Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a sleep disorder associated with abnormal pontomedullary synuclein protein. iRBD evolves into Parkinson's disease (PD) or another synucleinopathy, e.g., dementia with Lewy bodies (LBD) or multiple system atrophy (MSA), in up to 90% of cases (Schenck et al., 1986, 1996; Boeve et al., 2001; Luk et al., 2012; Boeve, 2013; Bunzeck et al., 2013). Thus, iRBD may provide an opportunity to understand the evolution of neurodegeneration as well as a window in which to intervene with disease altering therapies. It is thought that the α-synuclein pathology in more caudal brainstem regions in iRBD ascends to the substantia nigra (SN) of the midbrain as the disease evolves into PD or other synuclein disorders (Boeve, 2013). Iron, which is present in higher quantities in the substantia nigra and other structures, may also play a role in the loss of dopaminergic neurons through its pro-oxidant effects (Zecca et al., 2008; Kaur et al., 2009). In addition, several studies have demonstrated abnormalities in structural integrity and functional connectivity in patients with iRBD (Hanyu et al., 2012; Ellmore et al., 2013).

Magnetic resonance imaging (MRI) offers several non-invasive contrasts that are useful in evaluating the pathological hallmarks of patients with iRBD, and any MRI findings in iRBD patients can be compared with those in individuals with PD. Previous studies have focused on evaluating structural approaches such as diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) in patients with PD. This has included work that showed changes in DTI fractional anisotropy (FA) (Menke et al., 2009, 2010; Vaillancourt et al., 2009; Peran et al., 2010; Du et al., 2011) and mean diffusivity (MD) (Kamagata et al., 2012) in the substantia nigra of patients with PD. Others have shown that DTI may be useful in differentiating PD from other degenerative parkinsonian disorders and may also have the potential to monitor for disease progression (Prodoehl et al., 2013). Additionally, VBM demonstrated non-dopaminergic brainstem alterations in iRBD (Scherfler et al., 2011). VBM and DTI have also provided insights into non-motor features such as depression (Feldmann et al., 2008; Kostic et al., 2010), smell (Ibarretxe-Bilbao et al., 2010; Rolheiser et al., 2011) and cognitive changes (Ibarretxe-Bilbao et al., 2009; Song et al., 2011) in PD. Therefore, DTI and VBM may prove useful in evaluating iRBD as it evolves into a Parkinsonian condition. So far, it has only been possible to show discriminative properties of the MRI methods using fairly large numbers of patients and controls, and these methods have not yet revealed if they are able to characterize the clinical severity of PD (Gorell et al., 1995; Martin et al., 2008). Therefore, our group previously employed novel microstructural imaging methods to map the SN (Michaeli et al., 2007; Nestrasil et al., 2010), as well as other brainstem and subcortical regions, in PD (Karagulle Kendi et al., 2008; Tuite et al., 2012).

In our current work, we employed several MRI modalities that are sensitive to various brain tissue properties, such as microstructural integrity, iron loads, and functional connectivity. Namely, we utilized novel rotating frame relaxation mapping methods developed in our group including adiabatic T_1ρ (Michaeli et al., 2006), T_2ρ (Michaeli et al., 2004) and RAFF4 (Relaxation Along a Fictitious Field in the rotating frame of rank 4) (Liimatainen et al., 2010, 2011, 2015), together with DTI and resting-state functional MRI (rsfMRI). Our previous studies conducted in PD (Michaeli, 2007; Michaeli et al., 2007; Nestrasil et al., 2010; Tuite et al., 2012) and other brain conditions (Sierra et al., 2008; Jokivarsi et al., 2009; Mangia et al., 2013; Satzer et al., 2015) have shown that the proposed rotating frame methods provide information on different relaxation mechanisms in the human brain. T_2ρ is sensitive to diffusion and exchange of water protons in environments with different local magnetic susceptibilities and reflects iron content with higher sensitivity than conventional T₂ MRI (Michaeli et al., 2005, 2007). T_1ρ provides an indication of neuronal loss and can be used to assess PD nigral degeneration with a higher sensitivity than is possible with conventional T₁-based MRI (Michaeli et al., 2006, 2007). RAFF4 methodology, which is derived from adiabatic T_1ρ and T_2ρ (Liimatainen et al., 2010, 2011, 2015), has high sensitivity to myelin content (Satzer et al., 2015; Hakkarainen et al., 2016), and thus could provide information on microstructural integrity.

