Evidence map›Paper›PMID 33693995›Full record

ArticleEuropean radiology2021

Neurite orientation dispersion and density imaging parameters may help for the evaluation of epileptogenic tubers in tuberous sclerosis complex patients.

Xiali Shao, Xuewei Zhang, Wenrui Xu, Zhe Zhang, Jieying Zhang, Hua Guo, Tao Jiang, Weihong Zhang

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Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

11 citing papers in PubMed, 21 citations in OpenAlex.

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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

8 authors at 4 institutions in 1 country.

Xiali ShaoDepartment of Radiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, People's Republic of China.
Xuewei ZhangDepartment of Interventional Radiology, Emergency General Hospital, Beijing, People's Republic of China.
Wenrui XuDepartment of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, People's Republic of China.
Zhe ZhangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China.
Jieying ZhangCenter for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China.
Hua GuoCenter for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, People's Republic of China.
Tao JiangChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, People's Republic of China. zacharytaojiang@163.com.ORCID http://orcid.org/0000-0002-8529-4487
Weihong ZhangDepartment of Radiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Dongcheng District, Beijing, 100730, People's Republic of China. zhangweihong@pumch.cn.
Capital Medical University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNTsinghua University · CNBeijing Hospital · CN

Funding

Capital's Funds for Health Improvement and Research CFH 2018-2-2042National Key Research and Development Program of China 2016YFC0901500; 2016YFC0901501National Natural Science Foundation of China 81871335
6 · The paper itself

Abstract

objectivesTo investigate the usefulness of neurite orientation dispersion and density imaging (NODDI) in evaluating cortical tubers, especially epileptogenic tubers in tuberous sclerosis complex (TSC) patients.

methodsHigh-resolution conventional MRI and multi-shell diffusion-weighted imaging were performed in 27 TSC patients. Diffusion images were fitted to NODDI and DTI models. Tubers were visually assessed on different image types and scored by two neuroradiologists. For 10 patients who underwent epilepsy surgery, the contrast ratios between lesion and background tissue were measured on different image types, and these were compared between 16 epileptogenic tubers and 92 non-epileptogenic tubers.

resultsThere were significant differences in lesion conspicuity scores and lesion-background contrast ratios across different sequences (both p < 0.001). The post hoc analysis showed that both the conspicuity scores and contrast ratios of intracellular volume fraction (ICVF) derived from NODDI were higher than other image types. For the 16 epileptogenic tubers, lesion visibility on ICVF was better/equal in 4/12 tubers compared with conventional MRI and better/equal in 5/11 tubers compared with DTI. Significant differences were observed between epileptogenic and non-epileptogenic tubers on diffusion maps, especially on orientation dispersion index derived from NODDI (p < 0.0001).

conclusionsICVF demonstrated higher contrast than conventional MRI and DTI, which helped detection of subtle epileptogenic tubers. Moreover, NODDI parameters showed the potential to identify epileptogenicity. KEY POINTS: • The noninvasive localization of epileptogenic cortical tubers is essential for the preparation of epilepsy surgery for TSC patients. • ICVF derived from NODDI showed greater contrast than conventional MRI and DTI in detecting tubers, especially subtle epileptogenic ones. • Diffusion parameters, especially ODI derived from NODDI, can support the identification of epileptogenicity.

Indexed as

EpilepsyTuberous SclerosisBrainDiffusion Magnetic Resonance ImagingDiffusion Tensor ImagingHumansNeuritesDiffusionDiffusion tensor imagingEpilepsyMagnetic resonance imagingTuberous sclerosis complex

Identifiers

PMID33693995
OpenAlexW3134570458

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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.