Abstract
The microtubule-associated protein tau plays an important role in tauopathic diseases such as Alzheimer’s disease and primary tauopathies such as progressive supranuclear palsy and corticobasal degeneration. Tauopathy animal models, such as transgenic, knock-in mouse and rat models, recapitulating tauopathy have facilitated the understanding of disease mechanisms. Aberrant accumulation of hyperphosphorylated tau contributes to synaptic deficits, neuroinflammation, and neurodegeneration, leading to cognitive impairment in animal models. Recent advances in molecular imaging using positron emission tomography (PET) and magnetic resonance imaging (MRI) have provided valuable insights into the time course of disease pathophysiology in tauopathy animal models. High-field MRI has been applied for in vivo imaging in animal models of tauopathy, including diffusion tensor imaging for white matter integrity, arterial spin labeling for cerebral blood flow, resting-state functional MRI for functional connectivity, volumetric MRI for neurodegeneration, and MR spectroscopy. In addition, MR contrast agents for non-invasive imaging of tau have been developed recently. Many preclinical MRI indicators offer excellent translational value and provide a blueprint for clinical MRI in the brains of patients with tauopathies. In this review, we summarized the recent advances in using MRI to visualize the pathophysiology of tauopathy in small animals. We discussed the outstanding challenges in brain imaging using MRI in small animals and propose a future outlook for visualizing tau-related alterations in the brains of animal models.
Introduction
Six microtubule-associated protein tau (MAPT) isoforms are expressed in the adult human brain and are further categorized into 4-repeat (4R) and 3-repeat (3R) species (Lee et al., 2001). Tauopathy diseases include Alzheimer’s disease (AD) and primary tauopathies such as progressive supranuclear palsy (PSP), corticobasal degeneration (CBD), and frontotemporal dementia (FTD) with Parkinsonism linked to chromosome 17, and Pick’s disease (Ballatore et al., 2007). Primary tauopathies are pathologically characterized by the aggregation of hyperphosphorylated tau protein into neurofibrillary tangles, neuropil threads, and argentophilic glial inclusions (Lee et al., 2001). Thus, tau has been an important target in therapeutic development for AD and primary tauopathies, with several immunotherapies, antisense oligonucleotides, and aggregation inhibitors under clinical trials (DeVos et al., 2017; Congdon and Sigurdsson, 2018; Boxer et al., 2019, 2020; Ayalon et al., 2021; Grossman, 2021; Mullard, 2021; Novak et al., 2021). Animal models recapitulating tauopathy have facilitated the understanding of disease mechanisms and the development of treatment strategies (Albert et al., 2019; Roberts et al., 2020; Ayalon et al., 2021), including transgenic mouse lines P301S (PS19), EC-tau, P301L (JNPL3, rTg4510, pR5), rTg21221 (Lewis et al., 2000; Ramsden et al., 2005; Santacruz et al., 2005; Yoshiyama et al., 2007; Hoover et al., 2010; de Calignon et al., 2012) and rat models (Filipcik et al., 2012). In addition, knock-out hTau (Andorfer et al., 2003) and knock-in mouse models (Hashimoto et al., 2019; Saito et al., 2019; Hosokawa et al., 2021) have been recently developed. Animal models exhibit tau accumulation, neuroinflammation, synaptic dysfunction, brain regional atrophy, and cognitive impairment to different extents (Götz et al., 2018; Ishikawa et al., 2018; Ising et al., 2019). Magnetic resonance imaging (MRI) has been widely used to non-invasively probe the tissue changes associated with cerebral tau pathology in patients with AD and FTD (Du et al., 2006; Boxer et al., 2020; Young et al., 2021). Regional atrophy assessed by T2-weighted MRI, white matter integrity assessed by diffusion tensor imaging (DTI), and cerebral perfusion measured by arterial spin labeling (ASL) have emerged as potential biomarkers in AD and FTD. Recent advances in MRI and contrast agents (Wahsner et al., 2019) have provided valuable insights into the time course of disease pathophysiology in tau animal models, including tau, neuroinflammation, and structural and functional alterations.
Tau Imaging
Tau is located intracellularly and is subject to posttranslational modifications, including phosphorylation, acetylation, ubiquitylation, and truncation. Tau aggregates into nanofibrils with cofactors (Goedert et al., 1996) and displays typical sigmoidal kinetics of nucleation-dependent protein aggregation (Chakraborty et al., 2021). The smaller aggregates, tau oligomers, are considered more neurotoxic than the neurofibrillary tangle, induce synaptic and mitochondrial dysfunction, and impair memory functions in animal models (Lasagna-Reeves et al., 2011). Tau imaging has been even more challenging than amyloid imaging due to the intracellular location and size of tau aggregates, as well as the different tau isoforms (Villemagne et al., 2015). Positron emission tomography (PET) imaging of tau in tauopathy mouse models using various tau-targeted radioligands has been established (Maruyama et al., 2013; Brendel et al., 2016; Ono et al., 2017; Ishikawa et al., 2018; Ni et al., 2018; Tagai et al., 2020; Chaney et al., 2021; Cao et al., 2022). In addition, fluorescence imaging, two-photon microscopy, and photoacoustic imaging methods have been developed for in vivo mapping of tau accumulation in animal models (Wu et al., 2018; Calvo-Rodriguez et al., 2019; Ni et al., 2020a; Vagenknecht et al., 2021). To date, a few MRI tau imaging studies have been reported assisted with contrast agents (Table 1). Two MRI contrast agents have been reported for detecting tau in animal models in vivo. Yanagisawa et al. (2018) reported that the [19F]buta-1,3-diene derivative Shiga-X35 allowed the detection of tau aggregates in the forebrain region of 8–9-month-old female rTg4510 mice compared with wild-type mice at 7 T MRI. The detection was verified by colocalization with anti-phosphorylated tau antibody AT8-positive tau deposits. Badachhape et al. (2020) and Parekh et al. (2021) demonstrated tau imaging using the DNA aptamer-targeted liposomal-Gd nanoparticle TauX, which binds to the surface of hyperphosphorylative cells, for T1-weighted spin echo MRI in PS19 mice (Figure 1A). Increased TauX-enhanced post-contrast MR signal enhancement was detected at 2 months of age in PS19 mice (which showed tauopathy 4–6 months later) compared with wild-type mice, with an accuracy of approximately 0.8 (Figure 1B).
TABLE 1
Summary of MRI in animal models of tauopathy.
ASL, arterial spin labeling; BOLD, blood-oxygenation-level-dependent; CBF, cerebral blood flow; CE, contrast enhanced; CEST, chemical exchange saturation transfer imaging; CMRO2, cerebral metabolic rate of oxygen; CVR, cerebral vascular response; DCE, dynamic contrast enhanced; DTI, diffusion tensor imaging; fMRI, functional magnetic resonance imaging; ME, manganese enhanced; MRI, magnetic resonance imaging; MRS, magnetic resonance spectroscopy; MRTA, magnetic resonance texture analysis; PC, phase contrast; QSM, quantitative susceptibility mapping; rs, resting state; SE, spin echo; SWI, susceptibility-weighted imaging; TRUST, T2 relaxation under spin tagging; WM, white matter; w, weighted.
FIGURE 1
Functional Imaging
Hyperneuronal activity has been shown to enhance tau secretion and exacerbate tau pathology in several tauopathy mouse models, including rTg4510, EC-Tau (Wu et al., 2016), Thy-Tau22 (Gomez-Murcia et al., 2020), and the TAU58/2 lines (Przybyla et al., 2020). Pathological tau accumulates mainly in excitatory neurons rather than in inhibitory neurons, leading to neuronal network dysfunction and neural circuit impairment (Busche et al., 2008; Fu et al., 2019). Functional imaging techniques, such as manganese-enhanced MRI (MEMRI), ASL, resting-state functional MRI (rs-fMRI), and contrast-enhanced fMRI, have been widely used to probe brain functional alterations in small animals.
Resting-State Functional MRI and Task-Based fMRI
Blood-oxygen-level-dependent (BOLD) signals measured by rs-fMRI are widely used for non-invasive mapping of brain function between neural activity and its accompanying hemodynamics. Recent studies have shown that the spreading of misfolded tau follows a disease-specific region-dependent pattern in the brain not only in the anatomically connected regions but also in the functionally connected regions in patients with AD (Franzmeier et al., 2020; Vogel et al., 2021) and with FTD (Kim et al., 2020; Spinelli et al., 2021; Young et al., 2021). The default mode network (DMN) is a set of network nodes consisting of the medial prefrontal cortex, the posterior cingulate/precuneus, inferior parietal lobe, lateral temporal cortex, and hippocampal formation (Buckner and DiNicola, 2019). In patients with primary tauopathy, DMN regions are affected at an early stage (Zhou et al., 2010; Lee et al., 2014). Few fMRI studies have been reported thus far in tau mouse models (Table 1). As these studies are performed in different mouse lines, a direct comparison of the results is infeasible. Green et al. (2019) showed that functional networks were impaired by elevated tau accumulation in TauRD/ΔK280 mice compared with wild-type mice and were reversible by doxycycline treatment to regulate soluble tau for 8weeks (under 1.5% isoflurane during rs-fMRI) (Figure 1C). Degiorgis et al. (2020) demonstrated that there was hyperactivated functional connectivity in the hippocampus, amygdala, and isocortical areas in Thy-Tau22 mice at an early stage (5 months of age) compared with wild-type mice using rs-fMRI (maintained under medetomidine sedation during fMRI), which preceded the occurrence of memory impairment. A different observation was reported by Detrez et al. (2020), who found that progressive tau aggregation did not alter the functional brain network connectivity in hTau.P301L mice at 7 months of age after seeding with K18 tau at 3 months of age (under 0.5% isoflurane and medetomidine during fMRI) at 7 T MRI. Using task-based fMRI at 9.4 T, Nahavandi et al. (2017) reported differences in the visual processing pathway and a stronger midbrain BOLD response to visual stimulation in rTg4510 mice than in wild-type mice at 7.5 months of age. Interpretation of BOLD signals is challenged by their dependence on multiple factors, such as baseline physiological state, breathing, animal handling, ventilation, and anesthesia scheme (Grandjean et al., 2014a; Paasonen et al., 2018). In addition, variation in the fMRI signal might partly stem from technical factors, fluctuations, spatial localization, non-linearities, task, pulse sequence used, and data analysis approaches.
