{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T16:46:11Z","timestamp":1791996371868,"version":"4.4.0"},"reference-count":35,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["NSFC82430061: NSFC62401329: NSFC82271957"],"award-info":[{"award-number":["NSFC82430061: NSFC62401329: NSFC82271957"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2026,11]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>MR cytometry imaging is developed to characterize in\u00a0vivo microstructures. Its clinical value in predicting pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for breast cancer remains unknown.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To implement MR cytometry to predict pCR for breast cancer and compare the performance of different quantitative models (IMPULSED, JOINT, and EXCHANGE).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Study Type<\/jats:title>\n                    <jats:p>Prospective.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Subject<\/jats:title>\n                    <jats:p>209 female patients from center A (50.32\u2009\u00b1\u200911.06\u2009years) and B (48.05\u2009\u00b1\u200911.30\u2009years).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Field Strength\/Sequence<\/jats:title>\n                    <jats:p>3\u2009T; pulsed gradient spin\u2010echo diffusion\u2010weighted imaging (DWI) and oscillating gradient spin\u2010echo DWI of 17\/33\u2009Hz (center A) or 25\/50\u2009Hz (center B).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Assessment<\/jats:title>\n                    <jats:p>Tumor regions were manually delineated. Time\u2010dependent apparent diffusion coefficients (ADC) and model\u2010derived microstructural parameters (including cell diameter, intracellular volume fraction, cellularity, extracellular diffusivity, and water exchange rate constant) were calculated before and after NAC. Four multivariate logistic regression models, that is, time\u2010dependent ADCs, IMPULSED, JOINT, and EXCHANGE, were constructed to predict pCR; performance of combining MR cytometry with ADCs, that is, IMPULSED\u2010ADC, JOINT\u2010ADC, and EXCHANGE\u2010ADC, was also evaluated.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Statistical Tests<\/jats:title>\n                    <jats:p>\n                      Wilcoxon test, Mann\u2013Whitney U test, Logistic regression analysis, DeLong's test, and Pearson correlation analysis, with statistical significance set at\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.05.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Changes in intracellular volume fraction, cellularity, and water exchange rate constant before and after NAC exhibited significant differences between pCR and non\u2010pCR groups. The regression models of time\u2010dependent ADCs, IMPULSED, JOINT, and EXCHANGE yielded AUCs of 0.709, 0.716, 0.747, and 0.745 in predicting pCR for center A and 0.777, 0.809, 0.846, and 0.864 for center B; the combined models of IMPULSED\u2010ADC, JOINT\u2010ADC, and EXCHANGE\u2010ADC improved AUCs to 0.737, 0.761, and 0.758 for center A and 0.818, 0.860, and 0.868 for center B.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Data Conclusion<\/jats:title>\n                    <jats:p>JOINT and EXCHANGE, which incorporate transcytolemmal water exchange, outperformed impermeable IMPULSED in predicting NAC for breast cancer, and predictive performance can be further improved by combining MR cytometry parameters with time\u2010dependent ADCs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Evidence Level<\/jats:title>\n                    <jats:p>2.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Technical Efficacy<\/jats:title>\n                    <jats:p>Stage 2.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jmri.70484","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T07:10:57Z","timestamp":1786432257000},"page":"1346-1360","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Application of\n                    <scp>MR<\/scp>\n                    Cytometry in Predicting Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer: A Comparative Study"],"prefix":"10.1002","volume":"64","author":[{"given":"Jie","family":"Ding","sequence":"first","affiliation":[{"name":"Medical Imaging Center People's Hospital of Ningxia Hui Autonomous Region  Yinchuan 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