A5076314118- Prostate Cancer Diagnosis and Treatment
- Prostate Cancer Treatment and Research
- Radiomics and Machine Learning in Medical Imaging
- Urologic and reproductive health conditions
- Bladder and Urothelial Cancer Treatments
- MRI in cancer diagnosis
- Renal cell carcinoma treatment
- Colorectal Cancer Screening and Detection
- Surgical Simulation and Training
- AI in cancer detection
- Medical Imaging and Analysis
- Radiopharmaceutical Chemistry and Applications
- Advanced X-ray and CT Imaging
- Pelvic floor disorders treatments
- Urological Disorders and Treatments
- Hormonal and reproductive studies
- Advanced Image Processing Techniques
- Generative Adversarial Networks and Image Synthesis
- Urinary Bladder and Prostate Research
- Advanced Radiotherapy Techniques
- Anatomy and Medical Technology
- Genital Health and Disease
- Health Systems, Economic Evaluations, Quality of Life
- Delphi Technique in Research
- Soft Robotics and Applications
Technische Universität Dresden
2024-2025
Klinik und Poliklinik für Urologie
2012-2025
University Hospital Carl Gustav Carus
2023-2025
National Institutes of Health
2017-2023
National Cancer Institute
2017-2023
Johannes Gutenberg University Mainz
2008-2021
Center for Cancer Research
2017-2021
University Medical Center of the Johannes Gutenberg University Mainz
2016-2021
University Medical Center
2018-2021
University of Baltimore
2020
The use of 12-core systematic prostate biopsy is associated with diagnostic inaccuracy that contributes to both overdiagnosis and underdiagnosis cancer. Biopsies performed magnetic resonance imaging (MRI) targeting may reduce the misclassification cancer in men MRI-visible lesions.
Purpose To evaluate MRI features associated with pathologically defined extraprostatic extension (EPE) of prostate cancer and to propose an grading system for pathologic EPE. Materials Methods In this prospective study, consecutive male study participants underwent preoperative 3.0-T from June 2007 March 2017 followed by robotic-assisted laparoscopic radical prostatectomy. An MRI-based EPE was as follows: curvilinear contact length 1.5 cm or capsular bulge irregularity were grade 1, both 2,...
Multiparametric magnetic resonance imaging (MRI) in conjunction with MRI-transrectal ultrasound (TRUS) fusion-guided biopsies have improved the detection of prostate cancer. It is unclear whether MRI itself adds additional value to multivariable prediction models based on clinical parameters.To determine an MRI-based model can reduce unnecessary patients suspected cancer.Patients underwent MRI, MRI-TRUS biopsy, and 12-core systematic biopsy 1 session. The development cohort used derive...
No AccessJournal of UrologyAdult Urology1 Sep 2017Prospective Evaluation PI-RADS™ Version 2 Using the International Society Urological Pathology Prostate Cancer Grade Group System Sherif Mehralivand, Sandra Bednarova, Joanna. H. Shih, Francesca V. Mertan, Sonia Gaur, Maria J. Merino, Bradford Wood, Peter A. Pinto, L. Choyke, and Baris Turkbey MehralivandSherif Mehralivand Department Urology Pediatric Urology, University Medical Center, Mainz, Germany Urologic Oncology Branch, National...
The Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) has been in use since 2015; while interreader reproducibility studied, there a paucity of studies investigating the intrareader PI-RADSv2.
The purpose of this study was to prospectively evaluate Prostate Imaging Reporting and Data System version 2.1 (PI-RADSv2.1), which released in March 2019 update 2.0, for prostate cancer detection with transrectal ultrasound-MRI fusion biopsy 12-core systematic biopsy.
Multi-domain data are widely leveraged in vision applications taking advantage of complementary information from different modalities, e.g., brain tumor segmentation multi-parametric magnetic resonance imaging (MRI). However, due to possible corruption and protocols, the availability images for each domain could vary amongst multiple sources practice, which makes it challenging build a universal model with varied set input data. To tackle this problem, we propose general approach complete...
