Related Experiment Video

Updated: Jun 8, 2026

Three-Dimensional Shape Modeling and Analysis of Brain Structures
05:33

Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Increasing power to predict mild cognitive impairment conversion to Alzheimer's disease using hippocampal atrophy

Kelvin K Leung1, Kai-Kai Shen, Josephine Barnes

  • 1Centre for Medical Image Computing, University College London, WC1E 6BT, UK.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 1, 2010
PubMed

Insights

Identifying mild cognitive impairment (MCI) subjects who will progress to Alzheimer's disease (AD) is crucial. This study uses hippocampal shape analysis to improve the prediction of MCI to AD conversion, aiding clinical trials and patient care.

Area of Science:

  • Neuroimaging
  • Neurology
  • Biostatistics

Background:

  • Predicting Alzheimer's disease (AD) progression in mild cognitive impairment (MCI) is vital for early intervention and clinical trial design.
  • Hippocampal volume and atrophy rates are established predictors of cognitive decline and progression to AD.
  • Current methods for assessing hippocampal changes may lack the statistical power for precise MCI conversion prediction.

Purpose of the Study:

  • To develop and validate a novel method for identifying individuals with MCI who are likely to convert to AD.
  • To enhance the statistical power of detecting hippocampal atrophy indicative of AD progression.
  • To improve the classification accuracy of MCI converters versus stable MCI subjects.

Main Methods:

  • Utilized statistical shape models to analyze hippocampal shape differences between 60 normal controls and 60 AD subjects.
  • Generated regions of interest (ROIs) by thresholding p-maps derived from shape analysis at varying significance levels.
  • Calculated hippocampal atrophy rates within these ROIs using the boundary shift integral to classify MCI subjects.

Main Results:

  • The developed ROIs based on hippocampal shape analysis significantly increased statistical power for classification.
  • Hippocampal atrophy rates calculated within the novel ROIs demonstrated higher accuracy in distinguishing MCI converters from stable MCI subjects.
  • Successfully classified 86 MCI converters and 128 MCI stable subjects with improved discriminative ability.

Conclusions:

  • Statistical shape analysis of the hippocampus can generate informative ROIs for detecting AD-related atrophy.
  • The boundary shift integral within these specific ROIs enhances the prediction of MCI to AD conversion.
  • This approach offers a more powerful tool for identifying at-risk individuals in clinical settings and research.

More Related Videos

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease09:06

Whole-brain Segmentation and Change-point Analysis of Anatomical Brain MRI—Application in Premanifest Huntington's Disease

Published on: June 9, 2018

Related Concept Videos

Alzheimer Disease l: Introduction01:29

Alzheimer Disease l: Introduction

Alzheimer disease is a chronic, progressive, and irreversible neurodegenerative disorder and the most common cause of dementia in older adults. It leads to gradual neuronal loss, causing cognitive decline, behavioral changes, and loss of functional independence.Risk Factors and EtiologyThe disease is multifactorial. Age is the strongest risk factor, with prevalence doubling every 5 years after age 65. Genetic factors include mutations in genes such as APP, PSEN1, and PSEN2, which are associated...
Alzheimer's Disease: Overview01:26

Alzheimer's Disease: Overview

Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
The clinical diagnosis of AD hinges on the presence of memory and other cognitive impairments. Biomarkers, such as changes in Aβ and tau...
Alzheimer Disease ll: Pathophysiology01:23

Alzheimer Disease ll: Pathophysiology

Alzheimer disease involves structural changes in the brain that begin long before symptoms appear. The most distinctive features are extracellular neuritic plaques and intracellular neurofibrillary tangles.Neuritic plaques form in the cerebral cortex and around blood vessels. These plaques contain a dense core of beta-amyloid (Aβ)—a toxic protein fragment that clumps outside neurons. The core is surrounded by damaged neuronal extensions, as well as reactive astrocytes and microglia. Abnormal...
Dementia l: Introduction01:22

Dementia l: Introduction

Dementia is an acquired, progressive syndrome characterized by a decline in multiple cognitive domains severe enough to impair daily functioning and reduce independence. Although memory loss is a central feature, the diagnosis requires additional deficits involving language, executive function, visuospatial skills, judgment, calculation, or abstract reasoning. These cognitive impairments reflect underlying neurodegenerative or vascular processes that gradually disrupt neuronal networks...