Grey matter changes on brain MRI in subjective cognitive decline: a systematic review

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease and the leading cause of dementia, accounting for an estimated 50–70% of cases [1]. AD is an age-related condition and its global worldwide prevalence is expected to be much greater with increasing in the ageing population, reaching 106.8 million people in 2050 [2]. The global annual economic cost of dementia supposes an amount of one billion US dollars and it will increase up to 2 billion in 2030 [3]. It is estimated that a 1-year delay on disease onset would reduce the number of cases in 12 million by 2050, being an early and precise diagnostic, an essential tool for it [2].

Nowadays, we know that the natural history of AD is divided into three phases: the preclinical phase, where the pathogenic mechanisms of the disease have started but no objective cognitive decline can be diagnosed; the prodromal phase, where mild objective cognitive symptoms can be identified, but they are not severe enough to meet dementia criteria; and the dementia phase, where cognitive decline interferes with daily activities [4]. Some subjects in the preclinical phase of AD declare mild cognitive symptoms with no clinical evidence of cognitive impairment as compared with age-, sex- and education-matched subjects. This clinical construct has historically received many names such as subjective cognitive impairment, subjective memory impairment or decline or memory complaints, although it is currently referred to as subjective cognitive decline (SCD) [5, 6].

SCD prevalence is noticeably high (25–50%) in the population over 65 years old, albeit not all causes are AD-related. In fact, the aetiology of SCD is heterogeneous and can also be related to normal ageing and psychiatric or non-degenerative neurological disorders such as depression, cerebrovascular diseases or concussions [5]. To decrease this heterogeneity, Jessen et al. proposed to exclude from this concept those subjects whose cognitive complaints could be accounted for by other disorders (psychiatric, neurological or systemic), drugs or their abuse [5].

Research in this field has been focused on tracking biomarkers that could define the preclinical AD phase in this population, characterising risk groups to start potential treatments that could delay disease progression [7, 8]. The most frequently used techniques are cerebrospinal fluid analysis and different neuroimaging modalities such as magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (PET), amyloid PET or Tau PET.

The morphometric analysis of MRI images of the brain has become a widely used approach to investigate changes in brain structure in neurodegenerative disorders. Typically, changes in the grey matter have been assessed using T1-weighted images and the most frequently used methods to analyse them include the volumetric comparison of (manually, semi-automatically or automatically) delineated regions of interest (ROIs), whole-brain voxel-based comparison of grey matter (called voxel-based morphometry or VBM) and cortical surface-based comparison of cortical thickness. These methods of neuroimaging analyses have their own strengths and limitations and frequently show different results even with identical image sets [9, 10].

On the other hand, studies that evaluate changes in brain structure in subjects with SCD compared to control participants have shown heterogeneous results, in terms of areas affected and statistical significance, even in the AD-related structures such as the hippocampus [11‐13]. The aim of this systematic review is to give an overview of studies examining the differences in the grey matter volume of the brain between individuals with a clinical diagnosis of SCD and cognitive unimpaired persons detected by MRI.

This systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [14].

The main goal of this systematic review was to investigate whether individuals with SCD present volumetric or grey matter changes when compared with cognitively normal subjects. The main finding is that, among the reviewed studies, there is not a homogeneous and consistent structural change found in SCD compared with HC. The studies that found significant differences (disregarding the analysis method used) did so in the medial temporal lobe, a region implicated in AD [68, 69]. However, the results we have observed are heterogeneous in the different imaging analysis methods included in this review.