Manganese-Enhanced MRI
Manganese-enhanced MRI (MEMRI) is a sensitive in vivo neuroimaging method that detects the neuronal activity-based transport of Mn2+ into active neurons (Silva and Bock, 2008). Several in vivo MEMRI studies have demonstrated axonal transport deficits in rTg4510 (Perez et al., 2013; Majid et al., 2014; Fontaine et al., 2017; Bachstetter et al., 2020; Koren et al., 2020), Tau-KO (Lopes et al., 2016), JNPL3 (Bertrand et al., 2013), and Wtau-Tg mice (Kimura et al., 2007) compared with control mice (Table 1). Using MEMRI at 7 T, Fontaine et al. (2017) showed elevated changes in tissue R1 relaxation rates (ΔR1) after the administration of Mn2+, indicating early neuronal dysfunction at 3 months of age in rTg4510 mice before the onset of cognitive deficits (Figures 1D–H). However, concerns regarding the neurotoxicity of Mn2+ hinder the wide application of this method.
Arterial Spin Labeling
Arterial spin labeling MRI has been widely used in the clinical setting as well as in preclinical imaging in animal models. ASL MRI has demonstrated different spatial distributions of hypoperfusion in patients with FTD compared with AD (Du et al., 2006; Verfaillie et al., 2015; Meeter et al., 2017). ASL uses magnetically labeled blood water and allows the direct quantification of absolute cerebral blood flow (CBF) and cerebrovascular reactivity of the whole brain regions. In regions with very short or very long arterial transit times, the accuracy of ASL measurement is compromised. Previous studies on ASL measures of CBF in tauopathy animal models have yielded inconsistent results (Table 1). Park et al. (2020) showed that at 2–3 months of age, rTg4510 mice had comparable resting CBF, attenuated CBF response to whisker stimulation, and no cortical thinning compared with wild-type mice. Reduced resting CBF and CBF responses to whisker stimulation in the neocortex and the hippocampus, along with reduced cortical thickness, were detected at 7–8 months of age compared with wild-type mice (Figures 2A–D; Park et al., 2020). In the PS19 mice, an early impaired resting CBF and CBF response to whisker stimulation at 2–3 months of age was detected in the absence of cortical thinning compared with wild-type mice (Figures 2A–D). Moreover, tau induces postsynaptic protein PSD95-neuronal nitric oxide uncoupling and neurovascular dysfunction in rTg4510 and PS19 mice in a neurodegeneration-independent manner (Park et al., 2020). In contrast, a study by Wells et al. (2015b) and Holmes et al. (2016) reported elevated levels of CBF in the cortex, hippocampus, and thalamus in 7.5–9.5-month-old rTg4510 mice compared with wild-type mice. Another recent study by Govaerts et al. (2019) showed that the regional CBF levels are comparable between Tau.P301L mice and wild-type mice at 3, 6, and 12 months of age. Kindler et al. (2021) showed a comparable cortical and hippocampal CBF between pR5 mice and wild-type mice at 10 and 18 months of age. Wei et al. (2021) reported a reduced cerebral metabolic rate of oxygen while preserving CBF in Tau4RΔK (Tau) mice at 12 months of age compared with wild-type mice by using T2 relaxation under spin tagging, phase contrast, and ASL MRI. For cerebral vascular response quantification, pulsed ASL and pseudocontinuous ASL methods have been utilized. Using a hypercapnia (5% carbon dioxide)-challenged pulsed ASL vasoreactivity paradigm, Wells et al. (2015a) showed increased vascular responses to hypercapnia conditions in rTg4510 mice compared with wild-type mice at approximately 8 months of age. It is noted that information regarding the amount of carbon dioxide in exhaled air was not provided in this article. The varying results regarding the influence of tau on CBF (increasing, preserved, or reducing) require further investigation.
FIGURE 2
Structural MRI
Volumetric MRI
MRI investigations have revealed disease-specific patterns of gray and white matter atrophy in patients with PSP, CBD, Pick’s disease, and variants of FTD and AD, providing valuable tools for differential diagnosis (Boxer et al., 2006; Jabbari et al., 2020; Ulugut Erkoyun et al., 2020; Vogel et al., 2021; Young et al., 2021). In animal models of tauopathy, histological studies have demonstrated the deposition of neurofibrillary tangle pathology, particularly in the cortex and hippocampus, accompanied by regional atrophy. Both in vivo and ex vivo MRI studies have been performed to assess structural alterations. Ma et al. (2019) compared the results from in vivo and ex vivo volumetric MRI in rTg4510 mice and reported comparable readouts of brain atrophy compared with wild-type mice. MRI studies in animal models of tauopathies have revealed distinctive neuroimaging features and patterns of brain regional atrophy in rTg4510, hTau, EC-Tau, rTg21221, and PS19 mice as well as in R962-hTau rats (Table 1). Gray matter atrophy, cortical thinning, hippocampal atrophy, and ventricle enlargement that result from neurodegeneration have been reported in several MR studies in the rTg4510 tau mouse model compared with wild-type mice (Yang et al., 2011; Wells et al., 2015b; Holmes et al., 2016, 2017; Ishikawa et al., 2018; Ni et al., 2018; Ma et al., 2019; Barron et al., 2020; Park et al., 2020). In addition, Colgan et al. (2017) and O’Callaghan et al. (2017) reported tau-related tissue textural alterations using T2*-weighted MR textural analysis and T2*-weighted quantitative susceptibility mapping (QSM) in rTg4510 mice. In addition to the aforementioned MRI studies, optic nerve thinning and degeneration in the neurosensory retina have been reported in rTg4510 mice (Harrison et al., 2019).
In comparison with wild-type mice, hTau mice showed predominantly cortical thinning and rather spared hippocampi (Andorfer et al., 2003; Hashimoto et al., 2019). For P301S (PS19) mice, Yoshiyama et al. (2007) showed atrophy in the hippocampus and entorhinal cortex at 9–12 months of age and that atrophy was further present in the amygdala and neocortex at later stages (Wu et al., 2019; Takeuchi et al., 2020; Lee et al., 2021). Takeuchi et al. (2020) demonstrated that tauopathy and MRI-assessed brain atrophy and cognitive impairment in PS19 mice can be reversed by nasal vaccine delivery. In EC-TAU mice, Fung et al. (2020) showed that regional hippocampal atrophy (based on tensor-based morphometry analysis) compared with age-matched wild-type mice was associated with tau pathology preceding overt cell death. In rTg21221 mice that overproduced non-aggregating wild-type human tau but lacked neurofibrillary tangle accumulation, mainly ventricle enlargement was observed compared with wild-type mice (Wegmann et al., 2015; Musi et al., 2018). Malcolm et al. (2019) characterized recently developed R962-hTau rats and reported ventricular dilation and hippocampal atrophy in this model.
Diffusion Imaging
Diffusion imaging is based on the tissue water diffusion rate: DTI enables indirect measurement of the degree of anisotropy and structural orientation (Le Bihan et al., 2001), while diffusion kurtosis imaging (DKI) reports non-Gaussian water diffusion (Jensen and Helpern, 2010). DTI has been widely used to assess white matter integrity alterations non-invasively both in animal models and in the clinical setting (Mori and Zhang, 2006). The DTI scalars reflect various alterations: fractional anisotropy (FA) infers microstructural integrity, axonal diameter, and density of crossing fibers; radial diffusivity (RD) is the diffusivity perpendicular to axonal fibers and reflects myelin abnormalities; mean diffusivity (MD) is the average mobility of water molecules related to the white matter tissue microstructure; and axial diffusivity (AD) is the magnitude of diffusion parallel to fiber tracts associated with axonal pathologies (Assaf and Pasternak, 2008). Several DTI studies in tauopathy models have been reported, including rTg4510 (Sahara et al., 2014; Wells et al., 2015b; Holmes et al., 2016), Thy-Tau22 (Degiorgis et al., 2020), pR5 (Soni et al., 2021), Tg601 (Hara et al., 2017), JNPL3 (Nishioka et al., 2019), and TauRD/ΔK280 mice (Green et al., 2019), with varying results. Sahara et al. (2014) reported an age-dependent decrease in FA in the corpus callosum and anterior commissure in rTg4510 mice at 8 months of age, increased RD, and unaltered MD and AD in the corpus callosum. Colgan et al. (2016) found a lower FA and a higher MD in the corpus callosum of rTg4510 mice of 8.5 months of age compared with wild-type mice. Using neurite orientation dispersion and density imaging (NODDI) model, Colgan et al. (2016) showed that neurite density index (NDI) was increased in the cortex (with high tau load) but decreased in the hippocampus and corpus callosum of rTg4510 mice compared with wild-type mice, isotropic volume fraction (IsoVF) was increased in the cortex but decreased in the thalamus (a region void of tau) of rTg4510 mice compared with wild-type mice, and orientation dispersion index (ODI) was found to be reduced in the cortex and hippocampus but increased in the corpus callosum of rTg4510 mice compared with wild-type mice (Figure 2E). FA was increased in the hippocampus but reduced in the corpus callosum of rTg4510 mice compared with wild-type mice (Figure 2E; Colgan et al., 2016). Furthermore, the NDI readout correlated with the level of tau (PG-5 antibody staining) in the gray matter of the rTg4510 mouse brain. Wells et al. (2015b) demonstrated unaltered FA, MD, and AD and an increased RD in the corpus callosum and increased FA and MD in the gray matter (cortex and hippocampus) in rTg4510 mice compared with wild-type mice. Massalimova et al. (2021) showed decreased FA and increased MD, RD, and AD in the corpus callosum and decreased FA in the gray matter of the hippocampus in the pR5 line at 8.5 months of age compared with wild-type mice. Degiorgis et al. (2020) demonstrated a significant decrease in FA and fiber density in Thy-Tau22 mice at 5 months of age compared with wild-type mice. A DTI study in patients with FTD reported reduced FA values in the anterior corpus callosum, anterior and descending cingulum, and uncinate fiber tracts (Zhang et al., 2009; Torso et al., 2021). In comparison, in patients with AD, reduced FA was reported in the descending cingulum, posterior and anterior cingulum, and uncinate fiber tracts, correlating with the increased tau distribution assessed by PET (Kantarci et al., 2017; Jacobs et al., 2018; Sintini et al., 2019; Carlson et al., 2021). Thus, DTI may facilitate the differential diagnosis of FTD and AD in the clinical setting (Torso et al., 2021).
