Back to Search
Start Over
[Distinguishing benign and malignant lesions with time-signal intensity curve of dynamic contrast-enhanced breast MRI scanning].
- Source :
-
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition [Sichuan Da Xue Xue Bao Yi Xue Ban] 2011 Jul; Vol. 42 (4), pp. 556-9. - Publication Year :
- 2011
-
Abstract
- Objective: To determine the diagnostic value of time-signal intensity curve (TIC) in distinguishing breast malignant tumors from benign lesions.<br />Methods: Forty-four patients with 50 breast lesions were recruited in the study, including 24 pathologically confirmed benign lesions and 26 malignant tumors. All patients received dynamic contrast-enhanced breast MRI scanning a week before surgery. The time-signal intensity curves in the regions of interest (ROI) and eight items of TIC including shape, T peak, E peak, Slope(i), E1, E2, W peak-7, and W peak-9 were compared between benign lesions and malignant tumors. The receive operating characteristic curves (ROC) were depicted for those indicators with significant statistical differences.<br />Results: Six items of TIC including shape, T peak, Slope(i), E1, E2, and W peak-9 were significantly different (P<0.05) between malignant tumors and benign lesions. The sensitivities of shape, T peak, Slope(i), E1, E2, and W peak-9 for diagnosing breast malignant tumors were 92.3%, 95.83%, 80.77%, 61.53%, 69.23%, and 69.23% respectively. Their specificities were 87.5%, 92.3%, 95.8%, 87.5%, 79.17%, and 79.17% respectively. TIC curve shape, T peak and Slope(i) were better than E1, E2 and W peak-9 in diagnosing breast malignant lesions (P<0.05).<br />Conclusion: Benign and malignant breast tumors can be differentiated according to TIC. TIC curve shape, T peak and Slope(i) are better than E1, E2 and W peak-9 in distinguishing malignant breast tumors from benign lesions.
Details
- Language :
- Chinese
- ISSN :
- 1672-173X
- Volume :
- 42
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
- Publication Type :
- Academic Journal
- Accession number :
- 21866648