Evidence map›Paper›PMID 33778732›Full record

ArticleRadiology. Imaging cancer2020

Decoding and Systematization of Medical Imaging Features of Multiple Human Malignancies.

Lu Wang, Zhaoyu Liu, Jiayi Xie, Yuheng Chen, Xiaoqi Zhao, Zifan You, Mingshu Yang, Wei Qian, Jie Tian, Kristen Yeom and 1 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology. Imaging cancer, 2020. 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
0.1field-weighted citation impact, top 52% 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

11 authors at 3 institutions in 2 countries.

Lu WangSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Zhaoyu LiuSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Jiayi XieSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Yuheng ChenSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Xiaoqi ZhaoSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Zifan YouSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Mingshu YangSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Wei QianSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).
Jie TianSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).ORCID 0000-0003-2025-1870
Kristen YeomSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).ORCID 0000-0001-9860-3368
Jiangdian SongSchool of Medical Informatics, China Medical University, Shenyang, Liaoning, China (L.W., M.Y., J.S.); Department of Radiology, Shenjing Hospital of China Medical University, Shenyang, Liaoning, China (Z.L.); Department of Radiology, China Medical University, Shenyang, Liaoning, China (J.X., Y.C., X.Z., Z.Y.); Department of Electric and Computer Engineering, University of Texas-El Paso, El Paso, Tex (W.Q.); CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Radiology, Stanford University School of Medicine, 1201 Welch Rd Lucas Center PS055, Palo Alto, CA 94305 (K.Y., J.S.).ORCID 0000-0002-3355-9930
China Medical University · CNChinese Academy of Sciences · CNThe University of Texas at El Paso · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To summarize the data of previously reported medical imaging features on human malignancies to provide a scientific basis for more credible imaging feature selection for future studies. Materials and Methods: A search was performed in PubMed from database inception through March 23, 2018, for studies clearly stating the decoding of medical imaging features for malignancy-related objectives and/or hypotheses. The Newcastle-Ottawa scale was used for quality assessment of the included studies. Unsupervised hierarchical clustering was performed on the manually extracted features from each included study to identify the application rules of medical imaging features across human malignancies. CT images of 1000 retrospective patients with non-small cell lung cancer were used to reveal a pattern for the value distribution of complex texture features. Results: A total of 5026 imaging features of malignancies affecting 20 parts of the human body from 930 original articles were collated and assessed in this study. A meta-feature construct was proposed to facilitate the investigation of details of any high-dimensional complex imaging features of malignancy. A correlation atlas was constructed to clarify the general rules of applying medical imaging features to the analysis of human malignancy. Assessment of this data revealed a pattern of value distributions of the most commonly reported texture features across human malignancies. Furthermore, the significant expression of the gene mutational signature 1B across human cancer was highly consistent with the presence of the run length imaging feature across different human malignancy types. Conclusion: The results of this study may facilitate more credible imaging feature selection in all oncology tasks across a wide spectrum of human malignancies and help to reduce bias and redundancies in future medical imaging studies.

Indexed as

Carcinoma, Non-Small-Cell LungDiagnosis, Computer-AssistedLung NeoplasmsHumansRetrospective StudiesTomography, X-Ray Computed

Identifiers

PMID33778732
PMCPMC7983692
OpenAlexW3014785343

What OpenQuestion holds

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LicenceCC BY
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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.