Rotating frame relaxations offer a conceptual advantage as compared to free-precession relaxation methods for characterizing tissue properties thanks to their inherent sensitivity to slower motional regimes (Michaeli et al., 2008). Indeed, while water molecules undergo a large variety of motional regimes in tissue, the motions which are most sensitive to the intricate nature of tissue microstructure and composition are those in intermediate-slow regimes. Rotating frame relaxations during frequency swept pulses offer additional practical advantages as compared to continuous-wave T_1ρ, including a minimized sensitivity to B₁ distributions and a capability to simultaneously tune the contrast to multiple effective frequencies (Mangia et al., 2009). Although not common for clinical studies of neurological disorders, rotating frame relaxations with frequency swept pulses were proven as robust and sensitive methods for a variety of in vivo investigations conducted by our group (Michaeli et al., 2007; Sierra et al., 2008; Jokivarsi et al., 2009; Nestrasil et al., 2010; Griffith et al., 2011; Liimatainen et al., 2012; Tuite et al., 2012; Mangia et al., 2013; Satzer et al., 2015; Hakkarainen et al., 2016) and others (Andronesi et al., 2014; Casula et al., 2017; Okuaki et al., 2017).

Our previous applications of mapping adiabatic rotating frame relaxations in humans had been limited to single-slice acquisitions performed on a non-clinical 4 Tesla scanner (Michaeli et al., 2007; Nestrasil et al., 2010; Tuite et al., 2012; Mangia et al., 2013). With the present work, we piloted the extension of these methodologies to multi-slice acquisitions on a clinical 3 Tesla scanner, and we thus embarked on a small cross-sectional study of 10 healthy controls, 9 patients with iRBD, and 10 patients with PD. Rather than focusing on the endpoint of progression to a clinical PD diagnosis for iRBD subjects, the ultimate goal is to use 3 T MRI for characterizing the spectrum of abnormalities resulting from inexorable synuclein deposition and other pathological features in both PD and iRBD. Our study is a step forward for establishing biomarkers which can characterize PD and iRBD, and ultimately the development of parkinsonian syndromes from iRBD subjects.

Individuals enrolled in this study spanned from middle-age to older adults (Table 1). The age of PD and iRBD subjects was 66 years on average for both groups, while the healthy controls were on average 9 years younger (p < 0.02, corrected, for each of PD and iRBD vs. controls); the sex distribution was similar across all 3 groups. Disease duration spanned from 1 month to 4.5 years in the PD subjects, and from 1 to 15 years in the iRBD patients. As expected, PD subjects had significantly higher (worse) UPDRS scores and UPDRS-III scores than iRBD subjects (p = 0.00003 and p = 0.00009, respectively), but their MoCA values were comparable.

The adiabatic relaxation maps were well-registered to the anatomical images, with an average value of quality assessment of 0.21 ± 0.04 (normal range is between 0 and 1.1; 0 represents perfect registration initialization). The range of adiabatic T_1ρ (~130–180 ms), T_2ρ (~55–90 ms) and RAFF4 (~ 240–410 ms) measured at 3 T from the gray matter structures of interest were in good agreement with previous studies conducted at 4 T (Michaeli et al., 2007; Nestrasil et al., 2010; Liimatainen et al., 2015). In addition, rotating frame relaxation maps were highly reproducible among subjects. Indeed, between-subject variations among healthy controls were 3% for adiabatic T_1ρ, T_2ρ, and RAFF4 from the regions of interest. Diffusion parameters were more variable than relaxation parameters, with between-subjects variations of 9 and 4% for FA and MD, respectively. Between-subjects variations were considerably higher for functional connectivity parameters, namely 22 and 35% for network strength and ReHo, respectively.

