Resting-state Functional Magnetic Resonance Imaging Identifies Cerebrovascular Reactivity Impairment in Patients With Arterial Occlusive Diseases: A Pilot Study

Nishida, Sei; Takaya, Satoshi; Takahashi, Yuki; Kikuchi, Takayuki; Funaki, Takeshi; Yoshida, Kazumichi; Okada, Tomohisa; Kunieda, Takeharu; Togashi, Kaori; Fukuyama, Hidenao; Miyamoto, Susumu

doi:10.1093/neuros/nyy434

Cited by 14 publications

(14 citation statements)

References 39 publications

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“…In another longitudinal study, they found the sizes of the extended-delay regions and the corresponding delay values changed according to the vessel conditions (Khalil et al, 2018). Recently, Nishida et al (2018) has found the delay maps from patients with the arterial occlusive disease were correlated with the CVR maps from SPECT. These multimodal studies validated the method of BOLD delay and showed its great potential in perfusion assessment of cerebrovascular disease.…”

Section: Applications Of the Slfo Signalmentioning

confidence: 99%

Low Frequency Systemic Hemodynamic “Noise” in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications

2019

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Advances in functional magnetic resonance imaging (fMRI) acquisition have improved signal to noise to the point where the physiology of the subject is the dominant noise source in resting state fMRI data (rsfMRI). Among these systemic, non-neuronal physiological signals, respiration and to some degree cardiac fluctuations can be removed through modeling, or in the case of newer, faster acquisitions such as simultaneous multislice acquisition, simple spectral filtering. However, significant low frequency physiological oscillation (∼0.01–0.15 Hz) remains in the signal. This is problematic, as it is the precise frequency band occupied by the neuronally modulated hemodynamic responses used to study brain connectivity, precluding its removal by spectral filtering. The source of this signal, and its method of production and propagation in the body, have not been conclusively determined. Here, we summarize the defining characteristics of the systemic low frequency noise signal, and review some current theories about the signal source and the evidence supporting them. The strength and distribution of the systemic LFO signal make characterizing and removing it essential for accurate quantification, especially for resting state connectivity, when no stimulation can be compared with the signal. Widespread correlated non-neuronal signals obscure and distort the more localized patterns of neuronal correlations between interacting brain regions; they may even cause apparent connectivity between regions with no neuronal interaction. Here, we discuss a simple method we have developed to parse the global, moving, blood-borne signal from the stationary, neuronal connectivity signals, substantially reducing the negative correlations that result from global signal regression. Finally, we will discuss some of the uses to which the moving systemic low frequency oscillation can be put if we consider it a “signal” carrying information, rather than simply “noise” complicating the interpretation of resting state connectivity. Properly utilizing this signal may offer insights into subtle hemodynamic alterations that can be used as early indicators of circulatory dysfunction in a number of neuropsychiatric conditions, such as prodromal stroke, moyamoya, and Alzheimer’s disease.

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Section: Applications Of the Slfo Signalmentioning

confidence: 99%

Low Frequency Systemic Hemodynamic “Noise” in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications

2019

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“…The resilient nature of the lag map against the fMRI task condition was shown, further supporting its non-neuronal origin [28]. In parallel, a number of clinical studies have established the phase delays as a marker of cerebrovascular disorders [29–34]. Moreover, gross vascular anatomy has been detected consistently in these studies, replicating the results from respiratory challenges [35,36], which importantly suggests an equivalence between the sLFO and manipulated circulatory turbulences.…”

Section: Introductionmentioning

confidence: 71%

Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals

2019

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Perfusion-related information is reportedly embedded in the low-frequency component of a blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal. The blood-propagation pattern through the cerebral vascular tree is detected as an interregional lag variation of spontaneous low-frequency oscillations (sLFOs). Mapping of this lag, or phase, has been implicitly treated as a projection of the vascular tree structure onto real space. While accumulating evidence supports the biological significance of this signal component, the physiological basis of the “perfusion lag structure,” a requirement for an integrative resting-state fMRI-signal model, is lacking. In this study, we conducted analyses furthering the hypothesis that the sLFO is not only largely of systemic origin, but also essentially intrinsic to blood, and hence behaves as a virtual tracer. By summing the small fluctuations of instantaneous phase differences between adjacent vascular regions, a velocity response to respiratory challenges was detected. Regarding the relationship to neurovascular coupling, the removal of the whole lag structure, which can be considered as an optimized global-signal regression, resulted in a reduction of inter-individual variance while preserving the fMRI response. Examination of the T2* and S0, or non-BOLD, components of the fMRI signal revealed that the lag structure is deoxyhemoglobin dependent, while paradoxically presenting a signal-magnitude reduction in the venous side of the cerebral vasculature. These findings provide insight into the origin of BOLD sLFOs, suggesting that they are highly intrinsic to the circulating blood.

