Identifying potential predictable indicators for the management of tertiary hospitals.

BACKGROUND: The European University Hospitals Alliance (EUHA) recognises the need to move from the classical approach of measuring key performance indicators (KPIs) to an anticipative approach based on predictable indicators to take decisions (Key Decision Indicators, KDIs). It might help managers to anticipate poor results before they occur to prevent or correct them early. OBJECTIVE: This paper aims to identify potential KDIs and to prioritize those most relevant for high complexity hospitals. METHODS: A narrative review was performed to identify KPIs with the potential to become KDIs. Then, two surveys were conducted with EUHA hospital managers (n = 51) to assess potential KDIs according to their relevance for decision-making (Value) and their availability and effort required to be predicted (Feasibility). Potential KDIs are prioritized for testing as predictable indicators and developing in the short term if they were classified as highly Value and Feasible. RESULTS: The narrative review identified 45 potential KDIs out of 153 indicators and 11 were prioritized. Of nine EUHA hospitals, 25 members from seven answered, prioritizing KDIs related to the emergency department (ED), hospitalisation and surgical processes (n = 8), infrastructure and resources (n = 2) and health outcomes and quality (n = 1). The highest scores in this group were for those related to ED. The results were homogeneous among the different hospitals. CONCLUSIONS: Potential KDIs related to care processes and hospital patient flow was the most prioritized ones to test as being predictable. KDIs represent a new approach to decision-making, whose potential to be predicted could impact the planning and management of hospital resources and, therefore, healthcare quality.

Social work after stroke: identifying demand for support by recording stroke patients' and carers' needs in different phases after stroke.

BACKGROUND: Previous studies examining social work interventions in stroke often lack information on content, methods and timing over different phases of care including acute hospital, rehabilitation and out-patient care. This limits our ability to evaluate the impact of social work in multidisciplinary stroke care. We aimed to quantify social-work-related support in stroke patients and their carers in terms of timing and content, depending on the different phases of stroke care. METHODS: We prospectively collected and evaluated data derived from a specialized "Stroke-Service-Point" (SSP); a "drop in" center and non-medical stroke assistance service, staffed by social workers and available to all stroke patients, their carers and members of the public in the metropolitan region of Berlin, Germany. RESULTS: Enquiries from 257 consenting participants consulting the SSP between March 2010 and April 2012 related to out-patient and in-patient services, therapeutic services, medical questions, medical rehabilitation, self-help groups and questions around obtaining benefits. Frequency of enquiries for different topics depended on whether patients were located in an in-patient or out-patient setting. The majority of contacts involved information provision. While the proportion of male and female patients with stroke was similar, about two thirds of the carers contacting the SSP were female. CONCLUSION: The social-work-related services provided by a specialized center in a German metropolitan area were diverse in terms of topic and timing depending on the phase of stroke care. Targeting the timing of interventions might be important to increase the impact of social work on patient's outcome.

Potential determinants of efficacy of mirror therapy in stroke patients--A pilot study.

BACKGROUND: Mirror therapy (MT) was found to improve motor function after stroke. However, there is high variability between patients regarding motor recovery. OBJECTIVES: The following pilot study was designed to identify potential factors determining this variability between patients with severe upper limb paresis, receiving MT. METHODS: Eleven sub-acute stroke patients with severe upper limb paresis participated, receiving in-patient rehabilitation. After a set of pre-assessments (including measurement of brain activity at the primary motor cortex and precuneus during the mirror illusion, using near-infrared spectroscopy as described previously), four weeks of MT were applied, followed by a set of post-assessments. Discriminant group analysis for MT responders and non-responders was performed. RESULTS: Six out of eleven patients were defined as responders and five as non-responders on the basis of their functional motor improvement. The initial motor function and the activity shift in both precunei (mirror index) were found to discriminate significantly between responders and non-responders. CONCLUSIONS: In line with earlier results, initial motor function was confirmed as crucial determinant of motor recovery. Additionally, activity response to the mirror illusion in both precunei was found to be a candidate for determination of the efficacy of MT.

A validation study of the use of near-infrared spectroscopy imaging in primary and secondary motor areas of the human brain.