Rotating frame relaxation parameters tended to be higher in patients than in controls for most of the ROIs (Figure 4, Supplementary Table 1). When age was not used as a covariate, significant Holm-corrected group-differences between PD patients and controls were observed for T_1ρ in the amygdala (p = 0.0001), hippocampus (p = 0.03), pons (p = 0.011), putamen (p = 0.014), substantia nigra compacta (p = 0.018), and thalamus (p = 0.013), while between iRBD and controls T_1ρ differences occurred in the amygdala (p = 0.012), hippocampus (p = 0.038), midbrain (p = 0.016), pons (p = 0.011), and thalamus (p = 0.013). Group differences between PD and controls were also observed for T_2ρ in the amygdala (p = 0.033) and thalamus (p = 0.08), while none of the RAFF4 findings were significant. Holm-corrected group differences between iRBD and controls occurred for T_2ρ and RAFF4 in the midbrain (p = 0.024 and p = 0.005, respectively). On the other hand, diffusion parameters exhibited only one Holm-corrected group difference, namely MD in SNr of iRB vs. controls (p = 0.001). Network strengths were smaller in patients than in controls for most regions. Holm-corrected group differences were significant for the network of the accumbens of both patient groups vs. controls (p < 0.013), and for the networks of the amygdala and SNr of PD vs. controls (p = 0.040 and p = 0.028, respectively). Finally, differences in ReHo were observed only between PD and controls in the SNc (p = 0.021) and SNr (p = 0.007).

Including age as a covariate demonstrated that most of the above mentioned differences were largely accounted for by age (Figure 4, Supplementary Table 1), especially for T_1ρ outcomes. A lengthening of T_1ρ in the amygdala of PD patients as compared to controls was however still robustly detected with Holm-correction after age-adjustment (p = 0.005). PD patients also maintained a significantly longer T_1ρ in the SNc (p = 0.046) as compared to controls. Between iRBD and controls, only trend-level group differences were observed after age-adjustments, namely for T_1ρ in the amygdala (p = 0.075), and for T_2ρ and RAFF4 in the midbrain (p = 0.08 and p = 0.064, respectively). Network strength was still lower in the accumbens of iRBD patients as compared to controls (p = 0.003), but only a trend was observed between PD and controls (p = 0.085). Moreover, age-adjustments and Holm-correction maintained a significantly lower ReHo in the SNr of PD vs. control (p = 0.035), while only trend level differences were reached for the amygdala (p = 0.067).

Finally, after additionally correcting FDR for multiple testing (7 modalities), the longer T_1ρ in the amygdala of PD vs. controls remained significant (p = 0.038), along with the smaller network strength of the accumbens of iRBD vs. controls (p = 0.018).

In the current study we recruited an iRBD group in addition to a mild-moderately affected PD group with the ultimate goal of identifying similarities in MRI signatures of both diseases. Both patient groups were selected to have no diagnosis of dementia, with MoCA scores not less than 25 (Table 1, and Supplementary Figure 1). In addition, while iRBD subjects had findings on their UPDRS-III evaluations (Table 1, and Supplementary Figure 1), they were not thought to meet a clinical diagnosis of PD (Hughes et al., 1992) at enrollment. Motivated by the group-differences previously observed between PD subjects and controls when using adiabatic T_1ρ and T_2ρ (Michaeli et al., 2007; Nestrasil et al., 2010; Tuite et al., 2012), here we piloted a more extended imaging protocol which included T_1ρ and T_2ρ, RAFF4, DTI, and rsfMRI, and performed multi-slice acquisitions from the midbrain to characterize multiple subcortical brain regions rather than single slices of the brainstem as we used previously. Notably, mutli-slice mapping of T_1ρ, T_2ρ, and RAFF4 had never been implemented before, especially on a 3 Tesla clinical scanner. Here we demonstrate that 30-slices relaxation mapping is feasible with 5-min of acquisition time for each of T_1ρ and T_2ρ and 10-min for RAFF4. Thus the total acquisition time is similar to those employed for clinical MRI studies, and therefore such developments represent a critical step toward a future translation of the rotating frame methodologies to clinical trials. A multi-slice approach is needed for the purpose of obtaining more data that may allow an examination of regions involved in both motor and non-motor aspects of disease and that could be potentially useful in developing a prognostic biomarker (to predict whether iRBD patients are likely to develop PD) as well as a PD staging biomarker. With regard to the prognostic biomarker, based on clinical data, e.g., patients with greater cognitive impairment are more likely to have a different course than those without. If MRI methods can demonstrate pathology in sub-cortical regions involved in non-motor function, such as the amygdala or hippocampus, this information could be potentially useful in prognosis.

