Evidence map›Paper›PMID 39387925›Full record

ArticleJournal of cancer research and clinical oncology2024

Draw on advantages and avoid disadvantages: CT-derived individualized radiomic signature for predicting chemo-radiotherapy sensitivity in unresectable advanced non-small cell lung cancer.

Liping Yang, Mengyue Li, Yixin Liu, Zhiyun Jiang, Shichuan Xu, Hongchao Ding, Xing Gao, Shilong Liu, Lishuang Qi, Kezheng Wang

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In one paragraph

Article in Journal of cancer research and clinical oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Liping Yang *PET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, 150001, People's Republic of China.
Mengyue Li *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001, People's Republic of China.
Yixin LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001, People's Republic of China.
Zhiyun JiangPET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, 150001, People's Republic of China.
Shichuan XuDepartment of Equipment, The Second Hospital of Harbin, Harbin, People's Republic of China.
Hongchao DingDepartment of Physical Diagnosis, Heilongjiang Provincial Hospital, Harbin, People's Republic of China.
Xing GaoDepartment of Physical Diagnosis, Heilongjiang Provincial Hospital, Harbin, People's Republic of China.
Shilong LiuDepartment of Thoracic Radiation Oncology, Harbin Medical University Cancer Hospital, Harbin, 150001, People's Republic of China. liushilong1984@hrbmu.edu.cn.
Lishuang QiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150001, People's Republic of China. qilishuang7@ems.hrbmu.edu.cn.
Kezheng WangPET-CT/MR Department, Harbin Medical University Cancer Hospital, Harbin, 150001, People's Republic of China. wangkezheng9954001@163.com.

Funding

Hai Yan Fund of The Third Affiliated Hospital of Harbin Medical University JJZD2023-01National Natural Science Foundation of China 81872396National Undergraduate Innovation and Entrepreneurship Training Program 202110226018Provincial Key Research and Development Program of Heilongjiang Province GA21C001
6 · The paper itself

Abstract

backgroundPresently, the options of concurrent chemo-radiotherapy (CCR) in patients with locally advanced non-small cell lung cancer (LA-NSCLC) are controversial and there is no reliable prediction tool to stratify poor- and good-responders. Although radiomic analysis has provided new opportunities for personalized medicine in oncological practice, the repeatability and reproducibility of radiomic features are critical challenges that hinder their widespread clinical adoption. This study aimed to develop a qualitative radiomic signature based on the within-sample rank of radiomics features, and to use this novel method to predict CCR sensitivity in LA-NSCLC, avoiding the variability of quantitative signatures to multicenter effect.

methodsWe retrospectively analyzed 125 patients with stage III NSCLC who received treatment from our hospital. Radiomic features were extracted from pretreatment plain CT scans and constructed as feature pairs based on their within-sample rank. Fisher and univariate Cox analyses were performed to select feature pairs significantly associated with patients' overall survival (OS). NSCLC-Radiomic (R422) cohort including 104 NSCLC patients was used as an independent testing cohort. NSCLC-Radiogenomic (RG211) cohort with matched RNA sequencing profiles, was used for functional enrichment analysis to reveal the underlying biological mechanism reflected by the signature.

resultsA qualitative signature, consisting of 15 radiomic feature pairs (termed as 15-R

conclusionsWe developed a CT-derived 15-R

Indexed as

Carcinoma, Non-Small-Cell LungChemoradiotherapyLung NeoplasmsPrecision MedicineTomography, X-Ray ComputedAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRadiomicsRetrospective StudiesBioinformatic analysesConcurrent chemo-radiotherapyNon-small cell lung cancerQualitativeRadiomics

Identifiers

PMID39387925
PMCPMC11467094

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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.