{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T02:09:58Z","timestamp":1767838198887,"version":"3.49.0"},"reference-count":41,"publisher":"American Society of Clinical Oncology (ASCO)","issue":"7","content-domain":{"domain":["ascopubs.org"],"crossmark-restriction":true},"short-container-title":["JCO Clinical Cancer Informatics"],"published-print":{"date-parts":[[2023,1]]},"abstract":"<jats:sec><jats:title>PURPOSE<\/jats:title><jats:p> Breast cancer is the most frequent cancer in women worldwide. However, its diagnosis mostly depends on visual examination of radiologic images, leading to an overdiagnosis with substantial costs. Therefore, a quantitative approach such as dynamic contrast enhanced (DCE)-magnetic resonance imaging (MRI) through pharmacokinetic (PK) modeling is required for reliable analysis. As PK parameters lack information on parameter heterogeneity, texture-based analysis is required to quantify PK parameter heterogeneity. Therefore, this study focused on determining the usefulness of fractal dimension (FD) as a potential imaging biomarker of tumor heterogeneity for discriminating benign and malignant breast lesions. <\/jats:p><\/jats:sec><jats:sec><jats:title>METHODS<\/jats:title><jats:p> Parametric maps for PK parameters, extravasation rate of contrast agent from blood plasma to extravascular extracellular space (K<jats:sup>trans<\/jats:sup>) and volume fraction of extravascular extracellular space (v<jats:sub>e<\/jats:sub>), were generated for the regions of interest (ROIs) under the standard model using 18 lesions. Then, tumor ROI and pixel DCE-MRI time-course data were analyzed to extract pixel values of K<jats:sup>trans<\/jats:sup> and v<jats:sub>e<\/jats:sub>. For each ROI, FD values of K<jats:sup>trans<\/jats:sup> and v<jats:sub>e<\/jats:sub> were computed using the blanket method. <\/jats:p><\/jats:sec><jats:sec><jats:title>RESULTS<\/jats:title><jats:p> The FD values of K<jats:sup>trans<\/jats:sup> for benign and malignant lesions varied from 2.96 to 3.49 and from 2.37 to 3.16, respectively, whereas FD values of v<jats:sub>e<\/jats:sub> for benign and malignant lesions varied from 3.01 to 5.15 and 2.42 to 3.44, respectively. There were significant differences in FD values derived from K<jats:sup>trans<\/jats:sup> parametric maps ( P = .0053) and v<jats:sub>e<\/jats:sub> parametric maps ( P = .0271) between benign and malignant lesions according to the statistical analysis. <\/jats:p><\/jats:sec><jats:sec><jats:title>CONCLUSION<\/jats:title><jats:p> Incorporating texture heterogeneity changes in breast lesions captured by FD with quantitative DCE-MRI parameters generated under the standard model is a potential marker for prediction of malignant lesions. <\/jats:p><\/jats:sec>","DOI":"10.1200\/cci.22.00101","type":"journal-article","created":{"date-parts":[[2023,2,6]],"date-time":"2023-02-06T21:00:15Z","timestamp":1675717215000},"update-policy":"https:\/\/doi.org\/10.1200\/crossmark","source":"Crossref","is-referenced-by-count":2,"title":["Fractal Dimension Analysis of Pixel Dynamic Contrast Enhanced-Magnetic Resonance Imaging Pharmacokinetic Parameters for Discrimination of Benign and Malignant Breast 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