{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T12:10:35Z","timestamp":1789992635670,"version":"4.0.1"},"reference-count":17,"publisher":"FapUNIFESP (SciELO)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Radiol Bras"],"abstract":"<jats:p>Abstract  Objective: To evaluate a radiomics workflow applied to chest computed tomography (CT), examining its feasibility and performance across the steps of lung lesion segmentation, feature extraction, and clustering, as well as exploring its potential to distinguish between benign and malignant lung lesions.  Materials and Methods: This was a retrospective study including CT images of 32 histopathology-confirmed lesions (11 benign; 21 malignant). Lesions were segmented by using syngo.via Frontier Radiomics software, af-ter which &gt; 900 radiomic features were extracted with the same software. Data processing-including normal-ization, dimensionality reduction (principal component analysis), and unsupervised (k-means) clustering-was conducted in Python.  Results: The best clustering solution was obtained with a k = 2 (silhouette score = 0.4668), effectively separating benign lesions, which exhibited low heterogeneity, from malignant lesions, which exhibited complex patterns of texture and shape.  Conclusion: The application of a radiomics workflow proved feasible and potentially useful for differentiating between benign and malignant lung lesions on CT, underscoring its value as a complementary tool in thoracic oncology. How-ever, future studies using multicenter datasets, blinded evaluations, and more structured integration environments are warranted in order to support clinical validation and prototyping.<\/jats:p>","DOI":"10.1590\/0100-3984.2025.0005","type":"journal-article","created":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T11:25:31Z","timestamp":1789989931000},"source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of a radiomics workflow in chest CT: a pilot study of lung lesion segmentation, feature extraction, and clustering"],"prefix":"10.1590","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1994-9008","authenticated-orcid":false,"given":"Ana Carolina Costa da","family":"Silva","sequence":"first","affiliation":[{"name":"Siemens Healthineers, Computed Tomography,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5154-6035","authenticated-orcid":false,"given":"Paulo Henrique Ruis","family":"Garcia","sequence":"additional","affiliation":[{"name":"University of S\u00e3o Paulo,  Brazil; Siemens Healthineers, Education Services,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1731-4135","authenticated-orcid":false,"given":"Karina Yukimi Pexito","family":"Sakurai","sequence":"additional","affiliation":[{"name":"University of S\u00e3o Paulo School of Medicine,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8550-6312","authenticated-orcid":false,"given":"Douglas Carli","family":"Silva","sequence":"additional","affiliation":[{"name":"Siemens Healthineers, Education Services,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7020-4306","authenticated-orcid":false,"given":"Maria Vit\u00f3ria David","family":"Ludwig","sequence":"additional","affiliation":[{"name":"Hospital S\u00edrio-Liban\u00eas,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4414-5113","authenticated-orcid":false,"given":"Fabiana Reis Decicino","family":"Campos","sequence":"additional","affiliation":[{"name":"Hospital S\u00edrio-Liban\u00eas,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9424-9776","authenticated-orcid":false,"given":"M\u00e1rcio Valente Yamada","family":"Sawamura","sequence":"additional","affiliation":[{"name":"University of S\u00e3o Paulo School of Medicine,  Brazil; Hospital S\u00edrio-Liban\u00eas,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8263-9059","authenticated-orcid":false,"given":"Hye Ju","family":"Lee","sequence":"additional","affiliation":[{"name":"Hospital S\u00edrio-Liban\u00eas,  Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"530","published-online":{"date-parts":[[2026]]},"reference":[{"key":"ref1","series-title":"Global Cancer Observatory: Cancer Today [homepage on the Internet]","year":"2024"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1056\/NEJMoa1102873","article-title":"Reduced lung-cancer mortality with low-dose computed tomographic screening","volume":"365","author":"Aberle DR","year":"2011","journal-title":"N Engl J Med"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1148\/radiol.2015151169","article-title":"Radiomics: images are more than pictures, they are data","volume":"278","author":"Gillies RJ","year":"2016","journal-title":"Radiology"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1038\/nrclinonc.2017.141","article-title":"Radiomics: the bridge between medical imaging and personalized medicine","volume":"14","author":"Lambin P","year":"2017","journal-title":"Nat Rev Clin Oncol"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1186\/s40658-024-00685-5","article-title":"PET radiomics in lung cancer: ad-vances and translational challenges","volume":"11","author":"Zhang Y","year":"2024","journal-title":"EJNMMI Phys"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1016\/j.ymeth.2020.05.022","article-title":"Radiomics for precision medicine: current challenges, future prospects, and the proposal of a new framework","volume":"188","author":"Ibrahim A","year":"2021","journal-title":"Methods"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1148\/radiol.2020191145","article-title":"The Image Bio-marker Standardization Initiative: standardized quantitative ra-diomics for high-throughput image-based phenotyping","volume":"295","author":"Zwanenburg 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for the prediction of patient outcomes in non-small cell lung cancer","volume":"7","author":"Fave X","year":"2017","journal-title":"Sci Rep"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"842","DOI":"10.3390\/jpm11090842","article-title":"Making radiomics more reproducible across scanner and imaging protocol variations: a review of harmonization methods","volume":"11","author":"Mali SA","year":"2021","journal-title":"J Pers Med"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"2452","DOI":"10.21037\/tlcr-22-248","article-title":"Impact of image filtering and assessment of volume-confounding effects on CT radiomic features and derived survival models in non-small cell lung cancer","volume":"11","author":"Volpe S","year":"2022","journal-title":"Transl Lung Cancer Res"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"2872","DOI":"10.3390\/cancers16162872","article-title":"Comparative analysis of repeat-ability in CT radiomics and dosiomics features under image perturbation: a study in cervical cancer patients","volume":"16","author":"Ma Z","year":"2024","journal-title":"Cancers (Basel)"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.1148\/rg.2021210037","article-title":"Radiomics in oncology: a practical guide","volume":"41","author":"Shur JD","year":"2021","journal-title":"Radiographics"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1053\/j.sult.2022.02.003","article-title":"Radiomics: a primer on processing workflow and analysis","volume":"43","author":"Avery E","year":"2022","journal-title":"Semin Ultrasound CT MR"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/s44303-025-00104-z","article-title":"Radiomics in preclinical imaging research: methods, challenges and opportunities","volume":"3","author":"Riberdy V","year":"2025","journal-title":"NPJ Imaging"}],"container-title":["Radiologia Brasileira"],"original-title":["Avalia\u00e7\u00e3o de um fluxo de radi\u00f4mica em TC de t\u00f3rax: estudo piloto de segmenta\u00e7\u00e3o de les\u00f5es pulmonares, extra\u00e7\u00e3o de caracter\u00edsticas e clusteriza\u00e7\u00e3o"],"link":[{"URL":"http:\/\/www.scielo.br\/scielo.php?script=sci_pdf&pid=S0100-39842026000100602&tlng=en","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,21]],"date-time":"2026-09-21T11:25:34Z","timestamp":1789989934000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.scielo.br\/scielo.php?script=sci_arttext&pid=S0100-39842026000100602&tlng=en"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":17,"alternative-id":["S0100-39842026000100602"],"URL":"https:\/\/doi.org\/10.1590\/0100-3984.2025.0005","relation":{},"ISSN":["1678-7099"],"issn-type":[{"value":"1678-7099","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"article-number":"e20250005"}}