Age- and memory- related differences in hippocampal gray matter integrity are better captured by NODDI compared to single-tensor diffusion imaging

Highlights

• Multi-compartment diffusion imaging (NODDI) outperforms single tensor (DTI) approaches to capture age in hippocampal gray matter.

• Single tensor (DTI) measures of integrity (FA, MD) in gray matter are contaminated by free diffusion.

• Controlling for free diffusion or free water estimates using NODDI reduces age group differences in FA and MD.

• NODDI may be better suited to model hippocampal gray matter microstructure as it relates to age and episodic memory performance.

Abstract

Single-tensor diffusion imaging (DTI) has traditionally been used to assess integrity of white matter. For example, we previously showed that integrity of limbic white matter tracts declines in healthy aging and relates to episodic memory performance. However, multi-compartment diffusion models may be more informative about microstructural properties of gray matter. The current study examined hippocampal gray matter integrity using both single-tensor and multi-compartment (neurite orientation dispersion and density imaging, NODDI) diffusion imaging. Younger (20–38 years) and older (59–84 years) adults also completed the Mnemonic Similarity Task to measure mnemonic discrimination performance. Results revealed age-related declines in both single-tensor (lower fractional anisotropy, higher mean diffusivity) and multi-compartment (higher restricted, hindered and free diffusion) measures of hippocampal gray matter integrity. As expected, NODDI measures (hindered and free diffusion) captured more age-related variance than DTI measures. Moreover, mnemonic discrimination of highly similar lure items in memory was related to hippocampal gray matter integrity in younger but not older adults. These findings support the notion that age-related differences in gray matter integrity are better captured by multi-compartment versus single-tensor diffusion models and show that the relationship between mnemonic discrimination and hippocampal gray matter integrity is moderated by age.

Introduction

The hippocampus, which is critical for episodic memory, is known to be affected in healthy aging (Lister and Barnes, 2009; Scahill et al., 2003), even in absence of dementia (Park and Reuter-Lorenz, 2009). Structural neuroimaging studies, for example, have shown age-related declines in hippocampal macrostructure, with decreased volume seen in whole hippocampus in older adults relative to younger adults (Doxey and Kirwan, 2015; Raz et al., 2005). In the last decade, diffusion imaging has allowed for in vivo examinations of neural microstructure, with numerous studies reporting age-related differences in the integrity of white matter (de Lange et al., 2016; Gunning-Dixon et al., 2009; Madden et al., 2012), including white matter tracts projecting to and from the hippocampus (e.g., fornix, cingulum; Bennett et al., 2015; Bennett and Stark, 2016). However, few studies have assessed whether diffusion imaging may also be a promising tool for evaluating microstructural properties of hippocampal gray matter in aging, especially as it relates to episodic memory performance.

Diffusion imaging data is traditionally modeled as a single tensor per voxel that summarizes the rate of molecular water diffusion along three axes (diffusion tensor imaging, DTI; Beaulieu, 2002; Hassan et al., 2014). This single-tensor DTI approach yields metrics, such as the degree of restricted diffusion (fractional anisotropy, FA) and average rate of diffusion (mean diffusivity, MD), from which the integrity of underlying tissue can be inferred. In white matter, for example, higher FA and lower MD would be seen in regions with highly aligned, densely packed, and tightly myelinated axonal fibers. Across the lifespan, decreases in FA and increases in MD (Bennett et al., 2015; Gunning-Dixon et al., 2009; Madden et al., 2012) are interpreted as declines in white matter integrity (e.g., age-related demyelination). In gray matter, however, the underlying tissue is relatively less organized (e.g., dendrites, cell bodies, glia), resulting in lower FA and higher MD than white matter. Owing to this microstructural complexity, the single-tensor approach alone may not be suited for accurately modeling diffusion in gray matter.

