Amide proton transfer-weighted magnetic resonance imaging of human brain aging at 3 Tesla

Introduction

As the brain ages, a series of biochemical, molecular, functional, and structural changes occur (1). A large number of previous studies have been conducted exploring healthy and pathological aging processes and have revealed domains of functioning that are most susceptible to, for example, cerebral arterial stiffening (2-4), inflammation (5-7), oxidative stress (8), and poor glucoregulation (9). Magnetic resonance imaging (MRI) has been used widely to explore age-related neural changes (10,11). Structural MRI studies, for example, have demonstrated consistent age-related changes (12,13), and functional MRI (fMRI) has discovered alterations in functional connectivity with age (13). Positron emission tomography (PET) research has involved the neurochemical aspects of aging in healthy humans, such as glucose metabolism (14), tau deposition (15,16), and β-amyloid deposition (17).

As a specific type of chemical exchange saturation transfer (CEST) imaging (18,19), amide proton transfer-weighted (APTw) MRI is able to detect cellular endogenous mobile peptides and proteins in a non-invasive manner (20). This promising molecular imaging technique has been applied to several brain diseases since it was first reported in 2003 (21), ranging from cerebral/other tumors (22-25) to other non-oncologic neurological conditions, such as strokes (26-28), Parkinson’s disease (29), and traumatic brain injury (30,31). Remarkably, a recent study demonstrated that the APTw signal intensities in multiple brain regions were significantly higher in mild cognitive impairment patients than in normal controls (32). Nonetheless, whether APTw MRI can be an effective tool for researching normal brain aging is still uncharted territory. This proof-of-concept research attempted to apply APTw MRI to healthy people in a broad age range to explore characteristic changes during the aging of the normal brain. Conventional magnetization transfer (MT) imaging was used as a comparison, which was quantified by the MT ratio (MTR) associated with semi-solid macromolecules in tissue (33).

Methods

Subjects

This study was approved by the local institutional review board. All subjects gave written informed consent before participating in this study. Inclusion criteria for the study were as follows: aged between 25 and 75 years old; normal results of neurological examinations confirmed by an expert neurologist; no history of head trauma, central nervous system infection, or cerebral structural lesions; and no psychiatric diseases or exposure to psychotropic drugs.

MRI protocol

One 3 Tesla MRI scanner (Achieva; Philips Medical Systems, Best, The Netherlands) was used in this study. A multi-offset, single-slice, single-shot turbo spin echo (TSE) with combined APTw and conventional MT imaging, acquisition protocol was applied to the maximum cross-sectional areas of the hippocampus, the pons, the entorhinal cortex, and the thalamus (four slices). The sequence parameters used were: radiofrequency (RF) saturation power =2 µT; saturation duration =800 ms; repetition time =3,000 ms; echo time =11 ms; TSE factor= 54; matrix =105×100 (reconstructed to be 256×256); field of view =230×220 mm²; and slice thickness =6 mm. The 32 offsets were: 0, ±0.25, ±0.5, ±0.75, ±1, ±1.5, ±2 [2], ±2.5 [2], ±3 [2], ±3.25 [2], ±3.5 [6], ±3.75 [2], ±4 [2], ±4.5, ±5, ±6, and +15.6 ppm (the numbers in square brackets display the number of acquisitions, which was 1 if not specified). More offsets were applied near 0 ppm to improve the fitting accuracy of B₀ maps, and more offsets were used around ±3.5 ppm to increase the interpolation accuracy of APTw data for B₀ correction (34). This combined APTw/MT scan required about 12 minutes for each subject (3 min per slice).

Data analysis

The Interactive Data Language (IDL, version 8; Exelis Visual Information Solutions, Inc.) was used to analyze image data. The acquired MT/APT image series for each slice was registered to the saturated image at 3.5 ppm to reduce possible motion artifacts during the scanning, using a rigid-body transformation of three degrees of freedom, as described previously (35). The measured MT spectra (M_sat/M₀, plotted as a function of saturation frequency offset, relative to water, 31 offsets, in which M_sat and M₀ are the signal intensities with and without selective RF irradiation, respectively) were corrected for the B₀ field inhomogeneity effect on a voxel-by-voxel basis (29). Briefly, these MT spectra were fitted through all offsets using the 12th-order polynomial on a voxel-by-voxel basis (36). The fitted curves were interpolated using an offset resolution of 1 Hz. Following this, the corresponding B₀ field inhomogeneity was calculated according to the deviation of the minimum of the fitted curve from 0 ppm. Finally, the original MT spectra were interpolated and centered along the direction of the offset axis to shift their lowest intensities to 0 ppm. The realigned MT spectra were interpolated back to 31 offsets. For the conventional semi-solid MT imaging, we defined: MTR =1− M_sat(+15.6 ppm)/M₀. The APTw images were created by the MTR asymmetry (MTR_asym) at the offsets of ±3.5 ppm (21): MTR_asym(3.5 ppm) = M_sat(−3.5 ppm)/M₀ − M_sat(+3.5 ppm)/M₀.