MRI for Neurochemical Profiles
MR Spectroscopy
Magnetic resonance spectroscopy (MRS) is a highly sensitive MR method for characterizing neurochemical alterations in vivo using the infusion of substrates labeled with magnetic isotopes (Zhu and Barker, 2011). However, MRS has not been translated to clinical usage, where fast, simple, and reliable measurement is essential. A few MRS studies have been reported thus far on tauopathy animal models. Yang et al. (2011) revealed an increase in the hippocampal myoinositol to total creatine ratios (mIns/tCr, representing gliosis) in rTg4510 mice at 5 and 8 months of age compared with wild-type mice using 1H MRS at 9.4 T. Kim et al. (2017) demonstrated more pronounced neurochemical alterations in the olfactory bulbs than in the hippocampus in rTg4510 mice by using 1H MRS. Nilsen et al. (2013) showed that glutamate metabolism is impaired in P301L (pR5) mice compared with wild-type mice by using 1H and 13C MRS.
Chemical Exchange Saturation Transfer MRI
Molecular MRI based on chemical exchange saturation transfer (CEST) is a highly sensitive method that has enabled the detection of changes in the uptake of glucose, glutamate, and creatine without additional hardware (Nilsen et al., 2013; Mamoune et al., 2021). Recent advances in CEST MRI provide information on oxygen metabolism and tissue metabolite levels in the brain, with an increased translational value compared with MRS (Oz et al., 2014). Clinical CEST MRI has been reported using 3 and 7 T MRI (Jones et al., 2018; van Zijl and Knutsson, 2019; van Zijl et al., 2021). Protein-based amide proton transfer-weighted (APTw) CEST MRI has been reported in patients with mild cognitive impairment (Heo et al., 2019; Zhou et al., 2019; Zhang et al., 2020). Glucose CEST has been applied in several tau animal models (Table 1). Lauretti et al. (2017) showed reductions in brain glucose uptake and synaptic function, increased tau accumulation and phosphorylation, and memory impairments in hTau mice compared with control mice. Similar observations of reduced glucose uptake were reported in rTg4510 mice compared with wild-type mice (Wells et al., 2015b; Holmes et al., 2016). Chen et al. (2020) demonstrated reduced glucose uptake in a Tau4RΔK (Tau) mouse model by using on-resonance variable delay multiple pulse (onVDMP) MRI with improved labeling efficiency and sensitivity (Xu et al., 2019). Crescenzi et al. (2014, 2017) demonstrated that there is a reduction in glutamate levels in the hippocampus of PS19 mice compared with wild-type mice, as measured by longitudinal glutamate CEST. Glutamate reduction was found to be associated with the level of synapse loss Crescenzi et al., 2014, 2017). Using creatine CEST, Chen et al. (2021) recently detected a reduction in the cerebral creatine level in Tau4RΔK (Tau) mice compared with wild-type mice.
Discussion
There has been a rapid development in MRI technology in recent years, particularly in high-field MR scanners. For clinical application in humans, 7 and 10.5T MRIs have been reported (Ehman et al., 2017; Ladd et al., 2018). For small animal imaging, 7, 9.4, 11.7, 16, and up to 21.1 T high-field MRI has been utilized in the laboratory (Schepkin et al., 2010; Miyaoka and Lehnert, 2020; Ni, 2021), providing insights into the function and pathophysiology of the brain. Higher magnetic fields substantially increase the sensitivity and signal-to-noise ratio for MRI, although the tissue heating and non-uniformity of the radio-frequency field might affect the image quality. In addition, hybrid imaging systems such as PET-MRI have been increasingly used in preclinical imaging research for complementary molecular and anatomical information (Musafargani et al., 2018; Stortz et al., 2018).
Difference Among Animal Models
Different tauopathy mouse/rat models show distinct tempo-spatial patterns of pathological features, including tau deposits and regional atrophy (Jankowsky and Zheng, 2017; Götz et al., 2018). Tau accumulates in the entorhinal cortex, forebrain, and hippocampus of rTg4510 mice and mainly in the brainstem and spinal cord of the PS19 model (Clavaguera et al., 2009; Maruyama et al., 2013; Wegmann et al., 2019). In rTg4510 mice, atrophy was observed both in the cortex and in the hippocampus, while in hTau mice, cortical thinning was observed while the hippocampus was spared (Andorfer et al., 2003; Santacruz et al., 2005; Ni et al., 2018). Systematic approaches are needed for the direct comparison of datasets from different model systems (Oblak et al., 2020; Sukoff Rizzo et al., 2020).
Methodology and Reproducibility Considerations
Diverging results have been reported in the aforementioned functional MRI studies in tauopathy mice. The various anesthetic regimens used in these studies add to the complexity in interpreting the results. Anesthesia usage brings the benefit of excellent motion control while at the cost of potential interference with measures, particularly in fMRI-related experiments. The regional connectivity in the mouse brain has been shown to be influenced by the different anesthesia protocols utilized (Wu et al., 2017; van Alst et al., 2019). In addition to the isoflurane or low-dose isoflurane + medetomidine sedation that has been used in the aforementioned studies, ketamine and xylazine mixtures have also been reportedly used to achieve stable states in mice or rats (Grandjean et al., 2014b,2020; Shim et al., 2018; Mandino et al., 2020). A recent systematic review summarized the influence of anesthetics, doses, and timing on fMRI results in rodents (Steiner et al., 2021). Thus, standardization of pipelines is important for better interpretation of the results from fMRI studies. Physiological parameters such as heartbeat, breathing rate, and mouse/rat body temperature are routinely included in all in vivo animal studies. In addition, three physiological parameters, namely, blood oxygenation (arterial blood pressure of oxygen), ventilation (arterial partial pressure of carbon dioxide), and arterial blood pressure, can influence BOLD fMRI readouts in various study designs (Steiner et al., 2020) and are thus recommended for inclusion in the monitoring of animal status. Moreover, Chen et al. (2019) reported real-time monitoring and adaptive modulation of the brain hemodynamic system to further facilitate fMRI experiments.
Time Course of MRI Biomarkers in rTg4510 Mice
The rTg4510 mouse model is one of the most widely used tauopathy animal models (Santacruz et al., 2005). rTg4510 mice express high levels of mutant tau (approximately 13 times compared with the levels of endogenous murine tau) and develop neurofibrillary tangles (from 4 months of age), neuroinflammation, neuronal loss, and behavioral impairments with increasing age (Ramsden et al., 2005). A recent study showed that factors other than hTau overexpression contributed to the tauopathy-like phenotype in this model (Gamache et al., 2019). Although no MR angiography has been performed in rTg4510 mice, Harrison et al. (2020) investigated the paravascular fluid (glymphatic) movement in this model: impaired glymphatic flow and clearance of tau in rTg4510 mice compared with wild-type mice were detected by using dynamic contrast-enhanced MRI assisted with Gd-DTPA (Figures 2F–M). In this study, we summarized the findings from the aforementioned MRI studies regarding the time course of events in rTg4510 mice (Figure 3). Following known tau accumulation from 2 months of age (Santacruz et al., 2005), early alterations in synaptic function and neurochemical profiles were observed. The changes in BOLD fMRI, CBF, white matter integrity, and regional atrophy appeared at a later stage. Most of the reported MRI studies are cross-sectional in rTg4510 mice of different age groups. More MRI studies with longitudinal and multiparameter designs are needed to elucidate the time course of these events.
FIGURE 3
Translational Value
Longitudinal multimodal MRI, such as ASL, DTI, and rs-fMRI, has shown great potential as a diagnostic biomarker in FTD (Jiskoot et al., 2019) and for monitoring clinical trials (Staffaroni et al., 2019), providing added value to patients. Preclinical studies in animal models recapitulating human tauopathy provide an opportunity to study disease mechanisms and for extrapolation to human studies. In animal models, the measurements of structural alterations such as brain regional atrophy and white matter integrity yielded more homogenous results compared with the functional changes. As discussed in the “Functional Imaging” section, functional imaging studies using rs-fMRI and ASL MRI for CBF measurement have resulted in different observations in tau animal models. With the presence of such a discrepancy, special attention and further improvement of the protocol and standardization will be required if functional connectivity and CBF are to be used as evaluation readouts for treatment studies in animal models. Several recent studies have utilized awake fMRI to investigate the dysfunction of neural circuits in rodent disease models (Stenroos et al., 2018; Bergmann et al., 2020; Tsurugizawa et al., 2020; Dinh et al., 2021). Such a method will greatly increase the translational potential of the results from rodents to humans.