In principle, other MRI contrasts such as T₁-Magnetization Transfer (MT) signal (so-called neuromelanin-sensitive scan Ogisu et al., 2013) and T₁ relaxometry (Menke et al., 2009) could have been used, as they had been shown to reveal SN degeneration in PD. Such methods had been proven useful for visualizing and estimating the volumes of the SN structures. However, the neuromelanin-sensitive scan (Ogisu et al., 2013) is a qualitative approach based on signal intensity and it thus precludes a quantitative evaluation of SN tissue characteristics. On the other hand, T₁-relaxometry is a quantitative method that allows quantification of tissue relaxation properties. However, the T₁ measured in the SN did not reveal a difference between PD and controls (Menke et al., 2009), consistent with a lower sensitivity of free-precession relaxations to detect tissue degeneration as compared to rotating frame relaxations.

An important finding of the current study is that rotating frame relaxation parameters provided more robust characterizations of brain tissue as compared to DTI metrics, both in terms of observed coefficient of variations and in terms of their sensitivity to detect age-related and disease-related differences. The most prominent observation was that PD and iRBD groups share a lengthening of T_1ρ in a region that is non-motor related and appears abnormal during cognitive impairment and depression, i.e., the amygdala. However, group differences vs. controls were clearly more pronounced in PD patients than in iRBD patients, as they remained robustly significant for PD patients also after age-adjustments and corrections for multiple testing, whereas they reached only trend level in comparisons of iRBD subjects vs. controls. Dysfunction in olfactory, cardiovascular, sleep, sensory and cognitive functions is often present during PD, and even can precede the motor symptoms and the disease onset (for example, see Jellinger, 2015). Therefore, the differences between PD and iRBD vs. controls in non-motor areas detected by rotating frame T_1ρ MRI further support the critical importance of considering non-motor abnormalities in PD and iRBD. The T_1ρ results obtained in the amygdala of PD patients were overall consistent with previous findings of structural amygadalar deterioration in these patients (Bouchard et al., 2008; van Mierlo et al., 2015; Vriend et al., 2016). Since significant differences of amygadalar volumes were not observed in the present study (data not shown), and our PD subjects did not have significant mood or cognitive impairments, one may speculate that T_1ρ MRI may detect subtle tissue changes in the amygadala which occur prior to structural changes and/or symptom manifestations. Interestingly, the lengthening of T_1ρ in the amygdala as well as in SN regions of PD vs. controls, which is suggestive of neuronal degeneration in these areas, was accompanied by a deterioration of local functional connectivity as revealed by regional homogeneity.

Group differences were seen in rotating frame MRI parameters for other regions such as the thalamus, although such differences were largely explained by age. It is, however, still interesting to note that motor dysfunction in PD has been related to the change in activity of thalamic neurons in the motor circuits (Halliday, 2009). The slight lengthening of T_1ρ in the SNc of PD patients as compared to controls is in agreement with previous studies (Michaeli et al., 2007; Nestrasil et al., 2010), although the finding was not robust enough to survive after correcting FDR for multiple testing, most likely due to the limited number of subjects and/or due to lack of on-to-one age matching of PD and controls (although age was taken into account in the statistical analyses). Importantly, adiabatic T_2ρ was shown to pick up the difference in the SN of PD vs. control subjects in our previous studies conducted at 4 T (Michaeli et al., 2007; Nestrasil et al., 2010), but not in the current work. The differences in the outcomes among the current and previous studies could be attributed to the hardware used, i.e., higher magnetic field strength 4 T vs. 3 T (the lower field decreases sensitivity). Also, the multislice acquisition used in the current study may have impacted the efficiency of the contrast preparation module thus “diluting” the contrast as compared to the single slice used for the 4 T study. Importantly, in order to allow extended brain coverage, the spatial resolution used in this study was lower than previously used, thus leading to higher partial volume effects. Moreover, although the manual ROI segmentation of the SN was carefully performed, inaccuracies in placement are possible as there are unclear borders in T₂-weighted images (Bolding et al., 2013). Differences between current and previous studies may also be due to different subject characteristics, with the most notable being a shorter disease duration of the current cohort (on average 2.5 years) as compared to our previous studies (on average 5 years in Michaeli et al., 2007; and 7 years in Nestrasil et al., 2010). Similar arguments apply for the pons, where T_1ρ differences were previously observed (Tuite et al., 2012). In fact, in the present cohort we observed lengthening of T_1ρ in the pons of PD vs. controls only when comparisons were not adjusted for age.

