{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T15:03:15Z","timestamp":1783090995420,"version":"3.54.6"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T00:00:00Z","timestamp":1713225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Lung cancer, the second most common cancer, presents persistently dismal prognoses. Radiomics, a promising field, aims to provide novel imaging biomarkers to improve outcomes. However, clinical translation faces reproducibility challenges, despite efforts to address them with quality scoring tools.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>This study had two objectives: 1) identify radiomics biomarkers in post-radiotherapy stage III\/IV nonsmall cell lung cancer (NSCLC) patients, 2) evaluate research quality using the CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score) frameworks, and formulate an amalgamated CLEAR-RQS tool to enhance scientific rigor.<\/jats:p><\/jats:sec><jats:sec><jats:title>Materials and methods<\/jats:title><jats:p>A systematic literature review (Jun-Aug 2023, MEDLINE\/PubMed\/SCOPUS) was conducted concerning stage III\/IV NSCLC, radiotherapy, and radiomic features (RF). Extracted data included study design particulars, such as sample size, radiotherapy\/CT technique, selected RFs, and endpoints. CLEAR and RQS were merged into a CLEAR-RQS checklist. Three readers appraised articles utilizing CLEAR, RQS, and CLEAR-RQS metrics.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Out of 871 articles, 11 met the inclusion\/exclusion criteria. The Median cohort size was 91 (range: 10\u2013337) with 9 studies being single-center. No common RF were identified. The merged CLEAR-RQS checklist comprised 61 items. Most unreported items were within CLEAR\u2019s \u201cmethods\u201d and \u201copen-source,\u201d and within RQS\u2019s \u201cphantom-calibration,\u201d \u201cregistry-enrolled prospective-trial-design,\u201d and \u201ccost-effective-analysis\u201d sections. No study scored above 50% on RQS. Median CLEAR scores were 55.74% (32.33\/58 points), and for RQS, 17.59% (6.3\/36 points). CLEAR-RQS article ranking fell between CLEAR and RQS and aligned with CLEAR.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Radiomics research in post-radiotherapy stage III\/IV NSCLC exhibits variability and frequently low-quality reporting. The formulated CLEAR-RQS checklist may facilitate education and holds promise for enhancing radiomics research quality.<\/jats:p><\/jats:sec><jats:sec><jats:title>Clinical relevance statement<\/jats:title><jats:p>Current radiomics research in the field of stage III\/IV postradiotherapy NSCLC is heterogenous, lacking reproducibility, with no identified imaging biomarker. Radiomics research quality assessment tools may enhance scientific rigor and thereby facilitate radiomics translation into clinical practice.<\/jats:p><\/jats:sec><jats:sec><jats:title>Key Points<\/jats:title><jats:p><jats:list list-type=\"bullet\"><jats:list-item><jats:p><jats:italic>There is heterogenous and low radiomics research quality in postradiotherapy stage III\/IV nonsmall cell lung cancer.<\/jats:italic><\/jats:p><\/jats:list-item><jats:list-item><jats:p><jats:italic>Barriers to reproducibility are small cohort size, nonvalidated studies, missing technical parameters, and lack of data, code, and model sharing.<\/jats:italic><\/jats:p><\/jats:list-item><jats:list-item><jats:p><jats:italic>CLEAR (CheckList_for_EvaluAtion_of_Radiomics_research), RQS (Radiomics_Quality_Score), and the amalgamated CLEAR-RQS tool are useful frameworks for assessing radiomics research quality and may provide a valuable resource for educational purposes in the field of radiomics.<\/jats:italic><\/jats:p><\/jats:list-item><\/jats:list><\/jats:p><\/jats:sec>","DOI":"10.1007\/s00330-024-10736-1","type":"journal-article","created":{"date-parts":[[2024,4,16]],"date-time":"2024-04-16T15:28:39Z","timestamp":1713281319000},"page":"6527-6543","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Post-radiotherapy stage III\/IV non-small cell lung cancer radiomics research: a systematic review and comparison of CLEAR and RQS frameworks"],"prefix":"10.1007","volume":"34","author":[{"given":"Kevin","family":"Tran","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Ginzburg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Hong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ulrike","family":"Attenberger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6727-9507","authenticated-orcid":false,"given":"Hyun Soo","family":"Ko","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"key":"10736_CR1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","volume":"71","author":"H Sung","year":"2021","unstructured":"Sung H, Ferlay J, Siegel RL et al (2021) Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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They have not participated in the selection or review process for this article. The remaining authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Dr Wei Hong kindly provided statistical advice for this manuscript who is a medical oncologist and a certified biostatistician. However, no complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Written informed consent was not required by the Institutional Review Board.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was not required because this study did not include any intervention or extraction of private information of human subjects.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"There are no study subjects or cohorts overlap.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}