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Med. Biol."],"published-print":{"date-parts":[[2026,11,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    <jats:italic>Objective.<\/jats:italic>\n                    Radiomics analysis in positron emission tomography (PET) offers a high-dimensional representation of tissue characteristics, yet its reliability is limited by sensitivity to acquisition perturbations, particularly dose reduction. This study aims to introduce a nonlinear stability phenotyping framework to characterize dose\u2013response behavior of multi-organ radiomics and evaluate their potential relevance for future digital twin-oriented applications.\n                    <jats:italic>Approach.<\/jats:italic>\n                    A multi-center dataset of 550 total-body PET scans was analyzed. Dose reduction was simulated using list-mode subsampling (dose reduction factor \u2212 DRF = 2\u2013100). A total of 107 radiomics features were extracted per organ. Stability was quantified using intraclass correlation coefficient and summarized as stability fractions. Nonlinear models were fitted to organ- and feature-level trajectories. Stability phenotypes and critical thresholds were derived, along with organ-level instability metrics.\n                    <jats:italic>Main results.<\/jats:italic>\n                    Radiomics stability exhibited strongly nonlinear, organ-dependent behavior. Feature-level analysis identified frequent sigmoid-associated collapse patterns with high descriptive model fits (\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    &gt; 0.90). The liver showed the highest instability burden (30.8% unstable features), followed by esophagus and kidneys (18%\u201320%). Texture features were the primary source of instability, whereas shape features remained robust. Organ-level trajectories demonstrated heterogeneous responses, with some organs maintaining high stability (0.80\u20130.95) across DRFs, while others showed sharp declines (down to 0.64). Linear (stable) behavior dominated at the organ level, though masking underlying nonlinear feature dynamics.\n                    <jats:italic>Significance.<\/jats:italic>\n                    Radiomics stability in total-body PET follows nonlinear, phenotype-driven dynamics with identifiable tipping points and organ-specific sensitivity. The proposed framework provides a behavior-based approach for evaluating radiomics robustness and supports the selection of reliable features and organs for robust quantitative imaging and may inform future digital twin-oriented applications.\n                  <\/jats:p>","DOI":"10.1088\/1361-6560\/aeb699","type":"journal-article","created":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T12:49:44Z","timestamp":1792500584000},"page":"215002","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Nonlinear stability phenotypes and collapse dynamics of multi-organ radiomics in total-body PET imaging: toward digital twin-oriented robustness assessment"],"prefix":"10.1088","volume":"71","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8037-3071","authenticated-orcid":true,"given":"Mohammad Saber","family":"Azimi","sequence":"first","affiliation":[{"name":"\u00d3buda University"},{"name":"\u00d3buda University"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0222-116X","authenticated-orcid":true,"given":"Maryam","family":"Cheraghi","sequence":"additional","affiliation":[{"name":"Shahid Beheshti University of Medical Sciences"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7559-5297","authenticated-orcid":true,"given":"Habib","family":"Zaidi","sequence":"additional","affiliation":[{"name":"\u00d3buda University"},{"name":"Geneva University Hospital"},{"name":"University of Groningen"},{"name":"University of Southern Denmark"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"funding-acquisition","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"266","published-online":{"date-parts":[[2026,10,30]]},"reference":[{"key":"pmbaeb699bib1","doi-asserted-by":"publisher","first-page":"311","DOI":"10.3390\/jcm15010311","type":"journal-article","article-title":"The rise of total-body PET\/CT: advancing molecular imaging toward early cancer detection and potential future application in prevention healthcare","volume":"15","author":"Alongi","year":"2025","journal-title":"J. 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Published on behalf of Institute of Physics and Engineering in Medicine by IOP Publishing Ltd","name":"copyright_information","label":"Copyright Information"},{"value":"2026-07-27","name":"date_received","label":"Date Received","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-20","name":"date_accepted","label":"Date Accepted","group":{"name":"publication_dates","label":"Publication dates"}},{"value":"2026-10-30","name":"date_epub","label":"Online publication date","group":{"name":"publication_dates","label":"Publication dates"}}]}}