Evidence map›Paper›PMID 40065426›Full record

ArticleCancer imaging : the official publication of the International Cancer Imaging Society2025

DCE-MRI quantitative analysis and MRI-based radiomics for predicting the early efficacy of microwave ablation in lung cancers.

Chen Yang, Fandong Zhu, Jing Yang, Min Wang, Shijun Zhang, Zhenhua Zhao

Abstract read
In one paragraph

Article in Cancer imaging : the official publication of the International Cancer Imaging Society, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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.

Chen YangDepartment of Radiology, Shaoxing People's Hosipital, Shaoxing, China.
Fandong ZhuDepartment of Radiology, Shaoxing People's Hosipital, Shaoxing, China.
Jing YangDepartment of Radiology, Shaoxing People's Hosipital, Shaoxing, China.
Min WangDepartment of Pathology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, China.
Shijun Zhang *Department of Pathology, School of Medicine, Zhongda Hospital, Southeast University, Nanjing, China. shujun_zhang@163.com.
Zhenhua Zhao *Department of Radiology, Shaoxing People's Hosipital, Shaoxing, China. zhao2075@163.com.

Funding

National Health Commission innovative applied research project No. RCLX2315018Shaoxing City health science and technology project No. 2023SKY024the Key Laboratory of Functional Molecular Imaging of Tumor and Interventional Diagnosis and Treatment of Shaoxing city No. 2020ZDSYSO1Zhejiang Provincial Medical and Health Research Fund Project 2025KY1677Zhejiang Provincial Medical and Health Research Fund Project 2025KY1679
6 · The paper itself

Abstract

objectivesTo evaluate the feasibility and value of dynamic contrast-enhanced MRI (DCE-MRI) quantitative analysis and MRI-based radiomics in predicting the efficacy of microwave ablation (MWA) in lung cancers (LCs).

methodsForty-three patients with LCs who underwent DCE-MRI within 24 h of receiving MWA were enrolled in the study and divided into two groups according to the modified response evaluation criteria in solid tumors (m-RECIST) criteria: the effective treatment (complete response + partial response + stable disease, n = 28) and the ineffective treatment (progressive disease, n = 15). DCE-MRI datasets were processed by Omni. Kinetics software, using the extended tofts model (ETM) and exchange model (ECM) to yield pharmacokinetic parameters and their histogram features. Changes in quantitative perfusion parameters were compared between the two groups. Scientific research platform ( https://medresearch.shukun.net/ ) was used for radiomics analysis. A total of 1874 radiomic features were extracted for each tumor by manually segmentation of T1WI and Contrast-enhanced of T1WI (Ce-T1WI) fat inhibition sequence. The performances of radiomics models were evaluated by the receiver operating characteristic curve. Based on radiomics features, survival curves were generated by Kaplan-Meier survival analysis to evaluate patient outcomes. P < 0.05 was set for the significance threshold.

resultsThe V

conclusionsDCE-MRI quantitative analysis and MRI-based radiomics may be helpful in assessing the early response to MWA in patients with LCs.

Indexed as

Lung NeoplasmsMagnetic Resonance ImagingMicrowavesAgedContrast MediaDynamic Contrast Enhanced Magnetic Resonance ImagingFeasibility StudiesFemaleHumansMaleMiddle AgedRadiomicsRetrospective StudiesTreatment OutcomeContrast MediaDCE-MRILung cancerMicrowave ablationQuantitative analysisRadiomics

Identifiers

PMID40065426
PMCPMC11892232

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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.