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The Diagnosis Value Of 3.0T Dynamic Contrast Enhanced MRI(DCE-MRI) Combined With DWI On Identifying Benine And Malignant Breast Phymatoid Lesions

Posted on:2016-03-17Degree:MasterType:Thesis
Country:ChinaCandidate:Z X TangFull Text:PDF
GTID:2284330461463822Subject:Medical imaging and nuclear medicine
Abstract/Summary:PDF Full Text Request
Objective: To investigate the diagnosis value and the differential diagnosis value of 3.0T dynamic contrast enhancement magnetic resonance imaging(DCE-MRI) combined with DWI on the benign and malignant breast masses.Methods: Breast masses found in 88 cases by mammary gland molybdenum target X-ray photography and ultrasound examination for breasts were underwent 3.0T normally non-enhanced MRI, DWI and 6-phase consecutive DCE-MRI, and their MRI images were analyzed. According to the Breast Imaging Reporting and Data System MRI(2013 BI-RADS-MRI) standards proposed by the American College of Radiology, the morphological characteristics, internal enhancement characteristics and TIC type of masses, as well as the breast masses performance in DWI diffusion imaging were observed in proper order. SIEMENS VERIO 3.0T superconductive MRI scanners and 12-channel breast-specific phased array coil were applied in all MRI examinations, and the measurement for all data and image post-processing were completed on Mean-Curve software package built in this machine. SPSS 19.0 software was used for statistical analysis. Measurement data is expressed as x一±s. The chi square test was used for comparison of the difference of morphological features(including shape, border, and early enhancement rate), and for the comparison of TIC types between benign and malignant breast mass lesions. Independent-samples t test was used for the comparison of the early enhancement rate, between benign and malignant breast mass lesions. The receiver operating characteristic curve(ROC) of the early enhancement rate and the ADC values for diagnosing malignant breast masses was constructed respectively. The threshold of the early enhancement rate and the ADC values for diagnosing malignant breast masses was determined according to the highest point of Youden index(sensitivity+specificity-1), and the area under curve(AUC) was calculated. The sensitivity, specificity and accuracy for the differential diagnosis between benign and malignant breast masses using TIC types, early enhancement rate, ADC values and combined application of the above three methods were compared respectively according to the gold standard of histopathological diagnosis. The chi square test of row times column was used for comparison of the accuracy for malignant breast masses among the four methods. P<0.05 was defined as statistical significant.Results: Of there 88 breast mass lesions, 30 were benign and 58 were malignant according to the post operative histopathology. The main features of the benign breast mass lesions were as follows: ①shape: round and oval(26/30, 86.7%); ②margin: circumscribed(23/30, 76.7%); ③internal enhancement characteristics: homogeneous(24/30, 80.0%); ④the early enhancement rate<85.87%(26/30, 86.7%); ⑤type of TIC: type I(flow type)(22/30, 73.3%); ⑥signal intensity on DWI images: iso or slightly hyper(26/30, 86.7%)and⑦ADC value>1.209x10-3mm2/s(25/30, 83.3%). The main features of the malignant breast mass lesions were as follows: ①shape: irregular(49/58, 84.5%); ②margin: not circumscribed(50/58, 86.2%); ③internal enhancement characteristics: heterogeneous(45/58, 77.6%), rim enhancement(5/58, 8.6%), low signal separation(2/58, 3.4%); ④the early enhancement rate: >85.87%(56/58, 96.6%); ⑤type of TIC: type III(incremental type)(47/58, 81.0%); ⑥signal intensity on DWI images: hyper(55/58, 94.8%); ⑦and ADC value<1.209x10-3mm2/s(56/58, 96.6%). The shape differences(χ2=41.786, P<0.05)、the margin differences(χ2=34.256, P<0.05)and the distributional differences of internal enhancement characteristics(χ2=42.696, P < 0.05)of benign and malignant breast masses were statistically significant. TIC I and III type in breast benign and malignant masses distribution of significant differences(χ2=53.199, P < 0.05). And TIC I and III type curve in the diagnosis of breast masses of sensitivity, specificity and accuracy were 94.0%, 91.7% and 93.2% respectively. The early enhancement rate of benign breast masses was 64.74%±25.02%, the malignant breast masses was 117.62%±24.01%, the differences between benign and malignant breast masses with statistical significance(t=9.653, P<0.05). When b value was 800s/mm2, DWI diagrams of 88 masses appeared equisignal, slightly higher signal and high signal. And ADC values of benign and malignant masses were:(1.471±0.295)x10-3mm2/s and(1.063±0.126)x10-3mm2/s respectively, with statistically significant differences between them(t=7.247, P<0.05).Early enhancement rate as the standard for breast malignant masses diagnosis sensitivity, specificity and accuracy of 96.6%, 83.3% and 92.0%, respectively. TIC as malignant breast masses diagnostic criteria of sensitivity, specificity and accuracy of 81.0%, 73.3% and 78.4%, respectively. ADC values as the standard for malignant breast masses diagnosis sensitivity, specificity and accuracy was 96.6%, 86.7%, 93.2%. Combined application as the standard for the diagnosis of malignant breast masses sensitivity, specificity and accuracy were 98.3%, 93.3% and 96.6% respectively.Conclusion: DCE-MRI achieved a high sensitivity yet relatively low specificity for diagnosing malignant breast masses. DWI had no obvious reduced sensitivity but higher specificity than that of DCE-MRI for diagnosing malignant breast masses. Combined application of the above two methods may effectively raise the accuracy for diagnosing malignant breast masses without lose the sensitivity, which will be helpful for early found, early diagnose,and early treatment of breast cancer,and will supply more plentiful imaging data for individualized treatment planning.
Keywords/Search Tags:Breast masses, Magnetic resonance imaging, Dynamic contrast enhancement magnetic resonance imaging, early enhancement rate, Time intensity curve, Diffusion-weighted image
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