ArticleHuman brain mapping2019
Discriminating Alzheimer's disease progression using a new hippocampal marker from T1-weighted MRI: The local surface roughness.
Article in Human brain mapping, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Grey matter changes on brain MRI in subjective cognitive decline: a systematic review.Alzheimer's research & therapy · 2022Pooled it
- Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment.The Cochrane database of systematic reviews · 2020Pooled it
- A radiomics model predicts progression from mild cognitive impairment to alzheimer's disease using structural MRI.Scientific reports · 2025Article
- Advances in the use of structural and diffusion magnetic resonance imaging for characterizing SCD and MCI due to Alzheimer's disease.Frontiers in neuroscience · 2025Review
- Structural disruption in subjective cognitive decline and mild cognitive impairment.Brain imaging and behavior · 2024Article
- Neuroanatomical and neurocognitive changes associated with subjective cognitive decline.Frontiers in medicine · 2023Article
- Neuroimaging modalities in the detection of Alzheimer's disease-associated biomarkers.Psychoradiology · 2023Review
- Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease.Molecular neurodegeneration · 2020Review
- Multiparametric imaging hippocampal neurodegeneration and functional connectivity with simultaneous PET/MRI in Alzheimer's disease.European journal of nuclear medicine and molecular imaging · 2020Article
- Discriminating Alzheimer's disease progression using a new hippocampal marker from T1-weighted MRI: The local surface roughness.Human brain mapping · 2019Article
- Emotion Processing Dysfunction in Alzheimer's Disease: An Overview of Behavioral Findings, Systems Neural Correlates, and Underlying Neural Biology.American journal of Alzheimer's disease and other dementiasReview
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Authors and funding
5 authors.
Funding
Abstract
Hippocampal atrophy is one of the main hallmarks of Alzheimer's disease (AD). However, there is still controversy about whether this sign is a robust finding during the early stages of the disease, such as in mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Considering this background, we proposed a new marker for assessing hippocampal atrophy: the local surface roughness (LSR). We tested this marker in a sample of 307 subjects (normal control (NC) = 70, SCD = 87, MCI = 137, AD = 13). In addition, 97 patients with MCI were followed-up over a 3-year period and classified as stable MCI (sMCI) (n = 61) or progressive MCI (pMCI) (n = 36). We did not find significant differences using traditional markers, such as normalized hippocampal volumes (NHV), between the NC and SCD groups or between the sMCI and pMCI groups. However, with LSR we found significant differences between the sMCI and pMCI groups and a better ability to discriminate between NC and SCD. The classification accuracy of the LSR for NC and SCD was 68.2%, while NHV had a 57.2% accuracy. In addition, the classification accuracy of the LSR for sMCI and pMCI was 74.3%, and NHV had a 68.3% accuracy. Cox proportional hazards models adjusted for age, sex, and education were used to estimate the relative hazard of progression from MCI to AD based on hippocampal markers and conversion times. The LSR marker showed better prediction of conversion to AD than NHV. These results suggest the relevance of considering the LSR as a new hippocampal marker for the AD continuum.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.