{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T13:57:40Z","timestamp":1787925460160,"version":"build-2784847793"},"reference-count":31,"publisher":"Wiley","issue":"6","license":[{"start":{"date-parts":[[2017,11,22]],"date-time":"2017-11-22T00:00:00Z","timestamp":1511308800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/501100007162","name":"Guangdong Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["2014A020212232"],"award-info":[{"award-number":["2014A020212232"]}],"id":[{"id":"10.13039\/501100007162","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81271569"],"award-info":[{"award-number":["81271569"]}],"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":["U1301258"],"award-info":[{"award-number":["U1301258"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Magnetic Resonance Imaging"],"published-print":{"date-parts":[[2018,6]]},"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Diffusion\u2010weighted imaging (DWI) has been studied in breast imaging and can provide more information about diffusion, perfusion and other physiological interests than standard pulse sequences. The stretched\u2010exponential model has previously been shown to be more reliable than conventional DWI techniques, but different diagnostic sensitivities were found from study to study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>This work investigated the characteristics of whole\u2010lesion histogram parameters derived from the stretched\u2010exponential diffusion model for benign and malignant breast lesions, compared them with conventional apparent diffusion coefficient (ADC), and further determined which histogram metrics can be best used to differentiate malignant from benign lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Study Type<\/jats:title><jats:p>This was a prospective study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Population<\/jats:title><jats:p>Seventy females were included in the study.<\/jats:p><\/jats:sec><jats:sec><jats:title>Field Strength\/Sequence<\/jats:title><jats:p>Multi\u2010b value DWI was performed on a 1.5T scanner.<\/jats:p><\/jats:sec><jats:sec><jats:title>Assessment<\/jats:title><jats:p>Histogram parameters of whole lesions for distributed diffusion coefficient (DDC), heterogeneity index (\u03b1), and ADC were calculated by two radiologists and compared among benign lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma confirmed by pathology.<\/jats:p><\/jats:sec><jats:sec><jats:title>Statistical Tests<\/jats:title><jats:p>Nonparametric tests were performed for comparisons among invasive carcinoma, DCIS, and benign lesions. Comparisons of receiver operating characteristic (ROC) curves were performed to show the ability to discriminate malignant from benign lesions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The majority of histogram parameters (mean\/min\/max, skewness\/kurtosis, 10\u201390<jats:sup>th<\/jats:sup> percentile values) from DDC, \u03b1, and ADC were significantly different among invasive carcinoma, DCIS, and benign lesions. DDC<jats:sub>10%<\/jats:sub> (area under curve [AUC]\u2009=\u20090.931), ADC<jats:sub>10%<\/jats:sub> (AUC\u2009=\u20090.893), and \u03b1<jats:sub>mean<\/jats:sub> (AUC\u2009=\u20090.787) were found to be the best metrics in differentiating benign from malignant tumors among all histogram parameters derived from ADC and \u03b1, respectively. The combination of DDC<jats:sub>10%<\/jats:sub> and \u03b1<jats:sub>mean<\/jats:sub>, using logistic regression, yielded the highest sensitivity (90.2%) and specificity (95.5%).<\/jats:p><\/jats:sec><jats:sec><jats:title>Data Conclusion<\/jats:title><jats:p>DDC<jats:sub>10%<\/jats:sub> and \u03b1<jats:sub>mean<\/jats:sub> derived from the stretched\u2010exponential model provides more information and better diagnostic performance in differentiating malignancy from benign lesions than ADC parameters derived from a monoexponential model.<\/jats:p><jats:p><jats:bold>Level of Evidence:<\/jats:bold> 2<\/jats:p><jats:p><jats:bold>Technical Efficacy:<\/jats:bold> Stage 2<\/jats:p><jats:p>J. Magn. Reson. Imaging 2018;47:1701\u20131710.<\/jats:p><\/jats:sec>","DOI":"10.1002\/jmri.25904","type":"journal-article","created":{"date-parts":[[2017,11,22]],"date-time":"2017-11-22T13:02:46Z","timestamp":1511355766000},"page":"1701-1710","source":"Crossref","is-referenced-by-count":31,"title":["Breast lesion characterization using whole\u2010lesion histogram analysis with stretched\u2010exponential diffusion model"],"prefix":"10.1002","volume":"47","author":[{"given":"Chunling","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Radiology Guangdong General Hospital affiliated to South China University of Technology\/Guangdong Academy of Medical Sciences  P.R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Breast Center, Cancer Center Guangdong General Hospital affiliated to South China University of Technology\/Guangdong Academy of Medical Sciences  P.R. 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China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Ding","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Stony Brook University Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Karl","family":"Spuhler","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering Stony Brook University Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy","family":"Duong","sequence":"additional","affiliation":[{"name":"Department of Radiology Stony Brook Medicine Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Changhong","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Radiology Guangdong General Hospital affiliated to South China University of Technology\/Guangdong Academy of Medical Sciences  P.R. 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