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Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging

  • Authors:
    • Qingliang Niu
    • Xiaomei Jiang
    • Qin Li
    • Zhaolong Zheng
    • Hanwang Du
    • Shasha Wu
    • Xuexi Zhang

  • View Affiliations

  • Published online on: July 23, 2018     https://doi.org/10.3892/ol.2018.9196
  • Pages: 4607-4613
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Abstract

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has become a powerful tool for the diagnosis of breast cancer in the clinical setting due to its high sensitivity and specificity. Pharmacokinetic parameters, including Ktrans and area under the curve (AUC), and texture features derived from DCE-MRI have been used to specify the characteristics inside tumors. In the present study, 56 patients (average age 45.3±11.1; range 25-69 years) with histopathologically proved breast tumors were analyzed using the pharmacokinetic parameters and texture features. Malignant tumors displayed higher Ktrans and AUC values than the benign, Ktrans exhibited a significantly difference between the malignant and benign tumors (P=0.001) compared with the AUC values (P=0.029); texture features from DCE-MRI images and pharmacokinetic parameter maps also showed a good diagnostic ability. Alongside the routine method, principal components analysis (PCA) and Fisher discriminant analysis (FDA) were employed on these texture features to differentiate the breast lesions automatically. The Factor-1 scores of PCA were used to divide the patients into two groups, and the diagnosing accuracies of the FDA method on the texture features from DCE-MRI images, Ktrans maps, AUC maps were 93, 98 and 98%, with a cross validation accuracies of 82, 77 and 77%, respectively. To conclude, pharmacokinetic parameters, texture features and the combined computer-assisted classification method were discussed. All method involved in this study may be a potential assisted tool for radiological analysis on breast.
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October-2018
Volume 16 Issue 4

Print ISSN: 1792-1074
Online ISSN:1792-1082

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  • Source Normalized Impact per Paper (SNIP): 0.574
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Spandidos Publications style
Niu Q, Jiang X, Li Q, Zheng Z, Du H, Wu S and Zhang X: Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging. Oncol Lett 16: 4607-4613, 2018.
APA
Niu, Q., Jiang, X., Li, Q., Zheng, Z., Du, H., Wu, S., & Zhang, X. (2018). Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging. Oncology Letters, 16, 4607-4613. https://doi.org/10.3892/ol.2018.9196
MLA
Niu, Q., Jiang, X., Li, Q., Zheng, Z., Du, H., Wu, S., Zhang, X."Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging". Oncology Letters 16.4 (2018): 4607-4613.
Chicago
Niu, Q., Jiang, X., Li, Q., Zheng, Z., Du, H., Wu, S., Zhang, X."Texture features and pharmacokinetic parameters in differentiating benign and malignant breast lesions by dynamic contrast enhanced magnetic resonance imaging". Oncology Letters 16, no. 4 (2018): 4607-4613. https://doi.org/10.3892/ol.2018.9196