Abstract
INTRODUCTION:
Hippocampal sclerosis of aging (HS) is an important component of combined dementia neuropathology. However, the temporal evolution of its histologically-defined features is unknown. We investigated pre-mortem longitudinal hippocampal atrophy associated with HS, as well as with other dementia-associated pathologies.
METHODS:
We analyzed hippocampal volumes from MRI segmentations in 64 dementia patients with longitudinal MRI follow-up and post-mortem neuropathological evaluation, including HS assessment in the hippocampal head and body.
RESULTS:
Significant HS-associated hippocampal volume changes were observed throughout the evaluated timespan, up to 11.75 years before death. These changes were independent of age and Alzheimer’s Disease (AD) neuropathology, and specifically driven by CA1 and subiculum atrophy. AD pathology, but not HS, significantly associated with the rate of hippocampal atrophy.
DISCUSSION:
HS-associated volume changes are detectable on MRI earlier than 10 years before death. Based on these findings, volumetric cut-offs could be derived for in vivo differentiation between HS and AD.
Keywords: atrophy, dementia, hippocampal sclerosis of aging, hippocampus, longitudinal, magnetic resonance imaging, neuropathology
1. Introduction
Hippocampal sclerosis of aging (HS) is a pathological finding associated with worsened cognitive symptoms in dementia patients1,2. Since its first description by Dickson et al.3, it has been defined by severe neuronal loss in CA1 and subiculum subfields of the hippocampus, which is particularly prevalent over 85 years of age4. This qualitatively-observed lesion is disproportionate to expected damage by other coexisting pathologies. HS normally coexists with one or several dementia neuropathologies: Lewy bodies (LB)5,6, vascular pathology7,8, Alzheimer’s disease (AD)9,10, and most commonly, limbic-predominant age-related TDP-43 encephalopathy (LATE)11,12. Indeed, 80–100% patients with HS present LATE pathology, and HS is found in up to 90% of LATE cases13.
Despite its relevance within the dementia neuropathological spectrum, the contribution of HS is often overlooked. In several recent post-mortem studies on AD14,15, TDP-4316,17 and LB pathologies18,19, HS was not evaluated. Conversely, other studies have highlighted its importance20,21 and described histological findings proposed as early HS5,22. In line with this work, we recently characterized early pathological changes of HS, proposing this pathology forms a wider spectrum than initially defined23. Following this re-classification, the prevalence of HS could have been underestimated in previous studies, which reported a frequency of 3–30%1,2,9.
The histological definition of HS has limited the search for biomarkers of this pathology. Preliminary evidence suggests that HS patients have lower Mini-Mental State Examination (MMSE) scores, longer symptom duration10, and relatively preserved verbal and visuomotor functions24,25 compared to AD. Moreover, HS has been associated with reduced hippocampal volumes in pre-mortem MRI26. However, the utility of these changes as biomarkers is limited by a current lack of understanding of the timespan of HS. Since this pathology can, up to now, only be evaluated post-mortem27, its onset and duration remain unknown.
In this study, we aimed to characterize the timespan of hippocampal volume changes associated with HS. We studied data from dementia patients with pre-mortem MRI follow-up, spanning more than 10 years before death, and neuropathological evaluation. We describe longitudinal differences in hippocampal volume between subjects with HS (HS+) and without (HS-), following its classical definition, as well as according to our recently proposed evaluation including early stages23. Implementing a two-level HS assessment in the head and body of the hippocampus, we explore subfield volumetric changes in these two regions relative to HS. We also evaluate longitudinal volume differences as a function of other neuropathologies, thus dissociating their associated changes from those of HS, crucial for its in vivo identification.
2. Methods
2.1. Cohort
We studied data obtained between 2007 and 2020 from the Vallecas Alzheimer’s Center Study (VACS), a nursing home for dementia patients who undergo neuroimaging follow-up. Although follow-up is semestral by protocol, actual frequency depends on the state of each individual. Out of 102 patients with at least one pre-mortem MRI acquisition and post-mortem donation to the BT-CIEN brain bank, 10 were excluded from analyses due to: a) no usable T1 scan (n=4); b) neuropathological diagnosis of Frontotemporal Dementia (n=3), given its independent association with hippocampal sclerosis9; c) unattainable hippocampus evaluation due to extreme atrophy (n=1) or hemorrhage (n=2).