The electroencephalographically measured Bereitschafts (readiness)-potential in the supplementary motor area (SMA) serves as a signature of the preparation of motor activity. Using a multichannel, noninvasive near-infrared spectroscopy (NIRS) imager, we studied the vascular correlate of the readiness potential. Sixteen healthy subjects performed a self-paced or externally triggered motor task in a single or repetitive pattern, while NIRS simultaneously recorded the task-related responses of deoxygenated hemoglobin (HbR) in the primary motor area (M1) and the SMA. Right-hand movements in the repetitive sequence trial elicited a significantly greater HbR response in both the SMA and the left M1 compared to left-hand movements. During the single sequence condition, the HbR response in the SMA, but not in the M1, was significantly greater for self-paced than for externally cued movements. Nonetheless, an unequivocal temporal delay was not found between the SMA and M1. Near-infrared spectroscopy is a promising, noninvasive bedside tool for the neuromonitoring of epileptic seizures or cortical spreading depolarizations (CSDs) in patients with epilepsy, stroke, or brain trauma because these pathological events are associated with typical spatial and temporal changes in HbR. Propagation is a characteristic feature of these events which importantly supports their identification and characterization in invasive recordings. Unfortunately, the present noninvasive study failed to show a temporal delay during self-paced movements between the SMA and M1 as a vascular correlate of the readiness potential. Although this result does not exclude, in principle, the possibility that scalp-NIRS can detect a temporal delay between different regions during epileptic seizures or CSDs, it strongly suggests that further technological development of NIRS should focus on both improved spatial and temporal resolution. This article is part of a Special Issue entitled Status Epilepticus.

Imperceptible somatosensory stimulation alters sensorimotor background rhythm and connectivity.

Most sensory input to our body is not consciously perceived. Nevertheless, it may reach the cortex and influence our behavior. In this study, we investigated noninvasive neural signatures of unconscious cortical stimulus processing to understand mechanisms, which (1) prevent low-intensity somatosensory stimuli from getting access to conscious experience and which (2) can explain the associated impediment of conscious perception for additional stimuli. Stimulation of digit 2 in humans far below the detection threshold elicited a cortical evoked potential (P1) at 60 ms, but no further somatosensory evoked potential components. No event-related desynchronization was detected; rather, there was a transient synchronization in the alpha frequency range. Using the same stimulation during fMRI, a reduced centrality of contralateral primary somatosensory cortex (SI) was found, which appeared to be mainly driven by reduced functional connectivity to frontoparietal areas. We conclude that after subthreshold stimulation the (excitatory) feedforward sweep of bottom-up processing terminates in SI preventing access to conscious experience. We speculate that this interruption is due to a predominance of inhibitory processing in SI. The increase in alpha activity and the disconnection of SI from frontoparietal areas are likely correlates of an elevated perception threshold and may thus serve as a gating mechanism for the access to conscious experience.

Optimizing the regularization for image reconstruction of cerebral diffuse optical tomography.

Functional near-infrared spectroscopy (fNIRS) is an optical method for noninvasively determining brain activation by estimating changes in the absorption of near-infrared light. Diffuse optical tomography (DOT) extends fNIRS by applying overlapping "high density" measurements, and thus providing a three-dimensional imaging with an improved spatial resolution. Reconstructing brain activation images with DOT requires solving an underdetermined inverse problem with far more unknowns in the volume than in the surface measurements. All methods of solving this type of inverse problem rely on regularization and the choice of corresponding regularization or convergence criteria. While several regularization methods are available, it is unclear how well suited they are for cerebral functional DOT in a semi-infinite geometry. Furthermore, the regularization parameter is often chosen without an independent evaluation, and it may be tempting to choose the solution that matches a hypothesis and rejects the other. In this simulation study, we start out by demonstrating how the quality of cerebral DOT reconstructions is altered with the choice of the regularization parameter for different methods. To independently select the regularization parameter, we propose a cross-validation procedure which achieves a reconstruction quality close to the optimum. Additionally, we compare the outcome of seven different image reconstruction methods for cerebral functional DOT. The methods selected include reconstruction procedures that are already widely used for cerebral DOT [minimum l2-norm estimate (l2MNE) and truncated singular value decomposition], recently proposed sparse reconstruction algorithms [minimum l1- and a smooth minimum l0-norm estimate (l1MNE, l0MNE, respectively)] and a depth- and noise-weighted minimum norm (wMNE). Furthermore, we expand the range of algorithms for DOT by adapting two EEG-source localization algorithms [sparse basis field expansions and linearly constrained minimum variance (LCMV) beamforming]. Independent of the applied noise level, we find that the LCMV beamformer is best for single spot activations with perfect location and focality of the results, whereas the minimum l1-norm estimate succeeds with multiple targets.

