Hippocampal Surface Analysis in Subjective Memory Impairment, Mild Cognitive Impairment and Alzheimer’s Dementia

Tepest, Ralf; Wang, Lei; Csernansky, John G.; Neubert, Philip; Heun, Reinhard; Scheef, Lukas; Jessen, Frank

doi:10.1159/000161057

Cited by 48 publications

(32 citation statements)

References 45 publications

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“…Total hippocampal volume was not reduced in that sample; however, 3-dimensional surface analysis revealed a localized volume reduction [23] . Other studies with limited sample size also failed to identify hippocampal volume reduction in SMI [24] .…”

Section: Volume Loss Of the Medial Temporal Lobe Structures In Subjecmentioning

confidence: 65%

Volume Loss of the Medial Temporal Lobe Structures in Subjective Memory Impairment

Striepens¹,

Scheef

Wind³

et al. 2010

Dement Geriatr Cogn Disord

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169

109

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Background/Aims: Subjective memory impairment (SMI) has been suggested as a manifestation of Alzheimer’s Disease (AD) preceding mild cognitive impairment (MCI). In this study, we determined the volumes of the hippocampus, the entorhinal cortex (EC) and the amygdala to provide biological evidence for AD in SMI. Methods: Regional volumetric measures were manually traced on 3-Tesla MRI scans. Results: Total brain volume did not differ between the groups. Individuals with SMI had reduced volumes of the hippocampus bilaterally (right p = 0.001; left p < 0.001), the bilateral EC (right p = 0.031, left p = 0.006) and the right amygdala (p = 0.01) compared to the control group. Conclusion: Volume reduction of bilateral hippocampus, bilateral EC and right amygdala supports the concept of SMI as a very early manifestation of AD prior to MCI. SMI may indicate awareness of a degenerative process that can still be functionally compensated.

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Section: Volume Loss Of the Medial Temporal Lobe Structures In Subjecmentioning

confidence: 65%

Volume Loss of the Medial Temporal Lobe Structures in Subjective Memory Impairment

Striepens¹,

Scheef

Wind³

et al. 2010

Dement Geriatr Cogn Disord

Self Cite

169

109

View full text Add to dashboard Cite

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“…This result is consensual as it is independent from the specific method used: it has been reported using radial atrophy (Frisoni et al, , 2006Scher et al, 2007), large deformation high-dimensional brain mapping (Csernansky et al, 2000;Tang et al, 2014;Tepest et al, 2008;Wang et al, 2006Wang et al, , 2003, spherical harmonics (Gerardin et al, 2009;Lindberg et al, 2012) or a VBM-based analysis (Chételat et al, 2008); see Figure 1 for an illustration. In some studies, abnormalities were also found in medial regions of the surface, mostly corresponding to the (pre)subiculum (Frisoni et al, , 2006Wang et al, 2006) or even in all subfields Chow et al, 2012Chow et al, , 2015.…”

Section: Subfield Imaging In Admentioning

confidence: 71%

“…In their article, Tepest et al (2008) reported a slight inward deformation restricted to CA1 as compared to non-complaining healthy controls. This pattern was qualitatively similar to AD and MCI patients but did not reach the level of significance.…”

Section: Cognitively Intact Individuals At Risk For Admentioning

confidence: 96%

“…Among MCI patients, shape analysis identified a more focal pattern of atrophy, usually restricted to the lateral side of the hippocampus corresponding to CA1, and sometimes also including the subiculum (Chételat et al, 2008;Gerardin et al, 2009;Tang et al, 2014;Tepest et al, 2008). Volumetric studies showed a volume reduction predominant in CA1, and also involving either CA3/DG (Yassa et al, 2010b), CA4/DG (Pluta et al, 2012) or the subiculum La Joie et al, 2013).…”

Section: Subfield Imaging In Admentioning

confidence: 99%

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Structural imaging of hippocampal subfields in healthy aging and Alzheimer’s disease

