Guest Editors
Prof. Yong Xu
Email: xuyong8816@sina.com
Affiliation: Department of Urology, the Second Hospital of Tianjin Medical University, Tianjin Institute of Urology, Tianjin 300211, China
Homepage:
Research Interests: multimodal imaging-guided biopsy, mri/trus fusion precision biopsy, biomarker-driven precision diagnostics, ai-powered intelligent pathology, multidimensional risk stratification, biopsy complication management, lesion-targeted focal therapy
Prof. Gang Song
Email: songgang@cicams.ac.cn
Affiliation: Department of Urology, National Cancer Center / National Clinical Research Center for Cancer / Cancer Hospital,
Chinese Academy of Medical Sciences and Peking Union Medical College,
Beijing 100021, China
Homepage:
Research Interests: robotic radical prostatectomy
MRI-ultrasound fusion prostate biopsy
advanced prostate cancer management
nephron-sparing kidney cancer surgery
radical cystectomy
Assoc. Prof. Xingkang Jiang
Email: jiangx@tmu.edu.cn
Affiliation: Department of Urology, the Second Hospital of Tianjin Medical University, Tianjin Institute of Urology, Tianjin 300211, China
Homepage:
Research Interests: optimizing prostate biopsy techniques (MRI-targeted/regional biopsy, biopsy-free nomograms) to enhance significant cancer detection and reduce overdiagnosis.
investigating non-coding RNAs (lncRNAs/circRNAs) in prostate cancer resistance to docetaxel/apalutamide via β-catenin/HIF-1α and c-Myc signaling pathways.
exploring lncRNA/circRNA regulation of iron metabolism and ferroptosis in treatment resistance and heavy metal-induced carcinogenesis.
analyzing real-world treatment strategies and outcomes in diverse prostate cancer populations (e.g., elderly, young-onset patients).
developing urological devices (e.g., biopsy instruments) and AI-driven models for precision biopsy planning and treatment optimization
Summary
Prostate cancer diagnosis faces critical challenges in balancing detection accuracy with overtreatment risks. Traditional methods like systematic biopsy and PSA testing lack precision, underscoring the urgent need for advanced diagnostic strategies.
This Special Issue explores transformative innovations in precision diagnosis of prostate cancer, focusing on, but not limited to, the following areas:
· MRI-Guided Targeted Biopsies and Perilesional Sampling Techniques
Advances in imaging-guided biopsy methods—including MRI/TRUS fusion and perilesional approaches—to optimize biopsy yield and reduce sampling errors
· Biopsy-Free Diagnostic Pathways
Development and validation of non-invasive diagnostic tools using liquid or tissue-based biomarkers (e.g., ExoDX, MyProstateScore) to minimize reliance on invasive procedures
· Molecular Biomarker Integration for Risk Stratification
Utilization of novel molecular signatures to enhance differentiation between clinically significant and indolent disease, enabling more personalized management strategies
· AI-Driven Imaging and Pathology Solutions
Implementation of artificial intelligence in imaging and pathology workflows to reduce diagnostic subjectivity and improve accuracy
· Complication-Mitigation Strategies for Biopsy Procedures
Innovations aimed at minimizing procedural risks such as infection, bleeding, and discomfort associated with prostate biopsies
· Cost-Effectiveness Analyses in Diverse Healthcare Settings
Evaluation of the clinical utility and economic viability of precision diagnostic approaches across different healthcare systems
We welcome original research articles, clinical investigations, and comprehensive reviews that emphasize clinical translation, real-world applicability, and global relevance. Submissions should contribute to the advancement of early detection strategies in prostate cancer—specifically those that minimize unnecessary interventions and overtreatment while ensuring accurate identification of clinically significant diseases.
Keywords
prostate cancer, early detection, diagnosis, dcreening, biomarkers, liquid biopsy, multiparametric MRI, PSMA-PET, artificial Intelligence, risk Stratification, active surveillance, precision medicine
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