Evidence map›Paper›PMID 36292180›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Native T1 Mapping-Based Radiomics for Noninvasive Prediction of the Therapeutic Effect of Pulmonary Arterial Hypertension.

Yue Wang, Lu Lin, Xiao Li, Jian Cao, Jian Wang, Zhi-Cheng Jing, Sen Li, Hao Liu, Xin Wang, Zheng-Yu Jin and 1 more

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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.

Yue WangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Lu LinDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Xiao LiDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Jian CaoDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Jian WangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Zhi-Cheng JingDepartment of Cardiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.ORCID 0000-0003-0493-0929
Sen LiDepartment of Research & Development, Yizhun Medical AI Co., Ltd., 12th Floor 12, Block A, Beihang Zhizhen Building, No. 7 Zhichun Road, Haidian District, Beijing 100088, China.
Hao LiuDepartment of Research & Development, Yizhun Medical AI Co., Ltd., 12th Floor 12, Block A, Beihang Zhizhen Building, No. 7 Zhichun Road, Haidian District, Beijing 100088, China.
Xin WangDepartment of Research & Development, Yizhun Medical AI Co., Ltd., 12th Floor 12, Block A, Beihang Zhizhen Building, No. 7 Zhichun Road, Haidian District, Beijing 100088, China.
Zheng-Yu JinDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.
Yi-Ning WangDepartment of Radiology, State Key Laboratory of Complex Severe and Rare Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College Hospital, No. 1, Shuaifuyuan, Dongcheng District, Beijing 100730, China.

Funding

Beijing Municipal Natural Science Foundation 7214303National Natural Science Foundation of China 82102158
6 · The paper itself

Abstract

(1) Background: Novel markers for predicting the short-term therapeutic effect of pulmonary arterial hypertension (PAH) to assist in the prompt initiation of tailored treatment strategies are greatly needed and highly desirable. The aim of the study was to investigate the role of cardiac magnetic resonance (CMR) native T1 mapping radiomics in predicting the short-term therapeutic effect in PAH patients; (2) Methods: Fifty-five PAH patients who received targeted therapy were retrospectively included. Patients were subdivided into an effective group and an ineffective group by assessing the therapeutic effect after ≥3 months of treatment. All patients underwent CMR examinations prior to the beginning of the therapy. Radiomics features from native T1 mapping images were extracted. A radiomics model was constructed using the support vector machine (SVM) algorithm for predicting the therapeutic effect; (3) Results: The SVM radiomics model revealed favorable performance for predicting the therapeutic effect with areas under the receiver operating characteristic curve of 0.955 in the training cohort and 0.893 in the test cohort, respectively. With the optimal cutoff value, the radiomics model showed accuracies of 0.909 and 0.818 in the training and test cohorts, respectively; (4) Conclusions: The CMR native T1 mapping-based radiomics model holds promise for predicting the therapeutic effect in PAH patients.

Indexed as

native T1 mappingpulmonary arterial hypertensionradiomics

Identifiers

PMID36292180
PMCPMC9600513

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.