2.2. Neuropathological evaluation
Brain extraction and processing followed previously described procedures28. After extraction, the left hemisphere was fixed and cut into coronal slices for tissue block dissection. Blocks were cut into 4μm sections for hematoxylin/eosin and immunostaining (against amyloid-β, phospho-tau AT100, total α-synuclein, and total TDP-43).
Neuropathological evaluation was performed following consensus criteria, and patients were stratified into low- and high-burden groups for each pathology. High probability of Alzheimer’s Disease Neuropathological Change (ADNC) was determined based on National Institute on Aging (NIA) guidelines29. Cerebrovascular pathology assessment followed staging by Deramecourt et al.30 (0–20), with a score of 8 or higher being classified as high-burden. LB pathology was assessed through Braak α-synuclein staging (0–6)31, and high burden was assigned to values higher than 2 (pathology beyond the brainstem). TDP-43 proteinopathy was evaluated through LATE staging (0–3)11, and patients with hippocampal inclusions (stage 2 or higher) were categorized as high-burden. HS was assessed following our recently proposed staging system (0-IV) including early stages23, evaluated in both hippocampal head and body sections. Subjects presenting stages>0 in any of these two sections were classified as HS+. The classical HS definition was also employed4, with head sections presenting severe neuronal loss in CA1 and subiculum (stage>II) classified as HS+.
2.3. MRI acquisition
T1-weighted images were acquired using a 3T scanner (General Electric) with a phased array eight-channel head coil, employing 3D sagittal Fast Spoiled Gradient Recalled (FSPGR) configuration with inversion recovery (repetition/echo/inversion times 7/3.2/750ms, resolution 1×0.469×0.469mm).
2.4. Longitudinal hippocampal segmentation
Whole hippocampal and subfield volumes were obtained by processing all T1-weighted scans from included subjects with the FreeSurfer 7.1.1 longitudinal workflow32. To overcome slight movement artifacts, subcortical segmentations were substituted by the segmentation from SynthSeg33 prior to template creation. Segmentation of hippocampal subfields34 was then obtained and visually inspected to discard those with inaccurate subfield delineation. Out of 92 subjects, 7 resulted in errors along the pipeline and 21 had all segmentations discarded, resulting in 64 subjects with accurate data. For timepoints with accurate segmentations in both hemispheres, left and right volumes were averaged for statistical analyses.
2.5. Statistics
RStudio 11.4.1106 was used for statistical analyses and plots. To compare between HS groups, for categorical, non-normal numeric, and normal numeric variables, we used Pearson’s chi square, Kruskal-Wallis and t-tests respectively. To compare volumes at the timepoint closest to death, we modelled volume as a function of age at MRI, time to death, sex, and intracranial volume. We then added model residuals to volumes to obtain adjusted volume measures, which were compared using t-tests. Results from additional brain regions were FDR-corrected for multiple comparisons.
Linear mixed models with random intercept and slope were employed to model hippocampal volume as a function of time, assessing its interaction with the pathology of interest. In addition, age at death, sex and intracranial volume were included as independent variables. To account for differing times between last MRI and death, we verified all results were unaltered when including age at MRI instead.
3. Results
3.1. Cohort features
Among the 64 patients with accurate hippocampal segmentations, HS+ subjects presented expected differences: significantly longer disease duration, older age, and lower final severe-MMSE scores (Table 1). As expected, this group also presented higher ADNC and TDP-43 pathology burdens. Included pre-mortem MRI scans ranged between 1 and 11 per subject and covered a timespan of up to 11.75 years before death. Time between last included MRI and death was also significantly higher in HS+ patients, since scanning feasibility is directly affected by the patient’s cognitive state.
Table 1.