Analysing VBM results from 15 studies, half of them (n = 8) found significant results between groups, and the other half (n = 7) did not. In those studies that found structural atrophy in SCD compared with HC, the hippocampus was the most affected area. Interestingly, the right hippocampus was found to be smaller more often than the left one, being the right hippocampus affected every time that hippocampal volume was decreased in SCD. This hippocampal asymmetry was analysed for mild cognitive impairment (MCI) and AD groups in a meta-analysis [70]. In contrast with our study, this meta-analysis found a left-less-than-right atrophy pattern and a poorer performance in episodic memory tests in subjects with less left than right hippocampal volume. Fewer studies found affected areas that are also part of the temporal lobe (the amygdala, the insula and the temporal gyrus). Interestingly, up to 5 studies observe decreased volume in different regions of the frontal lobe in participants with SCD. This structure is not typically affected in the early stages of AD and possibly represents the heterogeneous aetiology of this clinical syndrome.

Evaluating the results from 35 neuroimaging studies using ROI analysis, half of the sample found significant results (n = 18), and the other half did not (n = 17). The temporal lobe was also the most studied area of the brain in ROI studies. Specifically, the hippocampus, the amygdala, the entorhinal cortex and the posterior cingulate cortex were the most studied regions of interest. Although these areas are usually affected in mild and advanced stages of AD [71‐73], there is no clear constant evidence of significant differences between SCD and HC individuals in these areas. One of the main limitations of ROI analysis may be the predetermination of the areas to be studied, especially when the underlying causes for SCD are not always AD-related. This selection bias can be avoided using other kinds of analyses such as voxel-based analysis. ROI segmentation is another possible source of bias, especially when manual segmentation is used. The distinction between manual versus automatic segmentation of ROIs could then be expected to be a determinant factor in the finding of significant differences. Manual segmentation was the gold standard for hippocampal volumetry [74, 75] but heterogeneity in anatomic definitions and tracing guidelines have hampered comparisons among different studies using hippocampal volumetry for diagnosis. Semiautomatic segmentation tries to solve this limitation and to reduce the inter- and intraobserver variability but fails to do so to the full extent [76]. Automatic segmentation is more consistent and time-efficient but needs larger samples to validate the technique. However, our review did not find this factor to be meaningful, possibly related with the sample size. Moreover, there is no clear evidence of volumetric changes in other ROIs. Nevertheless, this could be due to the reduced number of studies focusing on them.

Heterogeneity was also observed in studies measuring cortical thickness. Six studies showed statistically significant differences in the cortical thickness of participants with SCD compared to controls, while 4 did not. Although the entorhinal cortex is one of the most affected structures when significant cortical thinning was found, more studies are needed to consider it a reliable biomarker of preclinical AD.

The main limitations of our study are the different research settings and operationalisation of SCD used in the studies, the heterogeneity inherent to this clinical syndrome and the small sample of the studies measuring structural changes. Methodologically, an explanation for these heterogeneous results could be that the term SCD was recently established by Jessen in 2014, unifying the diverse diagnostic criteria and terminology used until then to refer to this potential early state of AD. Additionally, SCD may include vastly diverse samples, since it may include patients who underly AD pathology, other kinds of neurodegenerative disorders or cases in which memory complaints are simply associated with normal ageing. More consistent results may be expected by selecting participants with SCD and specific features which increase the likelihood of the presence of preclinical AD (referred as SCD plus [5]). Moreover, participants are studied in different research environments such as clinical settings and population-based cohorts. Rodríguez-Gómez et al. [77] found that SCD patients who have been referred to a memory clinic had an increased risk of developing cognitive impairment than patients from the general population. In this line, we found a trend pointing towards the recruitment from memory clinics as a predictive factor of statistical differences. On the other hand, the use of larger samples and multimodal analysis techniques might help to establish regions associated to SCD and its progression to then develop an early and accurate diagnosis of preclinical AD. Finally, another possible limitation of our study might be the publication bias, given that studies that do not find significant differences are less likely to be published, thus reducing our sample.

As a conclusion, we have found that studies assessing volumetric or grey matter changes in subjects with SCD when compared with cognitively normal subjects showed heterogeneous results. Almost half of the studies do not find any significant difference between both groups, and when differences are observed, diverse structures are involved. However, the medial temporal lobe is the structure more frequently observed.