Elsevier

NeuroImage

Volume 189, 1 April 2019, Pages 258-266
NeuroImage

Simultaneous task-based BOLD-fMRI and [18-F] FDG functional PET for measurement of neuronal metabolism in the human visual cortex

https://doi.org/10.1016/j.neuroimage.2019.01.003Get rights and content

Highlights

  • Simultaneous measurement of dynamic BOLD-fMRI and FDG-PET in response to a task.

  • Embedded block design enabled simultaneous tracking of haemodynamics and metabolim.

  • Approach will provide novel insights into haemodynamics and metabolim in cognition.

Abstract

Studies of task-evoked brain activity are the cornerstone of cognitive neuroscience, and unravel the spatial and temporal brain dynamics of cognition in health and disease. Blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI) is one of the most common methods of studying brain function in humans. BOLD-fMRI indirectly infers neuronal activity from regional changes in blood oxygenation and is not a quantitative metric of brain function. Regional variation in glucose metabolism, measured using [18-F] fluorodeoxyglucose positron emission tomography (FDG-PET), provides a more direct and interpretable measure of neuronal activity. However, while the temporal resolution of BOLD-fMRI is in the order of seconds, standard FDG-PET protocols provide a static snapshot of glucose metabolism. Here, we develop a novel experimental design for measurement of task-evoked changes in regional blood oxygenation and glucose metabolism with high temporal resolution. Over a 90-min simultaneous BOLD-fMRI/FDG-PET scan, [18F] FDG was constantly infused to 10 healthy volunteers, who viewed a flickering checkerboard presented in a hierarchical block design. Dynamic task-related changes in blood oxygenation and glucose metabolism were examined with temporal resolution of 2.5sec and 1-min, respectively. Task-related, temporally coherent brain networks of haemodynamic and metabolic connectivity were jointly coupled in the visual cortex, as expected. Results demonstrate that the hierarchical block design, together with the infusion FDG-PET technique, enabled both modalities to track task-related neural responses with high temporal resolution. The simultaneous MR-PET approach has the potential to provide unique insights into the dynamic haemodynamic and metabolic interactions that underlie cognition in health and disease.

Introduction

The human brain requires a continual supply of glucose to satisfy its energy requirements (Mergenthaler et al., 2013). The neural functions of the brain rely upon a stable and reliable energy supply delivered in the form of glucose via the blood across the blood-brain barrier and the blood-cerebrospinal fluid barrier (Serlin et al., 2015). The human brain accounts for 20% of the body's energy consumption at rest (Kety, 1957; Sokoloff, 1960), of which 70–80% is estimated to be used by neurons during synaptic transmission (Harris et al., 2012). It is increasingly recognised that access to a reliable energy supply is paramount to maintaining brain health, and early decrements in cerebral glucose metabolism are thought to initiate and contribute to the structural and functional neural changes that underlie age-related cognitive decline (Petit-Taboue et al., 1998) and neurodegenerative illnesses (Mosconi et al., 2009; Pagano et al., 2016). In humans, global and regional variations in the cerebral metabolic rate of glucose consumption (CMRGLC) can be studied using [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET), which provides a snapshot of glucose utilisation, often averaged over a 30–45min period following the injection of the FDG radiotracer.

As cerebral glucose metabolism primarily reflects synaptic transmission, FDG-PET brain imaging has long been used as a proxy for studying human neuronal function in health and disease. However, the FDG-PET bolus administration method has a very limited temporal resolution, representing the integral of the neural (and cognitive) activity occurring during the tracer uptake and PET scanning periods. In addition, PET technology has limited spatial resolution (Moses, 2011), which limits the inferences that can be made regarding the spatial localisation and specificity of metabolic measurements (note that recent advances in PET technology have yielded resolutions that approach that of BOLD-fMRI). In contrast, blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI) provides a haemodynamically based surrogate index of neuronal activity with a temporal resolution in the order of seconds (∼2sec; or sub-second resolution with advanced multiband MR sequences, e.g. (Feinberg and Yacoub, 2012)), and spatial resolution that can map sub-millimeter neuronal populations, given sufficient field strength and signal-to-noise ratio (Yacoub et al., 2001). During the 1990's the superior temporal and spatial resolution of BOLD-fMRI, together with the fact that it does not require exposure to ionising radiation, led to the BOLD-fMRI method quickly surpassing FDG-PET imaging as the method of choice for studying in vivo human brain function.

