in the health care process. Yet, little is known about the development of outpatient palliative care in recent years and about the parameters influencing its utilisation. Therefore, this study aimed to investigate the number and time of initiation for AAPV and specialised outpatient palliative care (SAPV) in a rural and small-town region in Lower Saxony on the basis of routinely collected general practice data. Furthermore, this study sought to estimate the influence of various parameters related to patients, practices and physicians on the provision of AAPV and SAPV. METHODS: All general practitioners (n=190) in two counties in Lower Saxony were invited to take part in the project "Optimal care at the end of life - OPAL" (Innovation Fund, 01VSF17028) between autumn 2018 and spring 2019. In the participating practices, clinical data pertaining to patients with statutory health insurance, who had died in the second or third quarter of 2018, were collected in pseudonymised form and analysed using selected indicators for end-of-life care. The number of hospital stays and the provision of AAPV and SAPV were the subject of the descriptive analyses. In order to take the cluster effect of the practices into account, mixed-model analyses were carried out. RESULTS: The data of 279 deceased patients (48% female; median age 82 years) from 31 general practices were analysed. In the last year of life, AAPV was provided for 78 deceased patients (28.0%) with a median onset of 20 days before death. 52 deceased patients (18.6%) received SAPV with a median onset of 28 days before death, respectively. In the last six months of life, 207 deceased patients (74.2%) were hospitalised at least once. The mixed-model analyses showed a greater probability of receiving AAPV (odds ratio (OR)=3.3) or SAPV (OR=3.2) in the last year of life for patients with oncological diseases. It was also shown that GPs with a higher value on the subscale practice organisation billed more AAPV (OR=1.4). DISCUSSION: The number of patients with SAPV is at least equivalent to the estimated needs known from the literature in both selected regions. In contrast, AAPV seems to be provided relatively rarely and rather late in the health care process. Relevant reasons for this may be the lack of concrete criteria for AAPV (e. g., ambiguities and competing codes for billing) as well as prognostic uncertainties of health care providers especially for patients with non-oncological diseases. CONCLUSION: Strategies to further develop end-of-life care should especially strengthen the AAPV provided by general practitioners and focus on patients with non-oncological diseases.

DUNEuro-A software toolbox for forward modeling in bioelectromagnetism.

Accurate and efficient source analysis in electro- and magnetoencephalography using sophisticated realistic head geometries requires advanced numerical approaches. This paper presents DUNEuro, a free and open-source C++ software toolbox for the numerical computation of forward solutions in bioelectromagnetism. Building upon the DUNE framework, it provides implementations of modern fitted and unfitted finite element methods to efficiently solve the forward problems of electro- and magnetoencephalography. The user can choose between a variety of different source models that are implemented. The software's aim is to provide interfaces that are extendable and easy-to-use. In order to enable a closer integration into existing analysis pipelines, interfaces to Python and MATLAB are provided. The practical use is demonstrated by a source analysis example of somatosensory evoked potentials using a realistic six-compartment head model. Detailed installation instructions and example scripts using spherical and realistic head models are appended.

GPs' perspective on End-of-Life Care - an evaluation based on the German version of the General Practice End of Life Care Index.

Objective: General practitioners (GPs) play a key role in the provision of general outpatient palliative care (AAPV) for the majority of patients at the end of life. The aim of this study was to evaluate the quality of End-of-Life Care (EoLC) from a GPs' perspective using the German version of the General Practice End of Life Care Index (GP-EoLC-I). Methods: Between autumn 2018 and spring 2019, all registered and eligible GPs in two counties in Lower Saxony (n=190) were asked to participate in a survey on EoLC using the German version of the self-assessment questionnaire GP-EoLC-I. The index comprises two subscales: clinical care (13 items) and practice organisation (12 items). The summated index of both subscales measures the quality of EoLC by GPs (25 items; range 14-40). The questionnaire was supplemented by questions on sociodemographic data, indicators for good palliative care (PC) and requirements to improve PC. Quantitative data were analysed by descriptive statistics and free text answers by conventional content analysis according to Hsieh and Shannon. Results: 52 GPs (females: n=16) of 34 practices (single practices: n=26) participated in the study. The mean GP-EoLC-I was 27.5 (SD 4.5). The items revealed potential for improvement: systematic identification of patients with potential PC needs, multidisciplinary case conferences to discuss PC patients, application of care protocols and symptom assessment tools, documentation of patients' wishes and beliefs as well as inclusion of family and carers. Regarding the indicators for good PC, the most relevant indicators from the GPs' perspective were collaboration and coordination, integration of relatives, advance care planning and documentation. As requirements to improve PC, GPs highlighted further training and the use of standardised tools such as instruments to support the systematic identification of PC patients. Conclusions: To our knowledge for the first time in Germany, an internationally tested self-assessment questionnaire measuring the quality of EoLC by GPs was applied. The GP-EoLC-I in this study was slightly lower than the index of GPs in the United Kingdom. Including relatives and family carers, implementing tools to support early identification of PC patients and strengthening cooperation between GPs and other stakeholders in PC may be promising approaches to improve general PC and EoLC in Germany.