Decoding vigilance with NIRS.

Sustained, long-term cognitive workload is associated with variations and decrements in performance. Such fluctuations in vigilance can be a risk factor especially during dangerous attention demanding activities. Functional MRI studies have shown that attentional performance is correlated with BOLD-signals, especially in parietal and prefrontal cortical regions. An interesting question is whether these BOLD-signals could be measured in real-world scenarios, say to warn in a dangerous workplace whenever a subjects' vigilance is low. Because fMRI lacks the mobility needed for such applications, we tested whether the monitoring of vigilance might be possible using Near-Infrared Spectroscopy (NIRS). NIRS is a highly mobile technique that measures hemodynamics in the surface of the brain. We demonstrate that non-invasive NIRS signals correlate with vigilance. These signals carry enough information to decode subjects' reaction times at a single trial level.

Automated real-time text messaging as a means for rapidly identifying acute stroke patients for clinical trials.

BACKGROUND: Recruiting stroke patients into acute treatment trials is challenging because of the urgency of clinical diagnosis, treatment, and trial inclusion. Automated alerts that identify emergency patients promptly may improve trial performance. The main purposes of this project were to develop an automated real-time text messaging system to immediately inform physicians of patients with suspected stroke and to test its feasibility in the emergency setting. METHODS: An electronic standardized stroke algorithm (SSA) was implemented in the clinical information system (CIS) and linked to a remote data capture system. Within 10 minutes following the documentation and storage of basic information to CIS, a text message was triggered for patients with suspected stroke and sent to a dedicated trial physician. Each text message provided anonymized information on the exact department and unit, date and time of admission, age, sex, and National Institute of Health Stroke Scale (NIHSS) of the patient. All necessary information needed to generate a text message was already available - routine processes in the emergency department were not affected by the automated real-time text messaging system. The system was tested for three 4-week periods. Feasibility was analyzed based on the number of patients correctly identified by the SSA and the door-to-message time. RESULTS: In total, 513 text messages were generated for patients with suspected stroke (median age 74 years (19-106); 50.3% female; median NIHSS 4 (0-41)), representing 96.6% of all cases. For 48.3% of these text messages, basic documentation was completed within less than 1 hour and a text message was sent within 60 minutes after patient admission. CONCLUSIONS: The system proved to be stable in generating text messages using IT-based CIS to identify acute stroke trial patients. The system operated on information which is documented routinely and did not result in a higher workload. Delays between patient admission and the text message were caused by delayed completion of basic documentation. To use the automated real-time text messaging system to immediately identify emergency patients suitable for acute stroke trials, further development needs to focus on eliminating delays in documentation for the SSA in the emergency department.

Monochromatic ultra-slow (~0.1 Hz) oscillations in the human electroencephalogram and their relation to hemodynamics.

Previous studies demonstrated the presence of Monochromatic Ultra-Slow Oscillations (MUSO) in human EEG. In the present study we explored the biological origin of MUSO by simultaneous recordings of EEG, Near-Infrared Spectroscopy (NIRS), arterial blood pressure, respiration and Laser Doppler flowmetry. We used a head-up tilt test in order to check whether MUSO might relate to Mayer waves in arterial blood pressure, known to be enhanced by the tilting procedure. MUSO were detected in 8 out of 10 subjects during rest and showed a striking monochromatic spectrum (0.07-0.14 Hz). The spatial topography of MUSO was complex, showing multiple foci variable across subjects. While the head-up tilt test increased the relative power of Mayer waves, it had no effect on MUSO. On the other hand, the relative spectral power of 0.1 Hz oscillations in EEG, NIRS and blood pressure signals were positively correlated across subjects in the tilted condition. Eight subjects showed a coherence between MUSO and NIRS/arterial blood pressure. Moreover, MUSO at different electrode sites demonstrated coherence not reducible to volume conduction, thus indicating that MUSO are unlikely to be generated by one source. We related our experimental findings to known biological phenomena being generated at about 0.1 Hz, i.e.: arterial blood pressure, cerebral and skin vasomotion, respiration and neuronal activity. While no definite conclusion can yet be drawn as to an exact physiological mechanism of MUSO, we suggest that these oscillations might be of a rather extraneuronal origin reflecting cerebral vasomotion.

A wearable multi-channel fNIRS system for brain imaging in freely moving subjects.

