{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,26]],"date-time":"2026-08-26T22:25:10Z","timestamp":1787783110622,"version":"build-2784847793"},"reference-count":38,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T00:00:00Z","timestamp":1686009600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P30 CA016672"],"award-info":[{"award-number":["P30 CA016672"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 CA231513"],"award-info":[{"award-number":["R01 CA231513"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["NMR in Biomedicine"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:p>Tumor acidosis is an important biomarker for aggressive tumors, and extracellular pH (pHe) of the tumor microenvironment can be used to predict and evaluate tumor responses to chemotherapy and immunotherapy. AcidoCEST MRI measures tumor pHe by exploiting the pH\u2010dependent chemical exchange saturation transfer (CEST) effect of iopamidol, an exogenous CT agent repurposed for CEST MRI. However, all pH fitting methodologies for acidoCEST MRI data have limitations. Herein we present results of the application of machine learning for extracting pH values from CEST <jats:italic>Z<\/jats:italic>\u2010spectra of iopamidol. We acquired 36,000 experimental CEST spectra from 200 phantoms of iopamidol prepared at five concentrations, five <jats:italic>T<\/jats:italic><jats:sub>1<\/jats:sub> values, and eight pH values at five temperatures, acquired at six saturation powers and six saturation times. We also acquired <jats:italic>T<\/jats:italic><jats:sub>1<\/jats:sub>, <jats:italic>T<\/jats:italic><jats:sub>2<\/jats:sub>, <jats:italic>B<\/jats:italic><jats:sub>1<\/jats:sub> RF power, and <jats:italic>B<\/jats:italic><jats:sub>0<\/jats:sub> magnetic field strength supplementary MR information. These MR images were used to train and validate machine learning models for the tasks of pH classification and pH regression. Specifically, we tested the L1\u2010penalized logistic regression classification (LRC) model and the random forest classification (RFC) model for classifying the CEST <jats:italic>Z<\/jats:italic>\u2010spectra for thresholds at pH\u20096.5 and 7.0. Our results showed that both RFC and LRC were effective for pH classification, although the RFC model achieved higher predictive value, and improved the accuracy of classification accuracy with CEST <jats:italic>Z<\/jats:italic>\u2010spectra with a more limited set of saturation frequencies. Furthermore, we used LASSO and random forest regression (RFR) models to explore pH regression, which showed that the RFR model achieved higher accuracy and precision for estimating pH across the entire pH range of 6.2\u20137.3, especially when using a more limited set of features. Based on these results, machine learning for analysis of acidoCEST MRI is promising for eventual in vivo determination of tumor pHe.<\/jats:p>","DOI":"10.1002\/nbm.4986","type":"journal-article","created":{"date-parts":[[2023,6,7]],"date-time":"2023-06-07T10:36:04Z","timestamp":1686134164000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["A machine learning approach that measures pH using acidoCEST MRI of iopamidol"],"prefix":"10.1002","volume":"36","author":[{"given":"Tianzhe","family":"Li","sequence":"first","affiliation":[{"name":"The University of Texas MD Anderson Cancer Center  Houston Texas USA"},{"name":"The University of Texas Health Science Center  Houston Texas USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julio","family":"C\u00e1rdenas\u2010Rodr\u00edguez","sequence":"additional","affiliation":[{"name":"Data Translators LLC  Oro Valley Arizona 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