Based on the structural M_sat(3.5 ppm) and M₀ images that were co-registered with APTw for each subject, two radiologists (Zewen Zhang and Jian Yao, who have had 5 and 28 years of experience in neurological imaging, respectively) reviewed all MR images and manually drew 12 regions of interest (ROIs), in consensus. These 12 ROIs (Figure S1) were as follows: the hippocampus, the white matter in the temporal lobe, and the gray matter in the temporal lobe (the first slice); the pons, the white matter in the occipital lobe, and the gray matter in the occipital lobe (the second slice); the entorhinal cortex, the white matter in the frontal lobe, and the gray matter in the frontal lobe (the third slice); and the thalamus, the putamen, and the caudate nucleus (the fourth slice). For each subject, the mean APTw and MTR values were obtained for each ROI, and data from the left and right hemispheres were combined for further analysis.

Figure S1 An example of the 12 regions of interest (ROIs) for quantitative analyses: (A) the first slice: hippocampus (red); white matter in the temporal lobe (green); and gray matter in the temporal lobe (blue); (B) the second slice: pons (red); white matter in the occipital lobe (green); and gray matter in the occipital lobe (blue); (C) the third slice: entorhinal cortex (red); white matter in the frontal lobe (green); and gray matter in the frontal lobe (blue); and (D) the fourth slice: thalamus (red); putamen (green); and caudate nucleus (blue).

Statistical analysis

All data in this study were analyzed with SPSS 25.0 (International Business Machines Corporation) statistical software. P<0.05 was considered statistically significant. After testing for normality, the independent samples t-test was used to analyze the statistical differences between the mean APTw or MTR values for male and female subjects. A one-way analysis of variance (ANOVA) was applied to assess the statistical differences among the mean APTw or MTR values for five different age groups (37-39). The Benjamini-Hochberg correction, as a practical and powerful approach (40), was used as a post-hoc test, with a false discovery rate of 0.05. Pearson correlation analyses were performed to assess the correlations between APTw, MTR, and age, with additional nonlinear regression analyses adopted for the APTw and MTR signals and age.

Results

Patient demographics

From November 2017 to December 2018, 106 healthy subjects (49 males and 57 females; age range, 25–75 years) who met the inclusion criteria were enrolled for this study and participated in MRI scanning. All subjects were divided into five age groups at ten-year intervals (37-39): young (25–34 years; n=21); mature (35–44 years; n=23); middle-aged (45–54 years; n=23); young-old (55–64 years; n=22); and middle-old (65–75 years; n=17). The descriptive information for these five age groups is provided in Table 1.

Table 1 Gender and age distribution of normal subjects recruited in this study
Full table

Comparison of APTw and MTR images for different ages

Two typical examples of MTR and APTw images from the mature and middle-old groups are shown in Figure 1. Compared to the mature subject (female; 37 y), the middle-old subject (male; 66 y) demonstrated clearly visible, relatively higher MTR and APTw signals in most brain regions.

Figure 1 MTR and APTw images for two examples from the mature (female; 37 y; A) and middle-old (male; 66 y; B) groups. MTR, magnetization transfer ratio; APTw, Amide proton transfer-weighted.

Quantitatively, there were no significant differences between the APTw or MTR values for the male and female groups in all ROIs. Differences in ROI-based mean APTw and MTR values among the five age groups are displayed in Figures 2 and 3, respectively. Among the five age groups, the APTw values were significantly different in 3 of 12 ROIs. Notably, significant APTw changes were observed in three white matter ROIs. In the white matter in the temporal lobe, the APTw values of the young, mature, middle-aged, and young-old groups were significantly lower (P=0.0063, 0.0051, 0.0063, and 0.0234, respectively) than that of the middle-old group. In the white matter in the occipital lobe, the APTw values of the mature, middle-aged, and young-old groups were significantly lower (P=0.0027, 0.0403, and 0.0403, respectively) than that of the middle-old group. Note that the APTw value of the young group was significantly higher (P=0.0403) than that of the mature group. In the white matter in the frontal lobe, the APTw values of the young group were significantly lower than those of the middle-aged, young-old, and middle-old groups (P=0.0099, 0.0211, and 0.0003, respectively), and the APTw values of the mature group were also significantly lower than those of the middle-aged and middle-old groups (P=0.0366 and 0.0011, respectively). As a comparison, the MTR values had significant differences in 2 of 12 ROIs. Namely, the MTR values in the pons were significantly lower (P=0.0018) in the young group than in the middle-old group, whereas the MTR values in the entorhinal cortex were significantly higher (P=0.0119) in the mature group than in the young-old group.

