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. 2024 Jan 23;102(2):e207854.
doi: 10.1212/WNL.0000000000207854. Epub 2023 Dec 18.

Association Between Hippocampal Volumes and Cognition in Cerebral Amyloid Angiopathy

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Association Between Hippocampal Volumes and Cognition in Cerebral Amyloid Angiopathy

Valentina Perosa et al. Neurology. .

Erratum in

  • Corrections to Received Date Information.
    [No authors listed] [No authors listed] Neurology. 2024 Jul 9;103(1):e209596. doi: 10.1212/WNL.0000000000209596. Epub 2024 Jun 3. Neurology. 2024. PMID: 38830175 Free PMC article. No abstract available.

Abstract

Background and objectives: Accumulating evidence suggests that gray matter atrophy, often considered a marker of Alzheimer disease (AD), can also result from cerebral small vessel disease (CSVD). Cerebral amyloid angiopathy (CAA) is a form of sporadic CSVD, diagnosed through neuroimaging criteria, that often co-occurs with AD pathology and leads to cognitive impairment. We sought to identify the role of hippocampal integrity in the development of cognitive impairment in a cohort of patients with possible and probable CAA.

Methods: Patients were recruited from an ongoing CAA study at Massachusetts General Hospital. Composite scores defined performance in the cognitive domains of memory, language, executive function, and processing speed. Hippocampal subfields' volumes were measured from 3T MRI, using an automated method, and multivariate linear regression models were used to estimate their association with each cognitive domain and relationship to CAA-related neuroimaging markers.

Results: One hundred twenty patients, 36 with possible (age mean [range]: 75.6 [65.6-88.9]), 67 with probable CAA (75.9 [59.0-94.0]), and 17 controls without cognitive impairment and CSVD (72.4 [62.5-82.7]; 76.4% female patients), were included in this study. We found a positive association between all investigated hippocampal subfields and memory and language, whereas specific subfields accounted for executive function (CA4 [Estimate = 5.43; 95% CI 1.26-9.61; p = 0.020], subiculum [Estimate = 2.85; 95% CI 0.67-5.02; p = 0.022]), and processing speed (subiculum [Estimate = 1.99; 95% CI 0.13-3.85; p = 0.036]). These findings were independent of other CAA-related markers, which did not have an influence on cognition in this cohort. Peak width of skeletonized mean diffusivity (PSMD), a measure of white matter integrity, was negatively associated with hippocampal subfields' volumes (CA3 [Estimate = -0.012; 95% CI -0.020 to -0.004; p = 0.034], CA4 [Estimate = -0.010; 95% CI -0.020 to -0.0007; p = 0.037], subiculum [Estimate = -0.019; 95% CI -0.042 to -0.0001; p = 0.003]).

Discussion: These results suggest that hippocampal integrity is an independent contributor to cognitive impairment in patients with CAA and that it might be related to loss of integrity in the white matter. Further studies exploring potential causes and directionality of the relationship between white matter and hippocampal integrity may be warranted.

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Conflict of interest statement

The authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.

Figures

Figure 1
Figure 1. Examples of MRI Markers of Cerebral Amyloid Angiopathy (CAA)
The figure shows typical MRI markers of CAA, such as lobar microbleeds visible as round hypointensities on susceptibility-weighted imaging (SWI) (A); cortical superficial siderosis (cSS), also detectable on SWI (B); MRI visible perivascular spaces (PVS) in the centrum semiovale, which are represented as hyperintense stripes on T2-weighted imaging (C); finally cortical microinfarcts, which are defined as T2 hyperintense lesions <3 mm (D).
Figure 2
Figure 2. Scatter Plots Showing the Significant Positive Association Between Volume of the Subiculum and Z-Score in Memory (A), Processing Speed (B), Language (C), and Executive Function (D)
(E) A coronal view on the hippocampi of one participant, displayed on a T1-weighted image. Both hippocampi display a moderate degree of atrophy. On the left side, the segmented hippocampal subfields obtained with FreeSurfer 6.0 are overlaid for visualization purposes. The segmentation algorithm partially relies on the molecular layer, which was well visible in our data set, as exemplarily shown on the left hippocampus (*).

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