Sampling Rate Effects on Resting State fMRI Metrics

Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning

Increased effect of physiological respiratory brain pulsations in focal-onset epilepsy

Abstract Neurological brain diseases induce increasing costs in health care around the world. Epilepsies are one of the most common neurological diseases globally. While seizure-freedom is achieved in a majority of patients with proper treatment, epilepsy can still be refractory to antiepileptic medication and can cause impaired quality of life and premature death compared to the general population. In clinical diagnostic work-up, the unpredictable and temporary nature of epileptic activity in the brain with several different specified and still unknown etiologies can make the precise localization of the epileptic foci difficult. A new pathophysiological theory behind epilepsies focuses on neuron-glia interactions and an impeccably functioning blood–brain barrier supporting the homeostasis for unhindered brain functionality. Cerebrospinal fluid is driven by brain pulsations via Aquaporin-4 in the brain and plays a critical role in supporting the water channels balance. Recently developed fast functional neuroimaging methods can be used to study whether this homeostasis is disturbed in patients with focal-onset epilepsy. Additionally, the fast functional MRI sequence, ultra-fast magnetic resonance encephalography (MREG), offers a method for differentiating distinct frequency brain pulsations. Previous evidence with intracranial electroencephalography has shown that respiration directly affects epileptic activity and brain function altogether. Thus, respiratory brain pulsations measured by MREG were a focus of particular interest in comparisons between patients with focal-onset epilepsy and healthy controls in this study, totaling 40and 102 subjects, respectively, gathered during 2012–2020 in Oulu, Finland and Freiburg, Germany. Additionally, we introduce data from 22 patients with new-onset seizure gathered in Oulu, Finland, allowing the exclusion of the potential effect of antiepileptic medication as a cause of the observed changes in observable brain pulsations. In conclusion, the methodology used in this study showed increased intrinsic respiratory brain pulsations in focal-onset epilepsy, offering a novel hypothesis of mechanisms behind the disease. Additionally, these pulsations were increased only at an individual level in epilepsy patients. Naturally, future comparative studies with current imaging studies and modalities will clarify the role and value of MREG in localizing the epileptogenic zone. These results could be explained by the transition in brain glymphatic water convection, which reciprocally affects potassium channels and, thus, brain electrophysiological homeostasis. This finding might at least partly explain the incomplete response to treatment in intractable epilepsy since a remedy to solute the clearance does not yet exist.Tiivistelmä Neurologiset aivosairaudet aiheuttavat alati kasvavia kustannuksia terveydenhuollolle eri puolilla maailmaa. Epilepsiat ovat yksi yleisimmistä neurologisista sairauksista maailmanlaajuisesti. Vaikka suurimmalla osalla potilaista saavutetaan kohtauksettomuus, epilepsia voi kuitenkin olla vaikea, jolloin asianmukaisesta lääkehoidostahuolimatta potilaalle aiheutuu merkittävää elämänlaadun alentumista ja kohonnut riskiennenaikaiselle kuolemalle verrattuna muuhun väestöön. Kliinisessä diagnostiikassa aivojen epileptisen toiminnan ennalta-arvaamattomuus ja kohtauksellisuus useiden tunnettujen ja tuntemattomien syiden vuoksi voi aiheuttaa haasteita epileptisen toiminnanpaikallistamiseen aivokudoksessa. Uusi patofysiologinen teoria epilepsian taustalla keskittyy hermosolujen ja sen tukikudoksen, eli neuronien ja glian vuorovaikutukseen ja veriaivoesteen toimintaan aivojen homeostaasin säilyttämiseksi. Aivo-selkäydinnesteen liikettä ajavat aivoissa tapahtuvat pulsaatiot, jotka Akvaporiini-4 kanavien välityksellä ylläpitävät aivojenvesikanavien tasapainoa. Uudella toiminnallisella neurokuvantamismenetelmällä voidaan tutkia, ovatko homeostaasia ylläpitävät aivojen pulsaatiot häiriintyneet paikallis-alkuisessa epilepsiassa. Lisäksi käytetty ultranopea magneettiresonanssienkefalogrammi (MREG), tarjoaa tutkimusmenetelmän eri taajuuksilla tapahtuvien aivopulsaatioidenerottamiseksi toisistaan. Aikaisemmin on osoitettu kallonsisäisillä aivosähkökäyrämittauksilla, että hengityksellä on suora vaikutus epileptiseen aivotoimintaan ja sen aktiivisuuteen. Tämän vuoksi MREG:lla mitatut aivojen hengityspulsaatiot olivat tutkimuksessa erityisenkiinnostuksen kohteena vertailtaessa paikallis-alkuista epilepsiaa sairastavia potilaita ja terveitä kontrolleja, joita kerättiin vuosien 2012–2020 aikana vastaavasti yhteensä 40 ja 102 kappaletta Oulussa ja Freiburgissa Saksassa. Lisäksi esittelemme Oulussa kerätyn 22 tuoreen kohtauspotilaan aineiston, joka mahdollisti lääkityksen vaikutuksenpoissulkemisen aivojen pulsaatioihin. Yhteenvetona voidaan todeta, että käytetty menetelmä osoitti aivojen hengityspulsaatioiden muuttuneen paikallisalkuisessa epilepsiassa tarjoten uuden hypoteettisenmekanismin epilepsian syynä. Lisäksi havaitsimme pulsaatioiden muuttumisen paikallisesti yksilöllisellä tasolla. Luonnollisesti tulevaisuudessa tarvitaan lisää komparatiivisia tutkimuksia eri modaliteettien välillä vertailemaan MREG:n hyödyllisyyttä epileptogeenisen alueen paikantamisessa. Saadut tulokset voidaan selittää aivojen muuttuneella glymfaattisen veden puhdistumalla, joka vaikuttaa aivokudoksessa vastavuoroisestikaliumkanaviin ja siten elektrofysiologiseen tasapainoon. Tämä voisi mahdollisesti selittää osittaista hoitovastetta vaikeassa epilepsiassa, koska glymfaattiseen puhdistumaan vaikuttavia hoitoja ei toistaiseksi ole käytössä