Whole cohort | HS− (n=26) | HS+ (n=38) | p value | |
---|---|---|---|---|
Demographics | Mean ± SD or % | |||
Sex (%Females) | 81.3 | 73.1 | 86.8 | 0.166 (a) |
Estimated age at symptom onset * | 76.5 ± 6 | 75 ± 6.5 | 77.6 ± 5.5 | 0.354(b) |
Age at death | 88.4 ± 6.6 | 84.6 ± 6.6 | 90.9 ± 5.3 | 10 −4 (c) |
sMMSE score at admission | 19.1 ± 9.2 | 20.5 ± 9.3 | 18.3 ± 9.1 | 0.287 (b) |
sMMSE score prior to death | 10.4 ± 10.6 | 14.9 ± 11 | 7.4 ± 9.3 | 0.005 (b) |
Follow-up | Mean ± SD | |||
Time in nursing home (years) | 4.7 ± 3.4 | 3.3 ± 3.3 | 5.7 ± 3.2 | 0.004 (b) |
Time between last MRI and death (years) | 3 ± 3.1 | 1.6 ± 2.2 | 4 ± 3.3 | 4·10 −4 (b) |
Number of MRI scans included | 3.2 ± 2.7 | 3 ± 2.5 | 3.3 ± 2.9 | 0.849 (b) |
Neuropathology burden | % | |||
High ADNC | 68.8 | 46.2 | 84.2 | 0.001 (a) |
High vascular pathology | 60.9 | 73.1 | 52.6 | 0.1 (a) |
Lewy bodies beyond brainstem (Braak>2) | 40.6 | 34.6 | 44.7 | 0.418 (a) |
TDP-43 inclusions in hippocampus (LATE>1) | 50 | 11.5 | 76.3 | 6·10 −7 (a) |
Early or advanced HS | 59.4 | 0 | 100 | - |
Classical HS | 29.7 | 0 | 50 | 2·10 −5 (a) |
NOTE. This cohort was composed by a predominantly female population of advanced age at death. The three right-most columns show values and comparison between groups with and without HS, with early and advanced stages included within the HS+ group. Results for comparison between groups do not change when stratifying groups by the classical HS definition. Significantly longer disease duration in the HS+ group is reflected by longer time in the nursing home.
Group comparisons by:
Pearson’s chi-2 test.
Kruskal-Wallis test.
T-test.
Age at symptom onset is estimated by neurologists based on medical records and interviews with caretakers.
Abbreviations: ADNC: Alzheimer’s Disease Neuropathological Change; HS: hippocampal sclerosis of aging; LATE: limbic age-related TDP-43 encephalopathy; MRI: Magnetic Resonance Imaging; SD: standard deviation; sMMSE: severe Mini-Mental State Examination; TDP-34: TAR DNA-binding protein 43.
3.2. Longitudinal hippocampal atrophy as a function of HS
As expected, whole hippocampal volume at the timepoint closest to death was significantly lower in the HS+ group (Figure S1). Volumes of other brain structures were also generally lower in HS+ subjects, but group differences were only significant in the amygdala (Figure S2). Next, we compared hippocampal volumes across time, correcting for age at death, sex, and intracranial volume. Including early and advanced stages (Figure 1A), HS+ patients displayed reduced hippocampal volumes compared to HS− (F=31.7, p=0.006). This difference was significant throughout the evaluated timespan, based on estimated marginal means (EMM) comparison (at −11.75 years, EMM difference between groups was 405±146 mm3, p=0.007). Critically, the rate of volume decline was not significantly different between groups. Significantly lower volumes without different decline rates were also found following the classical HS definition (Figure 1B), showing this association is independent of classification criteria (F=25.6, p=0.005).
These volume effects were still significant in a subset of the cohort including 26 HS+ subjects with closest ages at death to HS− subjects, further supporting the independence of results on age (Figure S3, Table S1). Moreover, correcting for age at MRI instead of at death did not alter these results. These effects were also independent of AD pathology burden (Figure 1C,1D). Furthermore, restricting analyses to subjects with high ADNC (n=44), differences between HS groups were still significant, following either HS staging (F=14.2, p=.015) or its classical definition (F=29.1, p=2·10−4).
