Article
Medicine, General & Internal
See Hyung Kim, Seung Hyun Cho, Won Hwa Kim, Hye Jung Kim, Jong Min Park, Gab Chul Kim, Hun Kyu Ryeom, Yu Sung Yoon, Jung Guen Cha
Summary: This retrospective cohort study aimed to identify effective factors predicting extraprostatic extension (EPE) in patients with prostate cancer. The study found that histopathological analysis and magnetic resonance imaging scores, along with basic clinical and demographic information, were potentially useful for predicting EPE in patients with prostate cancer.
JOURNAL OF CLINICAL MEDICINE
(2023)
Review
Oncology
Wei Li, Wenwen Shang, Feng Lu, Yuan Sun, Jun Tian, Yiman Wu, Anding Dong
Summary: The diagnostic performance of the extraprostatic extension (EPE) grading system for detecting EPE in patients with prostate cancer (PCa) was evaluated. The EPE grading system showed high sensitivity and moderate specificity, indicating its potential as a diagnostic tool for EPE detection. However, further studies are needed to validate its application in clinical practice.
FRONTIERS IN ONCOLOGY
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Andrea Ponsiglione, Arnaldo Stanzione, Gianluigi Califano, Marco De Giorgi, Claudia Colla Ruvolo, Imma D'Iglio, Simone Morra, Nicola Longo, Massimo Imbriaco, Renato Cuocolo
Summary: The purpose of this study was to assess the impact of prostate MRI image quality on the identification of extraprostatic extension of disease. The results showed that image quality had little impact on the accuracy of EPE Grade and Likert Scale Score, but had some impact on the MSKCCn score. The study suggests that assessing image quality using PI-QUAL is important for accurately evaluating EPE.
EUROPEAN JOURNAL OF RADIOLOGY
(2023)
Article
Oncology
Stefania L. Moroianu, Indrani Bhattacharya, Arun Seetharaman, Wei Shao, Christian A. Kunder, Avishkar Sharma, Pejman Ghanouni, Richard E. Fan, Geoffrey A. Sonn, Mirabela Rusu
Summary: This study proposes a computational method for the detection of extraprostatic extension (EPE) on multiparametric MRI using deep learning. The method achieves high sensitivity and specificity, providing a potential independent diagnostic aid for radiologists and facilitating treatment planning.
Article
Radiology, Nuclear Medicine & Medical Imaging
Wei Li, Anding Dong, Guohui Hong, Wenwen Shang, Xiaocui Shen
Summary: This meta-analysis evaluated the diagnostic performance of the ESUR scoring system for detecting extraprostatic extension in prostate cancer, finding moderate performance with significant factors contributing to heterogeneity being the cutoff values and malignancy rate.
EUROPEAN JOURNAL OF RADIOLOGY
(2021)
Article
Oncology
Ingeborg van den Berg, Timo F. W. Soeterik, Erik J. R. J. van der Hoeven, Bart Claassen, Wyger M. Brink, Diederik J. H. Baas, J. P. Michiel Sedelaar, Lizette Heine, Jim Tol, Jochem R. N. van der Voort van Zyp, Cornelis A. T. van den Berg, Roderick C. N. van den Bergh, Jean-Paul A. van Basten, Harm H. E. van Melick
Summary: Artificial intelligence algorithms can improve the prediction of lesion-specific EPE in prostate cancer patients, providing valuable information for counseling and surgical planning.
Review
Radiology, Nuclear Medicine & Medical Imaging
MeiLin Zhu, JiaHao Gao, Fang Han, LongLin Yin, LuShun Zhang, Yong Yang, JiaWen Zhang
Summary: This study evaluated the accuracy of MRI-inclusive nomograms and traditional clinical nomograms in predicting extraprostatic extension (EPE) in prostate cancer (PCa), and found that both had moderate diagnostic performance. The study provides baseline estimates for future studies, which are useful for evaluating preoperative risk stratification in PCa patients.
INSIGHTS INTO IMAGING
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Marco Gatti, Riccardo Faletti, Francesco Gentile, Enrico Soncin, Giorgio Calleris, Alberto Fornari, Marco Oderda, Alessandro Serafini, Giulio Antonino Strazzarino, Elena Vissio, Laura Bergamasco, Stefano Cirillo, Mauro Giulio Papotti, Paolo Gontero, Paolo Fonio
Summary: The objective of this study was to investigate the diagnostic accuracy of PI-RADS v2.1 multiparametric magnetic resonance imaging (mpMRI) features in predicting extraprostatic extension (mEPE) of prostate cancer (PCa), and to develop and validate a comprehensive mpMRI-derived score (mEPE-score). The results showed that the mEPE-score had excellent discriminating ability and allowed for consistent and reliable assessment for pathologic EPE.
