Evidence map›Paper›PMID 24900138›Full record

ArticleNuclear medicine and molecular imaging2014

Automated Analysis of (123)I-beta-CIT SPECT Images with Statistical Probabilistic Anatomical Mapping.

Jae Seon Eo, Ho-Young Lee, Jae Sung Lee, Yu Kyung Kim, Bum-Seok Jeon, Dong Soo Lee

Open access · bronzeAbstract read
In one paragraph

Article in Nuclear medicine and molecular imaging, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.3field-weighted citation impact, top 36% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 2 institutions in 1 country.

Jae Seon EoDepartment of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehang-ro, Jongro-gu, Seoul, 110-744 Korea ; Department of Nuclear Medicine, Korea University Anam Hospital, Seoul, Korea.
Ho-Young LeeDepartment of Nuclear Medicine, Seoul National University Bundang Hospital, Gyeonggi-do, Korea.
Jae Sung LeeDepartment of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehang-ro, Jongro-gu, Seoul, 110-744 Korea.
Yu Kyung KimDepartment of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehang-ro, Jongro-gu, Seoul, 110-744 Korea ; Department of Nuclear Medicine, Boramae Medical Center, Seoul, Korea.
Bum-Seok JeonDepartment of Neurology, Seoul National University College of Medicine, Seoul, Korea.
Dong Soo LeeDepartment of Nuclear Medicine, Seoul National University College of Medicine, 101 Daehang-ro, Jongro-gu, Seoul, 110-744 Korea ; Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, Korea.
Seoul National University · KRSeoul National University Bundang Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPopulation-based statistical probabilistic anatomical maps have been used to generate probabilistic volumes of interest for analyzing perfusion and metabolic brain imaging. We investigated the feasibility of automated analysis for dopamine transporter images using this technique and evaluated striatal binding potentials in Parkinson's disease and Wilson's disease. MATERIALS AND

methodsWe analyzed 2β-Carbomethoxy-3β-(4-(123)I-iodophenyl)tropane ((123)I-beta-CIT) SPECT images acquired from 26 people with Parkinson's disease (M:F = 11:15, mean age = 49 ± 12 years), 9 people with Wilson's disease (M: F = 6:3, mean age = 26 ± 11 years) and 17 normal controls (M:F = 5:12, mean age = 39 ± 16 years). A SPECT template was created using striatal statistical probabilistic map images. All images were spatially normalized onto the template, and probability-weighted regional counts in striatal structures were estimated. The binding potential was calculated using the ratio of specific and nonspecific binding activities at equilibrium. Voxel-based comparisons between groups were also performed using statistical parametric mapping.

resultsQualitative assessment showed that spatial normalizations of the SPECT images were successful for all images. The striatal binding potentials of participants with Parkinson's disease and Wilson's disease were significantly lower than those of normal controls. Statistical parametric mapping analysis found statistically significant differences only in striatal regions in both disease groups compared to controls.

conclusionWe successfully evaluated the regional (123)I-beta-CIT distribution using the SPECT template and probabilistic map data automatically. This procedure allows an objective and quantitative comparison of the binding potential, which in this case showed a significantly decreased binding potential in the striata of patients with Parkinson's disease or Wilson's disease.

Indexed as

123I-beta-CITAutomated analysisParkinson’s diseaseStatistical probabilistic anatomical mappingWilson’s disease

Identifiers

PMID24900138
PMCPMC4035165
OpenAlexW2036081700

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.