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Adv."],"published-print":{"date-parts":[[2026,8,21]]},"abstract":"<jats:p>\n                    Intra- and intertumoral heterogeneities raise fundamental biological questions and have important implications for accurate cancer diagnosis, prognosis, and treatment. These heterogeneities reflect tumor complexity, including a pronounced diversity in metabolic phenotypes and profiles. This study demonstrates that in vivo deuterium metabolic imaging (DMI) data acquired with sufficiently high spatiotemporal resolution provide a minimally invasive approach to assess these heterogeneities. A multifrequency DMI approach was used to examine tumor heterogeneities within and between colon cancer models. Regions of high and low glucose enrichment and labeled lactate accumulation could thus be detected; these were analyzed using unsupervised clustering strategies based on\n                    <jats:italic toggle=\"yes\">k<\/jats:italic>\n                    -means clustering of area-under-the-curve information, and principal components analysis with Gaussian mixture modeling. Spatial alignment of these imaging-derived clusters for\n                    <jats:sup>2<\/jats:sup>\n                    H-glucose and\n                    <jats:sup>2<\/jats:sup>\n                    H-lactate showed good agreement with each other as well as with histological sections, validating the biological relevance of the identified subregions. Immunohistochemical analyses showed that glucose-enriched subregions were positively correlated with the expression of GLUT1 and DLAT, while lactate-enriched areas showed elevated expression of LDHA and MCT4. These results demonstrate that in vivo DMI can distinguish metabolically distinct subregions within viable tumors and between tumor models. DMI-based metabolic maps could thus provide the means to characterize intra- and intertumoral heterogeneities, paving the way for imaging-based metabolic phenotyping in precision oncology.\n                  <\/jats:p>","DOI":"10.1126\/sciadv.aef4377","type":"journal-article","created":{"date-parts":[[2026,8,21]],"date-time":"2026-08-21T17:58:41Z","timestamp":1787335121000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":0,"title":["High\u2013spatiotemporal resolution deuterium metabolic imaging enables in vivo phenotyping of intra- and intertumoral heterogeneity"],"prefix":"10.1126","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7871-6369","authenticated-orcid":true,"given":"Xinjie","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China."},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sufei","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Respiratory and Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jinrui","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"ShaSha","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430071, China."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3868-4180","authenticated-orcid":true,"given":"Peng","family":"Sun","sequence":"additional","affiliation":[{"name":"Neusoft Medical Systems Co. 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