Article
Radiology, Nuclear Medicine & Medical Imaging
Ur Metser, Claudia Ortega, Nathan Perlis, Eli Lechtman, Alejandro Berlin, Reut Anconina, Yael Eshet, Rosanna Chan, Patrick Veit-Haibach, Theodorus H. van der Kwast, Amy Liu, Sangeet Ghai
Summary: F-18-DCFPyL PET/mpMR contributes to the diagnosis of clinically significant prostate cancer compared to mpMR, especially in lesions with PI-RADS >= 3. PSMA PET has higher sensitivity but lower specificity for detecting csPCa compared to mpMR.
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yatong Liu, Yu Zhu, Wei Wang, Bingbing Zheng, Xiangxiang Qin, Peijun Wang
Summary: This study proposes a multi-scale segmentation network with cascading pyramid convolution module (CPCM) and double-input channel attention module (DCAM) for automated and accurate segmentation of prostate cancer (PCa) lesions using multiparametric magnetic resonance imaging (mpMRI).
Article
Radiology, Nuclear Medicine & Medical Imaging
Mengsi Li, Jing Guo, Ping Hu, Huichuan Jiang, Juan Chen, Jiaxi Hu, Patrick Asbach, Ingolf Sack, Wenzheng Li
Summary: The study investigated the diagnostic performance of stiffness and fluidity quantified with tomoelastography compared to multiparametric MRI in depicting prostate cancer. The results showed that combining stiffness and fluidity improved the diagnostic performance of detecting PCa, demonstrating higher specificity and better differentiation in both the peripheral and transition zones.
Article
Engineering, Electrical & Electronic
Dong Liu, Long Wang, Yu Du, Ming Cong, Yongyao Li
Summary: In this study, a real-time and accurate automatic detection and segmentation algorithm for 3-D MR and TRUS images of the prostate is proposed, which achieves efficient and accurate detection and segmentation even under poor image quality conditions. The experimental results on public and private datasets demonstrate the superiority of this method.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Computer Science, Information Systems
Yuejing Qian, Zengyou Zhang, Bo Wang
Summary: Prostate cancer is a challenging malignant tumor to detect accurately. The newly designed method ProCDet based on MR images shows competitive performance in efficiently and accurately detecting prostate cancer.
Article
Pathology
Hemamali Samaratunga, Lars Egevad, John W. W. Yaxley, Shulammite Johannsen, Ian K. K. Le Fevre, Joanna L. L. Perry-Keene, Troy Gianduzzo, Charles Chabert, Gregory Coughlin, Robert Parkinson, Boon Kua, William Yaxley, Brett Delahunt
Summary: Anterior prostate cancer (APC) is commonly found in the transition zone and can now be detected earlier through improved imaging and biopsy techniques. This study examined the pathologic features and clinical significance of pure APC, finding a higher incidence rate and larger tumors compared to the pre-multiparametric magnetic resonance imaging era.
AMERICAN JOURNAL OF SURGICAL PATHOLOGY
(2023)
Article
Multidisciplinary Sciences
Oscar J. Pellicer-Valero, Jose L. Marenco Jimenez, Victor Gonzalez-Perez, Juan Luis Casanova Ramon-Borja, Isabel Martin Garcia, Maria Barrios Benito, Paula Pelechano Gomez, Jose Rubio-Briones, Maria Jose Ruperez, Jose D. Martin-Guerrero
Summary: This paper proposes a fully automatic system based on Deep Learning that performs localization, segmentation and Gleason grade group (GGG) estimation of prostate cancer (PCa) lesions from prostate mpMRIs. The system achieves excellent results in terms of lesion-level AUC/sensitivity/specificity and compares favorably with expert radiologists.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Tung-Shing Mamie Lih, Mingming Dong, Leslie Mangold, Alan Partin, Hui Zhang
Summary: This study investigated the clinical utility of urinary marker panels composed of urinary glycopeptides and/or urinary prostate-specific antigen (PSA) for distinguishing non-aggressive from aggressive prostate cancer. The multi-marker panels showed clinically meaningful results with area under the curve (AUC) ranging from 0.70 to 0.85.
SCIENTIFIC REPORTS
(2022)
Article
Immunology
Haojie Chen, Jiatong Zhou, Jia Luo, Yanyuan Wu, Yuhang Qian, Yuntian Shi, Fajun Qu, Bowen Shi, Jie Ding, Xingang Cui, Yongjiang Yu
Summary: The study aims to identify less invasive and easily applicable serum cytokine-derived biomarkers for the diagnostic utility and risk assessment ability of grey zone aggressive prostate cancer (AG PCa) early detection. The results confirmed TRAIL and IL-10 as potential serum biomarkers for AG PCa detection.
FRONTIERS IN IMMUNOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Linda C. P. Thijssen, Maarten de Rooij, Jelle O. Barentsz, Henkjan J. Huisman
Summary: This study investigates the feasibility of using the Blind/referenceless image spatial quality evaluator (Brisque) and radiomics in the automated image quality assessment of T2-weighted images for prostate cancer detection. The results show that Radiomics AI can accurately detect suboptimal quality T2-weighted images.
EUROPEAN JOURNAL OF RADIOLOGY
(2023)
Article
Oncology
Lina Zhu, Ge Gao, Yi Zhu, Chao Han, Xiang Liu, Derun Li, Weipeng Liu, Xiangpeng Wang, Jingyuan Zhang, Xiaodong Zhang, Xiaoying Wang
Summary: The cascaded deep learning model trained with ADC and T2WI achieves good performance for automated detection and localization of clinically significant prostate cancer (csPCa).