Hengitysfunktion monitorointi etäisyyskameran avulla

Tietotekniikan kehittyessä erilaisten sovellusten osuus jokapäiväisessä elämässä on kasvanut viime vuosien aikana nopeaa tahtia kaikkialla yhteiskunnassa. Tekniikan kehittyminen on myös luonut uusia keinoja ihmisten terveyden tarkkailemiseen, mittaamiseen ja valvomiseen niin henkilökohtaisella tasolla, kuin julkisessa terveydenhuollossa. Julkisen terveydenhuollon hoitoajoista kuluu paljon erilaiseen oheistoimintaan, eikä niinkään varsinaiseen potilaan hoitoon, mikä lisää kustannuksia. Tämän takia olisikin tärkeää, että pystyttäisiin hoitamaan potilaan seurantaa helposti, nopeasti ja mahdollisimman taloudellisesti. Hengitys ja sen seuranta on yksi osa-alue, jolla kustannuksia olisi mahdollista pienentää ja helpottaa tutkimusten suorittamista. Tässä diplomityössä on kehitetty uudenlainen menetelmä seurata potilaiden keuhkojen toimintaa helposti ja tarkasti. Kuvattu menetelmä on hankintahinnaltaan halpa ja potilasmukavuuden kannalta miellyttävä mahdollistaen näin paremman hoitomyöntyvyyden. Keuhkofunktion monitoroinnin perustana toimii kahdella etäisyyskameralla tapahtuva henkilön hengityksen seuranta. Etäisyyskameroina toimii tässä työssä kaksi Microsoftin Kinect-kameraa. Kahdella Kinect-kameralla toteutettuna ei hengityksen seurantaa ole aikaisemmin tehty. Tavoitteena on ollut luoda kahden kameran pistepilvet yhdistämällä laajempi ja tarkempi mittaus henkilön hengityksen liikkeistä. Mittaus suoritettiin muodostamalla yhdistetystä pistepilvestä kaksi virtuaalista hengitysvyötä rintakehän sekä vatsan seudulle ja tarkkailemalla näiden hengitysvöiden alueiden tilavuuden muutosta. Saatua tulosta verrattiin spirometriasta saatuun hengitysdataan. Työssä toteutetulla menetelmällä saavutettiin hyvät tulokset. Muodostettujen estimaattien hengityssyklien pituudet sekä tilavuudet todettiin korreloivan hyvin spirometrian vastaaviin arvoihin (R^2 = 0,9302). Tulokset osoittavat, että kuvatunlaista menetelmää voisi tulevaisuudessa olla mahdollista käyttää erilaisissa sovelluksissa.With the development of computer science the usage of all kinds of applications has increased rapidly everywhere in the society. Development has also created new ways to monitor and measure health in personal as well as public healthcare level. In the public healthcare a lot of time is lost to non-essential tasks that aren’t actual treatment which increases costs. Consequently it would be important to be able to monitor the patient easily, quickly and cost-efficiently. Respiration monitoring is one opportunity to decrease the costs and to ease the examination. In this diploma thesis, a new way to monitor patients’ respiratory function easily, yet accurately is developed. The described method is cheap and convenient to patients, enabling better co-operation. The basis of monitoring respiratory function was produced by using two depth cameras for monitoring person’s chest movement. Two Kinect cameras from Microsoft were used as depth cameras. Respiration monitoring by using two Kinect cameras has not been done before. The aim of this project was to create a better measure of persons respiration movement by combining point clouds from two cameras. From this point cloud, two virtual respiration belts were formed to monitor volume changes of two different areas. The areas were the chest and the abdomen. The results obtained were compared to the respiratory data given by spirometry. With the proposed method good results were attained. Respiration cycle lengths and volumes of constructed estimates correlated well with the corresponding values of spirometry (R^2 = 0,9302). Results indicate that presented method could be used in different kinds of applications in the future

