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We aim to identify subtypes using computed tomography (CT) imaging features of HCC and assess their value in predicting prognosis and the effectiveness of immunotherapy.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      We used unsupervised consensus clustering based on quantitative contrast-enhanced CT features to identify imaging subtypes and investigated their value in predicting prognosis and the effectiveness of immunotherapy in the discovery (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009103) and immunotherapy-treated (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009110) validation cohort. We also developed a gene-based classifier for imaging subtypes and tested their prognostic and biological relevance in two additional gene validation cohorts with publicly available gene expression data but without imaging data (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u2009551).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The imaging subtypes demonstrated significant correlations with overall survival across all cohorts (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009=\u20090.002,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and effectively predicted immunotherapy outcomes, with 1-year progression-free survival rates varying significantly (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). Imaging subtypes 1 and 3 with favorable and intermediate immunotherapy responses showed significant activation of B-cells, lymphocyte-mediated immunity, and immune response (adjusted\n                      <jats:italic>p<\/jats:italic>\n                      -value\u2009\u2264\u20090.047, false discovery rate \u2264 0.043). Imaging subtype 2 with poor immunotherapy responses displayed the least activated CD8+\u2009T cells, the lowest cytolytic activity, and the highest infiltration of neutrophil and regulatory T cells. Additionally, type I and II interferon responses were significantly downregulated in imaging subtype 2.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Unsupervised clustering of CT imaging features identified subtypes with significantly distinct prognosis and immune signatures. The imaging subtypes can serve as a marker for immunotherapy in HCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Relevance statement<\/jats:title>\n                    <jats:p>The imaging subtypes identified in this study demonstrate significant clinical relevance by providing a non-invasive approach to predict prognosis and immunotherapy response for HCC.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:list list-type=\"bullet\">\n                        <jats:list-item>\n                          <jats:p>We identified three novel imaging subtypes using unsupervised consensus clustering of quantitative CT imaging features for HCC.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>Imaging subtypes were independent predictors of overall survival and the effectiveness of immunotherapy for HCC.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>The imaging subtypes can be used as a marker for immunotherapy in HCC.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s41747-026-00730-1","type":"journal-article","created":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T13:20:10Z","timestamp":1779888010000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clustering of quantitative CT features identifies HCC subtypes with distinct prognosis and immune signatures"],"prefix":"10.1186","volume":"10","author":[{"given":"Shuang","family":"Wu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fang","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiexing","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingrui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyue","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Bao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3891-2721","authenticated-orcid":false,"given":"Yong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,27]]},"reference":[{"key":"730_CR1","doi-asserted-by":"publisher","first-page":"12","DOI":"10.3322\/caac.21820","volume":"74","author":"RL Siegel","year":"2024","unstructured":"Siegel RL, Giaquinto AN, Jemal A (2024) Cancer statistics, 2024. 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