2015

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Hippocampal atrophy, as evidenced using magnetic resonance imaging (MRI), is one of the most validated, easily accessible and widely used biomarkers of Alzheimer's disease (AD). However, its imperfect sensitivity and specificity have highlighted the need to improve the analysis of MRI data. Based on neuropathological data showing a differential vulnerability of hippocampal subfields to AD processes, neuroimaging researchers have tried to capture corresponding morphological changes within the hippocampus. The present review provides an overview of the methodological developments that allow the assessment of hippocampal subfield morphology in vivo, and summarizes the results of studies looking at the effects of AD and normal aging on these structures. Most studies highlighted a focal atrophy of the CA1 subfield in the early (predementia or even preclinical) stages of AD, before atrophy becomes more widespread at the dementia stage, consistent with the pathological literature. Preliminary studies have indicated that looking at this focal atrophy pattern rather than standard whole hippocampus volumetry improves diagnostic accuracy at the mild cognitive impairment (MCI) stage. However, controversies remain regarding changes in hippocampal subfield structure in normal aging and regarding correlations between specific subfield volume and memory abilities, very likely because of the strong methodological variability between studies. Overall, hippocampal subfield analysis has proven to be a promising technique in the study of AD. However, harmonization of segmentation protocols and studies on larger samples are needed to enable accurate comparisons between studies and to confirm the clinical utility of these techniques.

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“…Segmentation methods that can consistently and precisely delineate the structural boundaries can potentially generate more meaningful results and better detect the minute changes associated with disease progression. Shape analysis of the hippocampus, a medio-temporal lobe structure known for its involvement in long-term memory, has been applied in numerous studies of schizophrenia (Styner et al, 2004;Wang et al, 2008), Alzheimer's disease (Wang et al, 2003;Thompson et al, 2004;Wang et al, 2006;Apostolova et al, 2006;Tepest et al, 2008;Wang et al, 2009), and temporal lobe epilepsy (Hammers et al, 2007). Thus, improved accuracy and reliability of hippocampal segmentation is a relevant issue for future morphometric studies, if methods are to be eventually used for clinical purposes.…”

Section: Introductionmentioning

confidence: 99%

Optimal weights for local multi-atlas fusion using supervised learning and dynamic information (SuperDyn): Validation on hippocampus segmentation

et al. 2011

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We developed a novel method for spatially-local selection of atlas-weights in multi-atlas segmentation that combines supervised learning on a training set and dynamic information in the form of local registration accuracy estimates (SuperDyn). Supervised learning was applied using a jackknife learning approach and the methods were evaluated using leave-N-out cross-validation. We applied our segmentation method to hippocampal segmentation in 1.5T and 3T MRI from two datasets: 69 healthy middle-aged subjects (aged 44-49) and 37 healthy and cognitively-impaired elderly subjects (aged 72-84). Mean Dice overlap scores (left hippocampus, right hippocampus) of (83.3, 83.2) and (85.1, 85.3) from the respective datasets were found to be significantly higher than those obtained via equally-weighted fusion, STAPLE, and dynamic fusion. In addition to global surface distance and volume metrics, we also investigated accuracy at a spatially-local scale using a surface-based segmentation performance assessment method (SurfSPA), which generates cohort-specific maps of segmentation accuracy quantified by inward or outward displacement relative to the manual segmentations. These measurements indicated greater agreement with manual segmentation and lower variability for the proposed segmentation method, as compared to equally-weighted fusion.

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Hippocampal Surface Analysis in Subjective Memory Impairment, Mild Cognitive Impairment and Alzheimer’s Dementia

Cited by 48 publications

References 45 publications

Volume Loss of the Medial Temporal Lobe Structures in Subjective Memory Impairment

Volume Loss of the Medial Temporal Lobe Structures in Subjective Memory Impairment

Structural imaging of hippocampal subfields in healthy aging and Alzheimer’s disease

Optimal weights for local multi-atlas fusion using supervised learning and dynamic information (SuperDyn): Validation on hippocampus segmentation

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