Increased very low frequency pulsations and decreased cardiorespiratory pulsations suggest altered brain clearance in narcolepsy

Abstract Background: Narcolepsy is a chronic neurological disease characterized by daytime sleep attacks, cataplexy, and fragmented sleep. The disease is hypothesized to arise from destruction or dysfunction of hypothalamic hypocretin-producing cells that innervate wake-promoting systems including the ascending arousal network (AAN), which regulates arousal via release of neurotransmitters like noradrenalin. Brain pulsations are thought to drive intracranial cerebrospinal fluid flow linked to brain metabolite transfer that sustains homeostasis. This flow increases in sleep and is suppressed by noradrenalin in the awake state. Here we tested the hypothesis that narcolepsy is associated with altered brain pulsations, and if these pulsations can differentiate narcolepsy type 1 from healthy controls. Methods: In this case-control study, 23 patients with narcolepsy type 1 (NT1) were imaged with ultrafast fMRI (MREG) along with 23 age- and sex-matched healthy controls (HC). The physiological brain pulsations were quantified as the frequency-wise signal variance. Clinical relevance of the pulsations was investigated with correlation and receiving operating characteristic analysis. Results: We find that variance and fractional variance in the very low frequency (MREGvlf) band are greater in NT1 compared to HC, while cardiac (MREGcard) and respiratory band variances are lower. Interestingly, these pulsations differences are prominent in the AAN region. We further find that fractional variance in MREGvlf shows promise as an effective bi-classification metric (AUC = 81.4%/78.5%), and that disease severity measured with narcolepsy severity score correlates with MREGcard variance (R = −0.48, p = 0.0249). Conclusions: We suggest that our novel results reflect impaired CSF dynamics that may be linked to altered glymphatic circulation in narcolepsy type 1

Respiratory brain impulse propagation in focal epilepsy

Abstract Respiratory brain pulsations pertaining to intra-axial hydrodynamic solute transport are markedly altered in focal epilepsy. We used optical flow analysis of ultra-fast functional magnetic resonance imaging (fMRI) data to investigate the velocity characteristics of respiratory brain impulse propagation in patients with focal epilepsy treated with antiseizure medication (ASM) (medicated patients with focal epilepsy; ME, n = 23), drug-naïve patients with at least one seizure (DN, n = 19) and matched healthy control subjects (HC, n = 75). We detected in the two patient groups (ME and DN) several significant alterations in the respiratory brain pulsation propagation velocity, which showed a bidirectional change dominated by a reduction in speed. Furthermore, the respiratory impulses moved more in reversed or incoherent directions in both patient groups vs. the HC group. The speed reductions and directionality changes occurred in specific phases of the respiratory cycle. In conclusion, irrespective of medication status, both patient groups showed incoherent and slower respiratory brain impulses, which may contribute to epileptic brain pathology by hindering brain hydrodynamics

