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Consecutive 13-min acquisitions quantified Glx-C4\n                      <jats:sup>1<\/jats:sup>\n                      H-signal decay, converted to\n                      <jats:sup>2<\/jats:sup>\n                      H-Glx concentrations using baseline metabolite pool sizes. A four-pool kinetic model including\n                      <jats:sup>2<\/jats:sup>\n                      H-label loss was fitted to regional turnover curves to estimate oxidative flux (V\n                      <jats:sub>gt<\/jats:sub>\n                      ) and pyruvate dilution (Kdil). Model performance and parameter robustness were assessed with Monte-Carlo simulations.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In vivo\n                      <jats:sup>2<\/jats:sup>\n                      H-Glx turnover showed a saturated exponential rise (~\u200960\u00a0min), with a labelling plateau higher in striatum (1.85\u00a0\u03bcmol\/g) than hippocampus (1.55\u00a0\u03bcmol\/g). Metabolic modelling provided region-specific oxidative fluxes: V\n                      <jats:sub>gt<\/jats:sub>\n                      \u2009=\u20090.53\u2009\u00b1\u20090.15\u00a0\u03bcmol\/g\/min (hippocampus) and V\n                      <jats:sub>gt<\/jats:sub>\n                      \u2009=\u20090.81\u2009\u00b1\u20090.12\u00a0\u03bcmol\/g\/min (striatum), with consistent Kdil across regions. Simulations confirmed a good model robustness in retrieving V\n                      <jats:sub>gt<\/jats:sub>\n                      over a large range of experimental conditions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>\n                      This work shows the potential of indirect dynamic\n                      <jats:sup>1<\/jats:sup>\n                      H-[\n                      <jats:sup>2<\/jats:sup>\n                      H]-FID-MRSI for quantitative metabolic flux mapping of cerebral glucose oxidative metabolism.\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s10334-026-01363-6","type":"journal-article","created":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T13:20:09Z","timestamp":1779888009000},"page":"381-393","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Metabolic modelling and time-resolved mapping of glucose oxidative metabolism in the rat brain by indirect deuterium detection with 1H-FID-MRSI at 9.4\u00a0T"],"prefix":"10.1007","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-4905-7577","authenticated-orcid":false,"given":"Alessio","family":"Siviglia","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gianna","family":"Nossa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brayan","family":"Alves","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabian","family":"Niess","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anna","family":"Duguid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"suffix":"Jr.","given":"Zenon","family":"Star\u010duk","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wolfgang","family":"Bogner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernhard","family":"Strasser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristina","family":"Cudalbu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernard","family":"Lanz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,5,27]]},"reference":[{"key":"1363_CR1","doi-asserted-by":"publisher","DOI":"10.1152\/physrev.00062.2017","author":"GA Dienel","year":"2018","unstructured":"Dienel GA (2018) Brain glucose metabolism: integration of energetics with function. 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