{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T07:48:15Z","timestamp":1791791295542,"version":"4.3.4"},"reference-count":43,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2023YFF1204801"],"award-info":[{"award-number":["2023YFF1204801"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["YDZX20243100003001001"],"award-info":[{"award-number":["YDZX20243100003001001"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance in Med"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>\n                      Linear combination model fitting is widely used for spectral analysis in\n                      <jats:sup>1<\/jats:sup>\n                      H\u2010MRS but relies on basis sets with fixed spin\u2010system parameters, implicitly neglecting the sensitivity of chemical shifts to physiological and pathological tissue microenvironments. This study systematically evaluated the impact of frequency perturbations on spectral analysis and reassessed the validity of the Cram\u00e9r\u2010Rao lower bounds (CRLB) as a quality\u2010control metric for low\u2010concentration metabolites.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      The effects of frequency perturbations on spectral analysis were investigated using simulated datasets with different baseline models and lineshapes, followed by validation in a publicly available in vivo human brain\n                      <jats:sup>1<\/jats:sup>\n                      H\u2010MRS dataset (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200931). Estimated metabolite concentrations, relative concentration changes, estimation errors, and CRLB values were analyzed across all conditions.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Frequency perturbations produced minimal quantification changes in high\u2010concentration metabolites but substantially larger errors in several low\u2010concentration metabolites. Across both simulations and in vivo validation, relative concentration changes generally remained below 3% for high\u2010concentration metabolites but exceeded 10%\u201320% for several low\u2010concentration metabolites, including Gln, GSH, Asp, and NAAG. Importantly, substantial estimation errors frequently occurred despite CRLB values remaining within conventionally acceptable ranges. These findings were consistently observed across different baseline models, lineshapes, and in vivo validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Physiologically relevant frequency perturbations can introduce substantial quantification bias that is not consistently reflected by CRLB. These findings identify environmentally induced resonance\u2010frequency variations as an underrecognized source of quantification error in current linear\u2010combination model fitting and suggest that CRLB\u00a0alone is insufficient for assessing quantification reliability, particularly under conditions associated with altered brain temperature or tissue pH.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mrm.70613","type":"journal-article","created":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T07:19:56Z","timestamp":1791789596000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["How do Uncompensated Micro\u2010Shifts Systematically Confound Low\u2010Concentration Metabolite Quantification in\n                    <scp>\n                      <sup>1<\/sup>\n                      H\n                    <\/scp>\n                    \u2010\n                    <scp>MRS Analysis<\/scp>\n              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