In summary, MRI studies in tauopathy animal models have improved our understanding of the roles of tau and the progression of pathophysiology and facilitated the evaluation of treatment studies targeting tau. Further MRI studies are needed to further characterize the functional, structural, and molecular alterations in various tauopathy animal models.
Publisher’s Note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Statements
Author contributions
The author confirms being the sole contributor of this work and has approved it for publication.
Funding
RN received funding from Helmut Horten Stiftung and Vontobel Stiftung, University of Zurich (reference no. MEDEF-20-021).
Conflict of interest
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
References
1
AlbertM.Mairet-CoelloG.DanisC.LiegerS.CaillierezR.CarrierS.et al (2019). Prevention of tau seeding and propagation by immunotherapy with a central tau epitope antibody.Brain1421736–1750. 10.1093/brain/awz100
2
AndorferC.KressY.EspinozaM.de SilvaR.TuckerK. L.BardeY. A.et al (2003). Hyperphosphorylation and aggregation of tau in mice expressing normal human tau isoforms.J. Neurochem.86582–590. 10.1046/j.1471-4159.2003.01879.x
3
AssafY.PasternakO. (2008). Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review.J. Mol. Neurosci.3451–61. 10.1007/s12031-007-0029-0
4
AyalonG.LeeS. H.AdolfssonO.Foo-AtkinsC.AtwalJ. K.BlendstrupM.et al (2021). Antibody semorinemab reduces tau pathology in a transgenic mouse model and engages tau in patients with Alzheimer’s disease.Sci. Transl. Med13:eabb2639. 10.1126/scitranslmed.abb2639
5
BachstetterA. D.MorgantiJ. M.BodnarC. N.WebsterS. J.HigginsE. K.RobertsK. N.et al (2020). The effects of mild closed head injuries on tauopathy and cognitive deficits in rodents: primary results in wild type and rTg4510 mice, and a systematic review.Exp. Neurol.326:113180. 10.1016/j.expneurol.2020.113180
6
BadachhapeA.ParekhP. A.MuQ.BhavaneR.SrivastavaM.StupinI.et al (2020). A novel MRI contrast agent for identifying hyperphosphorylative neurons as a marker of future tau pathology.Alzheimers Dement.16:e041080.
7
BallatoreC.LeeV. M.TrojanowskiJ. Q. (2007). Tau-mediated neurodegeneration in Alzheimer’s disease and related disorders.Nat. Rev. Neurosci.8663–672. 10.1038/nrn2194
8
BarronA. M.JiB.FujinagaM.ZhangM. R.SuharaT.SaharaN.et al (2020). In vivo positron emission tomography imaging of mitochondrial abnormalities in a mouse model of tauopathy.Neurobiol. Aging94140–148. 10.1016/j.neurobiolaging.2020.05.003
9
BergmannE.GofmanX.KavushanskyA.KahnI. (2020). Individual variability in functional connectivity architecture of the mouse brain.Commun. Biol.3:738. 10.1038/s42003-020-01472-5
10
BertrandA.KhanU.HoangD. M.NovikovD. S.KrishnamurthyP.Rajamohamed SaitH. B.et al (2013). Non-invasive, in vivo monitoring of neuronal transport impairment in a mouse model of tauopathy using MEMRI.Neuroimage64693–702. 10.1016/j.neuroimage.2012.08.065
11
BoxerA. L.GeschwindM. D.BelforN.Gorno-TempiniM. L.SchauerG. F.MillerB. L.et al (2006). Patterns of brain atrophy that differentiate corticobasal degeneration syndrome from progressive supranuclear palsy.Arch. Neurol.6381–86. 10.1001/archneur.63.1.81
12
BoxerA. L.GoldM.FeldmanH.BoeveB. F.DickinsonS. L.FillitH.et al (2020). New directions in clinical trials for frontotemporal lobar degeneration: methods and outcome measures.Alzheimers Dement.16131–143. 10.1016/j.jalz.2019.06.4956
13
BoxerA. L.QureshiI.AhlijanianM.GrundmanM.GolbeL. I.LitvanI.et al (2019). Safety of the tau-directed monoclonal antibody BIIB092 in progressive supranuclear palsy: a randomised, placebo-controlled, multiple ascending dose phase 1b trial.Lancet Neurol.18549–558. 10.1016/S1474-4422(19)30139-5
14
BrendelM.JaworskaA.ProbstF.OverhoffF.KorzhovaV.LindnerS.et al (2016). Small-animal PET imaging of tau pathology with 18F-THK5117 in 2 transgenic mouse models.J. Nucl. Med.57792–798. 10.2967/jnumed.115.163493
15
BucknerR. L.DiNicolaL. M. (2019). The brain’s default network: updated anatomy, physiology and evolving insights.Nat. Rev. Neurosci.20593–608. 10.1038/s41583-019-0212-7
16
BuscheM. A.EichhoffG.AdelsbergerH.AbramowskiD.WiederholdK. H.HaassC.et al (2008). Clusters of hyperactive neurons near amyloid plaques in a mouse model of Alzheimer’s disease.Science3211686–1689. 10.1126/science.1162844
17
Calvo-RodriguezM.HouS. S.SnyderA. C.DujardinS.ShiraniH.NilssonK. P. R.et al (2019). In vivo detection of tau fibrils and amyloid β aggregates with luminescent conjugated oligothiophenes and multiphoton microscopy.Acta Neuropathol. Commun.7:171. 10.1186/s40478-019-0832-1
18
CarlsonM. L.TouegT. N.KhalighiM. M.CastilloJ.ShenB.AzevedoE. C.et al (2021). Hippocampal subfield imaging and fractional anisotropy show parallel changes in Alzheimer’s disease tau progression using simultaneous tau-PET/MRI at 3T.Alzheimers Dement.13:e12218. 10.1002/dad2.12218
19
CaoL.KongY.JiB.RenY.GuanY.NiR. (2022). Positron emission tomography in animal models of tauopathies.Front. Aging Neurosci.13:913. 10.3389/fnagi.2021.761913
20
ChakrabortyP.RivièreG.LiuS.de OpakuaA. I.DervişoğluR.HebestreitA.et al (2021). Co-factor-free aggregation of tau into seeding-competent RNA-sequestering amyloid fibrils.Nat. Commun.12:4231. 10.1038/s41467-021-24362-8
21
ChaneyA. M.Lopez-PiconF. R.SerrièreS.WangR.BochicchioD.WebbS. D.et al (2021). Prodromal neuroinflammatory, cholinergic and metabolite dysfunction detected by PET and MRS in the TgF344-AD transgenic rat model of AD: a collaborative multi-modal study.Theranostics116644–6667. 10.7150/thno.56059
22
ChenL.van ZijlP. C. M.WeiZ.LuH.DuanW.WongP. C.et al (2021). Early detection of Alzheimer’s disease using creatine chemical exchange saturation transfer magnetic resonance imaging.Neuroimage236:118071. 10.1016/j.neuroimage.2021.118071
23
ChenL.WeiZ.ChanK. W. Y.LiY.SuchalK.BiS.et al (2020). D-Glucose uptake and clearance in the tauopathy Alzheimer’s disease mouse brain detected by on-resonance variable delay multiple pulse MRI.J. Cereb. Blood Flow Metab.411013–1025. 10.1177/0271678X20941264
24
ChenX.SobczakF.ChenY.JiangY.QianC.LuZ.et al (2019). Mapping optogenetically-driven single-vessel fMRI with concurrent neuronal calcium recordings in the rat hippocampus.Nat. Commun.10:5239. 10.1038/s41467-019-12850-x
25
ClavagueraF.BolmontT.CrowtherR. A.AbramowskiD.FrankS.ProbstA.et al (2009). Transmission and spreading of tauopathy in transgenic mouse brain.Nat. Cell Biol.11909–913. 10.1038/ncb1901
26
ColganN.GaneshanB.HarrisonI. F.IsmailO.HolmesH. E.WellsJ. A.et al (2017). In vivo imaging of tau pathology using magnetic resonance imaging textural analysis.Front. Neurosci.11:599. 10.3389/fnins.2017.00599