3.3. Hippocampal subfield volume changes relative to HS
To test the regional specificity of hippocampal atrophy effects, we analyzed the association between HS stage and subfield volumes in both hippocampal head and body. The number of subjects at each stage, as well as demographic details, are shown in Table S2. Subfields were analyzed in two groups: CA1+subiculum, in which histological changes occur at earlier HS stages, and CA3+CA4, which may present changes in stage IV23. Throughout the evaluated timespan, CA1+subiculum volumes were significantly lower in both hippocampal head (Figure 2A) and body (Figure 2B) as a function of respective HS stages (head: F=5.8, p=0.035; body: F=8, p=0.003). Such association was not observed for CA3+4 volumes in the head (Figure 2C) or body (Figure 2D). Rates of volume change were not significantly different as a function of staging, nor between HS+ and HS− groups. We then evaluated CA1 and subiculum separately (Figure S4), evaluating longitudinal group differences through EMM comparisons. CA1 in the hippocampal head, and subiculum in the body, displayed significantly lower volumes in the HS+ group, as early as 11 and 9.5 years before death, respectively. These results were also significant following the classical HS definition.
Considering only the left hemisphere, in which neuropathological evaluation was performed, HS+ subjects displayed lower hippocampal and subfield volumes than HS-, but differences did not reach significance (Figure S5). The reduced sample size in these analyses (42 subjects with accurate left-hippocampus segmentations), limits their power to find significant longitudinal differences.
3.4. Longitudinal hippocampal atrophy as a function of other pathologies
Given the absence of an effect of HS on hippocampal atrophy rates, we evaluated whether other neuropathologies presented such association. Whole hippocampal volumes across time were analyzed separately as a function of AD, vascular, LB and TDP-43 pathologies, dividing patients into low- and high-burden groups. Considering the prevalence of co-pathologies (Table S3) and that ADNC is a major determinant of hippocampal atrophy and cognitive decline, ADNC burden was added as a covariate in models for the rest of pathologies, as done previously with HS. Groups displaying high ADNC probability (F=13.4, p=0.004) and TDP-43 burden (F=14.6, p=0.022) showed significantly lower volumes compared to their respective low-burden groups (Figure 3). In addition, ADNC severity displayed a significant interaction with time (p=.016), with faster decline rates in the high ADNC group. These results were independent of TDP-43 burden, which showed no significant effect on decline rate, independently of ADNC (Figure S6). No significant volume differences were found between burden groups for vascular and LB pathologies.
Considering baseline and final MMSE scores, cognitive decline followed a similar trend as hippocampal volume: HS+ subjects showed lower scores, with comparable decline rates, while high ADNC was associated with lower scores and faster decline (Figure S7). For subjects with more than one included MRI, correlations between hippocampal volume and MMSE scores at basal and final timepoints were significant, except for HS+ subjects in their final timepoint, which displayed a floor effect in cognition. This is in line with cognitive differences between HS groups being significant only at the final evaluation (Table 1), while volumes are already different at the earliest timepoint. Such cognitive worsening in HS+ subjects is partially explained by a longer dementia duration, as suggested by its inverse correlation with MMSE (Figure S7).
4. Discussion
We studied longitudinal hippocampal volume changes as a function of HS, a pathology for which no biomarkers currently exist. Previous work by our group23 and others26,35 revealed an association between HS and hippocampal atrophy, but the timespan of these changes remained unknown. We found lower hippocampal volumes in HS+ compared to HS− subjects throughout the evaluated timespan, up to 11.75 years before death. Volume decline rates did not differ between groups, suggesting volume reduction manifests prior to this evaluated timespan. Importantly, this trend was independent of age and ADNC burden. Our findings were also independent of the classification of early HS cases, indicating volume effects are driven by advanced stages, which present the HS classical cell loss signature.
Hippocampal atrophy is a well-established AD marker36,37. Yet, vascular38,39, TDP-4321 and LB pathologies40,41 are also associated with reduced hippocampal volumes, thus questioning its specificity for ADNC. Hippocampal atrophy rate has also been described as a useful AD predictor42,43, which is reinforced by our results. However, in contrast to our findings, larger-cohort studies found TDP-43 pathology to associate with faster hippocampal atrophy44, independently of AD45,46. Although our reported effects in symptomatic dementia suggest the impact of ADNC on atrophy rate is greater than that of TDP-43, its specificity is challenged by previous work and the intricate association between these pathologies.
