4761

Quantitative anisotropy-based fiber tractography reveals tracts moderating age-related decline in functional fitness

Paul B Camacho^1,2,3,4, Nishant Bhamidipati^1,5, Emily Erlenbach⁶, Veronica Garcia⁶, Edward McAuley^1,6, Nicholas Burd⁶, Jessica Damoiseaux^7,8, Brad P Sutton^1,2,5, and Neha P Gothe^1,6
¹Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ²Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ³Interdisciplinary Health Sciences Institute, University of Illinois at Urbana Champaign, Urbana, IL, United States, ⁴Carle-Illinois Advanced Imaging Center, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁵Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁶Kinesiology & Community Health, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁷Institute of Gerontology, Wayne State University, Detroit, MI, United States, ⁸Psychology, Wayne State University, Detroit, MI, United States

Synopsis

We present a moderation analysis of the effects of edge strengths from generalized q-sampling imaging-based tractography on the relationship between age and decline in functional fitness in older adults (n = 105, ages 55-79 years old, right-handed). The results of these moderation analyses suggest that the strengths of white matter structural connections involving the cerebellum, cingulum, and other areas involved in motor, sensory, and environmental perception may play a significant role in preserving functional fitness in older adults.

Introduction

White matter integrity in the brain is believed to decrease as damage to myelin sheaths accumulates with age in older adults ^1–3. These alterations of white matter microstructure have been correlated with motor function decline ^{4, 5}. Previous studies have explored these changes using traditional methods of analysis for magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI), showing age-related differences in metrics obtained from diffusion tensor imaging (DTI) and DTI-based structural connectivity ^{3, 6-8}. These methods are notably limited by modeling based on a unimodal gaussian distribution within each tensor ⁹. Generalized q-sampling imaging (GQI) ^{10, 11} processing has shown better resolution of the crossing-fibers problem ¹² and more conservative estimates for tractography, resulting in less false-positive tracts than DTI-based methods ^{10, 11}. We present a moderation analysis of the effects of GQI-based tract strengths on the relationship between age and functional fitness ^10–12.

Methods

This cross-sectional data is part of an ongoing larger longitudinal study at the Exercise Psychology Laboratory of the University of Illinois at Urbana-Champaign for which all methods were approved by the local independent review board and participants were recruited (see Table 1). As part of baseline testing, participants completed a timed upward and downward stair climbing tests as a measure of fitness and functional mobility ¹³. MRI data (see Table 2) was collected using a Siemens 3T Prisma system (Siemens Healthineers AG, Erlangen, Germany) at the Biomedical Imaging Center of the Beckman Institute for Advanced Science & Technology.

Preprocessing and diffusion reconstruction were performed using QSIPrep 0.14.3, which is based on Nipype1.6.1 ^{14, 15}, Nilearn0.8.1 ¹⁶, and Dipy ¹⁷. Anatomical preprocessing followed the standard FAST QSIPrep workflow (see full details at https://qsiprep.readthedocs.io/en/latest/preprocessing.html#preprocessing-pipeline-details) ^18–20. Diffusion preprocessing included MP-PCA denoising ²¹ with a 5-voxel window, B1 field inhomogeneity correction with the N4 algorithm ¹⁸, and DWI series mean intensity adjustment to match the mean intensity of the b=0 images matched across each separate DWI scanning sequence, head motion and Eddy current correction with FSL v6.0.3:b862cdd5 Eddy ^{22, 23}, fieldmap-based susceptibility distortion correction similar to that described in TOPUP ²⁴, and final interpolation using the jac method. The DWI time-series were resampled to ACPC, generating a preprocessed DWI run in ACPC space with 2mm isotropic voxel size.

Tractography was performed using diffusion orientation distribution functions (ODFs) reconstructed via generalized q-sampling imaging (GQI, ¹⁰) with a ratio of mean diffusion distance of 1.250.

The relationship between age and time to complete the upwards or downwards stair climbing tests was determined using Pearson’s r correlation in SciPy ²⁵. Using the PROCESS module model 1 ²⁶, moderation analyses were performed for effect of the strength of GQI-derived normalized fiber count for connections between regions defined by the AAL116 atlas ²⁷ on the relationship between age and time to complete the upwards and downwards stair walking test (see Figure 1 for a visualization of the model). Moderation effects were rejected if the p−value was greater than 0.0005 for the age-connection strength interaction term of the model; further restricting for multiple comparisons by considering only connections for which the size of age effect on test time had magnitude greater than 0.2 (small) and significant difference between levels.

