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Eskandari H.,Shahid Beheshti University | Talebpour A.,Shahid Beheshti University | Tabrizi S.H.,Shahid Beheshti University | Nowroozi M.R.,Uro Oncology Research Center
2012 19th Iranian Conference of Biomedical Engineering, ICBME 2012 | Year: 2012

This paper presents a fast and automatic algorithm for prostate segmentation in ultrasound images. An accurate prostate delineation on Transrectal ultrasound (TRUS) images has many applications including guiding the biopsy needle to the suspicious core when registered with a preoperative imaging modality, or in treatment planning and motion monitoring in therapy interventions. However, ultrasound image segmentation is a difficult task because of the speckles and relatively low tissue-to-tissue contrast in ultrasound images. The proposed method is based on the features extracted from the intensity of the TRUS images, specifically the gradient of it. Six 2D TRUS images acquired from one patient were used to evaluate the performance of the proposed algorithm. Quantitative assessment of the method was done by comparing the automatic segmentation results with the corresponding gold standard obtained from manual segmentation of the target organ. The resulted accuracy, sensitivity and specificity were 98.69±0.27%, 96.40±1.26% and 99.33±0.45%, respectively. © 2012 IEEE. Source


Mahdian R.,Pasteur Institute of Iran | Nodouzi V.,Pasteur Institute of Iran | Asgari M.,Tehran University of Medical Sciences | Rezaie M.,Medical Diagnosis and Reference Laboratories of Iranian Blood Transfusion | And 5 more authors.
Molecular Biology Reports | Year: 2014

Complex molecular changes that occur during prostate cancer (PCa) progression have been described recently. Whole genome sequencing of primary PCa samples has identified recurrent gene deletions and rearrangements in PCa. Specifically, these molecular events disrupt the gene loci of phosphatase and tensin homolog (PTEN) and membrane-associated guanylate kinase inverted-2 (MAGI2). In the present study, we analyzed the expression profile of MAGI2 gene in a cohort of clinical PCa (n = 45) and benign prostatic hyperplasia (BPH) samples (n = 36) as well as three PCa cell lines. We also studied the expression of PCa-related genes, including PTEN, NKX3.1, SPINK1, DD3, AMACR, ERG, and TMPRSS2-ERG fusion in the same samples. The expression of MAGI2 mRNA was significantly down-regulated in PC3, LNCaP and DU-145 PCa cell lines (p = 0.000), and also in clinical tumor samples (Relative expression = 0.307, p = 0.002, [95 % CI 0.002-12.08]). The expression of PTEN, NKX3.1, SPINK1, DD3, and AMACR genes was significantly deregulated in prostate tumor samples (p range 0.000-0.044). A significant correlation was observed between MAGI2 and NKX3.1 expression in tumor samples (p = 0.006). Furthermore, the inclusion of MAGI2 in the gene panel improved the accuracy for discrimination between PCa and BPH samples with the sensitivity and specificity of 0.88 [CI 0.76-0.95] and 0.83 [CI 0.68-0.92], respectively. The data presented here suggest that MAGI2 gene can be considered as a novel component of gene signatures for the detection of PCa. © 2014 Springer Science+Business Media. Source

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