Functional near infrared spectroscopy (fNIRS) is a versatile neuroimaging tool with an increasing acceptance in the neuroimaging community. While often lauded for its portability, most of the fNIRS setups employed in neuroscientific research still impose usage in a laboratory environment. We present a wearable, multi-channel fNIRS imaging system for functional brain imaging in unrestrained settings. The system operates without optical fiber bundles, using eight dual wavelength light emitting diodes and eight electro-optical sensors, which can be placed freely on the subject's head for direct illumination and detection. Its performance is tested on N=8 subjects in a motor execution paradigm performed under three different exercising conditions: (i) during outdoor bicycle riding, (ii) while pedaling on a stationary training bicycle, and (iii) sitting still on the training bicycle. Following left hand gripping, we observe a significant decrease in the deoxyhemoglobin concentration over the contralateral motor cortex in all three conditions. A significant task-related ΔHbO2 increase was seen for the non-pedaling condition. Although the gross movements involved in pedaling and steering a bike induced more motion artifacts than carrying out the same task while sitting still, we found no significant differences in the shape or amplitude of the HbR time courses for outdoor or indoor cycling and sitting still. We demonstrate the general feasibility of using wearable multi-channel NIRS during strenuous exercise in natural, unrestrained settings and discuss the origins and effects of data artifacts. We provide quantitative guidelines for taking condition-dependent signal quality into account to allow the comparison of data across various levels of physical exercise. To the best of our knowledge, this is the first demonstration of functional NIRS brain imaging during an outdoor activity in a real life situation in humans.

Impact of selection criteria on recruitment in an interventional stroke trial.

BACKGROUND: Randomized controlled clinical trials are the gold standard for scientific evaluation of clinical diagnostic and treatment concepts. Frequently, recruitment of participants is slower than expected, especially in acute conditions with a short time frame for inclusion. Simple prediction models have been proposed to extrapolate recruitment rates. We hypothesized a significant overestimation of recruitment when ignoring interdependence of selection criteria, leading to an insufficient representation of reality by available models. We proposed that slight modifications to inclusion criteria might augment recruitment without causing selection bias. METHODS: We analyzed recruitment in an acute intervention trial of acute ischemic stroke initiated by our facility. Frequencies of selection criteria were recorded and analyzed individually as well as cumulatively. We then amended the trial protocol by moderate modifications to the selection criteria. The main outcome criterion was the rate of recruited over screened patients, with the goal of increasing recruitment fourfold without adding unacceptable selection bias. A previously presented prediction model was applied to our trial and compared with actual recruitment. Data were compared between screening periods at recruitment prior to and after the implementation of the amendments. RESULTS: The impact of typical as well as novel inclusion criteria such as age limits, imaging-based definition of pathology, time between onset and presentation as well as inability to consent were quantified. Age restriction, definition of index event and late arrival after ictus were identified as the most challenging modifiable selection criteria. Amending those criteria increased recruitment by a factor of 4.1. Inability to consent was a significant exclusion criterion gaining impact with the target population. The selection criteria had a cumulative rather than separate recruitment-limiting impact. A previously presented model did not predict recruitment sufficiently. CONCLUSION: We describe frequencies of selection criteria in a typical cohort of patients suffering from acute cerebrovascular events, and their cumulative impact. These data may help to better understand recruitment limitations and allow designing future trials more effectively. Ability to consent especially is a major contributor to trial exclusion, strongly interfering with the targeted trial population of ischemic stroke. Tentative prescreening phases before site or trial initiation should be considered. No predictive statistical models of recruitment have been established so far.

Effect of a mirror-like illusion on activation in the precuneus assessed with functional near-infrared spectroscopy.

Mirror therapy is a therapy to treat patients with pain syndromes or hemiparesis after stroke. However, the underlying neurophysiologic mechanisms are not clearly understood. In order to determine the effect of a mirror-like illusion (MIR) on brain activity using functional near-infrared spectroscopy, 20 healthy right-handed subjects were examined. A MIR was induced by a digital horizontal inversion of the subjects' filmed hand. Optodes were placed on the primary motor cortex (M1) and the occipito-parietal cortex (precuneus, PC). Regions of interest (ROI) were defined a priori based on previous results of similar studies and confirmed by the analysis of effect sizes. Analysis of variance of the ROI signal revealed a dissociated pattern: at the PC, the MIR caused a significant inversion of a hemispheric lateralization opposite to the perceived hand, independent of the moving hand. In contrast, activity in M1 showed lateralization opposite to the moving hand, but revealed no mirror effect. These findings extend our understanding on interhemispheric rivalry and indicate that a MIR is integrated into visuomotor coordination similar to normal view, irrespective of the hand that is actually performing the task.

