PURPOSE: To identify features useful for differentiation between malignant and benign breast neoplasms using multivariate analysis of findings by MR imaging. MATERIAL AND METHODS: In a retrospective analysis, 61 patients with 64 breast masses underwent MR imaging and the time-signal intensity curves for precontrast dynamic postcontrast images were quantitatively analyzed. Statistical analysis was performed using a logistic regression model, which was prospectively tested in another 34 patients with suspected breast masses. RESULTS: Univariate analysis revealed that the reliable indicators for malignancy were first the appearance of the tumor border, followed by the washout ratio, internal architecture after contrast enhancement, and peak time. The factors significantly associated with malignancy were irregular tumor border, followed by washout ratio, internal architecture, and peak time. For differentiation between benignity and malignancy, the maximum cut-off point was to be found between 0.47 and 0.51. In a prospective application of this model, 91% of the lesions were accurately discriminated as benign or malignant lesions. CONCLUSION: Combination of contrast-enhanced dynamic and postcontrast-enhanced MR imaging provided accurate data for the diagnosis of malignant neoplasms of the breast. The model had an accuracy of 91% (sensitivity 90%, specificity 93%).
PURPOSE: To identify features useful for differentiation between malignant and benign breast neoplasms using multivariate analysis of findings by MR imaging. MATERIAL AND METHODS: In a retrospective analysis, 61 patients with 64 breast masses underwent MR imaging and the time-signal intensity curves for precontrast dynamic postcontrast images were quantitatively analyzed. Statistical analysis was performed using a logistic regression model, which was prospectively tested in another 34 patients with suspected breast masses. RESULTS: Univariate analysis revealed that the reliable indicators for malignancy were first the appearance of the tumor border, followed by the washout ratio, internal architecture after contrast enhancement, and peak time. The factors significantly associated with malignancy were irregular tumor border, followed by washout ratio, internal architecture, and peak time. For differentiation between benignity and malignancy, the maximum cut-off point was to be found between 0.47 and 0.51. In a prospective application of this model, 91% of the lesions were accurately discriminated as benign or malignant lesions. CONCLUSION: Combination of contrast-enhanced dynamic and postcontrast-enhanced MR imaging provided accurate data for the diagnosis of malignant neoplasms of the breast. The model had an accuracy of 91% (sensitivity 90%, specificity 93%).
Authors: Luminita A Tudorica; Karen Y Oh; Nicole Roy; Mark D Kettler; Yiyi Chen; Stephanie L Hemmingson; Aneela Afzal; John W Grinstead; Gerhard Laub; Xin Li; Wei Huang Journal: Magn Reson Imaging Date: 2012-07-06 Impact factor: 2.546
Authors: Anna G Sorace; Savannah C Partridge; Xia Li; Jack Virostko; Stephanie L Barnes; Daniel S Hippe; Wei Huang; Thomas E Yankeelov Journal: J Med Imaging (Bellingham) Date: 2018-01-22
Authors: Laura G Merckel; Helena M Verkooijen; Nicky H G M Peters; Ritse M Mann; Wouter B Veldhuis; Remmert K Storm; Teun Weits; Katya M Duvivier; Thijs van Dalen; Willem P Th M Mali; Petra H M Peeters; Maurice A A J van den Bosch Journal: PLoS One Date: 2014-04-08 Impact factor: 3.240