Combined spatiotemporal ICA (stICA) for continuous and dynamic lag structure analysis of MREG data

Abstract This study investigated lag structure in the resting-state fMRI by applying a novel independent component (ICA) method to magnetic resonance encephalography (MREG) data. Briefly, the spatial ICA (sICA) was used for defining the frontal and back nodes of the default mode network (DMN), and the temporal ICA (tICA), which is enabled by the high temporal resolution of MREG (TR=100ms), was used to separate both neuronal and physiological components of these two spatial map regions. Subsequently, lag structure was investigated between the frontal (DMNvmpf) and posterior (DMNpcc) DMN nodes using both conventional method with all-time points and a sliding-window approach. A rigorous noise exclusion criterion was applied for tICs to remove physiological pulsations, motion and system artefacts. All the de-noised tICs were used to calculate the null-distributions both for expected lag variability over time and over subjects. Lag analysis was done for the three highest correlating denoised tICA pairs. Mean time lag of 0.6 s (± 0.5 std) and mean absolute correlation of 0.69 (± 0.08) between the highest correlating tICA pairs of DMN nodes was observed throughout the whole analyzed period. In dynamic 2 min window analysis, there was large variability over subjects as ranging between 1–10 sec. Directionality varied between these highly correlating sources an average 28.8% of the possible number of direction changes. The null models show highly consistent correlation and lag structure between DMN nodes both in continuous and dynamic analysis. The mean time lag of a null-model over time between all denoised DMN nodes was 0.0 s and, thus the probability of having either DMNpcc or DMNvmpf as a preceding component is near equal. All the lag values of highest correlating tICA pairs over subjects lie within the standard deviation range of a null-model in whole time window analysis, supporting the earlier findings that there is a consistent temporal lag structure across groups of individuals. However, in dynamic analysis, there are lag values exceeding the threshold of significance of a null-model meaning that there might be biologically meaningful variation in this measure. Taken together the variability in lag and the presence of high activity peaks during strong connectivity indicate that individual avalanches may play an important role in defining dynamic independence in resting state connectivity within networks

Cardiovascular pulsatility increases in visual cortex before blood oxygen level dependent response during stimulus

Abstract The physiological pulsations that drive tissue fluid homeostasis are not well characterized during brain activation. Therefore, we used fast magnetic resonance encephalography (MREG) fMRI to measure full band (0–5 Hz) blood oxygen level-dependent (BOLDFB) signals during a dynamic visual task in 23 subjects. This revealed brain activity in the very low frequency (BOLDVLF) as well as in cardiac and respiratory bands. The cardiovascular hemodynamic envelope (CHe) signal correlated significantly with the visual BOLDVLF response, considered as an independent signal source in the V1-V2 visual cortices. The CHe preceded the canonical BOLDVLF response by an average of 1.3 (± 2.2) s. Physiologically, the observed CHe signal could mark increased regional cardiovascular pulsatility following vasodilation