Our subfield analyses revealed early HS-associated hippocampal atrophy is driven by CA1 and subiculum, consistent with its histological pattern. More specifically, CA1 in the hippocampal head displayed this reduction earliest. One distinguishing feature of our work is the evaluation of HS at two histological sections along the hippocampal long axis47, allowing region-specific subfield analyses. Previous studies assessed HS in a single hippocampal section, either unspecified4,7,20 or parallel to the lateral geniculate body3,22, prompting variable results. The reported early reduction in CA1 head volume points towards the anterior hippocampus as a key region in the pathology, highlighting its relevance for HS assessment.
Exploring volumetric differences in other brain regions at the timepoint closest to death, we found significantly lower amygdala volumes in HS+ subjects. In previous work, we found grey matter density differences relative to HS extending to the amygdala as well23. While this is consistent with TDP-43 pathology distribution, whether the amygdala presents additional histopathological alterations specific to HS is currently unknown, representing a relevant question for future research.
Together with our two-level HS assessment, other strengths of this study include an extensive neuropathological evaluation and unified MRI acquisition and processing pipelines. Moreover, segmentation accuracy was enhanced using SynthSeg33, robust to movement artifacts, prior to hippocampal segmentation. This work also entails several limitations, including the lack of data from pre-dementia onset or from cognitively healthy individuals. Differing times between last MRI and death represent another limitation, which we mitigated by using several time and age corrections. A modest sample size, combination of left and right hemisphere data, and a unilateral pathological evaluation are other limitations, as they impede accounting for HS asymmetry4,27. Our results can serve as foundation for larger studies to define volumetric ranges in individuals with HS and AD, and explore if HS-associated volume changes are observed at pre-dementia stages. These early volumetric differences could be combined with recently described FDG-PET medial-temporal hypometabolic changes in HS48 and TDP-4349,50, to reinforce the distinction of these pathologies from AD.
5. Conclusion
We describe reduced hippocampal volumes in HS+ dementia patients that are detectable earlier than a decade before death, independently of age. HS did not affect volume decline rates, which following a comprehensive pathological evaluation, were only found to significantly associate with ADNC burden. These results suggest AD pathology has the strongest effect on hippocampal atrophy during symptomatic dementia, and stimulate efforts to understand HS as a determining pathology throughout life, with early effects in pre-mortem MRI.
Supplementary Material
Acknowledgements
The authors wish to thank the participants of the VACS cohort and their family members, as well as the CIEN Foundation staff. Especially, we thank Paloma Ruiz and Laura Saiz for their work at BT-CIEN. We also thank Eva Alfayate and Felipe García from the neuroimaging department.
Funding
This work has been supported by the Queen Sofia Foundation and the CIEN Foundation. DOC was supported by “la Caixa” Foundation (ID 100010434), with fellowship code LCF/BQ/DR20/11790034. BAS and JEI were supported by a MISTI Global Seed Fund (0000000246). JEI was supported by the ERC (Starting Grant 677697), the NIH (1RF1MH123195, 1R01AG070988, 1UM1MH130981), and ARUK (ARUK-IRG2019A-003).
Footnotes
Conflicts
Declarations of interest: none
References
- 1.Amador-Ortiz C, Ahmed Z, Zehr C, Dickson D. Hippocampal sclerosis dementia differs from hippocampal sclerosis in frontal lobe degeneration. Acta Neuropathol. 2007;113(3):245–252. doi: 10.1007/s00401-006-0183-4 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Nelson PT, Fardo DW, Van Eldik LJ, et al. Hippocampal Sclerosis of Aging, a Prevalent and High-Morbidity Brain Disease. Acta Neuropathol. 2013;126(2):161–177. doi: 10.1007/s00401-013-1154-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Dickson DW, Davies P, Bevona C, et al. Hippocampal sclerosis: a common pathological feature of dementia in very old (≥80 years of age) humans. Acta Neuropathol. 1994;88(3):212–221. doi: 10.1007/BF00293396 [DOI] [PubMed] [Google Scholar]