Developmental changes in brain activation and functional connectivity during response inhibition in the early childhood brain.

Response inhibition is an attention function which develops relatively early during childhood. Behavioral data suggest that by the age of 3, children master the basic task requirements for the assessment of response inhibition but performance improves substantially until the age of 7. The neuronal mechanisms underlying these developmental processes, however, are not well understood. In this study, we examined brain activation patterns and behavioral performance of children aged between 4 and 6 years compared to adults by applying a go/no-go paradigm during near-infrared spectroscopy (NIRS) brain imaging. We furthermore applied task-independent functional connectivity measures to the imaging data to identify maturation of intrinsic neural functional networks. We found a significant group×condition related interaction in terms of inhibition-related reduced right fronto-parietal activation in children compared to adults. In contrast, motor-related activation did not differ between age groups. Functional connectivity analysis revealed that in the children's group, short-range coherence within frontal areas was stronger, and long-range coherence between frontal and parietal areas was weaker, compared to adults. Our findings show that in children aged from 4 to 6 years fronto-parietal brain maturation plays a crucial part in the cognitive development of response inhibition.

Towards whole-body fluorescence imaging in humans.

Dynamic near-infrared fluorescence (DNIF) whole-body imaging of small animals has become a popular tool in experimental biomedical research. In humans, however, the field of view has been limited to body parts, such as rheumatoid hands, diabetic feet or sentinel lymph nodes. Here we present a new whole-body DNIF-system suitable for adult subjects. We explored whether this system (i) allows dynamic whole-body fluorescence imaging and (ii) can detect modulations in skin perfusion. The non-specific fluorescent probe indocyanine green (ICG) was injected intravenously into two subjects, and fluorescence images were obtained at 5 Hz. The in- and out-flow kinetics of ICG have been shown to correlate with tissue perfusion. To validate the system, skin perfusion was modulated by warming and cooling distinct areas on the chest and the abdomen. Movies of fluorescence images show a bolus passage first in the face, then in the chest, abdomen and finally in the periphery (~10, 15, 20 and 30 seconds, respectively). When skin perfusion is augmented by warming, bolus arrives about 5 seconds earlier than when the skin is cooled and perfusion decreased. Calculating bolus arrival times and spatial fitting of basis time courses extracted from different regions of interest allowed a mapping of local differences in subcutaneous skin perfusion. This experiment is the first to demonstrate the feasibility of whole-body dynamic fluorescence imaging in humans. Since the whole-body approach demonstrates sensitivity to circumscribed alterations in skinperfusion, it may be used to target autonomous changes in polyneuropathy and to screen for peripheral vascular diseases.

Separation of indocyanine green boluses in the human brain and scalp based on time-resolved in-vivo fluorescence measurements.

Non-invasive detection of fluorescence from the optical tracer indocyanine green is feasible in the adult human brain when employing a time-domain technique with picosecond resolution. A fluorescence-based assessment may offer higher signal-to-noise ratio when compared to bolus tracking relying on changes in time-resolved diffuse reflectance. The essential challenge is to discriminate the fluorescence originating from the brain from contamination by extracerebral fluorescence and hence to reconstruct the bolus kinetics; however, a method to reliably perform the necessary separation is missing. We present a novel approach for the decomposition of the fluorescence contributions from the two tissue compartments. The corresponding sensitivity functions pertaining to the brain and to the extracerebral compartment are directly derived from the in-vivo measurement. This is achieved by assuming that during the initial and the late phase of bolus transit the fluorescence signal originates largely from one of the compartments. Solving the system of linear equations allows one to approximate time courses of a bolus for each compartment. We applied this method to repetitive measurements on two healthy subjects with an overall 34 boluses. A reconstruction of the bolus kinetics was possible in 62% of all cases.

Using NIRS as a predictor for EEG-based BCI performance.

Multimodal recordings of EEG and NIRS of 14 subjects are analyzed in the context of sensory-motor based Brain Computer Interface (BCI). Our findings indicate that performance fluctuations of EEG-based BCI control can be predicted by preceding Near-Infrared Spectroscopy (NIRS) activity. These NIRS-based predictions are then employed to generate new, more robust EEG-based BCI classifiers, which enhance classification significantly, while at the same time minimize performance fluctuations and thus increase the general stability of BCI performance.