No AccessJournal of UrologyAdult Urology1 Nov 2018Added Value Multiparametric Magnetic Resonance Imaging to Clinical Nomograms for Predicting Adverse Pathology in Prostate Cancer Kareem N. Rayn, Jonathan B. Bloom, Samuel A. Gold, Graham R. Hale, Joseph Baiocco, Sherif Mehralivand, Marcin Czarniecki, Vikram K. Sabarwal, Vladimir Valera, Bradford J. Wood, Maria Merino, Peter Choyke, Baris Turkbey, and Pinto RaynKareem Rayn Urologic Oncology Branch, National Institute, Institutes Health,...
// Sonia Gaur 1 , Nathan Lay 2 Stephanie A. Harmon 1, 3 Sreya Doddakashi Sherif Mehralivand 4, 5 Burak Argun 6 Tristan Barrett 7 Sandra Bednarova 8 Rossanno Girometti Ercan Karaarslan 9 Ali Riza Kural Aytekin Oto 10 Andrei S. Purysko 11 Tatjana Antic 12 Cristina Magi-Galluzzi 13 Yesim Saglican 14 Stefano Sioletic 15 Anne Y. Warren 16 Leonardo Bittencourt 17 Jurgen J. Fütterer 18 Rajan T. Gupta 19 Ismail Kabakus 20 Yan Mee Law 21 Daniel Margolis 22 Haytham Shebel 23 Antonio C. Westphalen 24...
Background The Prostate Imaging Reporting and Data System (PI‐RADS) provides guidelines for risk stratification of lesions detected on multiparametric MRI (mpMRI) the prostate but suffers from high intra/interreader variability. Purpose To develop an artificial intelligence (AI) solution PI‐RADS classification compare its performance with expert radiologist using targeted biopsy results. Study Type Retrospective study including data our institution publicly available ProstateX dataset....
To develop an artificial intelligence (AI)-based model for identifying patients with lymph node (LN) metastasis based on digital evaluation of primary tumors and train the using cystectomy specimens available from The Cancer Genome Atlas (TCGA) Project; our institution were included validation leave-out test cohort.
Multiple studies demonstrate magnetic resonance imaging (MRI)-targeted biopsy detects more clinically significant cancer than systematic biopsy; however, some cancers are detected by only. While these events rare, we sought to perform a retrospective analysis of cases ascertain the reasons that MRI-targeted missed which was subsequently on prostate biopsy.Patients were enrolled in prospective study comparing detection rates transrectal fusion and 12-core biopsy. Patients with an elevated...
Abstract The androgen receptor (AR) is a crucial player in various aspects of male reproduction and has been associated with the development progression prostate cancer (PCa). Therefore, protein linchpin current PCa therapies. Despite great research efforts, AR signaling pathway still not deciphered, emergence resistance biggest problem treatment. To discuss latest developments research, “1st International Androgen Receptor Symposium” offered forum for exchange clinical scientific...
Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation ModelThomas H. Sanford1, Ling Zhang2, Stephanie A. Harmon1,3, Jonathan Sackett1, Dong Yang2, Holger Roth2, Ziyue Xu2, Deepak Kesani1, Sherif Mehralivand1, Ronaldo Baroni4, Tristan Barrett5, Rossano Girometti6, Aytekin Oto7, Andrei S. Purysko8, Sheng Xu1, Peter Pinto1, Daguang Bradford J. Wood1, L. Choyke1 Baris Turkbey1Audio Available | Share
The purpose of this study was to evaluate in a multicenter dataset the performance an artificial intelligence (AI) detection system with attention mapping compared multiparametric MRI (mpMRI) interpretation prostate cancer.
The purpose of this study was to compare the diagnostic performance
Multiple drug resistance protein 4 (MRP4, ABCC4) belongs to the C subfamily of ATP-binding cassette (ABC) transporter superfamily and participates in transport diverse antiviral chemotherapeutic agents such as 6-mercaptopurine (6-MP) 9-(2-phosphonyl methoxyethyl) adenine (PMEA). We have undertaken a comprehensive functional characterization variants MRP4 found Caucasians other ethnicities. A total 11 missense genetic (nonsynonymous SNPs), fused green fluorescent (GFP), were examined Xenopus...
The purposes of this study were to assess correlation apparent diffusion coefficient (ADC) and normalized ADC (ratio tumor nontumor tissue) with the Prostate Imaging Reporting Data System version 2 (PI-RADSv2) updated International Society Urological Pathology (ISUP) categories determine how optimally use metrics for objective assistance in categorizing lesions within PI-RADSv2 guidelines.