Preoperative MR imaging in the evaluation of seminal vesicle invasion in prostate cancer: pattern analysis of seminal vesicle lesions

Cited 14 time in Web of Science Cited 18 time in Scopus

Jung, Dae Chul; Lee, Hak Jong; Kim, Seung Hyup; Choe, Ghee Young; Lee, Sang Eun

Issue Date
J Magn Reson Imaging 2008;28:144-150
MR imagingprostate cancerseminal vesicle
PURPOSE: To develop an image-based classification system for seminal vesicle lesions (SVL) to detect seminal vesicle invasion (SVI) in prostate cancer and to evaluate whether pattern analysis of SVL with MR imaging could improve the accuracy of evaluating SVI. MATERIALS AND METHODS: The MR images of 217 patients who had undergone retropubic radical prostatectomy (RRP) due to prostate cancer were retrospectively analyzed by two uroradiologists, focusing on SVL. The SVL on T2-weighted sequences was classified as five classes. In each class the results were correlated with histopathologic findings. RESULTS: Fourteen (6.5%) of 217 patients had evidence of SVI at histopathologic evaluation after RRP. Pattern analysis of SVL showed 71.4% sensitivity, 96.6% specificity for predicting SVI. ROC curves for the subjective scoring of SVI showed that reader 1 had an area under the curve (AUC) of 0.69 and reader 2 had an AUC of 0.81. The overall accuracy of pattern analysis was superior to both serum prostate-specific antigen (PSA) level and subjective scoring (P < 0.01, McNemar test). CONCLUSION: The classification system of SVL on the basis of their imaged morphologic features can provide an objective standard and simplify the abnormal findings to help predict SVI in prostate cancer. Pattern analysis of SVL with MR imaging improves the accuracy of detecting SVI.
Files in This Item:
There are no files associated with this item.
Appears in Collections:
College of Medicine/School of Medicine (의과대학/대학원)Pathology (병리학전공)Journal Papers (저널논문_병리학전공)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.