Sampling rate effects on resting state fMRI metrics

Abstract Low image sampling rates used in resting state functional magnetic resonance imaging (rs-fMRI) may cause aliasing of the cardiorespiratory pulsations over the very low frequency (VLF) BOLD signal fluctuations which reflects to functional connectivity (FC). In this study, we examine the effect of sampling rate on currently used rs-fMRI FC metrics. Ultra-fast fMRI magnetic resonance encephalography (MREG) data, sampled with TR 0.1 s, was downsampled to different subsampled repetition times (sTR, range 0.3–3 s) for comparisons. Echo planar k-space sampling (TR 2.15 s) and interleaved slice collection schemes were also compared against the 3D single shot trajectory at 2.2 s sTR. The quantified connectivity metrics included stationary spatial, time, and frequency domains, as well as dynamic analyses. Time domain methods included analyses of seed-based functional connectivity, regional homogeneity (ReHo), coefficient of variation, and spatial domain group level probabilistic independent component analysis (ICA). In frequency domain analyses, we examined fractional and amplitude of low frequency fluctuations. Aliasing effects were spatially and spectrally analyzed by comparing VLF (0.01–0.1 Hz), respiratory (0.12–0.35 Hz) and cardiac power (0.9–1.3 Hz) FFT maps at different sTRs. Quasi-periodic pattern (QPP) of VLF events were analyzed for effects on dynamic FC methods. The results in conventional time and spatial domain analyses remained virtually unchanged by the different sampling rates. In frequency domain, the aliasing occurred mainly in higher sTR (1–2 s) where cardiac power aliases over respiratory power. The VLF power maps suffered minimally from increasing sTRs. Interleaved data reconstruction induced lower ReHo compared to 3D sampling (p < 0.001). Gradient recalled echo-planar imaging (EPI BOLD) data produced both better and worse metrics. In QPP analyses, the repeatability of the VLF pulse detection becomes linearly reduced with increasing sTR. In conclusion, the conventional resting state metrics (e.g., FC, ICA) were not markedly affected by different TRs (0.1–3 s). However, cardiorespiratory signals showed strongest aliasing in central brain regions in sTR 1–2 s. Pulsatile QPP and other dynamic analyses benefit linearly from short TR scanning

Breath hold effect on cardiovascular brain pulsations:a multimodal magnetic resonance encephalography study

Abstract Ultra-fast functional magnetic resonance encephalography (MREG) enables separate assessment of cardiovascular, respiratory, and vasomotor waves from brain pulsations without temporal aliasing. We examined effects of breath hold- (BH) related changes on cardiovascular brain pulsations using MREG to study the physiological nature of cerebrovascular reactivity. We used alternating 32 s BH and 88 s resting normoventilation (NV) to change brain pulsations during MREG combined with simultaneously measured respiration, continuous non-invasive blood pressure, and cortical near-infrared spectroscopy (NIRS) in healthy volunteers. Changes in classical resting-state network BOLD-like signal and cortical blood oxygenation were reproduced based on MREG and NIRS signals. Cardiovascular pulsation amplitudes of MREG signal from anterior cerebral artery, oxygenated hemoglobin concentration in frontal cortex, and blood pressure decreased after BH. MREG cardiovascular pulse amplitudes in cortical areas and sagittal sinus increased, while cerebrospinal fluid and white matter remained unchanged. Respiratory centers in the brainstem — hypothalamus — thalamus — amygdala network showed strongest increases in cardiovascular pulsation amplitude. The spatial propagation of averaged cardiovascular impulses altered as a function of successive BH runs. The spread of cardiovascular pulse cycles exhibited a decreasing spatial similarity over time. MREG portrayed spatiotemporally accurate respiratory network activity and cardiovascular pulsation dynamics related to BH challenges at an unpreceded high temporal resolution

Increased interictal synchronicity of respiratory related brain pulsations in epilepsy

Abstract Respiratory brain pulsations have recently been shown to drive electrophysiological brain activity in patients with epilepsy. Furthermore, functional neuroimaging indicates that respiratory brain pulsations have increased variability and amplitude in patients with epilepsy compared to healthy individuals. To determine whether the respiratory drive is altered in epilepsy, we compared respiratory brain pulsation synchronicity between healthy controls and patients. Whole brain fast functional magnetic resonance imaging was performed on 40 medicated patients with focal epilepsy, 20 drug-naïve patients and 102 healthy controls. Cerebrospinal fluid associated respiratory pulsations were used to generate individual whole brain respiratory synchronization maps, which were compared between groups. Finally, we analyzed the seizure frequency effect and diagnostic accuracy of the respiratory synchronization defect in epilepsy. Respiratory brain pulsations related to the verified fourth ventricle pulsations were significantly more synchronous in patients in frontal, periventricular and mid-temporal regions, while the seizure frequency correlated positively with synchronicity. The respiratory brain synchronicity had a good diagnostic accuracy (ROCAUC = 0.75) in discriminating controls from medicated patients. The elevated respiratory brain synchronicity in focal epilepsy suggests altered physiological effect of cerebrospinal fluid pulsations possibly linked to regional brain water dynamics involved with interictal brain physiology