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Quantitative td-dMRI diffusion parameters and IVIM model measures are compared across NPI groups and molecular categories in 103 patients, using Mann-Whitney U tests. Logistic regression fusion is assessed with ROC curves via AUC, and outcomes support noninvasive preoperative differentiation.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/integrating-time-dependent-diffusion-mri-and-intravoxel-incoherent-motion-for-predicting-npi-and-molecular-subtypes-in-breast-cancer/358492/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/integrating-time-dependent-diffusion-mri-and-intravoxel-incoherent-motion-for-predicting-npi-and-molecular-subtypes-in-breast-cancer/358492.png","ImageObject",300,407,{"name":92,"@type":93},"Eliana","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-30","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",15,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the study’s main objective?","Question",{"text":113,"@type":114},"To evaluate whether combining time-dependent diffusion MRI (td-dMRI) with IVIM can predict breast cancer Nottingham Prognostic Index (NPI) grades and molecular subtypes.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How was the study conducted?",{"text":118,"@type":114},"One hundred three breast cancer patients who underwent td-DWI sequences were included. Diffusion parameters from td-dMRI and IVIM were measured and compared, then combined using binary logistic regression and assessed with ROC/AUC.",{"name":120,"@type":111,"acceptedAnswer":121},"What did the results show about high-grade vs low-grade NPI groups?",{"text":122,"@type":114},"The high-grade NPI group showed significantly higher D* and lower ADC50Hz, f, and Dex values compared with the low-grade group, and the integrated model achieved the highest AUC.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},358492,1790442047,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},4398048949847,"https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267","He etal. BMC Medical Imaging (2026) 26:63 [https://doi.org/10.1186/s12880-025-02128-8](https://doi.org/10.1186/s12880-025-02128-8)  \nBMC Medical Imaging  \nRESEARCH Open Access  \nIntegrating time-dependent diffusion MRI and intravoxel incoherent motion for predicting NPI and molecular subtypes in breast cancer  \nLitong He 1†, Zhiqiang Liu 1†, Lingqiao Yang2, Yanjin Qin3, Zhendong Luo4, Yunfei Zhang5, Xiaopeng Song6, Wei Mao6, Dan Wu7 and Tao Ai 1*  \nAbstract  \nObjectives To investigate the potential of combining time-dependent diffusion MRI (td-dMRI) with intravoxelincoherent motion (IVIM) to predict the Nottingham Prognostic Index (NPI) and molecular subtypes of breast cancer. Methods A total of 103 breast cancer patients who underwent td-DWI sequences were included. Quantitative diffusion parameters from td-dMRI (ADC0Hz, ADC25Hz, ADC50Hz, Diameter, fin, Dex, and Cellularity) and IVIM model (D, D*, f ) were measured and compared using the Mann-Whitney U-test in NPI grades and molecular subtypes. Binary logistic regression analysis was conducted to combine parameters, and the discriminative power of individual and combined models was assessed using Receiver Operating Characteristic curves with Area Under the Curve.  \nResults The high-grade NPI group exhibited significantly higher D* and lower ADC50Hz, f and Dex values compared to the low-grade group (p \u003C 0. 05) . The combined model achieved the highest AUC (0 . 863) . The luminal subtype showed increased fin and Cellularity, along with decreased ADC0Hz and ADC25Hz values compared to non-Luminal subtypes (p \u003C 0.05). The D and fin values were significantly different between HER2-enriched subtype and other subtypes  \n(p \u003C 0.05). The ADC0Hz, ADC25Hz, Diameter and Cellularity values differed significantly between triple-negative subtype and other subtypes (p \u003C 0. 05) .  \nConclusion The integration of td-dMRI and IVIM parameters offers a promising noninvasive strategy for preoperative differentiation of NPI grades and molecular subtypes in breast cancer.  \nCritical relevance statement The combination of td-dMRI and IVIM parameters may enhance the precision of prognostic estimation and the formulation of personalized treatment strategies in clinical practice.  \nKey points  \n• Preoperative prediction of breast cancer NPI and molecular subtypes is crucial.  \n†Litong He and Zhiqiang Liu contributed equally to this work.  \n*Correspondence: Tao Ai [aitao007@hotmail.com](aitao007@hotmail.com)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creati](http://creati)[vecommons.org/l](vecommons.org/l)icenses/by-nc-nd/4.0/.  \nHe et al. BMC Medical Imaging (2026) 26:63 Page 2 of 10  \n• IVIM and td-dMRI can assist in distinguishing NPI and molecular subtypes.  \n• The integration of IVIM and td-dMRI could facilitate accurate prognostic predictions.  \nKeywords Magnetic resonance imaging, Time-dependent diffusion, Intravoxel incoherent motion, Breast cancer, Nottingham prognostic index  \nIntro","cbCaitelmryZIWJg","https://ap.wps.com/l/cbCaitelmryZIWJg","pdf",1656730,"English","# Abstract\n## Objectives\n## Methods\n## Results\n## Conclusion\n## Key points\n# Introduction\n## Breast cancer heterogeneity and NPI","[{\"question\":\"What is the study’s main objective?\",\"answer\":\"To evaluate whether combining time-dependent diffusion MRI (td-dMRI) with IVIM can predict breast cancer Nottingham Prognostic Index (NPI) grades and molecular subtypes.\"},{\"question\":\"How was the study conducted?\",\"answer\":\"One hundred three breast cancer patients who underwent td-DWI sequences were included. Diffusion parameters from td-dMRI and IVIM were measured and compared, then combined using binary logistic regression and assessed with ROC/AUC.\"},{\"question\":\"What did the results show about high-grade vs low-grade NPI groups?\",\"answer\":\"The high-grade NPI group showed significantly higher D* and lower ADC50Hz, f, and Dex values compared with the low-grade group, and the integrated model achieved the highest AUC.\"}]","Integrating time-dependent diffusion MRI and intravoxel incoherent motion for predicting NPI and molecular subtypes in breast cancer | PDF",1790134382,25]