Quality indicators for the evaluation of end-of-life care in Germany - a retrospective cross-sectional analysis of statutory health insurance data.

BACKGROUND: The provision and quality of end-of-life care (EoLC) in Germany is inconsistent. Therefore, an evaluation of current EoLC based on quality indicators is needed. This study aims to evaluate EoLC in Germany on the basis of quality indicators pertaining to curative overtreatment, palliative undertreatment and delayed palliative care (PC). Results were compared with previous findings. METHODS: Data from a statutory health insurance provider (AOK Lower Saxony) pertaining to deceased members in the years 2016 and 2017 were used to evaluate EoLC. The main indicators were: chemotherapy for cancer patients in the last month of life, first-time percutaneous endoscopic gastrostomy (PEG) for patients with dementia in the last 3 months of life, number of hospitalisations and days spent in inpatient treatment in the last 6 months of life, and provision of generalist and specialist outpatient PC in the last year of life. Data were analysed descriptively. RESULTS: Data for 64,275 deceased members (54.3% female; 35.1% cancer patients) were analysed. With respect to curative overtreatment, 10.4% of the deceased with cancer underwent chemotherapy in the last month and 0.9% with dementia had a new PEG insertion in the last 3 months of life. The mean number of hospitalisations and inpatient treatment days per deceased member was 1.6 and 16.5, respectively, in the last 6 months of life. Concerning palliative undertreatment, generalist outpatient PC was provided for 28.0% and specialist outpatient PC was provided for 9.0% of the deceased. Regarding indicators for delayed PC, the median onset of generalist and specialist outpatient PC was 47.0 and 24.0 days before death, respectively. CONCLUSION: Compared to data from 2010 to 2014, the data analysed in the present study suggest an ongoing curative overtreatment in terms of chemotherapy and hospitalisation, a reduction in new PEG insertions and an increase in specialist PC. The number of patients receiving generalist PC remained low, with delayed onset. Greater awareness of generalist PC and the early integration of PC are recommended. TRIAL REGISTRATION: The study was registered in the German Clinical Trials Register ( DRKS00015108 ; 22 January 2019).

Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models.

Skull conductivity has a substantial influence on EEG and combined EEG and MEG source analysis as well as on optimized transcranial electric stimulation. To overcome the use of standard literature values, we propose a non-invasive two-level calibration procedure to estimate skull conductivity individually in a group study with twenty healthy adults. Our procedure requires only an additional run of combined somatosensory evoked potential and field data, which can be easily integrated in EEG/MEG experiments. The calibration procedure uses the P20/N20 topographies and subject-specific realistic head models from MRI. We investigate the inter-subject variability of skull conductivity and relate it to skull thickness, age and gender of the subjects, to the individual scalp P20/N20 surface distance between the P20 potential peak and the N20 potential trough as well as to the individual source depth of the P20/N20 source. We found a considerable inter-subject variability for (calibrated) skull conductivity (8.44 ± 4.84 mS/m) and skull thickness (5.97 ± 1.19 mm) with a statistically significant correlation between them (rho = 0.52). Age showed a statistically significant negative correlation with skull conductivity (rho = -0.5). Furthermore, P20/N20 surface distance and source depth showed large inter-subject variability of 12.08 ± 3.21 cm and 15.45 ± 4.54 mm, respectively, but there was no significant correlation between them. We also found no significant differences among gender subgroups for the investigated measures. It is thus important to take the inter-subject variability of skull conductivity and thickness into account by means of using subject-specific calibrated realistic head modeling.