Despite the apparent ubiquity of the use of BOLD-fMRI for studying human brain function over the last 25-years, the method has a number of shortcomings. The most significant shortcoming of BOLD-fMRI is that the method is not a direct or quantitative measure of neuronal activity. The BOLD-fMRI signal relies upon a complex interplay between metabolic and hemodynamic (blood flow, volume, oxygenation) responses, and the exact relationship between neuronal activity and the measured BOLD signal has not been fully characterised (Logothetis et al., 2001). Consequently BOLD-fMRI responses cannot be directly compared across brain regions, subjects and imaging sites, or quantitatively compared in the same individual across time (Logothetis, 2008). Furthermore, the BOLD signal contains physiological confounding signals that are non-neuronal, including respiration, heart rate, and arterial responsivity (Tong et al., 2018). Together these limitations substantially impact the utility of the method for comparing groups of individuals, especially in disease groups (e.g., patients versus healthy controls; aged versus young).

The recent development of simultaneous MR-PET scanning provides the possibility of performing joint spatio-temporal coherence analyses using simultaneously acquired BOLD-fMRI and FDG-PET datasets. Since the potential pitfalls associated with the interpretation of BOLD-fMRI signals are well established, the advantages of combining simultaneously acquired FDG-PET data with BOLD-fMRI may be unclear. The application of joint ICA analytical strategies has the potential to provide enhanced diagnostic and prognostic information compared to a single modality study. The introduction of simultaneous MR-PET allows for the possibility of performing joint analyses which benefit from the signal-to-noise, resolution and sensitivity of BOLD fMRI, together with the interpretability of metabolic measurements and repeatability of semi-quantitative and quantitative FDG-PET.

The technological developments that have led to MR-PET scanners (Chen et al., 2018) have now made it possible to simultaneously examine changes in blood oxygenation and glucose metabolism at rest, or in response to a stimulus or task, using simultaneously acquired BOLD-fMRI and FDG-PET datasets. BOLD-fMRI acquired simultaneously with PET using a bolus FDG administration has been used to compare sustained (slow) metabolic activity to transient (fast) blood oxygenation changes in rodents (Wehrl et al., 2013) and humans (Riedl et al., 2014). Riedl and co-workers (Riedl et al., 2014) compared simultaneous BOLD-fMRI/FDG-PET eyes closed versus eyes open rest in human subjects, and found that local glucose metabolism was highly correlated with BOLD functional connectivity. Wehrl et al. (2013) found that simultaneously acquired BOLD and FDG showed different spatial extent and location of peak neural activity using whisker barrel stimulation in the rat. These results suggested that FDG-PET measures a more widely distributed neuronal network than BOLD-fMRI, and potentially enables the identification of task-relevant secondary regions that are not detected by BOLD.

