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However, few studies have explored radiomics on micro-computed tomography (micro-CT) or its transferability to clinical CT. This study investigates the reproducibility and the potential biological correlation of radiomic features across\n                      <jats:italic>in vivo<\/jats:italic>\n                      CT,\n                      <jats:italic>ex vivo<\/jats:italic>\n                      CT, and\n                      <jats:italic>ex vivo<\/jats:italic>\n                      micro-CT in non-small-cell lung cancer (NSCLC).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      A retrospective cohort of 60 NSCLC patients with preoperative CT scans and surgical specimens was analyzed.\n                      <jats:italic>Ex vivo<\/jats:italic>\n                      CT and micro-CT images were acquired and compared with\n                      <jats:italic>in vivo<\/jats:italic>\n                      CT using standardized preprocessing, including normalization, resampling, and registration. Tumor regions of interest (ROIs) were semi-automatically segmented, and 93 radiomic features were extracted with Pyradiomics. Cross-modality reproducibility and associations with histotype were evaluated using Spearman correlation, intraclass correlation coefficient, Bland\u2013Altman analysis, and Mann\u2013Whitney\n                      <jats:italic>U<\/jats:italic>\n                      test.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Normalization and volume matching improved feature repeatability, with the highest agreement observed in normalized datasets using subsampled ROIs. Four texture-based features consistently showed high reproducibility and potential biological correlation, likely reflecting intratumoral heterogeneity and variation in cell density: DependenceNonUniformity, GrayLevelNonUniformity (GLDM and GLRLM), and Coarseness (NGTDM). These features reliably distinguished adenocarcinoma from squamous cell carcinoma across modalities, confirming their stability and potential as candidate features for transferable biomarkers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Harmonization and volume standardization are essential for cross-modality radiomic analyses. Stable texture features provide a potential transferable signature bridging micro-CT and clinical CT imaging in NSCLC, supporting their role as candidate features for further investigation in biologically oriented studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      Micro-CT serves as an intermediate imaging scale enabling radiomic feature extraction from\n                      <jats:italic>ex vivo<\/jats:italic>\n                      NSCLC tumors, allowing direct comparison with\n                      <jats:italic>in vivo<\/jats:italic>\n                      and\n                      <jats:italic>ex vivo<\/jats:italic>\n                      CT.\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      Intensity normalization and volume-matched subsampling between\n                      <jats:italic>in vivo<\/jats:italic>\n                      CT,\n                      <jats:italic>ex vivo<\/jats:italic>\n                      CT, and micro-CT reduced cross-modality feature variability, improving feature reproducibility.\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Relevance statement<\/jats:italic>\n                      <\/jats:bold>\n                      Normalization, volume matching, and cross-modality analysis support the identification of candidate texture features with consistent cross-scale behavior and exploratory associations with NSCLC histotype.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s41747-026-00780-5","type":"journal-article","created":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T14:04:05Z","timestamp":1791381845000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Bridging radiomics and histopathology: cross-modality consistency of radiomic features from CT to micro-CT in NSCLC"],"prefix":"10.1186","volume":"10","author":[{"given":"Leonardo","family":"Brizzi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chandra","family":"Bortolotto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2983-989X","authenticated-orcid":false,"given":"Raffaella Fiamma","family":"Cabini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesca","family":"Brero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Megalizzi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gioacchino","family":"D\u2019Ambrosio","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marta","family":"Filibian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberta","family":"Gioia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paola","family":"Falvo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giulia Maria","family":"Stella","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Olivia Maria","family":"Bottinelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Lascialfari","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenzo","family":"Preda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,7]]},"reference":[{"key":"780_CR1","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1016\/j.ejca.2011.11.036","volume":"48","author":"P Lambin","year":"2012","unstructured":"Lambin P, Rios-Velazquez E, Leijenaar R et al (2012) Radiomics: extracting more information from medical images using advanced feature analysis. 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