Evidence map›Paper›PMID 20075101›Full record

ArticleAJNR. American journal of neuroradiology2010

Differential diagnosis of dementia with Lewy Bodies and Alzheimer Disease using combined MR imaging and brain perfusion single-photon emission tomography.

H Goto, K Ishii, T Uemura, N Miyamoto, T Yoshikawa, K Shimada, S Ohkawa

Abstract readComparative Study
In one paragraph

Article in AJNR. American journal of neuroradiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. A Unified Continuous Staging Framework for Alzheimer's Disease and Lewy Body Dementia via Hierarchical Anatomical Features.Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention · 2026
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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.

H GotoDepartment of Radiology and Nuclear Medicine, Hyogo Brain and Heart Center, Himeji, Japan.
K Ishii
T Uemura
N Miyamoto
T Yoshikawa
K Shimada
S Ohkawa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeDiagnostic performance by MR imaging or by SPECT alone in discriminating DLB patients from AD patients has been estimated previously. However, the performance of a combination of MR imaging and SPECT has not yet been evaluated. Our aim was to evaluate the usefulness of combining MR imaging and SPECT to discriminate mild DLB from AD. MATERIALS AND

methodsNineteen patients with mild DLB and 19 age- and cognitive decline-matched patients with mild AD underwent both SPECT and MR imaging. Hippocampal, occipital, and striatal volume and SPECT count ratios were compared. Linear discriminant and ROC analyses were performed by using the parameters of striatal volume and the occipital SPECT ratio.

resultsThe striatal volume ratio in the DLB group was significantly lower than that in the AD group. The occipital SPECT ratio in the DLB group was lower than that in the AD group. The mean area under the ROC curve from combined MR imaging and SPECT (AUC = 0.898) was higher than that from MR imaging (AUC = 0.679) or SPECT (AUC = 0.798) alone.

conclusionsBy combining MR imaging and SPECT, we were able to distinguish patients with mild DLB from those with AD with a high level of accuracy. Our findings suggest that combining MR imaging and SPECT modalities is a useful and practical approach for diagnostically differentiating DLB from AD.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseBrainCorpus StriatumDiagnosis, DifferentialFemaleHippocampusHumansImage EnhancementImage Processing, Computer-AssistedLewy Body DiseaseMagnetic Resonance ImagingMaleMental Status ScheduleOccipital Lobe

Identifiers

PMID20075101
PMCPMC7964226

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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.