Evidence map›Paper›PMID 30178281›Full record

ArticleMetabolic brain disease2018

Contourlet-based hippocampal magnetic resonance imaging texture features for multivariant classification and prediction of Alzheimer's disease.

Ni Gao, Li-Xin Tao, Jian Huang, Feng Zhang, Xia Li, Finbarr O'Sullivan, Si-Peng Chen, Si-Jia Tian, Gehendra Mahara, Yan-Xia Luo and 5 more

Abstract read
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In one paragraph

Article in Metabolic brain disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
–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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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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

15 authors.

Ni GaoSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Li-Xin TaoSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Jian HuangDepartment of Epidemiology & Public Health, University College Cork, Cork, 78746, Ireland.
Feng ZhangSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Xia LiDepartment of Epidemiology & Public Health, University College Cork, Cork, 78746, Ireland.
Finbarr O'SullivanDepartment of Epidemiology & Public Health, University College Cork, Cork, 78746, Ireland.
Si-Peng ChenSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Si-Jia TianSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Gehendra MaharaSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Yan-Xia LuoSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Qi GaoSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Xiang-Tong LiuSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China.
Wei WangSchool of Medical Science, Edith Cowan University, Perth, WA, 6050, Australia.
Zhi-Gang LiangDepartment of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China.
Xiu-Hua GuoSchool of Public Health, Capital Medical University, No. 10 XitoutiaoYouanmenwai Street, Beijing, 100069, China. statguo@ccmu.edu.cn.ORCID http://orcid.org/0000-0002-6505-4945

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study is aimed to assess whether the addition of contourlet-based hippocampal magnetic resonance imaging (MRI) texture features to multivariant models improves the classification of Alzheimer's disease (AD) and the prediction of mild cognitive impairment (MCI) conversion, and to evaluate whether Gaussian process (GP) and partial least squares (PLS) are feasible in developing multivariant models in this context. Clinical and MRI data of 58 patients with probable AD, 147 with MCI, and 94 normal controls (NCs) were collected. Baseline contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters based on MRI, and regional CMgl measurement based on fluorine-18 fluorodeoxyglucose-positron emission tomography were included to develop GP and PLS models to classify different groups of subjects. GPR1 model, which incorporated MRI texture features and was based on GPG, performed better in classifying different groups of subjects than GPR2 model, which used the same algorithm and had the same data as GPR1 except that MRI texture features were excluded. PLS model, which included the same variables as GPR1 but was based on the PLS algorithm, performed best among the three models. GPR1 accurately predicted 82.2% (51/62) of MCI convertors confirmed during the 2-year follow-up period, while this figure was 53 (85.5%) for PLS model. GPR1 and PLS models accurately predicted 58 (79.5%) vs. 61 (83.6%) of 73 patients with stable MCI, respectively. For seven patients with MCI who converted to NCs, PLS model accurately predicted all cases (100%), while GPR1 predicted six (85.7%) cases. The addition of contourlet-based MRI texture features to multivariant models can effectively improve the classification of AD and the prediction of MCI conversion to AD. Both GPR and LPS models performed well in the classification and predictive process, with the latter having significantly higher classification and predictive accuracies. Advances in knowledge: We combined contourlet-based hippocampal MRI texture features, medical histories, symptoms, neuropsychological tests, volume-based morphometric (VBM) parameters, and regional CMgl measurement to develop models using GP and PLS algorithms to classify AD patients.

Indexed as

AgedAged, 80 and overAlzheimer DiseaseFemaleFollow-Up StudiesHippocampusHumansMagnetic Resonance ImagingMaleMiddle AgedMultivariate AnalysisAlzheimer’s diseaseContourletsGaussian processMild cognitive impairmentPartial least squaresTexture feature

Identifiers

PMID30178281

What OpenQuestion holds

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Registered trials

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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.