27
ColganN.SiowB.O’CallaghanJ. M.HarrisonI. F.WellsJ. A.HolmesH. E.et al (2016). Application of neurite orientation dispersion and density imaging (NODDI) to a tau pathology model of Alzheimer’s disease.Neuroimage125739–744. 10.1016/j.neuroimage.2015.10.043
28
CongdonE. E.SigurdssonE. M. (2018). Tau-targeting therapies for Alzheimer disease.Nat. Rev. Neurol.14399–415. 10.1038/s41582-018-0013-z
29
CrescenziR.DeBrosseC.NangaR. P.ByrneM. D.KrishnamoorthyG.D’AquillaK.et al (2017). Longitudinal imaging reveals subhippocampal dynamics in glutamate levels associated with histopathologic events in a mouse model of tauopathy and healthy mice.Hippocampus27285–302. 10.1002/hipo.22693
30
CrescenziR.DeBrosseC.NangaR. P.ReddyS.HarisM.HariharanH.et al (2014). In vivo measurement of glutamate loss is associated with synapse loss in a mouse model of tauopathy.Neuroimage101185–192. 10.1016/j.neuroimage.2014.06.067
31
de CalignonA.PolydoroM.Suárez-CalvetM.WilliamC.AdamowiczD. H.KopeikinaK. J.et al (2012). Propagation of tau pathology in a model of early Alzheimer’s disease.Neuron73685–697. 10.1016/j.neuron.2011.11.033
32
DegiorgisL.KaratasM.SourtyM.FaivreE.LamyJ.NobletV.et al (2020). Brain network remodelling reflects tau-related pathology prior to memory deficits in Thy-Tau22 mice.Brain1433748–3762. 10.1093/brain/awaa312
33
DetrezJ. R.Ben-NejmaI. R. H.Van KolenK.Van DamD.De DeynP. P.FransenE.et al (2020). Progressive tau aggregation does not alter functional brain network connectivity in seeded hTau.P301L mice.Neurobiol. Dis.143:105011. 10.1016/j.nbd.2020.105011
34
DeVosS. L.MillerR. L.SchochK. M.HolmesB. B.KebodeauxC. S.WegenerA. J.et al (2017). Tau reduction prevents neuronal loss and reverses pathological tau deposition and seeding in mice with tauopathy.Sci. Transl. Med.9:eaag0481. 10.1126/scitranslmed.aag0481
35
DinhT. N. A.JungW. B.ShimH.-J.KimS.-G. (2021). Characteristics of fMRI responses to visual stimulation in anesthetized vs. awake mice.NeuroImage226:117542. 10.1016/j.neuroimage.2020.117542
36
DuA. T.JahngG. H.HayasakaS.KramerJ. H.RosenH. J.Gorno-TempiniM. L.et al (2006). Hypoperfusion in frontotemporal dementia and Alzheimer disease by arterial spin labeling MRI.Neurology671215–1220. 10.1212/01.wnl.0000238163.71349.78
37
EhmanE. C.JohnsonG. B.Villanueva-MeyerJ. E.ChaS.LeynesA. P.LarsonP. E. Z.et al (2017). PET/MRI: where might it replace PET/CT?J. Magn. Reson. Imaging461247–1262. 10.1002/jmri.25711
38
FilipcikP.ZilkaN.BugosO.KucerakJ.KosonP.NovakP.et al (2012). First transgenic rat model developing progressive cortical neurofibrillary tangles.Neurobiol. Aging331448–1456. 10.1016/j.neurobiolaging.2010.10.015
39
FontaineS. N.IngramA.CloydR. A.MeierS. E.MillerE.LyonsD.et al (2017). Identification of changes in neuronal function as a consequence of aging and tauopathic neurodegeneration using a novel and sensitive magnetic resonance imaging approach.Neurobiol. Aging5678–86. 10.1016/j.neurobiolaging.2017.04.007
40
FranzmeierN.DewenterA.FrontzkowskiL.DichgansM.RubinskiA.NeitzelJ.et al (2020). Patient-centered connectivity-based prediction of tau pathology spread in Alzheimer’s disease.Sci. Adv.6:eabd1327. 10.1126/sciadv.abd1327
41
FuH.PossentiA.FreerR.NakanoY.Hernandez VillegasN. C.TangM.et al (2019). A tau homeostasis signature is linked with the cellular and regional vulnerability of excitatory neurons to tau pathology.Nat. Neurosci.2247–56. 10.1038/s41593-018-0298-7
42
FungC. W.GuoJ.FuH.FigueroaH. Y.KonofagouE. E.DuffK. E. (2020). Atrophy associated with tau pathology precedes overt cell death in a mouse model of progressive tauopathy.Sci. Adv.6:eabc8098. 10.1126/sciadv.abc8098
43
GamacheJ.BenzowK.ForsterC.KemperL.HlynialukC.FurrowE.et al (2019). Factors other than hTau overexpression that contribute to tauopathy-like phenotype in rTg4510 mice.Nat. Commun.10:2479. 10.1038/s41467-019-10428-1
44
GoedertM.JakesR.SpillantiniM. G.HasegawaM.SmithM. J.CrowtherR. A. (1996). Assembly of microtubule-associated protein tau into Alzheimer-like filaments induced by sulphated glycosaminoglycans.Nature383550–553. 10.1038/383550a0
45
Gomez-MurciaV.SandauU.FerryB.ParrotS.LaurentC.BasquinM.et al (2020). Hyperexcitability and seizures in the THY-Tau22 mouse model of tauopathy.Neurobiol. Aging94265–270. 10.1016/j.neurobiolaging.2020.06.004
46
GötzJ.BodeaL.-G.GoedertM. (2018). Rodent models for Alzheimer disease.Nat. Rev. Neurosci.19583–598. 10.1038/s41583-018-0054-8
47
GovaertsK.LechatB.StruysT.KremerA.BorghgraefP.Van LeuvenF.et al (2019). Longitudinal assessment of cerebral perfusion and vascular response to hypoventilation in a bigenic mouse model of Alzheimer’s disease with amyloid and tau pathology.NMR Biomed.32:e4037. 10.1002/nbm.4037
48
GrandjeanJ.CanellaC.AnckaertsC.AyrancıG.BougachaS.BienertT.et al (2020). Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis.Neuroimage205:116278. 10.1016/j.neuroimage.2019.116278
49
GrandjeanJ.SchroeterA.BatataI.RudinM. (2014a). Optimization of anesthesia protocol for resting-state fMRI in mice based on differential effects of anesthetics on functional connectivity patterns.Neuroimage102(Pt 2), 838–847. 10.1016/j.neuroimage.2014.08.043
50
GrandjeanJ.SchroeterA.HeP.TanadiniM.KeistR.KrsticD.et al (2014b). Early alterations in functional connectivity and white matter structure in a transgenic mouse model of cerebral amyloidosis.J. Neurosci.3413780–13789. 10.1523/JNEUROSCI.4762-13.2014
51
GreenC.SydowA.VogelS.Anglada-HuguetM.WiedermannD.MandelkowE.et al (2019). Functional networks are impaired by elevated tau-protein but reversible in a regulatable Alzheimer’s disease mouse model.Mol. Neurodegener.14:13. 10.1186/s13024-019-0316-6
52
GrossmanM. (2021). Lessons learned from a progressive supranuclear palsy trial.Lancet Neurol.20162–163. 10.1016/S1474-4422(21)00035-1
53
HaraY.MotoiY.HikishimaK.MizumaH.OnoeH.MatsumotoS. E.et al (2017). Involvement of the septo-hippocampal cholinergic pathway in association with septal acetylcholinesterase upregulation in a mouse model of tauopathy.Curr. Alzheimer Res.1494–103. 10.2174/1567205013666160602235800
54
HarrisonI. F.IsmailO.MachhadaA.ColganN.OheneY.NahavandiP.et al (2020). Impaired glymphatic function and clearance of tau in an Alzheimer’s disease model.Brain1432576–2593. 10.1093/brain/awaa179
55
HarrisonI. F.WhitakerR.BertelliP. M.O’CallaghanJ. M.CsincsikL.BocchettaM.et al (2019). Optic nerve thinning and neurosensory retinal degeneration in the rTg4510 mouse model of frontotemporal dementia.Acta Neuropathol. Commun.7:4.
56
HashimotoS.MatsubaY.KamanoN.MihiraN.SaharaN.TakanoJ.et al (2019). Tau binding protein CAPON induces tau aggregation and neurodegeneration.Nat. Commun.10:2394.