Recent advances in FDG infusion protocols (adapted from (Carson, 2000)), together with the improved PET signal detection of dual modality scanners (Chen et al., 2018) has now made it possible to study dynamic changes in glucose metabolism simultaneously with dynamic changes in blood oxygenation. The method described as ‘functional’ FDG-PET (FDG-fPET) involves the radiotracer administered as a constant infusion over the course of the entire PET scan (∼90-mins (Villien et al., 2014)). In a proof-of-concept study, Villien et al. (2014) adapted the constant infusion technique (Carson, 2000) and used simultaneous MR/FDG-fPET (but not fMRI) to show dynamic changes in glucose metabolism in response to checkerboard stimulation in the visual cortex with a temporal resolution of approximately 1 min. Subsequent studies using simultaneous MR/FDG-fPET (Hahn et al., 2016) and BOLD-fMRI/FDG-fPET (Hahn et al., 2018) have extended these findings to demonstrate simultaneous BOLD and FDG activity in the visual and motor cortices during alternate visual stimulation (eyes open versus closed) and finger tapping tasks. Interestingly, Hahn et al. (2018), found that endogenously-driven stimulation (i.e., eyes open rest and non-paced finger tapping without external behavioural cues) produced task-related CMRGLC and BOLD functional connectivity that were independent of each other; in other words, the task-specific changes were not correlated across the two imaging modalities. These results were surprising and in contrast to those reported in the rat (Wehrl et al., 2013). In a recent follow-up study, Rischka, Hahn and colleagues (Rischka et al., 2018) showed that endogenously-driven task-related CMRGLC changes can be detected with stimulation periods as low as 2 min; similar to their previous study, Rischka et al. found no correlation between CMRGLC and BOLD percent signal change.

To date, no study has reported the results of externally-triggered task-based simultaneous BOLD-fMRI/FDG-fPET mapping. The investigation of higher-order cognitive functions in the normal human brain, including attention, memory and executive function, require experimental paradigms and manipulations that result in coupled responses of the concurrent BOLD and FDG signal changes. Conversely, the uncoupling of changes in blood oxygenation and glucose metabolism are thought to underlie many of the cognitive deficits seen in ageing, neurodegenerative diseases and psychiatric conditions. Changes in dynamic regional glucose metabolism may even precede structural, functional and cognitive symptoms in some disease conditions (Pagano et al., 2016). The aim of this study was to test a novel task-based BOLD-fMRI/FDG-fPET experimental paradigm that produced concurrent BOLD and FDG signal changes, with a temporal resolution of 2 s and 1 min respectively. In this proof-of-concept study, we extended the work of Villien et al. (2014), and used a visual checkerboard with varying stimulation durations (Fig. 1) and a joint haemodynamic and metabolic analysis approach. We hypothesised that task-based changes in the BOLD signal detected in the brain would be temporally and spatially correlated with task-based changes in FDG metabolism. We identified and investigated joint visual networks and systematically examined the strength and relationship between the concurrently measured BOLD and FDG signals.

Section snippets

Materials & methods

All methods were reviewed by the Monash University Human Research Ethics Committee, in accordance with the Australian National Statement on Ethical Conduct in Human Research (2007). Administration of ionising radiation was approved by the Principal Medical Physicist, in accordance with the Australian Radiation Protection and Nuclear Safety Agency Code of Practice (2005). For participants aged over 18yrs, the annual dose constraint of 5mSV applies; here the effective dose was 4.9mSV.

Data from

Results

The image data for both modalities were analysed separately, and then jointly, using a joint ICA to calculate the coupled components. Here, we report the results for the primary visual network extracted from each analysis. This network was the first component obtained from each analysis, in a manner consistent with the experimental design (Fig. 1). The results for the other components estimated in each analysis are reported in the Supplementary Results.

The static FDG-PET analysis revealed

Discussion

In this brain imaging study, we investigated the relationship between simultaneously acquired measures of human brain activity. Extending the work of Villien et al. (2014), we developed and tested a novel experimental paradigm to evoke neural activity in the visual cortices with high temporal resolution using simultaneously acquired BOLD-fMRI and dynamic FDG-fPET. In the fPET analysis we focused on measurement of relative change in FDG uptake (glucose metabolism) but we did not quantify CMRGLC

Conclusions

In this study, we have presented a novel experimental design for the measurement of task-evoked changes in brain activity with high temporal resolution that uses simultaneous BOLD-fMRI/FDG-fPET imaging to capture metabolic and haemodynamics responses. We showed that this approach yields task-related activity in both modalities during simultaneous BOLD-fMRI/FDG-fPET acquisition. While studies of the resting-state of the brain are important for understanding quiescent neural activity, studies of

Conflicts of interest

The authors declare no conflict of interest. The funding source had no involvement in the study design, collection, analysis and interpretation of data.