Somatosensory activation of two fingers can be discriminated with ultrahigh-density diffuse optical tomography.

Topographic non-invasive near infrared spectroscopy (NIRS) has become a well-established tool for functional brain imaging. Applying up to 100 optodes over the head of a subject, allows achieving a spatial resolution in the centimeter range. This resolution is poor compared to other functional imaging tools. However, recently it was shown that diffuse optical tomography (DOT) as an extension of NIRS based on high-density (HD) probe arrays and supplemented by an advanced image reconstruction procedure allows describing activation patterns with a spatial resolution in the millimeter range. Building on these findings, we hypothesize that HD-DOT may render very focal activations accessible which would be missed by the traditionally used sparse arrays. We examined activation patterns in the primary somatosensory cortex, since its somatotopic organization is very fine-grained. We performed a vibrotactile stimulation study of the first and fifth finger in eight human subjects, using a 900-channel continuous-wave DOT imaging system for achieving a higher resolution than conventional topographic NIRS. To compare the results to a well-established high-resolution imaging technique, the same paradigm was investigated in the same subjects by means of functional magnetic resonance imaging (fMRI). In this work, we tested the advantage of ultrahigh-density probe arrays and show that highly focal activations would be missed by classical next-nearest neighbor NIRS approach, but also by DOT, when using a sparse probe array. Distinct activation patterns for both fingers correlated well with the expected neuroanatomy in five of eight subjects. Additionally we show that activation for different fingers is projected to different tissue depths in the DOT image. Comparison to the fMRI data yielded similar activation foci in seven out of ten finger representations in these five subjects when comparing the lateral localization of DOT and fMRI results.

Enhanced performance by a hybrid NIRS-EEG brain computer interface.

Noninvasive Brain Computer Interfaces (BCI) have been promoted to be used for neuroprosthetics. However, reports on applications with electroencephalography (EEG) show a demand for a better accuracy and stability. Here we investigate whether near-infrared spectroscopy (NIRS) can be used to enhance the EEG approach. In our study both methods were applied simultaneously in a real-time Sensory Motor Rhythm (SMR)-based BCI paradigm, involving executed movements as well as motor imagery. We tested how the classification of NIRS data can complement ongoing real-time EEG classification. Our results show that simultaneous measurements of NIRS and EEG can significantly improve the classification accuracy of motor imagery in over 90% of considered subjects and increases performance by 5% on average (p<0:01). However, the long time delay of the hemodynamic response may hinder an overall increase of bit-rates. Furthermore we find that EEG and NIRS complement each other in terms of information content and are thus a viable multimodal imaging technique, suitable for BCI.

Non-invasive optical imaging of stroke.

The acute onset of a neurological deficit is the key clinical feature of stroke. In most cases, however, pathophysiological changes in the cerebral vasculature precede the event, often by many years. Persisting neurological deficits may also require long-term rehabilitation. Hence, stroke may be considered a chronic disease, and diagnostic and therapeutic efforts must include identification of specific risk factors, and the monitoring of and interventions in the acute and subacute stages, and should aim at a pathophysiologically based approach to optimize the rehabilitative effort. Non-invasive optical techniques have been experimentally used in all three stages of the disease and may complement the established diagnostic and monitoring tools. Here, we provide an overview of studies using the methodology in the context of stroke, and we sketch perspectives of how they may be integrated into the assessment of the highly dynamic pathophysiological processes during the acute and subacute stages of the disease and also during rehabilitation and (secondary) prevention of stroke.

Contrast enhanced high-resolution diffuse optical tomography of the human brain using ICG.

Non-invasive diffuse optical tomography (DOT) of the adult brain has recently been shown to improve the spatial resolution for functional brain imaging applications. Here we show that high-resolution (HR) DOT is also advantageous for clinical perfusion imaging using an optical contrast agent. We present the first HR-DOT results with a continuous wave near infrared spectroscopy setup using a dense grid of optical fibers and indocyanine green (ICG) as an exogenic contrast agent. We find an early arrival of the ICG bolus in the intracerebral tissue and a delayed arrival of the bolus in the extracerebral tissue, achieving the separation of both layers. This demonstrates the method's potential for brain perfusion monitoring in neurointensive care patients.