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“…Essa dinâmica geralmente é identificada por atrasos, da ordem de segundos, nas flutuações de rs-fMRI que são obtidos através de correlações cruzadas do sinal BOLD de cada voxel com algum sinal de referência. Esta técnica foi aplicada com diferentes escolhas de sinais de referência, incluindo sinal da substância cinzenta (SIEGEL et al, 2016), sinal homotópico do hemisfério não lesado (BAUER et al, 2014), e sinal de máscaras que são iteradas (NISHIDA et al, 2019). A Figura 7 ilustra a metodologia de correlação entre todos os voxels com alguma curva de referência (em vermelho), fazendo adiantamento (em em cinza) e atrasando (em vermelho).…”

Section: Tempo De Atrasounclassified

“…Além disso, também é uma metodologia não invasiva que se correlaciona com alterações de CVR para identificar tecidos em risco de AVC isquêmico (NISHIDA et al, 2019). Tal grandeza se torna interessante para o estudo a partir de que o AVC isquêmico interrompe o suprimento vascular do cérebro, não apenas dentro, mas também fora das áreas de infarto e essas áreas adjacentes podem ser suceptíveis a novos eventos de falta de suprimentos hemodinâmicos, chamada de região de penumbra, que pode ser salva, justificando o interesse em delinear essas regiões precocemente (EBINGER et al, 2009).…”

Section: Tempo De Atrasounclassified

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Mapeamento da vasorreatividade cerebral sem estímulo vasoativo: um estudo de imagens em estado de repouso

Secchinato¹

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Cerebrovascular reactivity (CVR) represents the ability of the vascular smooth muscle to dilate or contract in response to changes in metabolic demand changes or vasoactive stimuli to regulate cerebral blood flow when necessary. This response can be affected in several neurological diseases, mainly cerebrovascular diseases, both in magnitude and in time delay. The latter is observed as a temporal shift (TS) of the response. Such measures are valuable to report the hemodynamic state of the brain and are of interest in several studies trying to predict the risk of stroke, such as in patients with carotid artery stenosis. However, standard methods require specific conditions, such as administering acetazolamide or inhalation of CO 2 while magnetic resonance images (MRI) are acquired. In the present study, we evaluated CVR and TS from fluctuations in the MRI signal based on the blood oxygenation-dependent contrast (BOLD) at rest, without performing hypercapnia challenges. In the first part of the study, we identified an adequate frequency range for temporal filtering of the resting-state signal to obtain CVR maps, based on the spatial correlation with standard CVR maps obtained with CO 2 inhalation and breath-holding. Five patients with unilateral severe asymptomatic carotid stenosis (70 ± 3 years) and five controls (65 ± 3 years) performed the experiment with CO 2 inhalation, and 23 healthy elderly (67 ± 6 years) performed the experiment with breath-holding. CVR maps obtained through the general linear regression model showed a more significant spatial correlation when using the regressor of the global signal filtered at 0.02 to 0.04 Hz when compared with reference maps. Thus, this frequency band was used for the second part of the study, in which we evaluated CVR and TS in 20 patients with unilateral severe asymptomatic carotid stenosis (12 women; 8 men; mean age = 67 ± 10 years) comparing with a group of healthy control (8 women; 12 men; mean age = 68 ± seven years). In patients, reduced CVR values were observed bilaterally in regions irrigated by the intermediary portion of the anterior cerebral artery (ACA) when compared to the proximal portion and for the proximal, middle cerebral artery (MCA) when compared to the distal (p < 0.05). TS values were higher in patients in the three portions of the MCA territory and the distal portion of the posterior cerebral artery (PCA) territory, in the hemisphere ipsilateral to the stenosis, when compared to the corresponding regions of the control group (p < 0.04 ). In addition, in patients, TS was higher in the distal MCA ipsilateral to the stenosis compared to the same region in the contralateral hemisphere (p = 0.0025). Similar regional changes in CVR and TS were observed when visually analyzing individual maps suggesting that the methodologies are complementary. These parameters may reflect subclinical hemodynamic changes and help investigate areas with a higher risk of neuronal damage or ischemic stroke at an individual level. Therefore, the study of cerebral hemodynamic...

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Resting-state Functional Magnetic Resonance Imaging Identifies Cerebrovascular Reactivity Impairment in Patients With Arterial Occlusive Diseases: A Pilot Study

Abstract: BOLD TS analysis has potential as a noninvasive alternative to current methods based on CVR for identification of tissue at risk of ischemic stroke.

Cited by 14 publications

References 39 publications

Low Frequency Systemic Hemodynamic “Noise” in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications

Low Frequency Systemic Hemodynamic “Noise” in Resting State BOLD fMRI: Characteristics, Causes, Implications, Mitigation Strategies, and Applications

Axial variation of deoxyhemoglobin density as a source of the low-frequency time lag structure in blood oxygenation level-dependent signals

Mapeamento da vasorreatividade cerebral sem estímulo vasoativo: um estudo de imagens em estado de repouso

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