- 4.Nelson PT, Schmitt FA, Lin Y, et al. Hippocampal sclerosis in advanced age: Clinical and pathological features. Brain. 2011;134(5):1506–1518. doi: 10.1093/brain/awr053 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Aoki N, Murray ME, Ogaki K, et al. Hippocampal sclerosis in Lewy body disease is a TDP-43 proteinopathy similar to FTLD-TDP Type A. Acta Neuropathol. 2015;129(1):53–64. doi: 10.1007/s00401-014-1358-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Trieu T, Sajjadi S, Kawas C, Nelson P, Corrada M. Risk factors of hippocampal sclerosis in the oldest old: The 90+ Study. Neurology. 2018;91(19):e1788–e1798. doi: 10.1212/WNL.0000000000006455 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Neltner JH, Abner EL, Baker S, et al. Arteriolosclerosis that affects multiple brain regions is linked to hippocampal sclerosis of ageing. Brain : a journal of neurology. 2014;137:255–267. doi: 10.1093/brain/awt318 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Sieben A, Van Langenhove T, Vermeiren Y, et al. Hippocampal Sclerosis in Frontotemporal Dementia: When Vascular Pathology Meets Neurodegeneration. J Neuropathol Exp Neurol. 2021;80(4):313–324. doi: 10.1093/jnen/nlab010 [DOI] [PubMed] [Google Scholar]
- 9.Brenowitz WD, Monsell SE, Schmitt FA, Kukull WA, Nelson PT. Hippocampal sclerosis of aging is a key Alzheimer’s disease mimic: clinical-pathologic correlations and comparisons with both alzheimer’s disease and non-tauopathic frontotemporal lobar degeneration. J Alzheimers Dis. 2014;39(3):691–702. doi: 10.3233/JAD-131880 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Lopez OL, Kofler J, Chang Y, et al. Hippocampal sclerosis, TDP‐43, and the duration of the symptoms of dementia of AD patients. Annals of clinical and translational neurology. 2020;7(9):1546–1556. doi: 10.1002/acn3.51135 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Nelson PT, Dickson DW, Trojanowski JQ, et al. Limbic-predominant age-related TDP-43 encephalopathy (LATE): consensus working group report. Brain : a journal of neurology. 2019;142(6):1503–1527. doi: 10.1093/brain/awz099 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Amador-Ortiz C, Lin W, Ahmed Z, et al. TDP-43 immunoreactivity in hippocampal sclerosis and Alzheimer’s disease. Ann Neurol. 2007;61(5):435–445. doi: 10.1002/ana.21154 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Besser LM, Teylan MA, Nelson PT. Limbic Predominant Age-Related TDP-43 Encephalopathy (LATE): Clinical and Neuropathological Associations. J Neuropathol Exp Neurol. 2020;79(3):305–313. doi: 10.1093/jnen/nlz126 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Alosco ML, Sugarman MA, Besser LM, et al. A Clinicopathological Investigation of White Matter Hyperintensities and Alzheimer’s Disease Neuropathology. J Alzheimers Dis. 2018;63(4):1347–1360. doi: 10.3233/JAD-180017 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Mattsson-Carlgren N, Grinberg LT, Boxer A, et al. Cerebrospinal Fluid Biomarkers in Autopsy-Confirmed Alzheimer Disease and Frontotemporal Lobar Degeneration. Neurology. 2022;98(11):e1137–e1150. doi: 10.1212/WNL.0000000000200040 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Hunter S, Hokkanen SRK, Keage HAD, et al. TDP-43 Related Neuropathologies and Phosphorylation State: Associations with Age and Clinical Dementia in the Cambridge City over-75s Cohort. J Alzheimers Dis. 2020;75(1):337–350. doi: 10.3233/JAD-191093 [DOI] [PubMed] [Google Scholar]
