Evidence map›Paper›PMID 32635379›Full record

ArticleDiagnostics (Basel, Switzerland)2020

Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer's Disease.

Mindaugas Baranauskas, Rytis Jurkonis, Arūnas Lukoševičius, Monika Makūnaitė, Vaidas Matijošaitis, Rymantė Gleiznienė, Daiva Rastenytė

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Mindaugas BaranauskasBiomedical Engineering Institute, Kaunas University of Technology, K. Baršausko g. 59-454, LT-44029 Kaunas, Lithuania.ORCID 0000-0003-0204-4886
Rytis JurkonisBiomedical Engineering Institute, Kaunas University of Technology, K. Baršausko g. 59-454, LT-44029 Kaunas, Lithuania.ORCID 0000-0002-9481-1773
Arūnas LukoševičiusBiomedical Engineering Institute, Kaunas University of Technology, K. Baršausko g. 59-454, LT-44029 Kaunas, Lithuania.ORCID 0000-0002-9268-5347
Monika MakūnaitėBiomedical Engineering Institute, Kaunas University of Technology, K. Baršausko g. 59-454, LT-44029 Kaunas, Lithuania.ORCID 0000-0002-7714-8850
Vaidas MatijošaitisLithuanian University of Health Sciences, A. Mickevičiaus g. 9, LT-44307 Kaunas, Lithuania.ORCID 0000-0001-9940-0255
Rymantė GleiznienėLithuanian University of Health Sciences, A. Mickevičiaus g. 9, LT-44307 Kaunas, Lithuania.ORCID 0000-0002-5206-3033
Daiva RastenytėLithuanian University of Health Sciences, A. Mickevičiaus g. 9, LT-44307 Kaunas, Lithuania.ORCID 0000-0002-5603-2357

Funding

Lietuvos Mokslo Taryba MIP-17-457
6 · The paper itself

Abstract

We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer's disease (AD) from healthy controls (HC). Standard neuropsychological evaluation and transcranial sonography (TCS) for endogenous brain tissue motion data collection are performed for 20 patients with AD and for 20 age- and sex-matched HC in a prospective manner. Essential modifications of our previous method in US waveform parametrization, raising the confidence of micrometer-range displacement signals in the presence of noise, are done. Four logistic regression models are constructed, and receiver operating characteristic (ROC) curve analyses are applied. All models have cut-offs from 61.0 to 68.5% and separate AD patients from HC with a sensitivity of 89.5% and a specificity of 100%. The area under a ROC curve of predicted probability in all models is excellent (from 95.2 to 95.7%). According to our models, AD patients can be differentiated from HC by a sharper morphology of some individual MTL spatial point displacements (i.e., by spreading the spectrum of displacements to the high-end frequencies with higher variability across spatial points within a region), by lower displacement amplitude differences between adjacent spatial points (i.e., lower strain), and by a higher interaction of these attributes.

Indexed as

Alzheimer’s diseasebrain pulsationdiagnosticradiofrequency ultrasoundsonographystrain

Identifiers

PMID32635379
PMCPMC7399840

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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.