Finally, the long-distance connectivity as measured by network strength was significantly lower for the accumbens of iRBD subjects relative to controls, while such difference was not noted for the PD subjects. On the other hand, rotating frame relaxation and DTI parameters did not show evident abnormalities in the accumbens. Another putative signature of iRBD subjects was a longer RAFF4 and T_2ρ in the midbrain, that could again be related to changes in non-motor features as opposed to motor function in the iRBD group.

In future studies, it would be important to follow the subjects for at least 3 years to identify iRBD patients who remain stable, those who progressed to PD, and those who progressed to LBD. Changes in nigrostriatal circuits are expected mainly in iRBD converted to PD, and to a lessser extent in iRBD converted to LBD. At the same time, it will be critical to fully characterize the iRBD and PD subjects with extensive behavioral and cognitive tests in order to fully understand the implications of the MRI findings. In addition, the lack in the present study of a complete age matching among controls and patients was a nuisance that had to be resolved with the inclusion of age-adjustments in the statistical analyses, and will have to be avoided in future investigations. Yet it allowed appreciating for the first time the interesting property that rotating frame relaxations may be exquisitely sensitive to age, a feature that may even be exploited in investigations that target aging itself. From an acquisition perspective, the rotating frame relaxation protocols also allow great deal of flexibility. Depending on the hypothesis to be tested, for instance if a focus on only hippocampus and amygdala are desired, one may design a specific rotating frame multi-slice acquisition protocol that achieves high spatial resolution with a reduced number of slices, while guaranteeing full coverage of the selected regions of interest. If acquisition time is limited, one may choose to collect only adiabatic T_1ρ and resting-state fMRI, and skip entirely DTI which did not reveal sufficient sensitivity to detect group differences in this pilot investigation. On the other hand, other developments are currently underway to further optimize the acquisition times along with the intrinsic contrasts of the readout scheme. One promising direction is to implement magnetization preparation modules within a 3D readout sequence with virtually zero-echo times sequence, such as SWeep Imaging with Fourier Transformation (SWIFT) (Idiyatullin et al., 2006). Initial steps in this directions of research have already been proven successful in animal studies (Zhang et al., 2016).

Assessment of PD and iRBD subjects through combined microstructural and functional approaches may be a platform for comprehensive analysis of ongoing neurodegeneration. In essence, this approach may allow for staging of degeneration. In the present study, several outcomes showed trend-level differences in multiple regions, indicating the need of larger cohorts in future studies. Therefore, further studies on large cohorts of patients including longitudinal investigations of how iRBD advance to PD are necessary to characterize the ability of MRI metrics to be used as biomarkers of progression of iRBD into PD or other neurodegenerative diseases.

We piloted for the first time the multi-slice mapping of rotating frame adiabatic T_1ρ and T_2ρ and non-adiabatic RAFF4 on a 3 Tesla scanner for human brain studies, which here involved control subjects along with non-demented iRBD and PD subjects. Rotating frame relaxations provided greater sensitivity to detect tissue abnormalities compared to conventional diffusion modalities that are commonly used to characterize tissue microstructure. The most prominent abnormality observed was a lengthening of T_1ρ in the amygdala of PD subjects, indicating neuronal degeneration in a non-motor area. This finding was even more prominent than what was detected by T_1ρ in the substantia nigra, i.e., the area related to the typical motor symptoms of PD. Significantly smaller network strength of the accumbens was also observed for iRBD subjects as compared to controls.

SiM participated in design of the work, acquisition, analysis, interpretation of the data and preparing the manuscript. AS participated in analysis and interpretation of the data, and preparing the manuscript. DM participated in analysis and interpretation of the data, and preparing the manuscript. MN participated in acquisition and analysis of the data, and editing the manuscript. PCB participated in analysis and interpretation of the data, and editing the manuscript. PB participated in analysis and interpretation of the data, and editing the manuscript. EA participated in acquisition of the data, and editing the manuscript. FG participated in analysis and interpretation of the data, and editing the manuscript. LE participated in design of the work, analysis and interpretation of the data, and editing the manuscript. MH participated in design of the work, interpretation of the data, and editing the manuscript. IN participated in analysis and interpretation of the data, and editing the manuscript. PT participated in design of the work, interpretation of the data, and preparing the manuscript. ShM participated in design of the work, acquisition, interpretation of the data and preparing the manuscript.