Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Chincarini, A.; Sensi, Francesco De; Rei, L.; Gemme, G.; Squarcia, S.; Longo, Renata; Brun, Francesco; Tangaro, Sabina; Bellotti, R.; Amoroso, Nicola; Bocchetta, Martina; Redolfi, Alberto; Bosco, Paolo; Boccardi, Marina; Frisoni, Giovanni B.; Nobili, Flavio

doi:10.1016/j.neuroimage.2015.10.065

Cited by 80 publications

(55 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For context, normal aging typically results in annual hippocampal volume changes of less than 1% even in the elderly (23, 24). The changes observed here after high-dose RT exceed those reported in Alzheimer's disease, where hippocampal atrophy is a hallmark feature and is correlated with cognitive decline (21–23). …”

Section: Discussioncontrasting

confidence: 76%

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Seibert

Karunamuni

Bartsch

et al. 2017

International Journal of Radiation Oncology*Biology*Physics

View full text Add to dashboard Cite

Purpose/Objectives Following brain radiation therapy (RT), patients often experience memory impairment, which may be partially mediated by damage to the hippocampus. Hippocampal sparing in RT planning is the subject of recent and ongoing clinical trials. Calculating appropriate hippocampal dose constraints would be improved by efficient in vivo measurements of hippocampal damage. In this study we sought to determine whether brain RT was associated with dose-dependent hippocampal atrophy. Materials/Methods Hippocampal volume was measured with MRI in 52 patients who underwent fractionated, partial brain RT for primary brain tumors. Study patients had high-resolution, 3D volumetric MRI prior to and one year post-RT. Images were processed using software with FDA clearance and CE (Conformité Européene) marking for automated measurement of hippocampal volume. Automated results were inspected visually for accuracy. Tumor and surgical changes were censored. Mean hippocampal dose was tested for correlation with hippocampal atrophy one year post-RT. Average hippocampal volume change was also calculated for hippocampi receiving high (>40 Gy) or low (<10 Gy) mean RT dose. A multivariate analysis was conducted with linear mixed-effects modeling to evaluate other potential predictors of hippocampal volume change, including patient (random effect), age, hemisphere, sex, seizure history, and baseline volume. Statistical significance was evaluated at α=0.05. Results Mean hippocampal dose was significantly correlated with hippocampal volume loss (r=−0.24, p=0.03). Mean hippocampal volume was significantly reduced one year after high-dose RT (mean −6%, p=0.009), but not after low-dose RT. In multivariate analysis, both RT dose and patient age were significant predictors of hippocampal atrophy (p<0.01). Conclusions The hippocampus demonstrates radiation dose-dependent atrophy following treatment for brain tumors. Quantitative MRI is a non-invasive imaging technique capable of measuring radiation effects on intracranial structures. This technique could be investigated as a potential biomarker for development of reliable dose constraints for improved cognitive outcomes.

show abstract

Section: Discussioncontrasting

confidence: 76%

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Seibert

Karunamuni

Bartsch

et al. 2017

International Journal of Radiation Oncology*Biology*Physics

View full text Add to dashboard Cite

show abstract

“…Whereas there is evidence that MD is also more sensitive to age than FA among those with mild stroke48, our sample composition has implications for another aspect of our results. Whereas hippocampal volume and ICVF did not appear to provide unique information about age in this sample, both ICVF (rather than FA)49 and hippocampal volume50 are important dementia biomarkers, emphasizing that our findings, which focus on normal ageing, cannot necessarily be generalized to clinical populations.…”

Section: Discussioncontrasting

confidence: 54%

Ageing and brain white matter structure in 3,513 UK Biobank participants

et al. 2016

View full text Add to dashboard Cite

Quantifying the microstructural properties of the human brain's connections is necessary for understanding normal ageing and disease. Here we examine brain white matter magnetic resonance imaging (MRI) data in 3,513 generally healthy people aged 44.64-77.12 years from the UK Biobank. Using conventional water diffusion measures and newer, rarely studied indices from neurite orientation dispersion and density imaging, we document large age associations with white matter microstructure. Mean diffusivity is the most age-sensitive measure, with negative age associations strongest in the thalamic radiation and association fibres. White matter microstructure across brain tracts becomes increasingly correlated in older age. This may reflect an age-related aggregation of systemic detrimental effects. We report several other novel results, including age associations with hemisphere and sex, and comparative volumetric MRI analyses. Results from this unusually large, single-scanner sample provide one of the most extensive characterizations of age associations with major white matter tracts in the human brain.

show abstract

“…Among neurodegenerative diseases, Alzheimer's disease (AD) is the most common type of dementia affecting over 5 million people [7, 8] and is characterized by a well-known stereotyped pattern involving a whole brain left privileged atrophy, especially affecting some regions related to cognitive functionality as the hippocampus [9–13]. However, it is not clear yet whether the combined use of MRI and DWI modalities can significantly enhance its diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Topological Measurements of DWI Tractography for Alzheimer’s Disease Detection

Amoroso

Monaco

Tangaro

et al. 2017

Computational and Mathematical Methods in Medicine

Self Cite

View full text Add to dashboard Cite

Neurodegenerative diseases affect brain morphology and connectivity, making complex networks a suitable tool to investigate and model their effects. Because of its stereotyped pattern Alzheimer's disease (AD) is a natural benchmark for the study of novel methodologies. Several studies have investigated the network centrality and segregation changes induced by AD, especially with a single subject approach. In this work, a holistic perspective based on the application of multiplex network concepts is introduced. We define and assess a diagnostic score to characterize the brain topology and measure the disease effects on a mixed cohort of 52 normal controls (NC) and 47 AD patients, from Alzheimer's Disease Neuroimaging Initiative (ADNI). The proposed topological score allows an accurate NC-AD classification: the average area under the curve (AUC) is 95% and the 95% confidence interval is 92%–99%. Besides, the combination of topological information and structural measures, such as the hippocampal volumes, was also investigated. Topology is able to capture the disease signature of AD and, as the methodology is general, it can find interesting applications to enhance our insight into disease with more heterogeneous patterns.

show abstract

Integrating longitudinal information in hippocampal volume measurements for the early detection of Alzheimer's disease

Abstract: Longitudinal volume measurements can provide meaningful clinical insight and added value with respect to the baseline provided the analysis procedure embeds the longitudinal information.

Cited by 80 publications

References 54 publications

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Radiation Dose–Dependent Hippocampal Atrophy Detected With Longitudinal Volumetric Magnetic Resonance Imaging

Ageing and brain white matter structure in 3,513 UK Biobank participants

Topological Measurements of DWI Tractography for Alzheimer’s Disease Detection

Contact Info

Product

Resources

About