The effect of stimulation type, head modeling, and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component.

Modeling and experimental parameters influence the Electro- (EEG) and Magnetoencephalography (MEG) source analysis of the somatosensory P20/N20 component. In a sensitivity group study, we compare P20/N20 source analysis due to different stimulation type (Electric-Wrist [EW], Braille-Tactile [BT], or Pneumato-Tactile [PT]), measurement modality (combined EEG/MEG - EMEG, EEG, or MEG) and head model (standard or individually skull-conductivity calibrated including brain anisotropic conductivity). Considerable differences between pairs of stimulation types occurred (EW-BT: 8.7 ± 3.3 mm/27.1° ± 16.4°, BT-PT: 9 ± 5 mm/29.9° ± 17.3°, and EW-PT: 9.8 ± 7.4 mm/15.9° ± 16.5° and 75% strength reduction of BT or PT when compared to EW) regardless of the head model used. EMEG has nearly no localization differences to MEG, but large ones to EEG (16.1 ± 4.9 mm), while source orientation differences are non-negligible to both EEG (14° ± 3.7°) and MEG (12.5° ± 10.9°). Our calibration results show a considerable inter-subject variability (3.1-14 mS/m) for skull conductivity. The comparison due to different head model show localization differences smaller for EMEG (EW: 3.4 ± 2.4 mm, BT: 3.7 ± 3.4 mm, and PT: 5.9 ± 6.8 mm) than for EEG (EW: 8.6 ± 8.3 mm, BT: 11.8 ± 6.2 mm, and PT: 10.5 ± 5.3 mm), while source orientation differences for EMEG (EW: 15.4° ± 6.3°, BT: 25.7° ± 15.2° and PT: 14° ± 11.5°) and EEG (EW: 14.6° ± 9.5°, BT: 16.3° ± 11.1° and PT: 12.9° ± 8.9°) are in the same range. Our results show that stimulation type, modality and head modeling all have a non-negligible influence on the source reconstruction of the P20/N20 component. The complementary information of both modalities in EMEG can be exploited on the basis of detailed and individualized head models.

Optimal care at the end of life (OPAL): study protocol of a prospective interventional mixed-methods study with pretest-posttest-design in a primary health care setting considering the view of general practitioners, relatives of deceased patients and health care stakeholders.

BACKGROUND: At the end of life, about 85-90% of patients can be treated within primary palliative care (PC) provided by general practitioners (GPs). In Germany, there is no structured approach for the provision of PC by GPs including a systematic as well as timely identification of patients who might benefit from PC, yet. The project "Optimal care at the end of life" (OPAL) focusses on an improvement of primary PC for patients with both oncological and non-oncological chronic progressive diseases in their last phase of life provided by GPs and health care services. METHODS: OPAL will take place in Hameln-Pyrmont, a rural region in Lower Saxony, Germany. Target groups are (a) GPs, (b) relatives of deceased patients and (c) health care providers. The study follows a three-phase approach in a mixed-methods and pre-post design. In phase I (baseline, t0) we explore the usual practice of providing PC for patients with chronic progressive diseases by GPs and the collaboration with other health care providers. In phase II (intervention) the Supportive and Palliative Care Indicators Tool (SPICT) for the timely identification of patients who might benefit from PC will be implemented and tested in general practices. Furthermore, a public campaign will be started to inform stakeholders, to connect health care providers and to train change agents. In phase III (follow-up, t1) we investigate the potential effect of the intervention to evaluate differences in the provision of PC by GPs and to convey factors for the implementation of SPICT in general practices. DISCUSSION: The project OPAL is the first study to implement the SPICT-DE regionwide in general practices in Germany. The project OPAL may contribute to an overall optimisation of primary PC for patients in Germany by reducing GPs' uncertainty in initiating PC, by consolidating their skills and competencies in identifying patients who might benefit from PC, and by improving the cooperation between GPs and different health care stakeholders. TRIAL REGISTRATION: The study was retrospectively registered at the German Clinical Trials Register (Deutsches Register Klinischer Studien; trial registration number: DRKS00015108 ; date of registration: 22th of January 2019).