{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T23:28:31Z","timestamp":1791502111427,"version":"4.3.4"},"reference-count":33,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"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":["82603743"],"award-info":[{"award-number":["82603743"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U24A200313"],"award-info":[{"award-number":["U24A200313"]}],"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"],"abstract":"ABSTRACT<\/jats:title>\n \n Background<\/jats:title>\n Although MR cytometry can probe microstructural features, the longitudinal trajectories of these changes during neoadjuvant chemotherapy (NAC) and their association with treatment response and prognosis remain poorly defined.<\/jats:p>\n <\/jats:sec>\n \n Purpose<\/jats:title>\n To characterize longitudinal changes in NAC\u2010associated cellular microstructural properties and evaluate microstructural parameters for predicting pathologic complete response (pCR) and disease\u2010free survival (DFS) in breast cancer.<\/jats:p>\n <\/jats:sec>\n \n Study Type<\/jats:title>\n Prospective.<\/jats:p>\n <\/jats:sec>\n \n Population<\/jats:title>\n 194 patients with invasive breast cancer underwent 713 MRI examinations.<\/jats:p>\n <\/jats:sec>\n \n Field Strength\/Sequence<\/jats:title>\n 3.0\u2009T, oscillating gradient spin\u2010echo (OGSE) and pulsed gradient spin\u2010echo (PGSE) sequences.<\/jats:p>\n <\/jats:sec>\n \n Assessment<\/jats:title>\n MR cytometry was acquired at four time\u2010points: pretreatment, early, mid\u2010, and late treatment. Microstructural parameters were estimated using the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model. Microstructural parameters were compared with histopathologic measurements.<\/jats:p>\n <\/jats:sec>\n \n Statistical Tests<\/jats:title>\n \n Generalized estimating equations, logistic regression, bootstrap resampling, the DeLong test with Bonferroni correction, Cox proportional hazards regression, Kaplan\u2013Meier analysis with the log\u2010rank test, the C\u2010index, and the Pearson correlation coefficient were performed.\n p<\/jats:italic>\n \u2009<\u20090.05 was significant.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Four logistic regression models were developed for predicting pCR, based on molecular subtype alone or combined with diameter at Time 1, ADC\n 50Hz<\/jats:sub>\n at Time 2, or cellularity at Time 2. The clinicopathological\u2013cellularity model achieved the best performance in predicting pCR (AUC\u2009=\u20090.89). For DFS, a Cox model incorporating ER status, HER2 status, cT stage, cN stage, and extracellular diffusivity at Time 1 yielded a C\u2010index of 0.81; patients stratified by the median risk score into low\u2010 and high\u2010risk groups differed significantly in DFS. Extracellular diffusion was positively correlated with pathologic stroma fraction (\n r<\/jats:italic>\n \u2009=\u20090.56).\n <\/jats:p>\n <\/jats:sec>\n \n Data Conclusion<\/jats:title>\n MR cytometry demonstrated longitudinal microstructural alterations during NAC and shows potential for predicting pCR and stratifying patients by DFS risk in breast cancer patients.<\/jats:p>\n <\/jats:sec>\n \n Level of Evidence<\/jats:title>\n 1.<\/jats:p>\n <\/jats:sec>\n \n Technical Efficacy<\/jats:title>\n Stage 2.<\/jats:p>\n <\/jats:sec>","DOI":"10.1002\/jmri.70587","type":"journal-article","created":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T12:21:59Z","timestamp":1791462119000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MR<\/scp>\n Cytometry of Microstructural Changes in Breast Cancer: Association With Treatment Response and Prognosis"],"prefix":"10.1002","author":[{"given":"Xiaoxia","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0866-1562","authenticated-orcid":false,"given":"Yao","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0475-8225","authenticated-orcid":false,"given":"Ruicheng","family":"Ba","sequence":"additional","affiliation":[{"name":"Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science Zhejiang University, Yuquan Campus Hangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ying","family":"Cao","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueqin","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaosong","family":"Lan","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sun","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lu","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Radiology Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC) Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Yin","sequence":"additional","affiliation":[{"name":"MR Collaborations Siemens Healthineers Ltd. 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