Evidence map›Paper›PMID 22158129›Full record

ReviewTopics in magnetic resonance imaging : TMRI2010

Challenges of High-resolution Diffusion Imaging of the Human Medial Temporal Lobe in Alzheimer Disease.

Michael M Zeineh, Samantha Holdsworth, Stefan Skare, Scott W Atlas, Roland Bammer

Abstract readReview
In one paragraph

Review in Topics in magnetic resonance imaging : TMRI, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

5 authors.

Michael M ZeinehStanford University, Stanford, CA 94305-5105, USA. mzeineh@stanford.edu
Samantha Holdsworth
Stefan Skare
Scott W Atlas
Roland Bammer

Funding

Improving SENSE MRI for Spiral and Echo-planar Imaging in StrokeR01EB002711 · NIBIB · STANFORD UNIVERSITY · PI ALBERS, GREGORY W · 2003 to 2015
$5.1M
Short Axis EPI for Diffusion Tensor MRI at High FieldR01EB008706 · NIBIB · STANFORD UNIVERSITY · PI BAMMER, ROLAND · 2008 to 2011
$2.7M
Real-Time MRI Motion Correction SystemR01EB011654 · NIBIB · STANFORD UNIVERSITY · PI ZEINEH, MICHAEL M · 2010 to 2013
$2.4M
Novel Acquisition Methods for Diffusion MRIR01EB006526 · NIBIB · STANFORD UNIVERSITY · PI BAMMER, ROLAND · 2009 to 2010
$791k
NIBIB NIH HHS R01 EB002711NIBIB NIH HHS R01 EB006526NIBIB NIH HHS R01 EB008706NIBIB NIH HHS R01 EB011654
6 · The paper itself

Abstract

The human medial temporal lobe performs an essential role in memory formation and retrieval. Diseases involving the hippocampus such as Alzheimer disease present a unique opportunity for advanced imaging techniques to detect abnormalities at an early stage. In particular, it is possible that diffusion imaging will measure abnormal microarchitecture beyond the realm of macroscopic imaging. However, this task is formidable because of the detailed anatomy of the medial temporal lobe, the difficulties in obtaining high-quality diffusion images of adequate resolution, and the challenges in diffusion data processing. Moreover, it is unclear if any differences will be significant for an individual patient or simply groups of patients. Successful endeavors will need to address each of these challenges in an integrated fashion. The rewards of such analysis may be detection of microscopic disease in vivo, which could represent a landmark accomplishment for the field of neuroradiology.

Indexed as

Alzheimer DiseaseBrain MappingDiffusion Magnetic Resonance ImagingHippocampusHumansImage EnhancementImage Interpretation, Computer-AssistedReproducibility of ResultsTemporal Lobe

Identifiers

PMID22158129
PMCPMC3238799

What OpenQuestion holds

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Registered trials

None linked

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.