57
HeoH.-Y.HanZ.JiangS.SchärM.van ZijlP. C. M.ZhouJ. (2019). Quantifying amide proton exchange rate and concentration in chemical exchange saturation transfer imaging of the human brain.NeuroImage189202–213. 10.1016/j.neuroimage.2019.01.034
58
HolmesH. E.ColganN.IsmailO.MaD.PowellN. M.O’CallaghanJ. M.et al (2016). Imaging the accumulation and suppression of tau pathology using multiparametric MRI.Neurobiol. Aging39184–194. 10.1016/j.neurobiolaging.2015.12.001
59
HolmesH. E.PowellN. M.MaD.IsmailO.HarrisonI. F.WellsJ. A.et al (2017). Comparison of in vivo and ex vivo MRI for the detection of structural abnormalities in a mouse model of tauopathy.Front. Neuroinform.11:20. 10.3389/fninf.2017.00020
60
HooverB. R.ReedM. N.SuJ.PenrodR. D.KotilinekL. A.GrantM. K.et al (2010). Tau mislocalization to dendritic spines mediates synaptic dysfunction independently of neurodegeneration.Neuron681067–1081. 10.1016/j.neuron.2010.11.030
61
HosokawaM.Masuda-SuzukakeM.ShitaraH.ShimozawaA.SuzukiG.KondoH.et al (2021). Development of a novel tau propagation mouse model endogenously expressing 3 and 4 repeat tau isoforms.BrainOnline ahead of print10.1093/brain/awab289
62
IshikawaA.TokunagaM.MaedaJ.MinamihisamatsuT.ShimojoM.TakuwaH.et al (2018). In vivo visualization of tau accumulation, microglial activation, and brain atrophy in a mouse model of tauopathy rTg4510.J. Alzheimers Dis.611037–1052. 10.3233/JAD-170509
63
IsingC.VenegasC.ZhangS.ScheiblichH.SchmidtS. V.Vieira-SaeckerA.et al (2019). NLRP3 inflammasome activation drives tau pathology.Nature575669–673. 10.1038/s41586-019-1769-z
64
JabbariE.HollandN.ChelbanV.JonesP. S.LambR.RawlinsonC.et al (2020). Diagnosis across the spectrum of progressive supranuclear palsy and corticobasal syndrome.JAMA Neurol.77377–387. 10.1001/jamaneurol.2019.4347
65
JacobsH. I. L.HeddenT.SchultzA. P.SepulcreJ.PereaR. D.AmariglioR. E.et al (2018). Structural tract alterations predict downstream tau accumulation in amyloid-positive older individuals.Nat. Neurosci.21424–431. 10.1038/s41593-018-0070-z
66
JankowskyJ. L.ZhengH. (2017). Practical considerations for choosing a mouse model of Alzheimer’s disease.Mol. Neurodegener.12:89. 10.1186/s13024-017-0231-7
67
JensenJ. H.HelpernJ. A. (2010). MRI quantification of non-gaussian water diffusion by kurtosis analysis.NMR Biomed.23698–710. 10.1002/nbm.1518
68
JiskootL. C.PanmanJ. L.MeeterL. H.DopperE. G. P.Donker KaatL.FranzenS.et al (2019). Longitudinal multimodal MRI as prognostic and diagnostic biomarker in presymptomatic familial frontotemporal dementia.Brain142193–208. 10.1093/brain/awy288
69
JonesK. M.PollardA. C.PagelM. D. (2018). Clinical applications of chemical exchange saturation transfer (CEST) MRI.J. Magn. Reson. Imaging4711–27. 10.1002/jmri.25838
70
KantarciK.MurrayM. E.SchwarzC. G.ReidR. I.PrzybelskiS. A.LesnickT.et al (2017). White-matter integrity on DTI and the pathologic staging of Alzheimer’s disease.Neurobiol Aging56172–179. 10.1016/j.neurobiolaging.2017.04.024
71
KimE. J.HwangJ. L.GausS. E.NanaA. L.DengJ.BrownJ. A.et al (2020). Evidence of corticofugal tau spreading in patients with frontotemporal dementia.Acta Neuropathol.13927–43. 10.1007/s00401-019-02075-z
72
KimJ.ChoiI. Y.DuffK. E.LeeP. (2017). Progressive pathological changes in neurochemical profile of the hippocampus and early changes in the olfactory bulbs of tau transgenic mice (rTg4510).Neurochem. Res.421649–1660. 10.1007/s11064-017-2298-5
73
KimuraT.YamashitaS.FukudaT.ParkJ.-M.MurayamaM.MizorokiT.et al (2007). Hyperphosphorylated tau in parahippocampal cortex impairs place learning in aged mice expressing wild-type human tau.EMBO J.265143–5152. 10.1038/sj.emboj.7601917
74
KindlerD.MaschioC.NiR.ZerbiV.RazanskyD.KlohsJ. (2021). Arterial spin labeling demonstrates preserved regional cerebral blood flow in the P301L mouse model of tauopathy.J. Cereb. Blood Flow Metab. Online ahead of print 10.1177/0271678X211062274
75
KorenS. A.HammM. J.CloydR.FontaineS. N.ChishtiE.LanzillottaC.et al (2020). Novel therapeutic targets to mitigate early neuronal dysfunction and cognitive deficits in tauopathy.bioRxiv [Priprint]10.1101/2020.07.31.229583
76
LaddM. E.BachertP.MeyerspeerM.MoserE.NagelA. M.NorrisD. G.et al (2018). Pros and cons of ultra-high-field MRI/MRS for human application.Prog. Nucl. Magn. Reson. Spectrosc.1091–50. 10.1016/j.pnmrs.2018.06.001
77
Lasagna-ReevesC. A.Castillo-CarranzaD. L.SenguptaU.ClosA. L.JacksonG. R.KayedR. (2011). Tau oligomers impair memory and induce synaptic and mitochondrial dysfunction in wild-type mice.Mol. Neurodegener.6:39. 10.1186/1750-1326-6-39
78
LaurettiE.LiJ. G.Di MecoA.PraticòD. (2017). Glucose deficit triggers tau pathology and synaptic dysfunction in a tauopathy mouse model.Transl. Psychiatry7:e1020. 10.1038/tp.2016.296
79
Le BihanD.ManginJ. F.PouponC.ClarkC. A.PappataS.MolkoN.et al (2001). Diffusion tensor imaging: concepts and applications.J. Magn. Reson. Imaging13534–546. 10.1002/jmri.1076
80
LeeS. E.KhazenzonA. M.TrujilloA. J.GuoC. C.YokoyamaJ. S.ShaS. J.et al (2014). Altered network connectivity in frontotemporal dementia with C9orf72 hexanucleotide repeat expansion.Brain1373047–3060. 10.1093/brain/awu248
81
LeeS. H.MeilandtW. J.XieL.GandhamV. D.NguH.BarckK. H.et al (2021). Trem2 restrains the enhancement of tau accumulation and neurodegeneration by β-amyloid pathology.Neuron1091283.e1286–1301.e1286. 10.1016/j.neuron.2021.02.010
82
LeeV. M.GoedertM.TrojanowskiJ. Q. (2001). Neurodegenerative tauopathies.Annu. Rev. Neurosci.241121–1159.
83
LewisJ.McGowanE.RockwoodJ.MelroseH.NacharajuP.Van SlegtenhorstM.et al (2000). Neurofibrillary tangles, amyotrophy and progressive motor disturbance in mice expressing mutant (P301L) tau protein.Nat. Genet.25402–405.
84
LopesS.Vaz-SilvaJ.PintoV.DallaC.KokrasN.BedenkB.et al (2016). Tau protein is essential for stress-induced brain pathology.Proc. Natl. Acad. Sci. U.S.A.113:E3755. 10.1073/pnas.1600953113
85
MaD.HolmesH. E.CardosoM. J.ModatM.HarrisonI. F.PowellN. M.et al (2019). Study the longitudinal in vivo and cross-sectional ex vivo brain volume difference for disease progression and treatment effect on mouse model of tauopathy using automated mri structural parcellation.Front. Neurosci.13:11. 10.3389/fnins.2019.00011
86
MajidT.AliY. O.VenkitaramaniD. V.JangM.-K.LuH.-C.PautlerR. G. (2014). In vivo axonal transport deficits in a mouse model of fronto-temporal dementia.NeuroImage4711–717. 10.1016/j.nicl.2014.02.005
87
MalcolmJ. C.BreuillaudL.Do CarmoS.HallH.WelikovitchL. A.MacdonaldJ. A.et al (2019). Neuropathological changes and cognitive deficits in rats transgenic for human mutant tau recapitulate human tauopathy.Neurobiol. Dis.127323–338. 10.1016/j.nbd.2019.03.018
88
MamouneK. E.BarantinL.AdriaensenH.TilletY. (2021). Application of chemical exchange saturation transfer (CEST) in neuroimaging.J. Chem. Neuroanat.114:101944. 10.1016/j.jchemneu.2021.101944
89
MandinoF.CerriD. H.GarinC. M.StraathofM.van TilborgG. A. F.ChakravartyM. M.et al (2020). Animal functional magnetic resonance imaging: trends and path toward standardization.Front. Neuroinform.13:78. 10.3389/fninf.2019.00078
90
MaruyamaM.ShimadaH.SuharaT.ShinotohH.JiB.MaedaJ.et al (2013). Imaging of tau pathology in a tauopathy mouse model and in Alzheimer patients compared to normal controls.Neuron791094–1108. 10.1016/j.neuron.2013.07.037
91
MassalimovaA.NiR.NitschR. M.ReisertM.von ElverfeldtD.KlohsJ. (2021). Diffusion tensor imaging reveals whole-brain microstructural changes in the P301L mouse model of tauopathy.Neurodegener. Dis.20173–184. 10.1159/000515754
92
MeeterL. H.KaatL. D.RohrerJ. D.van SwietenJ. C. (2017). Imaging and fluid biomarkers in frontotemporal dementia.Nat. Rev. Neurol.13406–419. 10.1038/nrneurol.2017.75
93
MiyaokaR. S.LehnertA. (2020). Small animal PET: a review of what we have done and where we are going.Phys. Med. Biol. Online ahead of print 10.1088/1361-6560/ab8f71
94
MoriS.ZhangJ. (2006). Principles of diffusion tensor imaging and its applications to basic neuroscience research.Neuron51527–539. 10.1016/j.neuron.2006.08.012
95
MullardA. (2021). Failure of first anti-tau antibody in Alzheimer disease highlights risks of history repeating.Nat. Rev. Drug. Discov. England203–5. 10.1038/d41573-020-00217-7
96
MusafarganiS.GhoshK. K.MishraS.MahalakshmiP.PadmanabhanP.GulyásB. (2018). PET/MRI: a frontier in era of complementary hybrid imaging.Eur. J. Hybrid Imaging2:12. 10.1186/s41824-018-0030-6
97
MusiN.ValentineJ. M.SickoraK. R.BaeuerleE.ThompsonC. S.ShenQ.et al (2018). Tau protein aggregation is associated with cellular senescence in the brain.Aging Cell17:e12840. 10.1111/acel.12840
98
NahavandiP.NiranjanA.OheneY.HarrisonI. F.IsmailO.MurrayT. K.et al (2017). [IC-P-193]: FMRI of visual stimuli in a tau model of alzheimer’s disease.Alzheimers Dement.13:142.
