[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-340698-105":59,"doc-detail-340698-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","optimized-synthetic-correlated-diffusion-imaging-for-improving-breast-cancer-tumor-delineation","Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation","","Breast cancer remains a major cause of cancer-related death in women worldwide, making precise diagnostic imaging essential for diagnosis, treatment planning, and follow-up monitoring. This work investigates synthetic correlated diffusion imaging (CDIs) and evaluates whether optimizing its correlated diffusion imaging protocol can improve tumor delineation for breast cancer. Specifically, the study optimizes coefficients of the calibrated signal mixing function by maximizing receiver operating characteristic AUC across a breast cancer patient cohort. Results show improved delineation by more than 0.03 versus an unoptimized protocol and the highest AUC compared with gold-standard modalities, supporting protocol optimization for specific cancer applications.",{"@graph":69,"@context":122},[70,84,105],{"@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/optimized-synthetic-correlated-diffusion-imaging-for-improving-breast-cancer-tumor-delineation/340698/",{"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/optimized-synthetic-correlated-diffusion-imaging-for-improving-breast-cancer-tumor-delineation/340698.png","ImageObject",300,407,{"name":92,"@type":93},"Theodora","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-22","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":29},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does this study address in breast cancer imaging?","Question",{"text":112,"@type":113},"The study targets the need for improved diagnostic imaging by enhancing breast cancer tumor delineation. It focuses on adapting synthetic correlated diffusion imaging to breast cancer.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How is the CDIs protocol optimized in this research?",{"text":117,"@type":113},"It optimizes coefficients of the calibrated signal mixing function in the CDIs protocol. The optimization maximizes the area under the receiver operating characteristic curve (AUC) across a breast cancer patient cohort.",{"name":119,"@type":110,"acceptedAnswer":120},"What evidence shows the optimized CDIs improves tumor delineation?",{"text":121,"@type":113},"Experiments indicate the optimized CDIs increases delineation of breast cancer tumors by over 0.03 compared with the unoptimized form. The optimized approach also achieves the highest AUC compared with gold-standard MRI modalities.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},340698,1790617651,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":29,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"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},687197207919,"https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552","sensors   \nArticle  \nOptimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation  \nChi-en Amy Tai * and Alexander Wong   \nCitation: Tai, C.-e.A.; Wong, A. Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation. Sensors 2024, 24, 8173. [https://](https://)[ ](https://)[doi.org/10.3390/s24248173](doi.org/10.3390/s24248173)  \nReceived: 3 November 2024  \nRevised: 11 December 2024  \nAccepted: 14 December 2024  \nPublished: 21 December 2024  \nCopyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \nDepartment of Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada; [alexander.wong@uwaterloo.ca](alexander.wong@uwaterloo.ca)  \n* Correspondence: [amy.tai@uwaterloo.ca](amy.tai@uwaterloo.ca)  \nAbstract: Breast cancer is a significant cause of death from cancer in women globally, highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumor identification is essential for diagnosis, treatment, and monitoring, emphasizing the importance of advanced imaging technologies that provide detailed views of tumor characteristics and disease. Recently, a new imaging modality named synthetic correlated diffusion imaging (CDIs ) has been showing promise for enhanced prostate cancer delineation when compared to existing MRI imaging modalities. In this study, we explore the efficacy of optimizing the correlated diffusion imaging (CDI) protocol to tailor it for breast cancer tumor delineation. More specifically, we optimize the coefficients of the calibrated signal mixing function in the CDIs protocol that controls the contribution of different gradient pulse strengths and timings by maximizing the area under the receiver operating characteristic curve (AUC) across a breast cancer patient cohort. Experiments showed that the optimized CDIs can noticeably increase the delineation of breast cancer tumors by over 0.03 compared to the unoptimized form, as well as providing the highest AUC when compared with gold-standard modalities. These experimental results demonstrate the importance of optimizing the CDIs imaging protocol for specific cancer applications to yield the best diagnostic imaging performance.  \nKeywords: breast cancer; tumor delineation; MRI; synthetic correlated diffusion imaging; optimization  \n1. Introduction  \nBreast cancer is a significant cause of death from cancer in women globally [1], highlighting the need for improved diagnostic imaging to enhance patient outcomes. Accurate tumor identification is essential for diagnosis, treatment, and monitoring [2], emphasizing the importance of advanced imaging technologies that provide detailed views of tumor characteristics and disease [3] .  \nRecently, a new imaging modality named synthetic correlated diffusion imaging (CDIs ) has been showing promise for enhanced prostate cancer delineation when compared to existing magnetic resonance imaging (MRI) modalities [4] . CDIs is an imaging technique that builds on correlated diffusion imaging (CDI) . CDI analyzes the distribution of diffusion in the cancerous tissue, with CDIs extending upon this idea by introducing synthetic signals at different gradient pulse strengths and timings where physical acquisitions are not available. The process begins with multiple native signal acquisitions obtained at different gradient pulse strengths and timings, which are then passed into a signal synthesizer that produces synthetic signals. The native signals are then mixed with the synthetic signals to obtain the CDIs signal. Though CDIs served as a strong indicator for prostate presence in tissue [4], a few challenges exist for r","cbCaisNp0FZW11UB","https://ap.wps.com/l/cbCaisNp0FZW11UB","pdf",7161648,13,"English","# Abstract\n# 1. Introduction\n# 2. Related Works\n## 2.1. Diffusion-Weighted Imaging (DWI)","[{\"question\":\"What problem does this study address in breast cancer imaging?\",\"answer\":\"The study targets the need for improved diagnostic imaging by enhancing breast cancer tumor delineation. It focuses on adapting synthetic correlated diffusion imaging to breast cancer.\"},{\"question\":\"How is the CDIs protocol optimized in this research?\",\"answer\":\"It optimizes coefficients of the calibrated signal mixing function in the CDIs protocol. The optimization maximizes the area under the receiver operating characteristic curve (AUC) across a breast cancer patient cohort.\"},{\"question\":\"What evidence shows the optimized CDIs improves tumor delineation?\",\"answer\":\"Experiments indicate the optimized CDIs increases delineation of breast cancer tumors by over 0.03 compared with the unoptimized form. The optimized approach also achieves the highest AUC compared with gold-standard MRI modalities.\"}]","Optimized Synthetic Correlated Diffusion Imaging for Improving Breast Cancer Tumor Delineation | PDF",1790038330,33]