A potentially more accurate way to assess microstructural properties of gray matter is with multi-compartment diffusion approaches that separately model different sources (compartments or volume fractions) of the total diffusion signal (Fukutomi et al., 2018; Kaden et al., 2016; Rae et al., 2017). Neurite Orientation Dispersion and Density Imaging (NODDI; Zhang et al., 2012), for example, models restricted diffusion (also known as neurite density index; NDI) as a set of sticks, hindered diffusion (also known as orientation dispersion index; ODI) as the dispersion of the sticks, and unrestricted diffusion (also known as isotropic fraction; fISO) as an isotropic sphere (Fukutomi et al., 2018; Rae et al., 2017; Zhang et al., 2012). Differences in these metrics may result from microstructural properties that affect intracellular, extracellular, and free sources of diffusion (e.g., age-related increases in cell swelling, loss of spines or synaptic remodeling, and vascular permeability; Clarke et al., 2018; Dickstein et al., 2013, Szebenyi et al., 2005; Elahy et al., 2015, respectively). An additional advantage of this multi-compartment approach is that the free diffusion metric can be used to account for free diffusion contamination in remaining integrity metrics, which is prevalent in the aging brain (Chad et al., 2018; Metzler-Baddeley, O'Sullivan, Bells, Pasternak and Jones, 2012; Rathi et al., 2014).

Multiple diffusion imaging studies have examined the effect of aging on gray matter integrity using either single-tensor (Bhagat and Beaulieu, 2004; Càmara et al., 2007; Carlesimo et al., 2010; Cherubini et al., 2009; Den Heijer et al., 2012; Pereira et al., 2014; Pfefferbaum et al., 2010; Rathi et al., 2014; Salminen et al., 2016; Sasson et al., 2012) or multi-compartment (Fukutomi et al., 2018; Kaden et al., 2016; Nazeri et al., 2017) approaches, but only a handful have assessed aging of hippocampal gray matter integrity. Using the single-tensor approach, studies have reported age-related increases in hippocampal MD (Carlesimo et al., 2010; Pereira et al., 2014), no change (Cherubini et al., 2009) or mixed results depending on the region profiled (Pfefferbaum et al., 2010; Salminen et al., 2016). After excluding free diffusion (e.g., using cerebrospinal fluid [CSF]-suppression diffusion imaging or region of interest [ROI] based segmentation), DTI studies have found both age-related increases in hippocampal FA (Rathi et al., 2014) and age-related decrease in anterior hippocampal relative anisotropy (Càmara et al., 2007). Using the NODDI multi-compartment approach, at least one study demonstrated that hindered diffusion within bilateral hippocampus increased with age in adults across a lifespan sample (age 21–84; Nazeri et al., 2015). However, because none of these studies directly compared single-tensor and multi-compartment models, it remains unknown whether these age differences in DTI and NODDI metrics are capturing similar microstructural mechanisms within hippocampus.

The functional relevance of hippocampal gray matter integrity in non-demented older adults also remains understudied. Previous single-tensor DTI studies have reported that hippocampal MD was associated with impaired episodic memory assessed by a list learning (Den Heijer et al., 2012) and visuospatial task (Carlesimo et al., 2010). An important component of successful episodic memory is mnemonic discrimination, the ability to discriminate between highly similar events in memory. Using a modified recognition task, the Mnemonic Similarity Task (MST; Stark et al., 2013; Kirwan and Stark, 2007), our group has previously shown that mnemonic discrimination declines in healthy aging (Stark, Yassa, Lacy and Stark, 2013) and that worse discrimination performance is related to lower integrity of white matter tracts projecting to (perforant path; Bennett and Stark, 2016; Yassa et al., 2010) and emanating from (fornix; Bennett et al., 2015) the hippocampus in adults across the lifespan. However, these effects have not been assessed for hippocampal gray matter integrity using either single-tensor or multi-compartment diffusion metrics.

Building on this work, the current study examined hippocampal gray matter integrity using both single-tensor (DTI) and multi-compartment (NODDI) diffusion modeling of the same diffusion data in younger and older adults (20–38 and 59–84 years, respectively) who also completed the MST. Our primary aim was to assess age-related differences in hippocampal gray matter integrity and in particular whether the multi-compartment diffusion approach was more sensitive to hippocampal aging than the single-tensor approach. To assess whether free diffusion influences traditional integrity metrics (e.g., from partial volume effects with adjacent CSF), the effect of age on single-tensor integrity measures were examined before (unthresholded DTI) and after (thresholded DTI) accounting for the NODDI free diffusion compartment. Our secondary aim was to determine whether hippocampal gray matter integrity relates to mnemonic discrimination performance.