Results

For the n = 105 participants (age: µ +/- σ = 64+/-6, 77 female), only the time to walking down a flight of stairs showed significant correlation with age (r = -0.5999, p-value = 1.3531E-11). Significant moderation on the effect of age on time to climb down a set of stairs was found for the strengths of 17 edges involving the cerebellum, 39 ipsilateral left edges, 46 ipsilateral right edges, and 8 contralateral edges (see Table 3 and Figure 2).

Discussion

The high number of connections within and to the cerebellum for which the normalized fiber count showed a significantly moderated the effect of age on time to climb down a flight of stairs suggest a significant role of the cerebellum in coordination ²⁹ for functional fitness. Similarly, connectivity within the cingulum and to other regions may be particularly important in moderating the relationship between age and coordination-demanding downward stair climbing due to the importance of the cingulum in visuospatial cognition ³⁰ and executive control ³¹.

Significant moderating edges also included areas associated with visual function (calcarine fissure ^{31, 32}, cuneus ³², middle temporal gyrus ³³), environmental perception and spatial awareness (precuneus ³², inferior temporal gyrus ^{34, 35}, angular gyrus ³⁶), motor control (putamen ^{37, 38}, pallidum ³⁹, thalamus ⁴⁰), and sensory and motor areas (insula ⁴¹, orbital superior frontal gyrus ^{32, 42, 43}, middle frontal gyrus ³², superior parietal gyrus ⁴⁴).

Tractography based on the model-free quantitative anisotropy peak estimates produced by GQI-based reconstruction may have produced less false positive tracts ¹¹ and better tracking in crossing fiber regions ¹². This difference in density may account for some connections being detected only in a subset of participants, which limited the number of degrees of freedom for moderation analyses.

Conclusion

The results of these moderation analyses suggest that the strengths of white matter structural connections involving the cerebellum, cingulum, and other areas involved in motor, sensory, and environmental perception play a significant role in preserving functional fitness in older adults.

Acknowledgements

The data used in this comparison was collected as part of a multi-arm clinical trial (Yoga, Aerobic and Stretching Exercise Effects on Neurocognition -NCT04323163) funded by the National Institute of Aging (NIA Grant AG066630) and led by principal investigator Neha P Gothe. We extend our gratitude to the NIA, members of the research staff, and all participants in the study.

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Figures

Figure 1: Example of PROCESS Model 1. Age is independent variable X, connection strength as measured by normalized fiber count between two regions is the moderator M, and time to complete the stair climbing test is the outcome Y. In PROCESS Model 1, the moderator changes the strength and/or positive or negative nature of the relationship between X and Y.

Table 1: Inclusion Criteria at Time of Study Enrollment.

Table 2: MRI Sequence Parameters. Five b-value = 0 s/mm² images and 64 gradient directions at b-value = 1500 s/mm² and b-value = 3000 s/mm² were included in the DWI sampling scheme with the Center for Magnetic Resonance Research multiband sequence, accompanied by phase encode direction flipped field maps. MPRAGE = magnetization prepared rapid gradient echo, TR = Relaxation Time, TE = Echo Time, TI = Inversion Time, DWI = Diffusion-Weighted Imaging, MBF = Multi-band acceleration factor.

Table 3: Numerical summaries for structural connection strength moderation of relationship between participant age and time to descend a set of 12 stairs. For each moderating edge, age effect sizes and their p-values are listed for three levels of connection strength: $$$ Level 1 = μ - σ $$$, $$$ Level 2 = µ $$$, $$$ Level 3 = µ + σ $$$. All but one (Age * Frontal Sup Orb R to Frontal Mid R) interaction terms survived Benjamini-Hochberg correction for multiple comparisons⁴⁵ (one for each unique edge in the AAL116 connectome) with a false discovery ratio of 0.05.

Figure 2: Visual comparison of participant age effect size at three levels of moderating structural connection strengths. For each moderating edge, age effect sizes maps are shown for three levels of connection strength (from left to right): $$$ Level 1 = μ - σ $$$, $$$ Level 2 = µ $$$, $$$ Level 3 = µ + σ $$$. Regions are labeled based on AAL116 atlas parcellation. For ease of heat value interpretation, edge colors are based on $$$ -1 * effect size $$$ as indicated by the color bar to the right of each circle plot.

Proc. Intl. Soc. Mag. Reson. Med. 30 (2022)

4761

DOI: https://doi.org/10.58530/2022/4761