99
NiR. (2021). Magnetic resonance imaging in animal models of Alzheimer’s disease amyloidosis.Int. J. Mol. Sci.22:12768. 10.3390/ijms222312768
100
NiR.ChenZ.GerezJ. A.ShiG.ZhouQ.RiekR.et al (2020a). Detection of cerebral tauopathy in P301L mice using high-resolution large-field multifocal illumination fluorescence microscopy.Biomed. Opt. Express114989–5002. 10.1364/BOE.395803
101
NiR.ZarbY.KuhnG. A.MüllerR.YundungY.NitschR. M.et al (2020b). SWI and phase imaging reveal intracranial calcifications in the P301L mouse model of human tauopathy.MAGMA33769–781. 10.1007/s10334-020-00855-3
102
NiR.JiB.OnoM.SaharaN.ZhangM. R.AokiI.et al (2018). Comparative in-vitro and in-vivo quantifications of pathological tau deposits and their association with neurodegeneration in tauopathy mouse models.J. Nucl. Med.59960–966. 10.2967/jnumed.117.201632
103
NilsenL. H.RaeC.IttnerL. M.GötzJ.SonnewaldU. (2013). Glutamate metabolism is impaired in transgenic mice with tau hyperphosphorylation.J. Cereb. Blood Flow Metab.33684–691. 10.1038/jcbfm.2012.212
104
NishiokaC.LiangH.-F.BarsamianB.SunS.-W. (2019). Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy model.NeuroImage189180–191. 10.1016/j.neuroimage.2019.01.007
105
NovakP.KovacechB.KatinaS.SchmidtR.ScheltensP.KontsekovaE.et al (2021). ADAMANT: a placebo-controlled randomized phase 2 study of AADvac1, an active immunotherapy against pathological tau in Alzheimer’s disease.Nat. Aging1521–534. 10.1038/s43587-021-00070-2
106
OblakA. L.FornerS.TerritoP. R.SasnerM.CarterG. W.HowellG. R.et al (2020). Model organism development and evaluation for late-onset Alzheimer’s disease: MODEL-AD.Alzheimers Dement.6:e12110.
107
O’CallaghanJ.HolmesH.PowellN.WellsJ. A.IsmailO.HarrisonI. F.et al (2017). Tissue magnetic susceptibility mapping as a marker of tau pathology in Alzheimer’s disease.Neuroimage159334–345. 10.1016/j.neuroimage.2017.08.003
108
OnoM.SaharaN.KumataK.JiB.NiR.KogaS.et al (2017). Distinct binding of PET ligands PBB3 and AV-1451 to tau fibril strains in neurodegenerative tauopathies.Brain140764–780. 10.1093/brain/aww339
109
OzG.AlgerJ. R.BarkerP. B.BarthaR.BizziA.BoeschC.et al (2014). Clinical proton MR spectroscopy in central nervous system disorders.Radiology270658–679. 10.1148/radiol.13130531
110
PaasonenJ.StenroosP.SaloR. A.KiviniemiV.GröhnO. (2018). Functional connectivity under six anesthesia protocols and the awake condition in rat brain.Neuroimage1729–20. 10.1016/j.neuroimage.2018.01.014
111
ParekhP.BadachhapeA.MuQ.BhavaneR.SrivastavaM.DevkotaL.et al (2021). Early detection of tau pathology.bioRxiv [Preprint]10.1101/2021.05.14.444233
112
ParkL.HochrainerK.HattoriY.AhnS. J.AnfrayA.WangG.et al (2020). Tau induces PSD95-neuronal NOS uncoupling and neurovascular dysfunction independent of neurodegeneration.Nat. Neurosci.231079–1089. 10.1038/s41593-020-0686-7
113
PautlerR. G.MongeauR.JacobsR. E. (2003). In vivo trans-synaptic tract tracing from the murine striatum and amygdala utilizing manganese enhanced MRI (MEMRI).Magn. Reson. Med.5033–39. 10.1002/mrm.10498
114
PerezP. D.HallG.KimuraT.RenY.BaileyR. M.LewisJ.et al (2013). In vivo functional brain mapping in a conditional mouse model of human tauopathy (taup301l) reveals reduced neural activity in memory formation structures.Mol. Neurodegener.8:9. 10.1186/1750-1326-8-9
115
PrzybylaM.van EerselJ.van HummelA.van der HovenJ.SabaleM.HarastaA.et al (2020). Onset of hippocampal network aberration and memory deficits in P301S tau mice are associated with an early gene signature.Brain1431889–1904. 10.1093/brain/awaa133
116
RamsdenM.KotilinekL.ForsterC.PaulsonJ.McGowanE.SantaCruzK.et al (2005). Age-dependent neurofibrillary tangle formation, neuron loss, and memory impairment in a mouse model of human tauopathy (P301L).J. Neurosci.2510637–10647. 10.1523/JNEUROSCI.3279-05.2005
117
RobertsM.SevastouI.ImaizumiY.MistryK.TalmaS.DeyM.et al (2020). Pre-clinical characterisation of E2814, a high-affinity antibody targeting the microtubule-binding repeat domain of tau for passive immunotherapy in Alzheimer’s disease.Acta Neuropathol. Commun.8:13. 10.1186/s40478-020-0884-2
118
SaharaN.PerezP. D.LinW.-L.DicksonD. W.RenY.ZengH.et al (2014). Age-related decline in white matter integrity in a mouse model of tauopathy: an in vivo diffusion tensor magnetic resonance imaging study.Neurobiol. Aging351364–1374. 10.1016/j.neurobiolaging.2013.12.009
119
SaitoT.MihiraN.MatsubaY.SasaguriH.HashimotoS.NarasimhanS.et al (2019). Humanization of the entire murine Mapt gene provides a murine model of pathological human tau propagation.J. Biol. Chem.29412754–12765. 10.1074/jbc.RA119.009487
120
SantacruzK.LewisJ.SpiresT.PaulsonJ.KotilinekL.IngelssonM.et al (2005). Tau suppression in a neurodegenerative mouse model improves memory function.Science309476–481. 10.1126/science.1113694
121
SchepkinV. D.BreyW. W.Gor’kovP. L.GrantS. C. (2010). Initial in vivo rodent sodium and proton MR imaging at 21.1 T.Magn. Reson. Imaging28400–407. 10.1016/j.mri.2009.10.002
122
ShimH. J.JungW. B.SchlegelF.LeeJ.KimS.KimS. G. (2018). Mouse fMRI under ketamine and xylazine anesthesia: robust contralateral somatosensory cortex activation in response to forepaw stimulation.Neuroimage17730–44. 10.1016/j.neuroimage.2018.04.062
123
SilvaA. C.BockN. A. (2008). Manganese-enhanced MRI: an exceptional tool in translational neuroimaging.Schizophr. Bull.34595–604. 10.1093/schbul/sbn056
124
SintiniI.SchwarzC. G.MartinP. R.Graff-RadfordJ.MachuldaM. M.SenjemM. L.et al (2019). Regional multimodal relationships between tau, hypometabolism, atrophy, and fractional anisotropy in atypical Alzheimer’s disease.Hum. Brain Mapp.401618–1631. 10.1002/hbm.24473
125
SoniN.MedeirosR.AlateeqK.ToX. V.NasrallahF. A. (2021). Diffusion tensor imaging detects acute pathology-specific changes in the P301L tauopathy mouse model following traumatic brain injury.Front. Neurosci.15:106. 10.3389/fnins.2021.611451
126
SpinelliE. G.GhirelliA.BasaiaS.CividiniC.RivaN.CanuE.et al (2021). Structural MRI signatures in genetic presentations of the frontotemporal dementia/motor neuron disease spectrum.Neurology97e1594–e1607. 10.1212/WNL.0000000000012702
127
StaffaroniA. M.LjubenkovP. A.KornakJ.CobigoY.DattaS.MarxG.et al (2019). Longitudinal multimodal imaging and clinical endpoints for frontotemporal dementia clinical trials.Brain142443–459. 10.1093/brain/awy319
128
SteinerA. R.Rousseau-BlassF.SchroeterA.HartnackS.Bettschart-WolfensbergerR. (2020). Systematic review: anaesthetic protocols and management as confounders in rodent blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI)-part a: effects of changes in physiological parameters.Front. Neurosci.14:577119. 10.3389/fnins.2020.577119
129
SteinerA. R.Rousseau-BlassF.SchroeterA.HartnackS.Bettschart-WolfensbergerR. (2021). Systematic review: anesthetic protocols and management as confounders in rodent blood oxygen level dependent functional magnetic resonance imaging (BOLD fMRI)—part B: effects of anesthetic agents, doses and timing.Animals11:199. 10.3390/ani11010199
130
StenroosP.PaasonenJ.SaloR. A.JokivarsiK.ShatilloA.TanilaH.et al (2018). Awake rat brain functional magnetic resonance imaging using standard radio frequency coils and a 3D printed restraint kit.Front. Neurosci.12:548. 10.3389/fnins.2018.00548
131
StortzG.ThiessenJ. D.BishopD.KhanM. S.KozlowskiP.RetièreF.et al (2018). Performance of a PET insert for high-resolution small-animal PET/MRI at 7 tesla.J. Nucl. Med.59536–542. 10.2967/jnumed.116.187666
132
Sukoff RizzoS. J.MastersA.OnosK. D.QuinneyS.SasnerM.OblakA.et al (2020). Improving preclinical to clinical translation in Alzheimer’s disease research.Alzheimers Dement.6:e12038. 10.1002/trc2.12038
133
TagaiK.OnoM.KubotaM.KitamuraS.TakahataK.SekiC.et al (2020). High-contrast in vivo imaging of tau pathologies in Alzheimer’s and non-Alzheimer’s disease tauopathies.Neuron10942.e8–58.e8. 10.1016/j.neuron.2020.09.042
134