- 17.Uemura MT, Robinson JL, Cousins KAQ, et al. Distinct characteristics of limbic-predominant age-related TDP-43 encephalopathy in Lewy body disease. Acta Neuropathol. 2021;143(1):15–31. doi: 10.1007/s00401-021-02383-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Gibson LL, Grinberg LT, ffytche D, et al. Neuropathological correlates of neuropsychiatric symptoms in dementia. Alzheimer’s Dement. 2022. doi: 10.1002/alz.12765 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Chen Z, Gan J, Yang Y, Meng Q, Han J, Ji Y. The vascular risk factors and vascular neuropathology in subjects with autopsy-confirmed dementia with Lewy bodies. Int J Geriatr Psychiatry. 2022;37(3). doi: 10.1002/gps.5683 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Barker WW, Luis CA, Kashuba A, et al. Relative Frequencies of Alzheimer Disease, Lewy Body, Vascular and Frontotemporal Dementia, and Hippocampal Sclerosis in the State of Florida Brain Bank. Alzheimer Disease & Associated Disorders. 2002;16(4) [DOI] [PubMed] [Google Scholar]
- 21.Josephs KA, Whitwell JL, Knopman DS, et al. Abnormal TDP-43 immunoreactivity in AD modifies clinicopathological and radiological phenotype. Neurology. 2008;70(19):1850. doi: 10.1212/01.WNL.0000304041.09418.B1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Hokkanen SRK, Hunter S, Polvikoski TM, et al. Hippocampal sclerosis, hippocampal neuron loss patterns and TDP‐43 in the aged population. Brain Pathology. 2018;28(4):548–559. doi: 10.1111/bpa.12556 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Ortega-Cruz D, Uceda-Heras A, Iglesias JE, Zea-Sevilla M, Strange B, Rabano A. A novel histological staging of hippocampal sclerosis that is evident in gray matter loss in vivo. Alzheimer’s Dement. 2023. doi: 10.1002/alz.12942 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Lippa CF, Dickson DW. Hippocampal sclerosis dementia: Expanding the phenotypes of frontotemporal dementias? Neurology. 2004;63(3):414–415. doi: 10.1212/01.WNL.0000136241.71716.72 [DOI] [PubMed] [Google Scholar]
- 25.Onyike CU, Pletnikova O, Sloane KL, Sullivan C, Troncoso JC, Rabins PV. Hippocampal sclerosis dementia: an amnesic variant of frontotemporal degeneration. Dementia & neuropsychologia. 2013;7(1):83–87. doi: 10.1590/S1980-57642013DN70100013 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Woodworth DC, Nguyen HL, Khan Z, Kawas CH, Corrada MM, Sajjadi SA. Utility of MRI in the identification of hippocampal sclerosis of aging. Alzheimer’s and Dementia. 2021;17(5):847–855. doi: 10.1002/alz.12241 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Zarow C, Sitzer T, Chui H. Understanding hippocampal sclerosis in the elderly: Epidemiology, characterization, and diagnostic issues. Curr Neurol Neurosci Rep. 2008;8(5):363–370. doi: 10.1007/s11910-008-0057-3 [DOI] [PubMed] [Google Scholar]
- 28.Martínez-Martín P, Avila J. Alzheimer Center Reina Sofia Foundation: Fighting the Disease and Providing Overall Solutions. Journal of Alzheimer’s disease : JAD. 2010;21(2):337–348. doi: 10.3233/JAD-2010-101149 [DOI] [PubMed] [Google Scholar]
- 29.Montine TJ, Phelps CH, Beach TG, et al. National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease: a practical approach. Acta Neuropathol. 2012;123(1):1–11. doi: 10.1007/s00401-011-0910-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Deramecourt V, Slade JY, Oakley AE, et al. Staging and natural history of cerebrovascular pathology in dementia. Neurology. 2012;78(14):1043–1050. doi: 10.1212/WNL.0b013e31824e8e7f [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Braak H, Del Tredici K, Rüb U, de Vos R,AI, Jansen Steur E,NH, Braak E. Staging of brain pathology related to sporadic Parkinson’s disease. Neurobiol Aging. 2003;24(2):197. doi: 10.1016/s0197-9 [DOI] [PubMed] [Google Scholar]
