{"title":"Improved prostate cancer localization with spatially regularized dynamic contrast-enhanced magnetic resonance imaging","authors":"Liu Lukai, M. Haider, D. Langer, I. Yetik","doi":"10.1109/ISBI.2010.5490094","DOIUrl":null,"url":null,"abstract":"Imaging methods to localize prostate cancer with sufficient accuracy are extremely useful in guiding biopsy, radiotherapy and surgery as well as to monitor disease progression. Imaging prostate cancer with multispectral magnetic resonance imaging (MRI) has shown a superior performance when compared to classical imaging modality transrectal ultrasound (TRUS). An important component of multispectral MRI is dynamic contrast-enhanced magnetic resonance imaging (DCE MRI). However, parametric images based on DCE MRI suffer from low signal-to-noise ratio (SNR). In this study, we propose a kinetic parametric imaging method with DCE MRI to overcome this problem using spatial regularization for improved prostate cancer localization. We demonstrate that the proposed method outperforms pixel-wise parametric imaging method, and that the performance of resulting tumor localization has a considerable improvement. Both visual and quantitative evaluations based on a task-based approach focused on tumor localization are provided.","PeriodicalId":250523,"journal":{"name":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2010.5490094","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Imaging methods to localize prostate cancer with sufficient accuracy are extremely useful in guiding biopsy, radiotherapy and surgery as well as to monitor disease progression. Imaging prostate cancer with multispectral magnetic resonance imaging (MRI) has shown a superior performance when compared to classical imaging modality transrectal ultrasound (TRUS). An important component of multispectral MRI is dynamic contrast-enhanced magnetic resonance imaging (DCE MRI). However, parametric images based on DCE MRI suffer from low signal-to-noise ratio (SNR). In this study, we propose a kinetic parametric imaging method with DCE MRI to overcome this problem using spatial regularization for improved prostate cancer localization. We demonstrate that the proposed method outperforms pixel-wise parametric imaging method, and that the performance of resulting tumor localization has a considerable improvement. Both visual and quantitative evaluations based on a task-based approach focused on tumor localization are provided.