TakeuchiH.ImamuraK.JiB.TsukitaK.EnamiT.TakaoK.et al (2020). Nasal vaccine delivery attenuates brain pathology and cognitive impairment in tauopathy model mice.NPJ Vaccines5:28. 10.1038/s41541-020-0172-y
135
TorsoM.RidgwayG. R.JenkinsonM.ChanceS., and the Frontotemporal Lobar Degeneration Neuroimaging Initiative and the 4-Repeat Tau Neuroimaging Initiative (2021). Intracortical diffusion tensor imaging signature of microstructural changes in frontotemporal lobar degeneration.Alzheimers Res. Ther.13:180. 10.1186/s13195-021-00914-4
136
TsurugizawaT.TamadaK.OnoN.KarakawaS.KodamaY.DebackerC.et al (2020). Awake functional MRI detects neural circuit dysfunction in a mouse model of autism.Sci. Adv.6:eaav4520. 10.1126/sciadv.aav4520
137
Ulugut ErkoyunH.GrootC.HeilbronR.NelissenA.van RossumJ.JuttenR.et al (2020). A clinical-radiological framework of the right temporal variant of frontotemporal dementia.Brain1432831–2843. 10.1093/brain/awaa225
138
VagenknechtP.OnoM.LuzginA.JiB.HiguchiM.NoainD.et al (2021). Non-invasive imaging of tau-targeted probe uptake by whole brain multi-spectral optoacoustic tomography.bioRxiv [Preprint]10.1101/2021.07.10.451626
139
van AlstT. M.WachsmuthL.DatunashviliM.AlbersF.JustN.BuddeT.et al (2019). Anesthesia differentially modulates neuronal and vascular contributions to the BOLD signal.Neuroimage19589–103. 10.1016/j.neuroimage.2019.03.057
140
van ZijlP.KnutssonL. (2019). In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound.J. Magn. Reson.30655–65. 10.1016/j.jmr.2019.07.034
141
van ZijlP. C. M.BrindleK.LuH.BarkerP. B.EddenR.YadavN.et al (2021). Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo.Curr. Opin. Chem. Biol.63209–218. 10.1016/j.cbpa.2021.06.003
142
VerfaillieS. C.AdriaanseS. M.BinnewijzendM. A.BenedictusM. R.OssenkoppeleR.WattjesM. P.et al (2015). Cerebral perfusion and glucose metabolism in Alzheimer’s disease and frontotemporal dementia: two sides of the same coin?Eur. Radiol.253050–3059. 10.1007/s00330-015-3696-1
143
VillemagneV. L.Fodero-TavolettiM. T.MastersC. L.RoweC. C. (2015). Tau imaging: early progress and future directions.Lancet Neurol.14114–124. 10.1016/S1474-4422(14)70252-2
144
VogelJ. W.YoungA. L.OxtobyN. P.SmithR.OssenkoppeleR.StrandbergO. T.et al (2021). Four distinct trajectories of tau deposition identified in Alzheimer’s disease.Nat. Med.27871–881. 10.1038/s41591-021-01309-6
145
WahsnerJ.GaleE. M.Rodríguez-RodríguezA.CaravanP. (2019). Chemistry of MRI contrast agents: current challenges and new frontiers.Chem. Rev.119957–1057. 10.1021/acs.chemrev.8b00363
146
WangX.LiW.MarcusJ.PearsonM.SongL.SmithK.et al (2020). MK-8719, a novel and selective O-GlcNAcase inhibitor that reduces the formation of pathological tau and ameliorates neurodegeneration in a mouse model of tauopathy.J. Pharmacol. Exp. Ther.374252–263. 10.1124/jpet.120.266122
147
WegmannS.BennettR. E.DelormeL.RobbinsA. B.HuM.McKenzieD.et al (2019). Experimental evidence for the age dependence of tau protein spread in the brain.Sci. Adv.5:eaaw6404. 10.1126/sciadv.aaw6404
148
WegmannS.MauryE. A.KirkM. J.SaqranL.RoeA.DeVosS. L.et al (2015). Removing endogenous tau does not prevent tau propagation yet reduces its neurotoxicity.Embo J.343028–3041. 10.15252/embj.201592748
149
WeiZ.XuJ.ChenL.HirschlerL.BarbierE. L.LiT.et al (2021). Brain metabolism in tau and amyloid mouse models of Alzheimer’s disease: an MRI study.NMR Biomed.34:e4568. 10.1002/nbm.4568
150
WellsJ. A.HolmesH. E.O’CallaghanJ. M.ColganN.IsmailO.FisherE. M.et al (2015a). Increased cerebral vascular reactivity in the tau expressing rTg4510 mouse: evidence against the role of tau pathology to impair vascular health in Alzheimer’s disease.J. Cereb. Blood Flow Metab.35359–362. 10.1038/jcbfm.2014.224
151
WellsJ. A.O’CallaghanJ. M.HolmesH. E.PowellN. M.JohnsonR. A.SiowB.et al (2015b). In vivo imaging of tau pathology using multi-parametric quantitative MRI.Neuroimage111369–378. 10.1016/j.neuroimage.2015.02.023
152
WuJ. W.HussainiS. A.BastilleI. M.RodriguezG. A.MrejeruA.RilettK.et al (2016). Neuronal activity enhances tau propagation and tau pathology in vivo.Nat. Neurosci.191085–1092. 10.1038/nn.4328
153
WuQ.LinY.GuJ.SigurdssonE. M. (2018). Dynamic assessment of tau immunotherapies in the brains of live animals by two-photon imaging.EBioMedicine35270–278. 10.1016/j.ebiom.2018.08.041
154
WuT.DejanovicB.GandhamV. D.GogineniA.EdmondsR.SchauerS.et al (2019). Complement C3 is activated in human AD Brain and is required for neurodegeneration in mouse models of amyloidosis and tauopathy.Cell Rep.282111.e2116–2123.e2116. 10.1016/j.celrep.2019.07.060
155
WuT.GrandjeanJ.BosshardS. C.RudinM.ReutensD.JiangT. (2017). Altered regional connectivity reflecting effects of different anaesthesia protocols in the mouse brain.Neuroimage149190–199. 10.1016/j.neuroimage.2017.01.074
156
XieZ.YangD.StephensonD.MortonD.HicksC.BrownT.et al (2010). Characterizing the regional structural difference of the brain between tau transgenic (rTg4510) and wild-type mice using MRI.Med. Image Comput. Comput. Assist. Interv.13308–315. 10.1007/978-3-642-15705-9_38
157
XuX.XuJ.ChanK. W. Y.LiuJ.LiuH.LiY.et al (2019). GlucoCEST imaging with on-resonance variable delay multiple pulse (onVDMP) MRI.Magn. Reson. Med.8147–56. 10.1002/mrm.27364
158
YanagisawaD.IbrahimN. F.TaguchiH.MorikawaS.KatoT.HiraoK.et al (2018). Fluorine-19 magnetic resonance imaging probe for the detection of tau pathology in female rTg4510 mice.J. Neurosci. Res.96841–851. 10.1002/jnr.24188
159
YangD.XieZ.StephensonD.MortonD.HicksC. D.BrownT. M.et al (2011). Volumetric MRI and MRS provide sensitive measures of Alzheimer’s disease neuropathology in inducible Tau transgenic mice (rTg4510).NeuroImage542652–2658. 10.1016/j.neuroimage.2010.10.067
160
YoshiyamaY.HiguchiM.ZhangB.HuangS. M.IwataN.SaidoT. C.et al (2007). Synapse loss and microglial activation precede tangles in a P301S tauopathy mouse model.Neuron53337–351. 10.1016/j.neuron.2007.01.010
161
YoungA. L.BocchettaM.RussellL. L.ConveryR. S.PeakmanG.ToddE.et al (2021). Characterizing the clinical features and atrophy patterns of MAPT-related frontotemporal dementia with disease progression modeling.Neurology97e941–e952. 10.1212/WNL.0000000000012410
162
ZhangY.SchuffN.DuA. T.RosenH. J.KramerJ. H.Gorno-TempiniM. L.et al (2009). White matter damage in frontotemporal dementia and Alzheimer’s disease measured by diffusion MRI.Brain1322579–2592. 10.1093/brain/awp071
163
ZhangZ.ZhangC.YaoJ.ChenX.GaoF.JiangS.et al (2020). Protein-based amide proton transfer-weighted MR imaging of amnestic mild cognitive impairment.NeuroImage25:102153. 10.1016/j.nicl.2019.102153
164
ZhouJ.GreiciusM. D.GennatasE. D.GrowdonM. E.JangJ. Y.RabinoviciG. D.et al (2010). Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease.Brain1331352–1367. 10.1093/brain/awq075
165
ZhouJ.HeoH. Y.KnutssonL.van ZijlP. C. M.JiangS. (2019). APT-weighted MRI: techniques, current neuro applications, and challenging issues.J. Magn. Reson. Imaging50347–364. 10.1002/jmri.26645
166
ZhuH.BarkerP. B. (2011). MR spectroscopy and spectroscopic imaging of the brain.Methods Mol. Biol.711203–226. 10.1007/978-1-61737-992-5_9
Summary
Keywords
magnetic resonance imaging (MRI), tau, animal model, FTD (frontotemporal dementia), Alzheimer’s disease, neurodegenaration
Citation
Ni R (2022) Magnetic Resonance Imaging in Tauopathy Animal Models. Front. Aging Neurosci. 13:791679. doi: 10.3389/fnagi.2021.791679
Received
08 October 2021
Accepted
27 December 2021
Published
25 January 2022
Volume
13 - 2021
Edited by
Rachel Bennett, Massachusetts General Hospital and Harvard Medical School, United States
Reviewed by
Zhiliang Wei, Johns Hopkins University, United States; Ian Francis Harrison, University College London, United Kingdom
Updates
Copyright
© 2022 Ni.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Ruiqing Ni, ni@biomed.ee.ethz.ch
This article was submitted to Alzheimer’s Disease and Related Dementias, a section of the journal Frontiers in Aging Neuroscience
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.