Figure 2 APTw values among the five different age groups were analyzed using the one-way analysis of variance (ANOVA), with the Benjamini-Hochberg correction for multiple testing. *, P<0.05, **, P<0.01, ***, P<0.001. Y, young; M, mature; MA, middle-aged; YO, young-old; MO, middle-old. APTw, Amide proton transfer-weighted.

Figure 3 MTR values among the five different age groups were analyzed using the one-way analysis of variance (ANOVA), with the Benjamini-Hochberg correction for multiple testing. *, P<0.05, **, P<0.01. Y, young; M, mature; MA, middle-aged; YO, young-old; MO, middle-old. MTR, magnetization transfer ratio.

Correlation analyses

As shown in Figure 4 and Table 2, there were significant positive correlations between the APTw and MTR values in 10 of 12 ROIs analyzed: the hippocampus (r=0.4016, P<0.0001); the white matter in the temporal lobe (r=0.7269, P<0.0001); the pons (r=0.4062, P<0.0001); the white matter in the occipital lobe (r=0.6496, P<0.0001); the gray matter in the occipital lobe (r=0.4690, P<0.0001); the white matter in the frontal lobe (r=0.4638, P<0.0001); the gray matter in the frontal lobe (r=0.2214, P=0.0226); the thalamus (r=0.5907, P<0.0001); the putamen (r=0.4110, P<0.0001); and the caudate nucleus (r=0.4821, P<0.0001). However, the APTw values indicated a significant negative correlation with the MTR values in the entorhinal cortex (r=−0.2141, P=0.0275).

Figure 4 The Pearson correlation analysis between APTw and MTR signals in the 12 regions of interest (ROIs). MTR, magnetization transfer ratio; APTw, amide proton transfer-weighted.

Table 2 The Pearson correlation analysis results between APTw and MTR signals in the 12 regions of interest (ROIs)
Full table

Figures 5 and 6 and Table 3 summarize the correlation analysis results of the APTw and MTR signals with age. The APTw signal intensity values showed significant positive correlations with age in 4 of 12 ROIs: the white matter in the temporal lobe (r=0.2628, P=0.0065); the white matter in the frontal lobe (r=0.4182, P<0.0001); the gray matter in the frontal lobe (r=0.2065, P=0.0337); and the caudate nucleus (r=0.2295, P=0.0180). In addition, the APTw values indicated a statistically insignificant increasing trend with age (r>0, P>0.05) in five ROIs (the gray matter in the temporal lobe, the white matter in the occipital lobe, the entorhinal cortex, the thalamus, and the putamen). Nevertheless, the MTR signal intensity values of the pons (r=0.2856, P=0.0030), the white matter in the occipital lobe (r=0.1972, P=0.0427), and the gray matter in the occipital lobe (r=0.1964, P=0.0436) showed significant positive correlations with age, while the MTR values of the entorhinal cortex (r=−0.1942, P=0.0461) displayed significant negative correlations with age.

Figure 5 The Pearson correlation analysis of APTw signal with age in the 12 regions of interest (ROIs). APTw, Amide proton transfer-weighted.

Figure 6 The Pearson correlation analysis of MTR signal with age in the 12 regions of interest (ROIs). MTR, magnetization transfer ratio.

Table 3 The Pearson correlation analysis results of APTw and MTR signals with age in the 12 regions of interest (ROIs)
Full table

As shown in Table 4 and Figures S2,S3, the data of all 12 ROIs had relatively poor goodness of fit (R²<0.2) to the second-order polynomial model. However, it can be seen that the B₂ coefficients of the APTw/age data-fitting were opposite of those of the MTR/age data-fitting in 8 of 12 ROIs.

Table 4 The non-linear regression analysis of APTw and MTR values (Y) versus age (X) using the model Y = B₂X² + B₁X + B₀ in the 12 regions of interest (ROIs)
Full table

Figure S2 The non-linear regression analysis of APTw value versus age in the 12 regions of interest (ROIs). APTw, Amide proton transfer-weighted.

Figure S3 The non-linear regression analysis of MTR value versus age in the 12 regions of interest (ROIs). MTR, magnetization transfer ratio.

