Detecting metastatic pelvic lymph nodes by F-18-2-deoxyglucose positron emission tomography in patients with prostate-specific antigen relapse after treatment for localized prostate cancer

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Title:	Detecting metastatic pelvic lymph nodes by F-18-2-deoxyglucose positron emission tomography in patients with prostate-specific antigen relapse after treatment for localized prostate cancer
Authors:	Chang, CH;Wu, HC;Tsai, JJP;Shen, YY;Changlai, SP;Kao, A
Contributors:	附設醫院醫研部;China Med Coll Hosp, Dept Med Res, Taichung 404, Taiwan;China Med Coll Hosp, Dept Urol, Taichung 404, Taiwan;Taichung Healthcare & Management Univ, Grad Inst Bioinformat, Taichung, Taiwan;Shin Kong Wu Ho Su Mem Hosp, Dept Nucl Med, Taipei, Taiwan;Shin Kong Wu Ho Su Mem Hosp, PET Ctr, Taipei, Taiwan;Chung Shan Med Univ Hosp, Dept Nucl Med, Taichung, Taiwan;Chung Shan Med Univ Hosp, PET Ctr, Taichung, Taiwan
Date:	2003
Issue Date:	2010-09-24 14:58:38 (UTC+8)
Publisher:	KARGER
Abstract:	Recent statistics show that breast cancer is a major cause of death among women in developed countries. Hence, finding an accurate and effective diagnostic method is very important. In this paper, we propose a high precision computer-aided diagnosis (CAD) system for sonography. We utilize a support vector machine (SVM) to classify breast tumors according to their texture information surrounding speckle pixels. We test our system with 250 pathologically-proven breast tumors including 140 benign and 110 malignant ones. Also we compare the diagnostic performances of three texture features, i.e., speckle-emphasis texture feature, nonspeckle-emphasis texture feature and conventional all pixels texture feature, applied to breast sonography using SVM. In our experiment, the accuracy of SVM with speckle information for classifying malignancies is 93.2% (233/250), the sensitivity is 95.45% (105/110), the specificity is 91.43% (128/140), the positive predictive value is 89.74% (105/117) and the negative predictive value is 96.24% (128/133). Based on the experimental results, speckle phenomenon is a useful tool to be used in computer-aided diagnosis; its performance is better than those of the other two features. Speckle phenomenon, which is considered as noise in sonography, can intrude into judgments of a physician using naked eyes but it is another story for application in a computer-aided diagnosis algorithm. (C) 2003 World Federation for Ultrasound in Medicine Biology.
Relation:	UROLOGIA INTERNATIONALIS 70(4):311-315
Appears in Collections:	[China Medical University Hospital] Jurnal articles

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