- 32.Reuter M, Schmansky NJ, Rosas HD, Fischl B. Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage. 2012;61(4):1402–1418. doi: 10.1016/j.neuroimage.2012.02.084 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Billot B, Greve DN, Puonti O, et al. SynthSeg: Segmentation of brain MRI scans of any contrast and resolution without retraining. Med Image Anal. 2023;86:102789. doi: 10.1016/j.media.2023.102789 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Iglesias JE, Augustinack JC, Nguyen K, et al. A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI. Neuroimage. 2015;115:117–137. doi: 10.1016/J.NEUROIMAGE.2015.04.042 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Dawe RJ, Bennett DA, Schneider JA, Arfanakis K. Neuropathologic correlates of hippocampal atrophy in the elderly: a clinical, pathologic, postmortem MRI study. PLoS One. 2011;6(10):e26286. doi: 10.1371/journal.pone.0026286 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Risacher LS, Saykin JA, Wes DJ, Shen L, Firpi AH, McDonald CB. Baseline MRI Predictors of Conversion from MCI to Probable AD in the ADNI Cohort. Current Alzheimer Research. 2009;6(4):347–361. doi: 10.2174/156720509788929273 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Jack CRJ, Bennett DA, Blennow K, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14(4):535–562. doi: 10.1016/j.jalz.2018.02.018 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.van de Pol L, Gertz H, Scheltens P, Wolf H. Hippocampal atrophy in subcortical vascular dementia. Neurodegener Dis. 2011;8(6):465–469. doi: 10.1159/000326695 [DOI] [PubMed] [Google Scholar]
- 39.Fein G, Di Sclafani V, Tanabe J, et al. Hippocampal and cortical atrophy predict dementia in subcortical ischemic vascular disease. Neurology. 2000;55(11):1626–1635. doi: 10.1212/wnl.55.11.1626 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Chow N, Aarsland D, Honarpisheh H, et al. Comparing hippocampal atrophy in Alzheimer’s dementia and dementia with lewy bodies. Dement Geriatr Cogn Disord. 2012;34(1):44–50. doi: 10.1159/000339727 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Elder GJ, Mactier K, Colloby SJ, et al. The influence of hippocampal atrophy on the cognitive phenotype of dementia with Lewy bodies. Int J Geriatr Psychiatry. 2017;32(11):1182–1189. doi: 10.1002/gps.4719 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Apostolova LG, Mosconi L, Thompson PM, et al. Subregional hippocampal atrophy predicts Alzheimer’s dementia in the cognitively normal. Neurobiol Aging. 2010;31(7):1077–1088. doi: 10.1016/j.neurobiolaging.2008.08.008 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.den Heijer T, van der Lijn F, Koudstaal PJ, et al. A 10-year follow-up of hippocampal volume on magnetic resonance imaging in early dementia and cognitive decline. Brain. 2010;133(Pt 4):1163–1172. doi: 10.1093/brain/awq048 [DOI] [PubMed] [Google Scholar]
- 44.Josephs KA, Dickson DW, Tosakulwong N, et al. Rates of hippocampal atrophy and presence of post-mortem TDP-43 in patients with Alzheimer’s disease: a longitudinal retrospective study. Lancet Neurol. 2017;16(11):917–924. doi: 10.1016/S1474-4422(17)30284-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Josephs KA, Martin PR, Weigand SD, et al. Protein contributions to brain atrophy acceleration in Alzheimer’s disease and primary age-related tauopathy. Brain. 2020;143(11):3463–3476. doi: 10.1093/brain/awaa299 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Buciuc M, Wennberg AM, Weigand SD, et al. Effect Modifiers of TDP-43-Associated Hippocampal Atrophy Rates in Patients with Alzheimer’s Disease Neuropathological Changes. J Alzheimers Dis. 2020;73(4):1511–1523. doi: 10.3233/JAD-191040 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Strange BA, Witter MP, Lein ES, Moser EI. Functional organization of the hippocampal longitudinal axis. Nature Reviews Neuroscience. 2014;15(10):655–669. doi: 10.1038/nrn3785 [DOI] [PubMed] [Google Scholar]
- 48.Botha H, Mantyh WG, Murray ME, et al. FDG-PET in tau-negative amnestic dementia resembles that of autopsy-proven hippocampal sclerosis. Brain. 2018;141(4):1201–1217. doi: 10.1093/brain/awy049 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 49.Buciuc M, Botha H, Murray ME, et al. Utility of FDG-PET in diagnosis of Alzheimer-related TDP-43 proteinopathy. Neurology. 2020;95(1):e23. doi: 10.1212/WNL.0000000000009722 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 50.Grothe MJ, Moscoso A, Silva-Rodríguez J, et al. Differential diagnosis of amnestic dementia patients based on an FDG-PET signature of autopsy-confirmed LATE-NC. Alzheimer’s Dement. 2022. doi: 10.1002/alz.12763 [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.