Transcranial ultrasound pulse stimulation reduces cortical atrophy in Alzheimer's patients: A follow‐up study

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Introduction

Ultrasound for the brain is a revolutionary therapeutic concept. The first clinical data indicate that 2–4 weeks of therapy with transcranial pulse stimulation (TPS) improve functional networks and cognitive performance of Alzheimer's disease (AD) patients for up to 3 months. No data currently exist on possible benefits concerning brain morphology, namely the cortical atrophy characteristic of AD.

Methods

We performed a pre‐/post‐therapy analysis of cortical thickness in a group of N = 17 AD patients.

Results

We found a significant correlation between neuropsychological improvement and cortical thickness increase in AD‐critical brain areas.

Discussion

AD patients who benefit from TPS appear to manifest reduced cortical atrophy within the default mode network in particular, whose memory‐related subsystems are believed to be disrupted in AD. TPS may therefore hold promise as a new add‐on therapy for AD.

Related collections

Most cited references 23

Record: found
Abstract: found
Article: not found

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Rahul Desikan, Florent Ségonne, Bruce Fischl … (2006)

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

0 comments Cited 2657 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Cortical surface-based analysis. I. Segmentation and surface reconstruction.

Anders Dale, Bruce Fischl, Martin I. Sereno (2000)

Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging. Copyright 1999 Academic Press.

0 comments Cited 1687 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Within-subject template estimation for unbiased longitudinal image analysis.

Martin Reuter, Nicholas Schmansky, H. Diana Rosas … (2012)

Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

0 comments Cited 507 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Tudor Popescu: tudor.popescu@univie.ac.at

Roland Beisteiner: roland.beisteiner@meduniwien.ac.at

Journal

Journal ID (nlm-ta): Alzheimers Dement (N Y)

Journal ID (iso-abbrev): Alzheimers Dement (N Y)

Journal ID (doi): 10.1002/(ISSN)2352-8737

Journal ID (publisher-id): TRC2

Title: Alzheimer's & Dementia : Translational Research & Clinical Interventions

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Electronic): 2352-8737

Publication date (Electronic): 25 February 2021

Publication date Collection: 2021

Volume: 7

Issue: 1 ( doiID: 10.1002/trc2.v7.1 )

Electronic Location Identifier: e12121

Affiliations

[ ¹ ] Department of Behavioural and Cognitive Biology University of Vienna Vienna Austria

[ ² ] Department of Neurology Medical University of Vienna Vienna Austria

[ ³ ] Centre for Clinical Brain Sciences University of Edinburgh Edinburgh UK

Author notes

[*] [* ] Correspondence

Tudor Popescu, Department of Behavioural and Cognitive Biology, University of Vienna, Althanstrasse 14, A‐1090 Vienna, Austria.

E‐mail: tudor.popescu@ 123456univie.ac.at

Roland Beisteiner, Department of Neurology, Medical University of Vienna, Spitalgasse 23, A‐1090 Vienna, Austria. E‐mail: roland.beisteiner@ 123456meduniwien.ac.at

Article

Publisher ID: TRC212121

DOI: 10.1002/trc2.12121

PMC ID: 7906128

PubMed ID: 33681449

SO-VID: 1189d360-e498-48d7-abe3-8ddde750b1df

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

History

Date received : 10 April 2020

Date revision received : 01 September 2020

Date accepted : 11 November 2020

Page count

Figures: 1, Tables: 1, Pages: 6, Words: 3226

Funding

Funded by: Medical University of Vienna and University of Vienna

Award ID: SO10300020

Funded by: Austrian Science Fund , open-funder-registry 10.13039/501100002428;

Award ID: P23611

Award ID: KLIF453

Award ID: KLIF455

Custom metadata

source-schema-version-number 2.0

cover-date 2021

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:5.9.9 mode:remove_FC converted:25.02.2021

Keywords: alzheimer's disease,brain stimulation,cortical atrophy,cortical thickness,default mode network,ultrasound

Data availability:

Keywords: alzheimer's disease, brain stimulation, cortical atrophy, cortical thickness, default mode network, ultrasound

Transcranial ultrasound pulse stimulation reduces cortical atrophy in Alzheimer's patients: A follow‐up study

Read this article at

Abstract

Introduction

Methods

Results

Discussion

Related collections

Alternative approaches to Alzheimer's Disease

Most cited references 23

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Cortical surface-based analysis. I. Segmentation and surface reconstruction.

Within-subject template estimation for unbiased longitudinal image analysis.

Author and article information

Contributors

Journal

Affiliations

Author notes

Article

History

Page count

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 350

Cited by 16

Most referenced authors 263