Author contributions

SJ, ZC and GE designed the study; all authors contributed to analysis design; FS, SL, JB analysed the data; all authors contributed to manuscript preparation.

Acknowledgements

We thank Richard McIntyre, Alexandra Carey and Jason Bradley for assistance with the implementation of the constant-infusion technique and scanning protocol. We thank Edwina Orchard, Irene Graafsma and Disha Sasan, and the staff at Monash Biomedical Imaging for assistance with data collection.

Jamadar is supported by an Australian Research Council Discovery Early Career Researcher Award (ARC DECRA DE150100406). Jamadar, Ward and Egan are supported by the ARC Centre of Excellence for Integrative

References (59)

  • A. Hyvärinen et al.

    Independent component analysis: algorithms and applications

    Neural Network.

    (2000)
  • S. Jamadar et al.

    The spatial and temporal dynamics of anticipatory preparation and response inhibition in task-switching

    Neuroimage

    (2010)
  • S.S. Kety

    The general metabolism of the brain in vivo

  • P. Mergenthaler et al.

    Sugar for the brain: the role of glucose in physiological and pathological brain function

    Trends Neurosci.

    (2013)
  • W.W. Moses

    Fundamental limits of spatial resolution in PET

    Nucl. Instrum. Methods Phys. Res. Sect. A Accel. Spectrom. Detect. Assoc. Equip.

    (2011)
  • M. Petit-Taboue et al.

    Effects of healthy aging on the regional cerebral metabolic rate of glucose assessed with statistical parametric mapping

    Neuroimage

    (1998)
  • L. Rischka

    Reduced task durations in functional PET imaging with [18F] FDG approaching that of functional MRI

    Neuroimage

    (2018)
  • Y. Serlin et al.

    Anatomy and physiology of the blood–brain barrier

  • M. Villien

    Dynamic functional imaging of brain glucose utilization using fPET-FDG

    Neuroimage

    (2014)
  • P.G. Ward

    Combining images and anatomical knowledge to improve automated vein segmentation in MRI

    Neuroimage

    (2018)
  • A. Aiello et al.

    From transverse angular momentum to photonic wheels

    Nat. Photon.

    (2015)
  • C.M. Bauer et al.

    Differentiating between normal aging, mild cognitive impairment, and Alzheimer's disease with FDG-PET: effects of normalization region and partial volume correction method

    J. Alzheimers Dis. Park.

    (2013)
  • C.F. Beckmann et al.

    Investigations into resting-state connectivity using independent component analysis

    Phil. Trans. Biol. Sci.

    (2005)
  • B. Biswal et al.

    Functional connectivity in the motor cortex of resting human brain using echo-planar mri

    Magn. Reson. Med.

    (1995)
  • M.G. Bright et al.

    Multiparametric measurement of cerebral physiology using calibrated fMRI

    Neuroimage

    (2017)
  • N. Burgos

    Attenuation correction synthesis for hybrid PET-MR scanners: application to brain studies

    IEEE Trans. Med. Imag.

    (2014)
  • V.D. Calhoun et al.

    Feature-based fusion of medical imaging data

    IEEE Trans. Inf. Technol. Biomed.

    (2009)
  • V.D. Calhoun et al.

    A method for making group inferences from functional MRI data using independent component analysis

    Hum. Brain Mapp.

    (2001)
  • V. Calhoun

    Method for multimodal analysis of independent source differences in schizophrenia: combining gray matter structural and auditory oddball functional data

    Hum. Brain Mapp.

    (2006)
  • Cited by (49)

    View all citing articles on Scopus
    View full text