Discussion

This study demonstrated the feasibility and value of using the APTw MRI signal as a new imaging biomarker for exploring normal aging. Overall, the mean APTw values in the older group were higher than those in the younger group. The ANOVA analyses showed significant differences among the five age groups in the three white matter regions. The Pearson correlation analyses showed positive correlations with age in most brain regions analyzed (4 of 12 ROIs with significant positive correlations and 5 with increasing trends). As a comparison, the mean MTR values did not appear to be significantly different among the five age groups, but they indicated positive correlations with age in 6 of 12 ROIs (3 with significant positive correlations and 3 with increasing trends). In addition, the mean APTw and MTR values revealed significant correlations in 11 of 12 ROIs (10 with significant positive correlations and 1 with a significant negative correlation).

APT imaging quantified by MTR_asym(3.5 ppm) is sensitive to mobile proteins in tissues, for instance, proteins in the cytoplasm (41), and conventional MT imaging quantified by MTR can detect semi-solid macromolecules that exist in the relatively solid environment of cells, such as proteins in the cell membrane and nucleus (33). Theoretically, the APTw and MTR values are associated with the concentrations of mobile proteins and semi-solid macromolecules, respectively, in addition to some other factors (20). Misfolded protein aggregation is a typical feature of brain aging (42,43). In aging brains, the most commonly altered proteins are β-amyloid, hyperphosphorylated forms of microtubule-associated tau, α-synuclein, and transactive response DNA binding protein 43 (TDP43). Specifically, β-amyloid and tau may cause Alzheimer’s disease, α-synuclein may lead to Parkinson’s disease and dementia with Lewy bodies, and TDP43 may result in amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP (44-47). Previous postmortem studies have also demonstrated that these altered proteins can accumulate in the brains of cognitively healthy old people (48-52). Therefore, the concentration of semi-solid macromolecules and mobile proteins in brain tissues may increase relatively with age, which is consistent with the previous report (53). Notably, as the area affected earliest by pathological proteins (54), the entorhinal cortex should have an increasing MTR value in the aging brain. However, our result seemed to be the opposite. The significant negative correlation between entorhinal cortex MTR and age may be attributable to the death of entorhinal cortex neurons and degeneration (55).

Interestingly, the APTw signals in the temporal lobe, the occipital lobe, and the frontal lobe were higher in the gray matter than in the white matter (56) (Figure 2), a trend that was opposite to the MTR signals (Figure 3). The reason for this may be attributable to the fact that grey matter contains numerous cell bodies and relatively few myelinated axons, whereas white matter involves relatively few cell bodies and mainly comprises long-range myelinated axons (57). The myelinated axons have a large amount of semi-solid lipids (cholesterol, phospholipids, and glycolipids) and structural proteins, while the cell bodies of neurons are rich in mobile cytoplasmic proteins (58,59). Moreover, the APTw/age data-fitting parabolas opened upward in most cerebral regions (9 of 12 ROIs), in contrast to the MTR/age data-fitting parabolas. This may imply that the mobile protein content in aging brains decreased in these cerebral regions during the young stage [as observed during pediatric brain development (60)] and then increased gradually, contrary to the trend of the semi-solid macromolecular content change. The exact molecular mechanism behind this needs to be explored in a future study.

This study had several limitations. Firstly, four cerebral slices were acquired by a single-slice protocol, and so the MRI signals of other brain regions were unexplored in this study. In the future, we intend to expand the coverage of APTw MRI to the whole brain by using a three-dimensional (3D) APT imaging acquisition protocol that has been reported previously (61). Secondly, ROI placement was manually implemented due to the limited slice, which was difficult for the cortical gray matter. An automatic segmentation based on 3D APT imaging acquisition may improve the ROI accuracy in the future. Finally, the upfield nuclear Overhauser enhancement signal, from semi-solid and mobile protons and some other possible effects, might have contaminated the APTw signal quantified by MTR_asym(3.5 ppm) in this study (20). Several modified APTw imaging acquisition or analysis methods may be applied to quantify pure APT effects in a future study (62-68). Notably, it has been demonstrated that the APT effect is dominant in APTw imaging, and the possible impact of the water T₁ on APTw imaging was actually slight for the pulse sequence parameters applied here (65,66).

In conclusion, this exploratory study evaluated normal brain aging by APTw imaging for the first time. Our early results have indicated that there is great potential for APTw MRI to provide important complementary information with which to assess normal brain aging at the protein level, in a non-invasive manner. Further research about normal brain aging with the combined APTw and MTR imaging biomarkers may assist in the early detection of aging-related neurodegenerative disorders and in monitoring the clinical therapeutic effects.

Acknowledgments

The authors thank Ms. Mary McAllister for editorial assistance.

Funding: None.

Footnote

Conflicts of Interest: The authors have no conflicts of interest to declare.

Ethical Statement: This study was approved by the local institutional review board. All subjects gave written informed consent before participating in this study.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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