EUROPEAN RADIOLOGY
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
Moon Hyung Choi, Dong Hwan Kim, Young Joon Lee, Sung Eun Rha, Ji Youl Lee
Summary: This study aimed to evaluate the diagnostic performance of each MRI feature of the PI-RADS for predicting extraprostatic extension in prostate cancer. After screening 1955 studies, 17 studies with a total of 3062 men were included. Among the six MRI features, breach of the capsule with direct tumor extension and tumor-capsule interface > 10 mm were the most predictive of extraprostatic extension with the highest specificity (98.0%) and sensitivity (86.3%), respectively.
INSIGHTS INTO IMAGING
(2023)
Article
Multidisciplinary Sciences
Cheol Keun Park, Yeon Seung Chung, Young Deuk Choi, Won Sik Ham, Won Sik Jang, Nam Hoon Cho
Summary: The study focused on the extraprostatic extension (EPE) in pT3a prostate cancer, proposing a sub-staging system based on EPE classification. By measuring the number and radial distance of EPE, a significant predictive algorithm for biochemical recurrence (BCR) was established. The combination of radial distance and number of EPEs proved to be the most effective predictor of BCR, potentially aiding in personalized prognosis for patients.
SCIENTIFIC REPORTS
(2021)
Article
Biotechnology & Applied Microbiology
Jun-Yi Xiang, Xiao-Shan Huang, Jian-Xia Xu, Ren-Hua Huang, Xiao-Zhong Zheng, Li-Ming Xue, Yu-Long Liu
Summary: This study compared the accuracy of MRI, Partin tables, MSKCCn, and combined models in predicting extraprostatic extension (EPE) in prostate cancer and analyzed the clinical value of EPE grade. The results showed that combining EPE grade with Partin tables and MSKCCn significantly improved the diagnostic efficiency of the clinical model and increased the clinical benefit.
BIOMED RESEARCH INTERNATIONAL
(2022)
Review
Radiology, Nuclear Medicine & Medical Imaging
Luis F. F. Calimano-Ramirez, Mayur K. K. Virarkar, Mauricio Hernandez, Savas Ozdemir, Sindhu Kumar, Dheeraj R. R. Gopireddy, Chandana Lall, K. C. Balaji, Mutlu Mete, Kazim Z. Z. Gumus
Summary: This study evaluated the use of MRI-based radiomics and nomograms for predicting extraprostatic extension (EPE) in prostate cancer. The quality of current radiomics literature was also assessed. The results showed that radiomics can accurately predict EPE, but there is a need for improving quality and standardizing the workflow.
ABDOMINAL RADIOLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Aydan Arslan, Ercan Karaarslan, A. Levent Guner, Yesim Saglican, Mustafa Bilal Tuna, Ali Riza Kural
Summary: This study compares the efficacy of PET and MR1 for lymph node metastasis and extraprostatic extension in cases with newly diagnosed prostate cancer. The results show that MR has lower sensitivity in detecting extracapsular invasion, while PET has lower sensitivity in detecting metastatic lymph nodes.
ACADEMIC RADIOLOGY
(2022)
Article
Oncology
Andreas G. Wibmer, Michael W. Kattan, Francesco Alessandrino, Alexander D. J. Baur, Lars Boesen, Felipe Boschini Franco, David Bonekamp, Riccardo Campa, Hannes Cash, Violeta Catala, Sebastien Crouzet, Sounil Dinnoo, James Eastham, Fiona M. Fennessy, Kamyar Ghabili, Markus Hohenfellner, Angelique W. Levi, Xinge Ji, Vibeke Logager, Daniel J. Margolis, Paul C. Moldovan, Valeria Panebianco, Tobias Penzkofer, Philippe Puech, Jan Philipp Radtke, Olivier Rouviere, Heinz-Peter Schlemmer, Preston C. Sprenkle, Clare M. Tempany, Joan C. Vilanova, Jeffrey Weinreb, Hedvig Hricak, Amita Shukla-Dave
Summary: In this study, a nomogram combining MRI findings with other patient data was developed to accurately diagnose extraprostatic tumor growth in patients with newly diagnosed prostate cancer. The nomogram showed significantly greater accuracy compared to clinical benchmark models, providing a valuable tool for physicians in predicting extraprostatic extension of prostate cancer.
Article
Oncology
Lili Xu, Gumuyang Zhang, Xiaoxiao Zhang, Xin Bai, Weigang Yan, Yu Xiao, Hao Sun, Zhengyu Jin
Summary: The EPE grade based on MRI demonstrated good performance for evaluating extraprostatic extension in prostate cancer patients, showing promising clinical utility. Combining EPE grade with clinical models improved diagnostic performance, indicating the potential value of integrating EPE grade into clinical practice.
FRONTIERS IN ONCOLOGY
(2021)