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
Naseruddin Hoti, Tung-Shing Lih, Mingming Dong, Zhen Zhang, Leslie Mangold, Alan W. Partin, Lori J. Sokoll, Qing Kay Li, Hui Zhang
Summary: Prostate cancer is a leading cause of death in men in the United States. The commonly used method of diagnosis involves digital rectal examination and serum PSA assay, followed by prostate gland biopsy. However, false elevations in PSA levels can lead to unnecessary biopsies. This study evaluated the use of urinary PSA as a predictive marker for aggressive prostate cancer, and found that it had higher predictive power compared to serum PSA. Combining serum and urinary PSA levels further enhanced the detection of aggressive prostate cancer.
Article
Radiology, Nuclear Medicine & Medical Imaging
Byungjai Kim, Kinam Kwon, Changheun Oh, Hyunwook Park
Summary: An anomaly detection method for pixel-level detection in multicontrast MRI was proposed using a deep neural network. The algorithm showed significant improvements in quantitative and qualitative evaluations compared to previous methods. The effectiveness of each module in the proposed framework was validated through ablation studies.
Article
Chemistry, Multidisciplinary
Augustinas Matulevicius, Arnas Bakavicius, Albertas Ulys, Mantas Trakymas, Jurgita Usinskiene, Ieva Naruseviciute, Rasa Sabaliauskaite, Kristina Zukauskaite, Sonata Jarmalaite, Feliksas Jankevicius
Summary: The study demonstrates the high accuracy of multiparametric magnetic resonance imaging and ultrasound fusion-guided targeted prostate biopsy for detecting clinically significant prostate cancer. It also shows that adapted systematic biopsy does not provide additional benefit.
APPLIED SCIENCES-BASEL
(2022)
Article
Urology & Nephrology
Lorenzo Cereser, Gianluca Giannarini, Filippo Bonato, Stefano Pizzolitto, Giuseppe Como, Claudio Valotto, Vincenzo Ficarra, Fabrizio Dal Moro, Chiara Zuiani, Rossano Girometti
Summary: This study compared the accuracy of multiple abbreviated mpMRI-derived protocols in detecting clinically significant prostate cancer. The results showed that cesMRI was equivalent to mpMRI in terms of cancer detection and reducing the number of PI-RADSv2 category 3 assignments.
MINERVA UROLOGY AND NEPHROLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Stephane Lobreaux, Christelle Melodelima
Article
Radiology, Nuclear Medicine & Medical Imaging
Flavie Bratan, Christelle Melodelima, Remi Souchon, Au Hoang Dinh, Florence Mege-Lechevallier, Sebastien Crouzet, Marc Colombel, Albert Gelet, Olivier Rouviere
Article
Radiology, Nuclear Medicine & Medical Imaging
A. Hoang Dinh, R. Souchon, C. Melodelima, F. Bratan, F. Mege-Lechevallier, M. Colombel, O. Rouviere
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2015)
Article
Radiology, Nuclear Medicine & Medical Imaging
Olivier Rouviere, Christelle Melodelima, Au Hoang Dinh, Flavie Bratan, Gaele Pagnoux, Thomas Sanzalone, Sebastien Crouzet, Marc Colombel, Florence Mege-Lechevallier, Remi Souchon
EUROPEAN RADIOLOGY
(2017)
Meeting Abstract
Urology & Nephrology
Ji-Wann Lee, Albert Gelet, Jeremy Soria, Marc Colombel, Pascal Pommier, Christelle Melodelima, Olivier Rouviere, Lionel Badet, Sebastien Crouzet
JOURNAL OF UROLOGY
(2016)
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Radiology, Nuclear Medicine & Medical Imaging
J. Champagnac, C. Melodelima, T. Martinelli, G. Pagnoux, L. Badet, L. Juillard, O. Rouviere
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2016)
Article
Radiology, Nuclear Medicine & Medical Imaging
F. Alonzo, C. Melodelima, F. Bratan, T. Vitry, S. Crouzet, A. Gelet, O. Rouviere
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2016)
Article
Radiology, Nuclear Medicine & Medical Imaging
Au Hoang Dinh, Christelle Melodelima, Remi Souchon, Paul C. Moldovan, Flavie Bratan, Gaele Pagnoux, Florence Mege-Lechevallier, Alain Ruffion, Sebastien Crouzet, Marc Colombel, Olivier Rouviere
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Biotechnology & Applied Microbiology
Christophe Regnault, Isabelle A. M. Worms, Christine Oger-Desfeux, Christelle Melode Lima, Sylvie Veyrenc, Marie-Laure Bayle, Bruno Combourieu, Aurelie Bonin, Julien Renaud, Muriel Raveton, Stephane Reynaud
News Item
Biochemistry & Molecular Biology
Stephane Joost, Severine Vuilleumier, Jeffrey D. Jensen, Sean Schoville, Kevin Leempoel, Sylvie Stucki, Ivo Widmer, Christelle Melodelima, Jonathan Rolland, Stephanie Manel
Article
Biochemistry & Molecular Biology
Stephane Lobreaux, Stephanie Manel, Christelle Melodelima
MOLECULAR ECOLOGY RESOURCES
(2014)
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
O. Rouviere, R. Souchon, C. Melodelima
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2018)
Article
Radiology, Nuclear Medicine & Medical Imaging
S. Transin, R. Souchon, C. Gonindard-Melodelima, R. de Rozario, P. Walker, M. Funes de la Vega, R. Loffroy, L. Cormier, O. Rouviere
DIAGNOSTIC AND INTERVENTIONAL IMAGING
(2019)
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Genetics & Heredity
Christelle Melodelima, Stephane Lobreaux